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UOP Role of Information Technology Questions
Q1) Examine how information technology fits in the value chain.
Q2) Evaluate the role of information technology in creati ...
UOP Role of Information Technology Questions
Q1) Examine how information technology fits in the value chain.
Q2) Evaluate the role of information technology in creating competitive advantage.
Q3) Analyze the impact of technology-supported business decisions.
Colorado Technical University Program Design and Development Worksheet
Identifying Types of Data and Developing an Information-Sharing PlanReturn to the issue you are addressing from the Riverb ...
Colorado Technical University Program Design and Development Worksheet
Identifying Types of Data and Developing an Information-Sharing PlanReturn to the issue you are addressing from the Riverbend City: Examining the Ruby Lake Community media piece. Address the following for this assignment:Create a data reporting table for the program you are developing, similar to Table 15.3 on page 441 of your Program Development in the 21st Century textbook. Address all data types relevant for your selected program and structure data for each of the four key aspects:Responsibility.Timeframe.Methods.Recipients.Prepare an example of a data reporting tool that would help you assure the quality of program implementation and an understanding of whether or not your program objectives are being met. You may choose any aspects of project implementation on which to report data, such as staffing, budgeting, information systems, etcetera.Review the scoring guide for the assignment carefully to determine what is required to achieve a distinguished level of performance.Assignment RequirementsWritten Communication: Written communication should be free of errors that detract from the overall message.APA Formatting: The paper, including resources and citations, should be formatted according to current APA style and formatting guidelines.Length of Paper: 3–5 typed, double-spaced pages, not including the title page and references.Font and Font Size: Times New Roman, 12 point.Chapter 15 pg 419-449 Program Development in the 21st Century: An Evidence-Based Approach to Design, Implementation, and EvaluationISBN: 9781452238142By: Nancy G. CalleyBUT THE PROGRAM IS EFFECTIVEOn Tuesday afternoon, Reggie received a call from his contract manager telling him that his contract for mentoring at–risk youth would not be renewed next year because funding for children’s services had been reallocated. The contract manager went on to explain that the county was facing budget cuts and, therefore, had to make decisions about which programs to continue funding. While these decisions were difficult to make, they were based on identifying the most essential programs and those that had produced strong outcomes. Unfortunately, the mentoring programs were not viewed as essential nor was there evidence of their success.When Reggie heard this, he was flabbergasted. He explained to the contract manager that he had been conducting a program evaluation since his program’s inception 2 ½ years ago and that the outcomes were extremely positive. He quickly shared with her some of the highlights of his program:Teens who had been successfully matched with mentors: 342Percentage of mentees who graduated high school compared with the region’s 67% graduation rate: 94%Percentage of the mentees who pursued college: 68%Of the 32% who did not pursue college, percentage who pursued vocational training or were employed: 25%Percentage of the mentees who were either living at home or living independently: 92%Percentage of the mentees who had been involved in criminal activities post–mentoring services: less than 5%Percentage of the mentees who had experienced substance abuse problems: 6%; less than 3% required treatmentPercentage of mentees and parents/caregivers who identified having had a mentor as one of the most important aspects of their teenage years: 94% and 98%, respectivelyTotal cost per youth: $302 (compared with the $1,680–$6,440 costs related to much more intensive case management services and comprehensive community–based programs for court–involved youth—precisely what Reggie’s program was designed to prevent being needed)After quickly reviewing these outcomes with the contract manager, Reggie promised to send her the full set of evaluation data and the summary report. He told her that he had been planning to send her the report and evaluation results once he had 3 full years of data and said he was sorry that he had held onto the information.The contract manager shared her surprise with Reggie, stating that she wished she had known sooner about the program’s success, since it very well could have meant that the funds for mentoring programs would not have been cut. However, legislative action had already been taken, so the funding decisions were final. She did encourage Reggie to make the evaluation findings available and told him that they may still prove fruitful in the next funding cycle’s decision–making process.CONSIDERING REGGIEWhat did Reggie do right, and what mistakes did he make?If you were Reggie, what would you do next?What practices should Reggie put in place to ensure that relevant program information is shared with all who have a need to know on an ongoing basis?About This ChapterThis chapter’s focus is the significance of data, the critical information that data provides about all aspects of a program and organization, and most importantly, the invaluable need for comprehensive information sharing. We will examine both indirect and direct benefits of information sharing. In addition, we will explore the various types of data that are collected as part of comprehensive program development, including outcomes data, process evaluation data, human resource data, financial data, compliance and quality improvement data, and other pertinent data. We will explore the questions related to whom information should be shared with and why, as well as how frequently and through what medium information should be communicated. To guide comprehensive data collection and to illustrate the importance of examining all the program data in order to understand the total program operations, the Quarterly/Annual Comprehensive Data Report Tool is provided. The chapter concludes with a case illustration to further reinforce the content of the chapter, followed by a data report plan exercise and questions for reflection and discussion.STEP XIII: DEVELOP AN INFORMATION–SHARING PLANSignificance of Information SharingSeemingly, Reggie did everything right. At the implementation of a new program (i.e., mentoring), he designed and implemented a comprehensive process evaluation and a comprehensive outcome evaluation. He methodically collected and analyzed the data and, as a result, was intimately aware of the significant details of his program and the impact that it had made. However, he made one unforgiving mistake: He failed to share the data that he had collected and analyzed with all the people who had a need to know. As a result, his highly successful program would cease to operate.While Reggie’s example illustrates one of the toughest lessons about the business of which program development is a part, it is unfortunately not uncommon. As mental health and human service professionals have continued to become much more concerned with evaluation methods and other data collection activities, there continues to be a lag in following through once data has been collected. This can create obvious challenges, particularly since any data that is collected but not used should not have been collected in the first place, since it incurred a cost without producing a benefit.There are many other important lessons that Reggie’s vignette illustrates (see Box 15.1).BOX 15.1LESSONS FROM REGGIEComprehensive program evaluation must be conducted at the start of any new program.Outcome data is essential and, therefore, must be collected.Output data, such as cost–effectiveness, is essential and, therefore, must be collected.Program data must be shared frequently and regularly with all stakeholders.Collecting and analyzing data without sharing it with stakeholders may have devastating results.Collecting and analyzing data and not sharing the results may have the same effect as if no data had been collected or analyzed.Conducting various types of evaluation and sharing the findings with stakeholders may have a direct effect on your program’s sustainability.Whereas each of these lessons is significant, the more critical issue related to information sharing has to do with why data is collected in the first place. A large part of this answer is provided in previous chapters in the discussions related to program design, implementation, and evaluation and assessment. However, in addition to implementation and evaluation data, other data must be collected, such as client demographic data and financial data. Through comprehensive data collection and analysis, mental health professionals are empowered—empowered to better understand and manage their program. The notion that information is power can be clearly illuminated in program development efforts, particularly as the more knowledgeable the program developer is about the program, the easier it is to articulate the program to others. Conversely, without detailed information about the ongoing operations of the program, it’s more challenging both to communicate the program to others and to garner support for the program. Because the operations provided by human service organizations depend on people (Gibelman & Furman, 2008), the central role that ongoing communication, including information sharing and data sharing, plays in supporting a program’s operations is critical.More importantly, without effective means by which to communicate the work that mental health professionals provide and the impact that this work makes, mental health care itself is at risk. Morris et al. (2010) speak about this global issue from an Irish perspective:As with all areas of health care in Ireland and internationally, the health information deficit in the mental health services serves to impede the decisions of policymakers, health care workers, patients, and their families. It is imperative that mental health information becomes more accessible, useful, and comprehensible so that a culture of information gathering and use can be fostered both internationally and in Ireland. This information can then provide the evidence required for the provision of high–quality health care. (p. 360)Direct and Indirect BenefitsIn addition to what is listed above, there are numerous other benefits—both direct and indirect—that may result from sharing information related to program operations and outcomes with stakeholders. Indirect benefits refer to benefits that may not produce a direct result but that produce some impact, whereas direct benefits are those whose effect is concrete. For instance, by sharing information about program operations with staff, employees may have an increased level of engagement with the program/organization. This level of engagement may not be quantifiable, but it may mean that some employees choose to remain at the organization even when other more lucrative opportunities arise. Because you may not be aware of this impact, particularly since you may not have had any idea that someone was considering leaving, the impact is indirect—yet still significant. Alternatively, the sum effect of employee engagement may produce the direct benefit of employee retention, especially since employee retention results in decreased expenditures associated with hiring. This benefit can be tremendous, as any effective program developer and human resources manager can tell you exactly what it costs to replace an entry–level professional employee (e.g., case manager, therapist), which may range from $6,000 to $12,000. Thus, reducing unwanted employee turnover is an objective of most managers, because replacing an employee creates additional and often unnecessary expense to the organization that cannot be recouped. The costs are largely attributed to such administrative work as processing new applicants, hiring–related activities, coordination of employee benefits, and new employee orientation and training, among others. Considering these unnecessary costs, it is not difficult to see the benefit of staff retention.Box 15.2 provides a snapshot of other indirect and direct benefits related to information sharing.BOX 15.2INDIRECT AND DIRECT BENEFITS RELATED TO INFORMATION SHARINGIndirect BenefitsIncreased ownership in the program/organization among employees, resulting from increased knowledge of shared responsibilitiesCreation of a culture of transparency and shared commitmentMore flexible workforce that can more easily adapt to changes when needed as a result of being consistently informedDirect BenefitsMore productive and effective workforce as a result of increased knowledge of the businessProblems and deficits able to be quickly identified and resolved so that program/organization is continuously improvingMore competitive program and organization as a result of increased productivity and effectivenessIncreased business and growth opportunitiesProgram/organizational sustainabilityTypes of DataThere are multiple types of data that mental health and human service professionals collect as part of the program management process. Indeed, at times, some mental health professionals claim that they are more data collectors than mental health professionals—with responsibilities of collecting intake information and administering and collecting assessment data, treatment planning data, quality assurance data, contract compliance data, and so on. However, the issue is not one of data collector versus mental health professional but, rather, of mental health professional whose role very much involves data collection and management. Data is pertinent to our ability to effectively assess and treat clients, manage staff and other resources, manage programs and organizations, and continue to enjoy our livelihood. Or put even more succinctly, “Data collection is the sine qua non of effectiveness–based program planning” (Kettner, Moroney, & Martin, 2008, p. 19). Data collection and management, therefore, must be both respected and appreciated—not as an added job but as one of the most integral parts of our job. Once this has occurred, the power that information holds can be fully unleashed.While there is an enormous amount of data that may be collected, the primary reason for collecting the data has to do with gaining knowledge about all aspects of the program. However, all data that is collected must be fully justified. And as Gard, Flannigan, and Cluskey (2004, p. 176) remind us, the four questions that should guide the data collection process are as follows:What do we want to know?Why do we want to know it?What should we measure?How should we measure it?Knowing that all data that is collected has a specific use is essential. Often, the most essential data is collected for a process or outcome evaluation, human resource management, financial management, or contract compliance and quality improvement activities. While these data sets can be reviewed independently, they also must be thoroughly reviewed concurrently, thus forming a complete picture of the program. By doing so, a critical understanding of how each of the data sets interacts with the others can be achieved. Each of these various types of data sets is discussed next.Process Evaluation DataAs discussed in Chapter 12, a comprehensive process evaluation allows you to assess the myriad aspects of a program throughout its implementation. Depending on the type and scope of the process evaluation, a variety of data can be collected that includes client demographic and other descriptive characteristics and program outputs such as number and type of interventions provided, treatment length, and number and qualifications of staff providing treatment. In addition, coverage and equity data can be collected to provide specific information about who is being served and who is not being served.Demographic and descriptive data can be highly useful in gaining increased understanding and knowledge of your client population and, therefore, must also be collected and analyzed. This data has multiple uses, including as part of a process evaluation in identifying the target population and needs, increasing knowledge about program outcomes as related to client subpopulations and specific characteristics, advocacy efforts, and pursuing funding opportunities. Indeed, possessing specific and comprehensive knowledge about client populations is essential to effective program management. Box 15.3 provides a sample of possible types of demographic information that may be collected and reported.BOX 15.3SAMPLE OF DEMOGRAPHIC DATA CHARACTERISTICS FOR A TRANSITIONAL HOUSING PROGRAMAgeGenderRaceEthnicityLanguageDependent children (ages, gender, and special needs)Intimate partner statusSpecial needsAcademic historyEmployment historyHistory of homelessnessFamily, friends, and other supportsDemographic data provides rich information; however, it is often in collecting this type of data that mental health professionals run into trouble. Much too often, data is collected that is not needed—data that is not going to be used for a specific purpose. This goes back to the issue that no data should be collected that does not have a specifically identified use, because otherwise, you risk doing a disservice to those whom you are serving as well as wasting time and money For instance, each of the data elements in Box 15.3must serve a specific purpose, to justify why it is being collected. And in this case, each data element does serve a purpose, as illustrated in Table 15.1.Table 15.1Data Elements and RationaleIn addition to the specific purposes listed above, client demographic and descriptive data also can be used to learn specifically about program coverage and program equity—significant information for program developers, communities, and funding sources.Coverage data provide feedback on the extent to which a program is a) meeting the community need and b) reaching its target population. Monitored during program implementation, coverage data can be used not only to determine the extent to which the target group is being reached but also to ensure that individuals ineligible for the program are not served. (Kettner et al., 2008, p. 258)Similarly, equity data provides feedback on the various subgroups within a region to identify what, if any, disparities exist in regard to who is being served.Unless a program is targeted at a specific subgroup of a community, all other things being equal, geographical subareas and subgroups should be served by a program in roughly the same proportion as their composition in the community. Equity data can be used to ensure adequate coverage of subgeographical areas and subgroups during implementation or at the end of a program to document that a program is or is not reaching some geographical subarea or subgroup. Utilized in a performance measurement approach, coverage data provides stakeholders with information about the distribution of outputs, quality outputs, and outcomes across subgeographical areas and subgroups. (Kettner et al., 2008, pp. 258–259)In addition to client demographic and descriptive data, various types of information are collected specifically for the process evaluation to provide comprehensive information related to program implementation and operations and to promote further knowledge of outcomes. Several of the types of data that are collected as part of a process evaluation are reviewed in Chapter 12; so please refer back to that chapter if needed. Briefly, information about the implementation process itself is collected, including the number of resources (e.g., staff, money) allocated to the program, location of service delivery, and unexpected occurrences, to name a few.To reiterate, fidelity assessment may be included in the process evaluation in order to specifically assess the degree to which a treatment is delivered as intended. The five major areas of fidelity are treatment design, training, treatment, receipt of treatment, and treatment skill enactment (Borelli et al., 2005), and each requires specific data to be collected and analyzed. Treatment design data may include number and type of interventions and theoretical basis of treatment, while training may include the content and methods used to prepare staff to deliver the treatment and staff credentials. Treatment delivery data may include the number and type of interventions actually delivered, the time frame in which treatment was delivered, and the credentials of the individual(s) delivering the treatment. Other specific data that may be collected and analyzed in a fidelity assessment were also discussed in Chapter 12; so again, please refer back for a more comprehensive discussion of data types involved in a fidelity assessment.Because of the unique power that process evaluation data holds—including demographic and fidelity assessment data—sharing this information with stakeholders is critical. Client demographic data can be particularly useful not only in increasing knowledge of your particular target population or region but also in informing the broader field about client needs and characteristics. Therefore, this information is of great value to staff, funding agents, and other professionals. In addition, this data is pivotal to ongoing program planning efforts. For instance, program modifications may need to be made to a program that was originally designed for adolescents but that currently has a majority client population of older teens, since there are often significant developmental differences between the two groups. Likewise, a subpopulation of clients may not speak English, and therefore, specific program modifications and additional supports will be required to effectively serve this group. In addition, information about the type and scope of resources, such as staff credentials, administrative oversight, and adjunctive services, is essential not only to fully understanding all the aspects that contribute to the program’s success but also to understanding all that must be in place to effectively support the program. This information has specific relevance to planning, managing, and sustaining programs and is directly related to the program’s finances.Because treatment fidelity data speaks directly to the design of a particular treatment, sharing information about the degree to which fidelity has been maintained throughout implementation is critical for program staff. As such, this information provides direct feedback about their performance as well as about the success or failure of the program developer in planning for retaining treatment fidelity. In addition, this information is critical to clients as part of the informed consent process and as consumers of services with a right to know that they did receive what they were told they would receive. Moreover, this information is significant to funders, as it speaks to accountability and treatment design. Finally, this information is essential to other professionals and stakeholders in continued efforts to better understand treatment design and to understand the relationship between design, implementation, and outcomes.Outcomes Evaluation DataThe types of data collected in the outcomes evaluation are specific to the program’s objectives and, therefore, are unique to a program. However, there are also often common outcomes relevant to different types of programs. For instance, a treatment program for juvenile sex offenders and a second–chance academic program for young adults (i.e., a high school diploma program for young adults) may share the outcome of academic success. Whereas both programs may share an outcome related to academic success, the outcomes for juvenile sex offenders may also include recidivism (i.e., reoffending), improved family functioning, and increased independence.Outcomes are generated directly from the program design. For instance, family therapy and the development of a family support network are designed to improve family functioning and, therefore, must be evaluated to determine if the interventions did indeed lead to the anticipated outcomes. This interdependent nature between design, implementation, and evaluation is essential to understanding the complexity of programs and program development efforts, and therefore, highlighting these relationships in discussions of outcomes is helpful in increasing knowledge of the program’s efforts.In addition, because outcomes reflect a program’s success, they are critical to all stakeholders, including clients, staff, funding agents, community members, legislators, and professionals in the field. Staff are particularly interested in outcomes since they reflect another measure of their performance and, as such, provide another integral link to what they do and why they do it—a critical benefit to us all while working with individuals. However, whereas it is necessary and healthy for any organization to continuously evaluate outcomes, caution must be exercised in the degree to which outcomes are directly associated with employee performance. Indeed, the employee is a vehicle by which an intervention is delivered, and therefore, rarely is it the employee who failed but, rather, the intervention that failed.Funding sources and legislators are specifically interested in outcomes since this information is pertinent to decisions about continued and future funding. Community members are interested in outcomes, since they also have a particular interest in what works and what doesn’t. After all, as taxpayers, community members provide primary support for nonprofit services. Finally, other mental health professionals have a vested interest in the continued development of knowledge and understanding not only related to what works but why it works so that efforts can continue to develop and implement the most effective types of services and treatment.Continuous collecting, analyzing, and reporting of outcomes must occur to ensure that all stakeholders are well informed about outcomes. Without doing so, the dilemma that Reggie faced may become a reality for other mental health professionals—regardless of just how good the work they are doing is.Human Resources DataHuman resources data includes all data pertaining to staff (i.e., personnel). This includes but is not limited to such data as illustrated in Box 15.4.BOX 15.4EXAMPLES OF HUMAN RESOURCES DATAHiringJob descriptionsPerformance reviewsEducational recordsMedical informationSalary informationInsuranceCompany–sponsored retirement plan informationTax informationCitizenship informationStaff vacancies (unfilled positions)Training completed by staffStaff credentialsRetentionSeparationDisciplinary actionStaff challenges/problemsStaff commendations/rewardsSample of Human Resources DataHuman resource professionals maintain various documents and data pertaining to staff and are responsible for each staff member’s personnel file to ensure that confidential information remains confidential. The types of data that are private and, therefore, must be maintained in a confidential manner include medical and other personal information, salary, tax and citizenship information, and disciplinary action. Whereas this data is relevant to program managers/administrators, specific personal information is not relevant to program staff, and it is not permissible to disclose such information to staff who do not have a justified need to know. However, data related to staff that can be reported in aggregate and that is not considered confidential is highly useful to program developers/clinicians and all program staff, as it relates to program operations.This data, including staff vacancies, hiring, credentials, job descriptions, and training activity, is often most valuable to program managers and staff when examined as trend data—for instance, you might examine staff training needs versus training completion on a quarterly basis to strategize methods to address training needs. Or you may evaluate staff retention to determine what trends might exist related to when staff end their employment and the reasons why they choose to do so.By collecting and analyzing data related to staff, program managers are equipped with pertinent information about their staffing infrastructure. For example, if employee exit interview results indicate that 76% of staff voluntarily terminated their employment last year due to either not feeling connected to the program/organization or due to the lack of professional development activities the organization offered, this essential information can be used in staff retention efforts. However, this data is meaningful to all staff—not simply the manager/supervisors—particularly because sharing this type of information among staff and involving staff in retention efforts may serve to engage staff. As a result, the method by which future retention efforts are developed may in fact be a critical retention tool.Financial DataFinancial data comprise all the program’s finances—costs and revenue. Data such as employee salaries, office space, furniture, supplies, administrative support services, and the contract rate(s) are all essential financial data. Financial data is pertinent to program planning, management, and sustain–ability and, as a result, must be collected and analyzed frequently. Effective program developers and managers are keenly aware of the financial aspects of their program(s) and maintain close attention to financial details. Basic information that all mental health professionals should know is the per client cost of a program. This is typically gathered as part of the process evaluation (Byford et al., 2007) and provides essential information for increasing economic knowledge of the program. A basic method for computing this cost is to divide the number of clients served by the total cost of the contract amount or revenue produced. For instance, if the total contract amount for a mentoring program is $100,000 and you serve 260 youth, the cost per client is $384.62. This means that the cost of mentoring services per youth is approximately $384.62. Knowing this most basic economic information is critical to fully understanding a program and understanding the financial needs related to specific interventions. It has particular significance to maintaining funding, pursuing new funding, and advocacy efforts. Moreover, employees and other professionals are interested in this since it provides another critical perspective of programming and the financial aspects of interventions.By frequently sharing financial information, employees are able to feel more closely connected to the business that is their work—and, at least from my perspective, one of the most important businesses conducted on earth. That is precisely why it is so important that we protect it, and one form of protection is to demonstrate respect for our business by increasing the knowledge of all stakeholders about the business. Moreover, frequently sharing financial information with employees promotes transparency and contributes to a more engaged workforce.Two other groups with whom financial information has specific ramifications are community members and funders. In fact, sharing financial information with community members in concert with information about program outcomes may also be particularly helpful in garnering more financial support through donations and other means. In addition, sharing financial information with funding sources not only is required but also provides critical information that is useful in ongoing contract negotiations and decisions about releasing new funds.Compliance and Quality Improvement DataCompliance data refers to compliance with requirements of contracting organizations, accrediting bodies, licensing organizations, other oversight organizations, or self–imposed requirements. Compliance data often includes both outcome data and other types of data. For instance, contracting organizations are specifically interested in a program’s effectiveness in treating clients; however, they are often equally interested in the credentials of staff and the availability of services. Box 15.5 provides a sample of contract compliance data.BOX 15.5SAMPLE OF CONTRACT COMPLIANCE DATAAcceptance rate of all referred clientsLength of time from initial referral to program admissionNumber of clients served annuallyPercentage of clients successfully treated in accordance with preestablished success criteriaPercentage of clinicians with a master’s degree or above in major mental health discipline and licensure as a mental health therapistPercentage of clients discharged prematurelyCompliance data often overlaps with process evaluation data, because contractors have a vested interest in ensuring that programs/models are implemented as designed. Because contract compliance data reflects the degree to which goals or targets are met, contractors or other oversight organizations dictate the required target thresholds. For some issues, such as the percentage of qualified therapists, there is no tolerance for noncompliance, meaning the required compliance rate is 100%; for other areas, compliance may be set at less than 100% or at a specific number. For instance, the percentage of clients discharged prematurely (without completing the program) may be set at 85%, the expected length of time between referral and program admission may not exceed 48 hours for any client, and there may be a requirement to serve a minimum of 160 clients per year.Contract compliance data has obvious implications. Failure to comply with performance expectations may result in the cancellation or nonrenewal of a contract. Therefore, collecting, analyzing, and sharing this data with all program stakeholders is critical to the program’s sustainability.Quality improvement data is required by accrediting bodies and is often a standard part of organizational practices and, thereby, self–imposed by organizations. Quality improvement speaks to the specific areas in which improvement is sought and the improvement goals. While it is a standard part of business operations today, quality improvement originated in Japan (Senge, 2006) in the 1940s. Unlike contract compliance goals that are predetermined by contractors or other oversight organizations, quality improvement goals often evolve organically from data analysis findings. For instance, if exit interview data indicated that staff chose to leave the organization due to lack of engagement, a quality improvement goal might be developed to address this specific issue. The goal, such as 95% of staff will be engaged with the program within 6 months of employment as measured by the Employee Engagement Scale (hypothetical standardized assessment instrument—with sound psychometric properties, of course), is developed by program staff with specific strategies by which to attain it. Through the collection and analysis of various program data, staff are able to quickly identify areas in need of improvement and can then develop means by which to address these areas.The structure surrounding quality goals may vary considerably from organization to organization, with some organizations using quality improvement committees to lead quality improvement efforts and others requiring a specified number of quality goals in key areas (e.g., client satisfaction, community relations). However, what is of greatest import is not how quality improvement efforts occur but, rather, that they occur and that their purpose is fully understood by all stakeholders. This is because of what quality improvement efforts reflect—a commitment to quality and continuous improvement.Whereas contractors and/or accrediting bodies often require reporting of both contract compliance data and quality improvement data—even when not required—it is wise to share this data with oversight organizations since it reflects the program/organization’s dedication to quality. Equally important is that this data is shared frequently and with all staff. Contract compliance and quality improvement data are byproducts of the work of staff, and therefore, all staff must have open and continuous access to this data. By ensuring that this occurs, staff are able to better understand the critical issues that compose their program and are able to more effectively participate in ongoing improvement efforts.Other Pertinent DataIn addition to the five major areas just discussed, there are other types of data that must be collected and shared with various groups. Other client data, such as satisfaction with services, is not only required by several accrediting bodies and/or contractors but particularly meaningful to program staff and necessary for program improvement efforts. Employee information, such as employee satisfaction, engagement, and retention each provide pivotal data for use in continuous improvement efforts. In addition, organizational structures and decision–making processes are pertinent areas to both employees and funders, since they directly impact efficiency and effectiveness and provide additional guidance to employees.Whereas there are lots of other types of data that are pertinent to collect, analyze, and share with others, you must be guided by the premise of collecting and analyzing the right data and sharing that data as frequently as needed with all who need to receive it. By doing this, data collection and information sharing can be highly efficient and can contribute to the overall effectiveness of the program operations.Data ReportingWE’RE DOING WHAT?At a recent fundraising event hosted by a nonprofit agency, one of the agency’s board members was speaking with Kyle, one of the agency clinicians. The board member shared his excitement about the new contract on which the program director (Kyle’s supervisor) was bidding and discussing how, if awarded, the contract could result in a significant expansion of services for the agency. Kyle smiled and agreed about the positive prospects the new contract could bring and then delicately extricated himself from the conversation, going in search of one of his program colleagues. On finding a fellow clinician, he recounted the conversation he had had with the board member, stating that he had no idea that his supervisor was pursuing a new contract. Kyle’s colleague was not aware of this either. Flummoxed by the apparent lack of information they both had about their program, they agreed they would need to follow up with their supervisor in the morning.Have you ever experienced this type of awkward situation? Someone knows something about your program/agency that you should know as well, and after hearing this information from another source, you feel uncomfortable and not wholly aware of why you weren’t informed. Unfortunately, this happens all too often and typically not because there is a motive to withhold information; rather, in the absence of any type of information–sharing structure, information is not properly or effectively shared. In other words, there must be a method to your madness, and this is particularly true where information sharing is concerned.This can be easily accomplished by putting a specific structure in place to ensure that information is effectively shared. By doing this, the extensive work accomplished in the data collection and analysis process can be fully realized. In terms of developing a basic structure to promote effective sharing of information, each of the following aspects of data reporting should be established:The individual(s) responsible for reporting the dataThe time frames in which data will be reportedThe means by which data will be reportedThe recipients who will receive the various types of dataEach of these issues is discussed below.Responsibilities for Data ReportingAssigning responsibilities is a prerequisite for accountability—in any business or other endeavor. Therefore, the starting point for effective information sharing lies first and foremost in identifying who is responsible for reporting what type of data/information. Because there are often various types of data (as described above), there may be various individuals assigned to reporting specific types of data to different groups. For instance, clinicians might report program outcomes to the program staff, whereas the chief financial officer might report the program’s financial status to the board of directors. However, as I have emphasized throughout this text, program developers/mental health professionals must have comprehensive knowledge about the programs with which they are involved. And there is no better indicator of the degree of knowledge a program developer has about her/his program than her/his ability to report on the various data related to the program. During those times when program developers are not directly reporting program data, they must be fully aware of the data and its implications.Along these same lines, all program staff should be knowledgeable about the various aspects of their programs—regardless of the degree to which they directly interact with specific data. This is because information does often translate into power, and thus, by being empowered to report on various data, the staff person is gaining new knowledge and is given an opportunity to develop new skills related to reporting data. Therefore, data reporting must not be simply the role of one person (e.g., program developer/director) but a role shared by many and one in which assignments change related to the type of data reported by the specific staff person. By spreading out responsibilities for data reporting among all staff persons, program managers may in fact engage more staff with the program and the organization while providing specific opportunities for professional development. Table 15.2 provides an example of how the small staff of a gambling prevention program for teens shares data reporting responsibilities.The five staff persons illustrated in Table 15.2compose the entire program staff: Kimberly (program manager), LaShawn, Rhonda, Dorothy, and Roma (prevention specialists). Each staff person is responsible for regularly leading the collection, analysis, and reporting of their assigned data to the rest of the program staff for a year at a time. By using this type of schema for sharing data–reporting responsibilities, Kimberly is able to ensure that each of her staff members is highly knowledgeable about the major aspects of the program. Regardless of the manner in which data reporting responsibilities are assigned, the primary objective is that responsibilities are shared among program and organizational staff to ensure that everyone who is a part of the program is knowledgeable about the various aspects of the program.Table 15.2Data Reporting AssignmentsReporting Time FramesEstablishing time frames for reporting data can be as important to ensuring that information is shared as is assigning responsibility for data reporting. As you witnessed by Reggie’s example, his program may have continued if short–term and frequent time frames for reporting had been established.Time frames provide another necessary level of structure to the information–sharing process and another level of reinforcement for accountability. Whereas data about each major area of a program should minimally be shared on a quarterly basis with all program staff, specific types of data may need to be shared much more frequently, depending on the data type and special circumstances. For instance, if program revenue that is paid on a fee–for–service basis has fallen below the annual projected revenue, resulting in the possibility of reducing a staff position unless the revenue improves quickly, revenue data may require analysis and reporting on a weekly basis. On the other hand, it may not be appropriate to report on outcome goals more frequently than each quarter, because the limited number of outcomes occurring on a weekly or biweekly basis may not reflect aggregate outcome data and will, therefore, skew the actual outcomes picture as a result of focusing on a few outcomes rather than the total outcomes.Methods for Data ReportingOnce decisions about who is responsible for reporting specific data are made and the time frames within which data will be reported have been established, the methods by which data will be reported must be identified. The methods for reporting specific types of data may be varied based on the recipients, and multiple methods may be used to communicate the same data. Methods for reporting data include but are not limited toverbal communication in meetings or other group forums,presentations of data in meetings or other group forums,comprehensive written reports,written snapshots of data (i.e., data briefs),electronic snapshots of data posted on the Intranet,annual reports, andwebsite postings.Methods should be selected based on effectiveness to reach the intended recipients and the rationale for sharing the specific data. For instance, verbal communication of data in biweekly staff meetings may be a highly effective method for ensuring that critical information is frequently shared with program staff. However, quarterly board of directors meetings may require both a formal presentation of data as well as an accompanying report to ensure that the information is effectively communicated and that the information provided is thorough enough to allow for effective governance.Because effective communication is critical to information sharing, methods for reporting data should be continuously evaluated to ensure that they are working. Simply because the development of a presentation involves quite a bit of work and contains significant information, that does not automatically translate into the information being effectively communicated. Gathering the input of recipients about preferences of communication methods, engaging in follow–up dialogue to discuss information shared, and engaging in more rigorous evaluation of the effectiveness of information sharing can be helpful in ongoing efforts to ensure productive information sharing.Data RecipientsFinally, the various groups of individuals who will receive the data must be identified—the data recipients. Technically, data recipients are all stakeholders. This includes but is not limited to program staff, clients, administrators, contractors, accrediting bodies, the governing board, and the public. Each of these groups has a need to know specific program information, and as such, program developers have an obligation to regularly share data with each group. Further, for some groups, there are specific requirements about what data must be reported, how often it must be reported, and in what format it must be reported. For instance, written reports on contract compliance data might be required on a semiannual basis by contractors. Alternatively, while specific requirements may not exist regarding information sharing with program staff, best practices may indicate that specific program data is shared on a weekly basis to ensure a well–informed workforce.The basic rule of thumb regarding who should receive program information is that anyone who has a need to know should know, and they should know as soon as possible. This will ensure that what happened to Kyle does not happen to other clinicians or program staff—that is, learning about a possible significant change in the program from a board member.As you can see, all these aspects of data reporting are interconnected—responsibilities for data reporting, time frames, methods, and recipients. By thoroughly considering each, program managers posture themselves to effectively share information and data with their stakeholders. The next section provides specific examples and tools to aid in accomplishing this.Data Protections and SafeguardsBecause the bulk of data collected by mental health professionals is related to those whom we serve, our first obligation is to protect the privacy of our clients and to ensure that information about them is maintained in a confidential manner. There are several state and federal laws that set forth rules on this—most notably, HIPAA (1996) and HITECH (2009), which provide strict guidance for the collection, storage, protection, and use of health–related information, with strong protections for the privacy of individuals’ health information (Mai et al., 2007). In addition, federal guidelines regarding the protection of substance use information—42 CFR Part 2—confidentiality of alcohol and drug abuse records, and federal and state therapist patient confidentiality laws provide specific guidance. If you are not wholly familiar with the federal laws regarding client/patient protected health information, this is an area with which you will need to become quite familiar.All data collection must be conducted in accordance with legal statutes and with all necessary protections in place. In addition, all research activities must be conducted with necessary oversight procedures in place, including authorization and ongoing monitoring from an institutional review board/human subjects committee. Organizations must have comprehensive policies and procedures in place specifically dealing with client confidentiality, data storage and maintenance, data sharing, and reporting through release and disclosure. Organizations also must ensure that required hardware and other electronic safeguards are in place to protect electronic data.Just as both state and federal laws and other guidance regarding client confidentiality have changed dramatically over the past several years, with continued changes in electronic technology and continued development of knowledge related to data collection and protection, change will likely continue to occur. It is essential that mental health professionals maintain current knowledge regarding the rules that govern the collection, use, and storage of confidential information to ensure appropriate guidance in this area.Developing the Data Reporting PlanAs discussed earlier, without a solid framework to structure data reporting and information sharing, it is likely that pertinent information will not be shared with those who have a need to know or that information will not be shared in a timely fashion. Therefore, structure is needed to guide these activities. The Annual Data Reporting Plan in Table 15.3 provides an example of how to structure data reporting by addressing each of the four key aspects (i.e., responsibility, time frame, methods, recipients). Please note as you review Table 15.3 that the time frames and methods are intended as a guide only—contractors, organizational policies, and other oversight organizations may require more stringent reporting time frames and methods.Table 15.3Annual Data Reporting PlanWhereas the Annual Data Reporting Plan illustrates the broad data types that should be shared, there are numerous details that are needed to guide this type of data collection, analysis, and reporting. The Quarterly/Annual Comprehensive Data Report Tool (Box 15.6) was developed precisely to guide and provide essential structure to the data collection, analysis, and reporting process.BOX 15.6QUARTERLY/ANNUAL COMPREHENSIVE DATA REPORT TOOLProgram:Data reporting time frameReporter:1. Clients serveda. Total number served during report period:b. Total program capacity:c. Is program capacity limited by contract?d. If unlimited, what is your target goal for number of clients for the year?e. How does current number of clients compare with last quarter or last year?f. If reporting quarterly data, how does this quarter’s data compare with the same quarter 1 year ago?g. What types of trends in client numbers exist?h. Provide evidence for item g trends:i. Reasons/explanations for client population trends:j. Projected number of clients to be served next quarter:2. Clients discharged/released/no longer in programa. Provide the definition of successful termination for your program:b. Number of successful terminations during report period:c. Percentage of total terminations that were successful:d. Number of unsuccessful terminations during report period:e. Percentage of total terminations that were unsuccessful:f. Reasons for unsuccessful terminations:g. Please state how those numbers compare with last quarter/last year data:h. If reporting quarterly data, how does this quarter’s termination data compare with the same quarter 1 year ago?i. Any trends identified in terminations (e.g., increase in unsuccessful terminations due to truancy during the summer):j. Any program plans, enhancements, or changes that you made as a result of the successful or unsuccessful discharge data:3. Contract compliancea. What percentage of contract compliance items were you in full (100%) compliance with this reporting period?b. Please state each of the specific contract compliance items that were not in full compliance during report period:c. How does the percentage of contract compliance results compare with last quarter/last year?d. If reporting quarterly data, how does the percentage of contract compliance results compare with the same quarter 1 year ago?e. Please state any program plans to address any contract compliance challenges:4. Assessmentsa. What standardized assessment instruments, if any, are used within your program?b. How are the results used in individual treatment planning?c. If you provide an assessment at entry and at termination, please discuss the differences/similarities in scores:d. Please discuss your aggregate program assessment data for report period:e. If applicable, please discuss how you have used the aggregate assessment data to make program changes:5. Quality improvement statusa. Please report on the results of each program outcome goal:b. Please discuss how you have used the results of your quality improvement data:c. Please discuss how your quality improvement activities have been used in program changes and program development:d. Please discuss the frequency with which your program’s quality plan changes and why:e. How often is quality improvement data reviewed with staff?f. Please state the methods that you use to promote and share quality improvement initiatives with program staff:6. Human resourcesa. What is your current staff vacancy rate?b. What is your staff turnover rate during the report period?c. How does your staff turnover rate compare with last quarter/last year?d. How does your staff turnover rate compare with the same quarter last year?e. Please share any strategies that you have utilized to increase or impact employee retention or satisfaction?f. Please state any plans or successful strategies you have used to address staffing challenges:g. Please state any methods you have used to modify/adapt staffing patterns as a result of changes in program utilization or programming design:h. Please provide any additional relevant HR information:7. Financial informationa. What was your program revenue during the last quarter?b. How does your total program revenue compare with the same quarter 1 year ago?c. Is program paid on a per diem, contract program, or fee–for–service basis?d. Referring to item 1e, if you are experiencing a reduction in clients or have not been at capacity during the quarter, how much impact has client reduction had on your budget/financial implications?e. Referring to item 1e, if you are experiencing a reduction in clients or have not been at capacity during the quarter, what types of marketing strategies have you employed to address program utilization?f. Please provide any additional relevant financial data:8. Comprehensive overview and targeted areasa. After reviewing all the information in the report, what do you believe your program did well this quarter?b. What do you believe are the primary areas of concern that need to be addressed during the next quarter?c. Please discuss the methods that you will use to address these concerns:d. Please provide any additional comments about your findings based on this analysis:This tool was adapted from one that I originally developed for Spectrum Human Services, Inc. and Affiliated Companies while employed by the agency. The tool continues to be used by all the agency’s programs as a critical part of their quarterly and annual comprehensive program review process.As you can see, the Quarterly/Annual Comprehensive Data Report guides the data collection, analysis, and reporting process, promoting a comprehensive picture of the program through which systematic and ongoing program planning can occur. The report covers each of the major aspects of the program. The report is used on both a quarterly and an annual basis to provide guidance and to ensure comprehensive review. Whereas the report itself provides a summary of data, it does not take the place of other data–specific reports that provide additional information about specific aspects (e.g., contract compliance goals, quality improvement plan).SummaryThe collection, analysis, and reporting of data is a critical part of ongoing information sharing and is often essential to the sustainability of a program. Because information is not only powerful but empowering, information–sharing responsibilities must be delegated among multiple levels of program staff. This only serves as another mechanism by which to possibly engage program staff with the program as well as reinforce the role that each staff member has in a program’s success (and failures). In addition, collecting data without sharing it with all stakeholders who have a need to know is akin to buying a treadmill and never using it—it’s an investment that yields no return. Therefore, if data is collected, it must be shared. Furthermore, information sharing should be systematically guided to ensure that data is getting to all who need it. Particularly in the 21st century, when competition in mental health and human services is fierce and only the strong survive, effective data reporting can only help to ensure a program’s sustainability.CASE ILLUSTRATIONDavid’s semi–independent living program for adults with developmental disabilities had been operating for 1 year. David held a 1–year anniversary celebration with the program staff to mark the occasion, and he invited all the agency’s staff and administrators.David had put a great deal of effort into ensuring that all pertinent information about the program was continuously collected, analyzed, and immediately shared with all the people who had a right to and a need for the information—his staff being one of the most important recipients. To ensure that his staff were fully aware of all aspects of the program, David had insisted that all the staff collaboratively develop the process evaluation, outcomes evaluation, and initial quality improvement goals. In a
ITS4090 SOUTH Week 3 Applied System Analysis Question 3 Help
Using the Microsoft Word document you created in W2 Assignment 2, add to it by completing the following tasks:Create physi ...
ITS4090 SOUTH Week 3 Applied System Analysis Question 3 Help
Using the Microsoft Word document you created in W2 Assignment 2, add to it by completing the following tasks:Create physical DFDs.Create a physical data model.Discuss in detail the differences between the logical process and the physical process and data models.Discuss which objects your application should include.Draft the inheritance structure of your objects.Create class diagrams in UML 2.0.Submission Details:Support your responses with appropriate research and specific examples.Cite any sources in APA format.Name your document SU_ITS4090_W3_PP3_LastName_FirstInitial.doc.
INFO 321 American Public System Functional Dependencies and Sample Data Project
Assignment InstructionsTerm Project - week 8 - (17%): You were just hired to create a database to track blood draws at a l ...
INFO 321 American Public System Functional Dependencies and Sample Data Project
Assignment InstructionsTerm Project - week 8 - (17%): You were just hired to create a database to track blood draws at a lab.Discussions with the representatives focused on two entities, Blood Draws and Patients; the following key points were agreed:1 Each blood draw is assigned a unique DrawNum2 Each Patient has a unique PatID3 Each blood draw is taken from one patient, each patient may have more than one blood draw.4 No fields beyond those in the report / spreadsheet are neededDrawNum is a unique number assigned to each blood draw, Date is the date of the blood draw, Nvials is the number vials drawn, PatID is the ID for the patient – it is unique for each patient, fName is the patient’s first name, lName is the patient’s last name, DOB is the patient’s date of birthThe objective of this exercise is to demonstrate an understanding of basic concepts covered in the course. The exercise is a straight forward application of those concepts – there are no “hidden” complexities – should you identify something in the key points or data that adds complexity, contact the instructor before submission – you may be over thinking the exercise.The sample data may not represent all possible values – consider each field’s domain during the design.The objective is to replace the following report / spreadsheet with a relational database. The submission will consist of a word compatible document to record the design process, and an Access DB. (A matching Excel spreadsheet is attached. This is provided to reduce typos - do not assume the spreadsheet is a table in the normalized design.)Here is the un-normalized (UNF) relational schema (table) notation for the above report:BloodDraws (DrawNum, Date, Nvials, PatID, fName, lName, DOB)The functional dependencies are:DrawNum - - > Date, Nvials, PatID, fName, lName, DOBPatID - - > fName, lName, DOBThe specific tasks to perform are listed below, the percentage corresponds to the grade weight for each task: Organize your document to match the tasks.Name your document Last Name_TermProject (i.e. Smith_TermProject). When you are asked to provide an explanation or description, you must include sufficient content to demonstrate that you understand the definition, term, concept, etc. and how it applies to this exercise.SUGGESTION: Review the Terms and Concepts Forum, especially the Normalization One-To-Many example. There is also a normalization MP4 file that can be downloaded from the Resources section.Follow the below outline in your submission – include the section numbers – and a portion of each question in the submission.1) Review the existing report, functional dependencies and sample data (consider field domains and common knowledge) then document any assumptions you feel are appropriate (beyond those in the key points) and identify the initial entities (person, place, thing). (10%)2 Describe functional dependency and explain each row of the functional dependencies provided above (use field names and values). (15%) (you do not need to describe full, partial or transitive dependency in this task)3) Based on multiplicity – in plain English explain the relationship between the Entities provided in the above description – (either one-to-many, or many-to-many). (15%) 4) Design: all tables and fields must be specified at each normal form levela) First Normal Forum (1NF) assessment / action10%- Copy the 1NF definition from the text (include quotes and page number)- Assess the UNF table provided and if necessary, make the changes needed to conform to the 1NF definition. Explain any action taken and why.- Specify all 1NF table(s) using relational schema notation or spreadsheet format (see - the above example or page 111 Figure 4.2.6 of the text). Ensure primary keys are identified.- Explain how each table(s) meets the 1NF definition (use field names and values)b) Second Normal Form (2NF) assessment / action10%- Copy the 2NF definition from the text (include quotes and page number)- Assess the 1NF table(s) in the previous section and if necessary, make the changes needed to conform to the 2NF definition. Explain any action taken and why.- Specify all 2NF table(s) using relational schema notation or spreadsheet format. Ensure primary keys are identified.- Explain how each table meets the 2NF definition (use field names and values)c) Third Normal Form (3NF) assessment / action10%- Copy the 3NF definition from the text (include quotes and page number)- Assess the 2NF table(s) in the previous section and if necessary, make the changes needed to conform to the 3NF definition. Explain any action taken and why.- Specify all 3NF table(s) using relational schema notation or spreadsheet format. Ensure primary keys are identified.- Explain how each table meets the 3NF definition (use field names and values)5) Using the 3NF tables in your design, create an new MS Access database, load the sample data provided, and ensure any table relationship are established.Name your database Last Name_TermProject (i.e. Smith_TermProject). (5%).6) Create a Query, for the following request: List each Patient and their blood draws; include the following fields PatID, fName, lName, DrawNum, date, and Nvials, sort Ascending by lName. Name the Query BloodDraws. (5%)7) Create a Form: for New Patient Input, name the form NewPatient. (5%)8) Create a Report: List all Blood Draws (5%)Upload the database to the assignment area as one of the deliverables9) Submission content organization, clarity, spelling and grammar (10%) Contact the instructor with any questions.<o:p>
Portland Community College The Tri State Book Festival Thesis Paper
any thing is in the file look at it, when you understand you can start and I'm using a Mac so is better you are using appl ...
Portland Community College The Tri State Book Festival Thesis Paper
any thing is in the file look at it, when you understand you can start and I'm using a Mac so is better you are using apple computer when you get the question I will upload the word so you can correct what the directions say , and look for a long term tutor to help
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Colorado Technical University Program Design and Development Worksheet
Identifying Types of Data and Developing an Information-Sharing PlanReturn to the issue you are addressing from the Riverb ...
Colorado Technical University Program Design and Development Worksheet
Identifying Types of Data and Developing an Information-Sharing PlanReturn to the issue you are addressing from the Riverbend City: Examining the Ruby Lake Community media piece. Address the following for this assignment:Create a data reporting table for the program you are developing, similar to Table 15.3 on page 441 of your Program Development in the 21st Century textbook. Address all data types relevant for your selected program and structure data for each of the four key aspects:Responsibility.Timeframe.Methods.Recipients.Prepare an example of a data reporting tool that would help you assure the quality of program implementation and an understanding of whether or not your program objectives are being met. You may choose any aspects of project implementation on which to report data, such as staffing, budgeting, information systems, etcetera.Review the scoring guide for the assignment carefully to determine what is required to achieve a distinguished level of performance.Assignment RequirementsWritten Communication: Written communication should be free of errors that detract from the overall message.APA Formatting: The paper, including resources and citations, should be formatted according to current APA style and formatting guidelines.Length of Paper: 3–5 typed, double-spaced pages, not including the title page and references.Font and Font Size: Times New Roman, 12 point.Chapter 15 pg 419-449 Program Development in the 21st Century: An Evidence-Based Approach to Design, Implementation, and EvaluationISBN: 9781452238142By: Nancy G. CalleyBUT THE PROGRAM IS EFFECTIVEOn Tuesday afternoon, Reggie received a call from his contract manager telling him that his contract for mentoring at–risk youth would not be renewed next year because funding for children’s services had been reallocated. The contract manager went on to explain that the county was facing budget cuts and, therefore, had to make decisions about which programs to continue funding. While these decisions were difficult to make, they were based on identifying the most essential programs and those that had produced strong outcomes. Unfortunately, the mentoring programs were not viewed as essential nor was there evidence of their success.When Reggie heard this, he was flabbergasted. He explained to the contract manager that he had been conducting a program evaluation since his program’s inception 2 ½ years ago and that the outcomes were extremely positive. He quickly shared with her some of the highlights of his program:Teens who had been successfully matched with mentors: 342Percentage of mentees who graduated high school compared with the region’s 67% graduation rate: 94%Percentage of the mentees who pursued college: 68%Of the 32% who did not pursue college, percentage who pursued vocational training or were employed: 25%Percentage of the mentees who were either living at home or living independently: 92%Percentage of the mentees who had been involved in criminal activities post–mentoring services: less than 5%Percentage of the mentees who had experienced substance abuse problems: 6%; less than 3% required treatmentPercentage of mentees and parents/caregivers who identified having had a mentor as one of the most important aspects of their teenage years: 94% and 98%, respectivelyTotal cost per youth: $302 (compared with the $1,680–$6,440 costs related to much more intensive case management services and comprehensive community–based programs for court–involved youth—precisely what Reggie’s program was designed to prevent being needed)After quickly reviewing these outcomes with the contract manager, Reggie promised to send her the full set of evaluation data and the summary report. He told her that he had been planning to send her the report and evaluation results once he had 3 full years of data and said he was sorry that he had held onto the information.The contract manager shared her surprise with Reggie, stating that she wished she had known sooner about the program’s success, since it very well could have meant that the funds for mentoring programs would not have been cut. However, legislative action had already been taken, so the funding decisions were final. She did encourage Reggie to make the evaluation findings available and told him that they may still prove fruitful in the next funding cycle’s decision–making process.CONSIDERING REGGIEWhat did Reggie do right, and what mistakes did he make?If you were Reggie, what would you do next?What practices should Reggie put in place to ensure that relevant program information is shared with all who have a need to know on an ongoing basis?About This ChapterThis chapter’s focus is the significance of data, the critical information that data provides about all aspects of a program and organization, and most importantly, the invaluable need for comprehensive information sharing. We will examine both indirect and direct benefits of information sharing. In addition, we will explore the various types of data that are collected as part of comprehensive program development, including outcomes data, process evaluation data, human resource data, financial data, compliance and quality improvement data, and other pertinent data. We will explore the questions related to whom information should be shared with and why, as well as how frequently and through what medium information should be communicated. To guide comprehensive data collection and to illustrate the importance of examining all the program data in order to understand the total program operations, the Quarterly/Annual Comprehensive Data Report Tool is provided. The chapter concludes with a case illustration to further reinforce the content of the chapter, followed by a data report plan exercise and questions for reflection and discussion.STEP XIII: DEVELOP AN INFORMATION–SHARING PLANSignificance of Information SharingSeemingly, Reggie did everything right. At the implementation of a new program (i.e., mentoring), he designed and implemented a comprehensive process evaluation and a comprehensive outcome evaluation. He methodically collected and analyzed the data and, as a result, was intimately aware of the significant details of his program and the impact that it had made. However, he made one unforgiving mistake: He failed to share the data that he had collected and analyzed with all the people who had a need to know. As a result, his highly successful program would cease to operate.While Reggie’s example illustrates one of the toughest lessons about the business of which program development is a part, it is unfortunately not uncommon. As mental health and human service professionals have continued to become much more concerned with evaluation methods and other data collection activities, there continues to be a lag in following through once data has been collected. This can create obvious challenges, particularly since any data that is collected but not used should not have been collected in the first place, since it incurred a cost without producing a benefit.There are many other important lessons that Reggie’s vignette illustrates (see Box 15.1).BOX 15.1LESSONS FROM REGGIEComprehensive program evaluation must be conducted at the start of any new program.Outcome data is essential and, therefore, must be collected.Output data, such as cost–effectiveness, is essential and, therefore, must be collected.Program data must be shared frequently and regularly with all stakeholders.Collecting and analyzing data without sharing it with stakeholders may have devastating results.Collecting and analyzing data and not sharing the results may have the same effect as if no data had been collected or analyzed.Conducting various types of evaluation and sharing the findings with stakeholders may have a direct effect on your program’s sustainability.Whereas each of these lessons is significant, the more critical issue related to information sharing has to do with why data is collected in the first place. A large part of this answer is provided in previous chapters in the discussions related to program design, implementation, and evaluation and assessment. However, in addition to implementation and evaluation data, other data must be collected, such as client demographic data and financial data. Through comprehensive data collection and analysis, mental health professionals are empowered—empowered to better understand and manage their program. The notion that information is power can be clearly illuminated in program development efforts, particularly as the more knowledgeable the program developer is about the program, the easier it is to articulate the program to others. Conversely, without detailed information about the ongoing operations of the program, it’s more challenging both to communicate the program to others and to garner support for the program. Because the operations provided by human service organizations depend on people (Gibelman & Furman, 2008), the central role that ongoing communication, including information sharing and data sharing, plays in supporting a program’s operations is critical.More importantly, without effective means by which to communicate the work that mental health professionals provide and the impact that this work makes, mental health care itself is at risk. Morris et al. (2010) speak about this global issue from an Irish perspective:As with all areas of health care in Ireland and internationally, the health information deficit in the mental health services serves to impede the decisions of policymakers, health care workers, patients, and their families. It is imperative that mental health information becomes more accessible, useful, and comprehensible so that a culture of information gathering and use can be fostered both internationally and in Ireland. This information can then provide the evidence required for the provision of high–quality health care. (p. 360)Direct and Indirect BenefitsIn addition to what is listed above, there are numerous other benefits—both direct and indirect—that may result from sharing information related to program operations and outcomes with stakeholders. Indirect benefits refer to benefits that may not produce a direct result but that produce some impact, whereas direct benefits are those whose effect is concrete. For instance, by sharing information about program operations with staff, employees may have an increased level of engagement with the program/organization. This level of engagement may not be quantifiable, but it may mean that some employees choose to remain at the organization even when other more lucrative opportunities arise. Because you may not be aware of this impact, particularly since you may not have had any idea that someone was considering leaving, the impact is indirect—yet still significant. Alternatively, the sum effect of employee engagement may produce the direct benefit of employee retention, especially since employee retention results in decreased expenditures associated with hiring. This benefit can be tremendous, as any effective program developer and human resources manager can tell you exactly what it costs to replace an entry–level professional employee (e.g., case manager, therapist), which may range from $6,000 to $12,000. Thus, reducing unwanted employee turnover is an objective of most managers, because replacing an employee creates additional and often unnecessary expense to the organization that cannot be recouped. The costs are largely attributed to such administrative work as processing new applicants, hiring–related activities, coordination of employee benefits, and new employee orientation and training, among others. Considering these unnecessary costs, it is not difficult to see the benefit of staff retention.Box 15.2 provides a snapshot of other indirect and direct benefits related to information sharing.BOX 15.2INDIRECT AND DIRECT BENEFITS RELATED TO INFORMATION SHARINGIndirect BenefitsIncreased ownership in the program/organization among employees, resulting from increased knowledge of shared responsibilitiesCreation of a culture of transparency and shared commitmentMore flexible workforce that can more easily adapt to changes when needed as a result of being consistently informedDirect BenefitsMore productive and effective workforce as a result of increased knowledge of the businessProblems and deficits able to be quickly identified and resolved so that program/organization is continuously improvingMore competitive program and organization as a result of increased productivity and effectivenessIncreased business and growth opportunitiesProgram/organizational sustainabilityTypes of DataThere are multiple types of data that mental health and human service professionals collect as part of the program management process. Indeed, at times, some mental health professionals claim that they are more data collectors than mental health professionals—with responsibilities of collecting intake information and administering and collecting assessment data, treatment planning data, quality assurance data, contract compliance data, and so on. However, the issue is not one of data collector versus mental health professional but, rather, of mental health professional whose role very much involves data collection and management. Data is pertinent to our ability to effectively assess and treat clients, manage staff and other resources, manage programs and organizations, and continue to enjoy our livelihood. Or put even more succinctly, “Data collection is the sine qua non of effectiveness–based program planning” (Kettner, Moroney, & Martin, 2008, p. 19). Data collection and management, therefore, must be both respected and appreciated—not as an added job but as one of the most integral parts of our job. Once this has occurred, the power that information holds can be fully unleashed.While there is an enormous amount of data that may be collected, the primary reason for collecting the data has to do with gaining knowledge about all aspects of the program. However, all data that is collected must be fully justified. And as Gard, Flannigan, and Cluskey (2004, p. 176) remind us, the four questions that should guide the data collection process are as follows:What do we want to know?Why do we want to know it?What should we measure?How should we measure it?Knowing that all data that is collected has a specific use is essential. Often, the most essential data is collected for a process or outcome evaluation, human resource management, financial management, or contract compliance and quality improvement activities. While these data sets can be reviewed independently, they also must be thoroughly reviewed concurrently, thus forming a complete picture of the program. By doing so, a critical understanding of how each of the data sets interacts with the others can be achieved. Each of these various types of data sets is discussed next.Process Evaluation DataAs discussed in Chapter 12, a comprehensive process evaluation allows you to assess the myriad aspects of a program throughout its implementation. Depending on the type and scope of the process evaluation, a variety of data can be collected that includes client demographic and other descriptive characteristics and program outputs such as number and type of interventions provided, treatment length, and number and qualifications of staff providing treatment. In addition, coverage and equity data can be collected to provide specific information about who is being served and who is not being served.Demographic and descriptive data can be highly useful in gaining increased understanding and knowledge of your client population and, therefore, must also be collected and analyzed. This data has multiple uses, including as part of a process evaluation in identifying the target population and needs, increasing knowledge about program outcomes as related to client subpopulations and specific characteristics, advocacy efforts, and pursuing funding opportunities. Indeed, possessing specific and comprehensive knowledge about client populations is essential to effective program management. Box 15.3 provides a sample of possible types of demographic information that may be collected and reported.BOX 15.3SAMPLE OF DEMOGRAPHIC DATA CHARACTERISTICS FOR A TRANSITIONAL HOUSING PROGRAMAgeGenderRaceEthnicityLanguageDependent children (ages, gender, and special needs)Intimate partner statusSpecial needsAcademic historyEmployment historyHistory of homelessnessFamily, friends, and other supportsDemographic data provides rich information; however, it is often in collecting this type of data that mental health professionals run into trouble. Much too often, data is collected that is not needed—data that is not going to be used for a specific purpose. This goes back to the issue that no data should be collected that does not have a specifically identified use, because otherwise, you risk doing a disservice to those whom you are serving as well as wasting time and money For instance, each of the data elements in Box 15.3must serve a specific purpose, to justify why it is being collected. And in this case, each data element does serve a purpose, as illustrated in Table 15.1.Table 15.1Data Elements and RationaleIn addition to the specific purposes listed above, client demographic and descriptive data also can be used to learn specifically about program coverage and program equity—significant information for program developers, communities, and funding sources.Coverage data provide feedback on the extent to which a program is a) meeting the community need and b) reaching its target population. Monitored during program implementation, coverage data can be used not only to determine the extent to which the target group is being reached but also to ensure that individuals ineligible for the program are not served. (Kettner et al., 2008, p. 258)Similarly, equity data provides feedback on the various subgroups within a region to identify what, if any, disparities exist in regard to who is being served.Unless a program is targeted at a specific subgroup of a community, all other things being equal, geographical subareas and subgroups should be served by a program in roughly the same proportion as their composition in the community. Equity data can be used to ensure adequate coverage of subgeographical areas and subgroups during implementation or at the end of a program to document that a program is or is not reaching some geographical subarea or subgroup. Utilized in a performance measurement approach, coverage data provides stakeholders with information about the distribution of outputs, quality outputs, and outcomes across subgeographical areas and subgroups. (Kettner et al., 2008, pp. 258–259)In addition to client demographic and descriptive data, various types of information are collected specifically for the process evaluation to provide comprehensive information related to program implementation and operations and to promote further knowledge of outcomes. Several of the types of data that are collected as part of a process evaluation are reviewed in Chapter 12; so please refer back to that chapter if needed. Briefly, information about the implementation process itself is collected, including the number of resources (e.g., staff, money) allocated to the program, location of service delivery, and unexpected occurrences, to name a few.To reiterate, fidelity assessment may be included in the process evaluation in order to specifically assess the degree to which a treatment is delivered as intended. The five major areas of fidelity are treatment design, training, treatment, receipt of treatment, and treatment skill enactment (Borelli et al., 2005), and each requires specific data to be collected and analyzed. Treatment design data may include number and type of interventions and theoretical basis of treatment, while training may include the content and methods used to prepare staff to deliver the treatment and staff credentials. Treatment delivery data may include the number and type of interventions actually delivered, the time frame in which treatment was delivered, and the credentials of the individual(s) delivering the treatment. Other specific data that may be collected and analyzed in a fidelity assessment were also discussed in Chapter 12; so again, please refer back for a more comprehensive discussion of data types involved in a fidelity assessment.Because of the unique power that process evaluation data holds—including demographic and fidelity assessment data—sharing this information with stakeholders is critical. Client demographic data can be particularly useful not only in increasing knowledge of your particular target population or region but also in informing the broader field about client needs and characteristics. Therefore, this information is of great value to staff, funding agents, and other professionals. In addition, this data is pivotal to ongoing program planning efforts. For instance, program modifications may need to be made to a program that was originally designed for adolescents but that currently has a majority client population of older teens, since there are often significant developmental differences between the two groups. Likewise, a subpopulation of clients may not speak English, and therefore, specific program modifications and additional supports will be required to effectively serve this group. In addition, information about the type and scope of resources, such as staff credentials, administrative oversight, and adjunctive services, is essential not only to fully understanding all the aspects that contribute to the program’s success but also to understanding all that must be in place to effectively support the program. This information has specific relevance to planning, managing, and sustaining programs and is directly related to the program’s finances.Because treatment fidelity data speaks directly to the design of a particular treatment, sharing information about the degree to which fidelity has been maintained throughout implementation is critical for program staff. As such, this information provides direct feedback about their performance as well as about the success or failure of the program developer in planning for retaining treatment fidelity. In addition, this information is critical to clients as part of the informed consent process and as consumers of services with a right to know that they did receive what they were told they would receive. Moreover, this information is significant to funders, as it speaks to accountability and treatment design. Finally, this information is essential to other professionals and stakeholders in continued efforts to better understand treatment design and to understand the relationship between design, implementation, and outcomes.Outcomes Evaluation DataThe types of data collected in the outcomes evaluation are specific to the program’s objectives and, therefore, are unique to a program. However, there are also often common outcomes relevant to different types of programs. For instance, a treatment program for juvenile sex offenders and a second–chance academic program for young adults (i.e., a high school diploma program for young adults) may share the outcome of academic success. Whereas both programs may share an outcome related to academic success, the outcomes for juvenile sex offenders may also include recidivism (i.e., reoffending), improved family functioning, and increased independence.Outcomes are generated directly from the program design. For instance, family therapy and the development of a family support network are designed to improve family functioning and, therefore, must be evaluated to determine if the interventions did indeed lead to the anticipated outcomes. This interdependent nature between design, implementation, and evaluation is essential to understanding the complexity of programs and program development efforts, and therefore, highlighting these relationships in discussions of outcomes is helpful in increasing knowledge of the program’s efforts.In addition, because outcomes reflect a program’s success, they are critical to all stakeholders, including clients, staff, funding agents, community members, legislators, and professionals in the field. Staff are particularly interested in outcomes since they reflect another measure of their performance and, as such, provide another integral link to what they do and why they do it—a critical benefit to us all while working with individuals. However, whereas it is necessary and healthy for any organization to continuously evaluate outcomes, caution must be exercised in the degree to which outcomes are directly associated with employee performance. Indeed, the employee is a vehicle by which an intervention is delivered, and therefore, rarely is it the employee who failed but, rather, the intervention that failed.Funding sources and legislators are specifically interested in outcomes since this information is pertinent to decisions about continued and future funding. Community members are interested in outcomes, since they also have a particular interest in what works and what doesn’t. After all, as taxpayers, community members provide primary support for nonprofit services. Finally, other mental health professionals have a vested interest in the continued development of knowledge and understanding not only related to what works but why it works so that efforts can continue to develop and implement the most effective types of services and treatment.Continuous collecting, analyzing, and reporting of outcomes must occur to ensure that all stakeholders are well informed about outcomes. Without doing so, the dilemma that Reggie faced may become a reality for other mental health professionals—regardless of just how good the work they are doing is.Human Resources DataHuman resources data includes all data pertaining to staff (i.e., personnel). This includes but is not limited to such data as illustrated in Box 15.4.BOX 15.4EXAMPLES OF HUMAN RESOURCES DATAHiringJob descriptionsPerformance reviewsEducational recordsMedical informationSalary informationInsuranceCompany–sponsored retirement plan informationTax informationCitizenship informationStaff vacancies (unfilled positions)Training completed by staffStaff credentialsRetentionSeparationDisciplinary actionStaff challenges/problemsStaff commendations/rewardsSample of Human Resources DataHuman resource professionals maintain various documents and data pertaining to staff and are responsible for each staff member’s personnel file to ensure that confidential information remains confidential. The types of data that are private and, therefore, must be maintained in a confidential manner include medical and other personal information, salary, tax and citizenship information, and disciplinary action. Whereas this data is relevant to program managers/administrators, specific personal information is not relevant to program staff, and it is not permissible to disclose such information to staff who do not have a justified need to know. However, data related to staff that can be reported in aggregate and that is not considered confidential is highly useful to program developers/clinicians and all program staff, as it relates to program operations.This data, including staff vacancies, hiring, credentials, job descriptions, and training activity, is often most valuable to program managers and staff when examined as trend data—for instance, you might examine staff training needs versus training completion on a quarterly basis to strategize methods to address training needs. Or you may evaluate staff retention to determine what trends might exist related to when staff end their employment and the reasons why they choose to do so.By collecting and analyzing data related to staff, program managers are equipped with pertinent information about their staffing infrastructure. For example, if employee exit interview results indicate that 76% of staff voluntarily terminated their employment last year due to either not feeling connected to the program/organization or due to the lack of professional development activities the organization offered, this essential information can be used in staff retention efforts. However, this data is meaningful to all staff—not simply the manager/supervisors—particularly because sharing this type of information among staff and involving staff in retention efforts may serve to engage staff. As a result, the method by which future retention efforts are developed may in fact be a critical retention tool.Financial DataFinancial data comprise all the program’s finances—costs and revenue. Data such as employee salaries, office space, furniture, supplies, administrative support services, and the contract rate(s) are all essential financial data. Financial data is pertinent to program planning, management, and sustain–ability and, as a result, must be collected and analyzed frequently. Effective program developers and managers are keenly aware of the financial aspects of their program(s) and maintain close attention to financial details. Basic information that all mental health professionals should know is the per client cost of a program. This is typically gathered as part of the process evaluation (Byford et al., 2007) and provides essential information for increasing economic knowledge of the program. A basic method for computing this cost is to divide the number of clients served by the total cost of the contract amount or revenue produced. For instance, if the total contract amount for a mentoring program is $100,000 and you serve 260 youth, the cost per client is $384.62. This means that the cost of mentoring services per youth is approximately $384.62. Knowing this most basic economic information is critical to fully understanding a program and understanding the financial needs related to specific interventions. It has particular significance to maintaining funding, pursuing new funding, and advocacy efforts. Moreover, employees and other professionals are interested in this since it provides another critical perspective of programming and the financial aspects of interventions.By frequently sharing financial information, employees are able to feel more closely connected to the business that is their work—and, at least from my perspective, one of the most important businesses conducted on earth. That is precisely why it is so important that we protect it, and one form of protection is to demonstrate respect for our business by increasing the knowledge of all stakeholders about the business. Moreover, frequently sharing financial information with employees promotes transparency and contributes to a more engaged workforce.Two other groups with whom financial information has specific ramifications are community members and funders. In fact, sharing financial information with community members in concert with information about program outcomes may also be particularly helpful in garnering more financial support through donations and other means. In addition, sharing financial information with funding sources not only is required but also provides critical information that is useful in ongoing contract negotiations and decisions about releasing new funds.Compliance and Quality Improvement DataCompliance data refers to compliance with requirements of contracting organizations, accrediting bodies, licensing organizations, other oversight organizations, or self–imposed requirements. Compliance data often includes both outcome data and other types of data. For instance, contracting organizations are specifically interested in a program’s effectiveness in treating clients; however, they are often equally interested in the credentials of staff and the availability of services. Box 15.5 provides a sample of contract compliance data.BOX 15.5SAMPLE OF CONTRACT COMPLIANCE DATAAcceptance rate of all referred clientsLength of time from initial referral to program admissionNumber of clients served annuallyPercentage of clients successfully treated in accordance with preestablished success criteriaPercentage of clinicians with a master’s degree or above in major mental health discipline and licensure as a mental health therapistPercentage of clients discharged prematurelyCompliance data often overlaps with process evaluation data, because contractors have a vested interest in ensuring that programs/models are implemented as designed. Because contract compliance data reflects the degree to which goals or targets are met, contractors or other oversight organizations dictate the required target thresholds. For some issues, such as the percentage of qualified therapists, there is no tolerance for noncompliance, meaning the required compliance rate is 100%; for other areas, compliance may be set at less than 100% or at a specific number. For instance, the percentage of clients discharged prematurely (without completing the program) may be set at 85%, the expected length of time between referral and program admission may not exceed 48 hours for any client, and there may be a requirement to serve a minimum of 160 clients per year.Contract compliance data has obvious implications. Failure to comply with performance expectations may result in the cancellation or nonrenewal of a contract. Therefore, collecting, analyzing, and sharing this data with all program stakeholders is critical to the program’s sustainability.Quality improvement data is required by accrediting bodies and is often a standard part of organizational practices and, thereby, self–imposed by organizations. Quality improvement speaks to the specific areas in which improvement is sought and the improvement goals. While it is a standard part of business operations today, quality improvement originated in Japan (Senge, 2006) in the 1940s. Unlike contract compliance goals that are predetermined by contractors or other oversight organizations, quality improvement goals often evolve organically from data analysis findings. For instance, if exit interview data indicated that staff chose to leave the organization due to lack of engagement, a quality improvement goal might be developed to address this specific issue. The goal, such as 95% of staff will be engaged with the program within 6 months of employment as measured by the Employee Engagement Scale (hypothetical standardized assessment instrument—with sound psychometric properties, of course), is developed by program staff with specific strategies by which to attain it. Through the collection and analysis of various program data, staff are able to quickly identify areas in need of improvement and can then develop means by which to address these areas.The structure surrounding quality goals may vary considerably from organization to organization, with some organizations using quality improvement committees to lead quality improvement efforts and others requiring a specified number of quality goals in key areas (e.g., client satisfaction, community relations). However, what is of greatest import is not how quality improvement efforts occur but, rather, that they occur and that their purpose is fully understood by all stakeholders. This is because of what quality improvement efforts reflect—a commitment to quality and continuous improvement.Whereas contractors and/or accrediting bodies often require reporting of both contract compliance data and quality improvement data—even when not required—it is wise to share this data with oversight organizations since it reflects the program/organization’s dedication to quality. Equally important is that this data is shared frequently and with all staff. Contract compliance and quality improvement data are byproducts of the work of staff, and therefore, all staff must have open and continuous access to this data. By ensuring that this occurs, staff are able to better understand the critical issues that compose their program and are able to more effectively participate in ongoing improvement efforts.Other Pertinent DataIn addition to the five major areas just discussed, there are other types of data that must be collected and shared with various groups. Other client data, such as satisfaction with services, is not only required by several accrediting bodies and/or contractors but particularly meaningful to program staff and necessary for program improvement efforts. Employee information, such as employee satisfaction, engagement, and retention each provide pivotal data for use in continuous improvement efforts. In addition, organizational structures and decision–making processes are pertinent areas to both employees and funders, since they directly impact efficiency and effectiveness and provide additional guidance to employees.Whereas there are lots of other types of data that are pertinent to collect, analyze, and share with others, you must be guided by the premise of collecting and analyzing the right data and sharing that data as frequently as needed with all who need to receive it. By doing this, data collection and information sharing can be highly efficient and can contribute to the overall effectiveness of the program operations.Data ReportingWE’RE DOING WHAT?At a recent fundraising event hosted by a nonprofit agency, one of the agency’s board members was speaking with Kyle, one of the agency clinicians. The board member shared his excitement about the new contract on which the program director (Kyle’s supervisor) was bidding and discussing how, if awarded, the contract could result in a significant expansion of services for the agency. Kyle smiled and agreed about the positive prospects the new contract could bring and then delicately extricated himself from the conversation, going in search of one of his program colleagues. On finding a fellow clinician, he recounted the conversation he had had with the board member, stating that he had no idea that his supervisor was pursuing a new contract. Kyle’s colleague was not aware of this either. Flummoxed by the apparent lack of information they both had about their program, they agreed they would need to follow up with their supervisor in the morning.Have you ever experienced this type of awkward situation? Someone knows something about your program/agency that you should know as well, and after hearing this information from another source, you feel uncomfortable and not wholly aware of why you weren’t informed. Unfortunately, this happens all too often and typically not because there is a motive to withhold information; rather, in the absence of any type of information–sharing structure, information is not properly or effectively shared. In other words, there must be a method to your madness, and this is particularly true where information sharing is concerned.This can be easily accomplished by putting a specific structure in place to ensure that information is effectively shared. By doing this, the extensive work accomplished in the data collection and analysis process can be fully realized. In terms of developing a basic structure to promote effective sharing of information, each of the following aspects of data reporting should be established:The individual(s) responsible for reporting the dataThe time frames in which data will be reportedThe means by which data will be reportedThe recipients who will receive the various types of dataEach of these issues is discussed below.Responsibilities for Data ReportingAssigning responsibilities is a prerequisite for accountability—in any business or other endeavor. Therefore, the starting point for effective information sharing lies first and foremost in identifying who is responsible for reporting what type of data/information. Because there are often various types of data (as described above), there may be various individuals assigned to reporting specific types of data to different groups. For instance, clinicians might report program outcomes to the program staff, whereas the chief financial officer might report the program’s financial status to the board of directors. However, as I have emphasized throughout this text, program developers/mental health professionals must have comprehensive knowledge about the programs with which they are involved. And there is no better indicator of the degree of knowledge a program developer has about her/his program than her/his ability to report on the various data related to the program. During those times when program developers are not directly reporting program data, they must be fully aware of the data and its implications.Along these same lines, all program staff should be knowledgeable about the various aspects of their programs—regardless of the degree to which they directly interact with specific data. This is because information does often translate into power, and thus, by being empowered to report on various data, the staff person is gaining new knowledge and is given an opportunity to develop new skills related to reporting data. Therefore, data reporting must not be simply the role of one person (e.g., program developer/director) but a role shared by many and one in which assignments change related to the type of data reported by the specific staff person. By spreading out responsibilities for data reporting among all staff persons, program managers may in fact engage more staff with the program and the organization while providing specific opportunities for professional development. Table 15.2 provides an example of how the small staff of a gambling prevention program for teens shares data reporting responsibilities.The five staff persons illustrated in Table 15.2compose the entire program staff: Kimberly (program manager), LaShawn, Rhonda, Dorothy, and Roma (prevention specialists). Each staff person is responsible for regularly leading the collection, analysis, and reporting of their assigned data to the rest of the program staff for a year at a time. By using this type of schema for sharing data–reporting responsibilities, Kimberly is able to ensure that each of her staff members is highly knowledgeable about the major aspects of the program. Regardless of the manner in which data reporting responsibilities are assigned, the primary objective is that responsibilities are shared among program and organizational staff to ensure that everyone who is a part of the program is knowledgeable about the various aspects of the program.Table 15.2Data Reporting AssignmentsReporting Time FramesEstablishing time frames for reporting data can be as important to ensuring that information is shared as is assigning responsibility for data reporting. As you witnessed by Reggie’s example, his program may have continued if short–term and frequent time frames for reporting had been established.Time frames provide another necessary level of structure to the information–sharing process and another level of reinforcement for accountability. Whereas data about each major area of a program should minimally be shared on a quarterly basis with all program staff, specific types of data may need to be shared much more frequently, depending on the data type and special circumstances. For instance, if program revenue that is paid on a fee–for–service basis has fallen below the annual projected revenue, resulting in the possibility of reducing a staff position unless the revenue improves quickly, revenue data may require analysis and reporting on a weekly basis. On the other hand, it may not be appropriate to report on outcome goals more frequently than each quarter, because the limited number of outcomes occurring on a weekly or biweekly basis may not reflect aggregate outcome data and will, therefore, skew the actual outcomes picture as a result of focusing on a few outcomes rather than the total outcomes.Methods for Data ReportingOnce decisions about who is responsible for reporting specific data are made and the time frames within which data will be reported have been established, the methods by which data will be reported must be identified. The methods for reporting specific types of data may be varied based on the recipients, and multiple methods may be used to communicate the same data. Methods for reporting data include but are not limited toverbal communication in meetings or other group forums,presentations of data in meetings or other group forums,comprehensive written reports,written snapshots of data (i.e., data briefs),electronic snapshots of data posted on the Intranet,annual reports, andwebsite postings.Methods should be selected based on effectiveness to reach the intended recipients and the rationale for sharing the specific data. For instance, verbal communication of data in biweekly staff meetings may be a highly effective method for ensuring that critical information is frequently shared with program staff. However, quarterly board of directors meetings may require both a formal presentation of data as well as an accompanying report to ensure that the information is effectively communicated and that the information provided is thorough enough to allow for effective governance.Because effective communication is critical to information sharing, methods for reporting data should be continuously evaluated to ensure that they are working. Simply because the development of a presentation involves quite a bit of work and contains significant information, that does not automatically translate into the information being effectively communicated. Gathering the input of recipients about preferences of communication methods, engaging in follow–up dialogue to discuss information shared, and engaging in more rigorous evaluation of the effectiveness of information sharing can be helpful in ongoing efforts to ensure productive information sharing.Data RecipientsFinally, the various groups of individuals who will receive the data must be identified—the data recipients. Technically, data recipients are all stakeholders. This includes but is not limited to program staff, clients, administrators, contractors, accrediting bodies, the governing board, and the public. Each of these groups has a need to know specific program information, and as such, program developers have an obligation to regularly share data with each group. Further, for some groups, there are specific requirements about what data must be reported, how often it must be reported, and in what format it must be reported. For instance, written reports on contract compliance data might be required on a semiannual basis by contractors. Alternatively, while specific requirements may not exist regarding information sharing with program staff, best practices may indicate that specific program data is shared on a weekly basis to ensure a well–informed workforce.The basic rule of thumb regarding who should receive program information is that anyone who has a need to know should know, and they should know as soon as possible. This will ensure that what happened to Kyle does not happen to other clinicians or program staff—that is, learning about a possible significant change in the program from a board member.As you can see, all these aspects of data reporting are interconnected—responsibilities for data reporting, time frames, methods, and recipients. By thoroughly considering each, program managers posture themselves to effectively share information and data with their stakeholders. The next section provides specific examples and tools to aid in accomplishing this.Data Protections and SafeguardsBecause the bulk of data collected by mental health professionals is related to those whom we serve, our first obligation is to protect the privacy of our clients and to ensure that information about them is maintained in a confidential manner. There are several state and federal laws that set forth rules on this—most notably, HIPAA (1996) and HITECH (2009), which provide strict guidance for the collection, storage, protection, and use of health–related information, with strong protections for the privacy of individuals’ health information (Mai et al., 2007). In addition, federal guidelines regarding the protection of substance use information—42 CFR Part 2—confidentiality of alcohol and drug abuse records, and federal and state therapist patient confidentiality laws provide specific guidance. If you are not wholly familiar with the federal laws regarding client/patient protected health information, this is an area with which you will need to become quite familiar.All data collection must be conducted in accordance with legal statutes and with all necessary protections in place. In addition, all research activities must be conducted with necessary oversight procedures in place, including authorization and ongoing monitoring from an institutional review board/human subjects committee. Organizations must have comprehensive policies and procedures in place specifically dealing with client confidentiality, data storage and maintenance, data sharing, and reporting through release and disclosure. Organizations also must ensure that required hardware and other electronic safeguards are in place to protect electronic data.Just as both state and federal laws and other guidance regarding client confidentiality have changed dramatically over the past several years, with continued changes in electronic technology and continued development of knowledge related to data collection and protection, change will likely continue to occur. It is essential that mental health professionals maintain current knowledge regarding the rules that govern the collection, use, and storage of confidential information to ensure appropriate guidance in this area.Developing the Data Reporting PlanAs discussed earlier, without a solid framework to structure data reporting and information sharing, it is likely that pertinent information will not be shared with those who have a need to know or that information will not be shared in a timely fashion. Therefore, structure is needed to guide these activities. The Annual Data Reporting Plan in Table 15.3 provides an example of how to structure data reporting by addressing each of the four key aspects (i.e., responsibility, time frame, methods, recipients). Please note as you review Table 15.3 that the time frames and methods are intended as a guide only—contractors, organizational policies, and other oversight organizations may require more stringent reporting time frames and methods.Table 15.3Annual Data Reporting PlanWhereas the Annual Data Reporting Plan illustrates the broad data types that should be shared, there are numerous details that are needed to guide this type of data collection, analysis, and reporting. The Quarterly/Annual Comprehensive Data Report Tool (Box 15.6) was developed precisely to guide and provide essential structure to the data collection, analysis, and reporting process.BOX 15.6QUARTERLY/ANNUAL COMPREHENSIVE DATA REPORT TOOLProgram:Data reporting time frameReporter:1. Clients serveda. Total number served during report period:b. Total program capacity:c. Is program capacity limited by contract?d. If unlimited, what is your target goal for number of clients for the year?e. How does current number of clients compare with last quarter or last year?f. If reporting quarterly data, how does this quarter’s data compare with the same quarter 1 year ago?g. What types of trends in client numbers exist?h. Provide evidence for item g trends:i. Reasons/explanations for client population trends:j. Projected number of clients to be served next quarter:2. Clients discharged/released/no longer in programa. Provide the definition of successful termination for your program:b. Number of successful terminations during report period:c. Percentage of total terminations that were successful:d. Number of unsuccessful terminations during report period:e. Percentage of total terminations that were unsuccessful:f. Reasons for unsuccessful terminations:g. Please state how those numbers compare with last quarter/last year data:h. If reporting quarterly data, how does this quarter’s termination data compare with the same quarter 1 year ago?i. Any trends identified in terminations (e.g., increase in unsuccessful terminations due to truancy during the summer):j. Any program plans, enhancements, or changes that you made as a result of the successful or unsuccessful discharge data:3. Contract compliancea. What percentage of contract compliance items were you in full (100%) compliance with this reporting period?b. Please state each of the specific contract compliance items that were not in full compliance during report period:c. How does the percentage of contract compliance results compare with last quarter/last year?d. If reporting quarterly data, how does the percentage of contract compliance results compare with the same quarter 1 year ago?e. Please state any program plans to address any contract compliance challenges:4. Assessmentsa. What standardized assessment instruments, if any, are used within your program?b. How are the results used in individual treatment planning?c. If you provide an assessment at entry and at termination, please discuss the differences/similarities in scores:d. Please discuss your aggregate program assessment data for report period:e. If applicable, please discuss how you have used the aggregate assessment data to make program changes:5. Quality improvement statusa. Please report on the results of each program outcome goal:b. Please discuss how you have used the results of your quality improvement data:c. Please discuss how your quality improvement activities have been used in program changes and program development:d. Please discuss the frequency with which your program’s quality plan changes and why:e. How often is quality improvement data reviewed with staff?f. Please state the methods that you use to promote and share quality improvement initiatives with program staff:6. Human resourcesa. What is your current staff vacancy rate?b. What is your staff turnover rate during the report period?c. How does your staff turnover rate compare with last quarter/last year?d. How does your staff turnover rate compare with the same quarter last year?e. Please share any strategies that you have utilized to increase or impact employee retention or satisfaction?f. Please state any plans or successful strategies you have used to address staffing challenges:g. Please state any methods you have used to modify/adapt staffing patterns as a result of changes in program utilization or programming design:h. Please provide any additional relevant HR information:7. Financial informationa. What was your program revenue during the last quarter?b. How does your total program revenue compare with the same quarter 1 year ago?c. Is program paid on a per diem, contract program, or fee–for–service basis?d. Referring to item 1e, if you are experiencing a reduction in clients or have not been at capacity during the quarter, how much impact has client reduction had on your budget/financial implications?e. Referring to item 1e, if you are experiencing a reduction in clients or have not been at capacity during the quarter, what types of marketing strategies have you employed to address program utilization?f. Please provide any additional relevant financial data:8. Comprehensive overview and targeted areasa. After reviewing all the information in the report, what do you believe your program did well this quarter?b. What do you believe are the primary areas of concern that need to be addressed during the next quarter?c. Please discuss the methods that you will use to address these concerns:d. Please provide any additional comments about your findings based on this analysis:This tool was adapted from one that I originally developed for Spectrum Human Services, Inc. and Affiliated Companies while employed by the agency. The tool continues to be used by all the agency’s programs as a critical part of their quarterly and annual comprehensive program review process.As you can see, the Quarterly/Annual Comprehensive Data Report guides the data collection, analysis, and reporting process, promoting a comprehensive picture of the program through which systematic and ongoing program planning can occur. The report covers each of the major aspects of the program. The report is used on both a quarterly and an annual basis to provide guidance and to ensure comprehensive review. Whereas the report itself provides a summary of data, it does not take the place of other data–specific reports that provide additional information about specific aspects (e.g., contract compliance goals, quality improvement plan).SummaryThe collection, analysis, and reporting of data is a critical part of ongoing information sharing and is often essential to the sustainability of a program. Because information is not only powerful but empowering, information–sharing responsibilities must be delegated among multiple levels of program staff. This only serves as another mechanism by which to possibly engage program staff with the program as well as reinforce the role that each staff member has in a program’s success (and failures). In addition, collecting data without sharing it with all stakeholders who have a need to know is akin to buying a treadmill and never using it—it’s an investment that yields no return. Therefore, if data is collected, it must be shared. Furthermore, information sharing should be systematically guided to ensure that data is getting to all who need it. Particularly in the 21st century, when competition in mental health and human services is fierce and only the strong survive, effective data reporting can only help to ensure a program’s sustainability.CASE ILLUSTRATIONDavid’s semi–independent living program for adults with developmental disabilities had been operating for 1 year. David held a 1–year anniversary celebration with the program staff to mark the occasion, and he invited all the agency’s staff and administrators.David had put a great deal of effort into ensuring that all pertinent information about the program was continuously collected, analyzed, and immediately shared with all the people who had a right to and a need for the information—his staff being one of the most important recipients. To ensure that his staff were fully aware of all aspects of the program, David had insisted that all the staff collaboratively develop the process evaluation, outcomes evaluation, and initial quality improvement goals. In a
ITS4090 SOUTH Week 3 Applied System Analysis Question 3 Help
Using the Microsoft Word document you created in W2 Assignment 2, add to it by completing the following tasks:Create physi ...
ITS4090 SOUTH Week 3 Applied System Analysis Question 3 Help
Using the Microsoft Word document you created in W2 Assignment 2, add to it by completing the following tasks:Create physical DFDs.Create a physical data model.Discuss in detail the differences between the logical process and the physical process and data models.Discuss which objects your application should include.Draft the inheritance structure of your objects.Create class diagrams in UML 2.0.Submission Details:Support your responses with appropriate research and specific examples.Cite any sources in APA format.Name your document SU_ITS4090_W3_PP3_LastName_FirstInitial.doc.
INFO 321 American Public System Functional Dependencies and Sample Data Project
Assignment InstructionsTerm Project - week 8 - (17%): You were just hired to create a database to track blood draws at a l ...
INFO 321 American Public System Functional Dependencies and Sample Data Project
Assignment InstructionsTerm Project - week 8 - (17%): You were just hired to create a database to track blood draws at a lab.Discussions with the representatives focused on two entities, Blood Draws and Patients; the following key points were agreed:1 Each blood draw is assigned a unique DrawNum2 Each Patient has a unique PatID3 Each blood draw is taken from one patient, each patient may have more than one blood draw.4 No fields beyond those in the report / spreadsheet are neededDrawNum is a unique number assigned to each blood draw, Date is the date of the blood draw, Nvials is the number vials drawn, PatID is the ID for the patient – it is unique for each patient, fName is the patient’s first name, lName is the patient’s last name, DOB is the patient’s date of birthThe objective of this exercise is to demonstrate an understanding of basic concepts covered in the course. The exercise is a straight forward application of those concepts – there are no “hidden” complexities – should you identify something in the key points or data that adds complexity, contact the instructor before submission – you may be over thinking the exercise.The sample data may not represent all possible values – consider each field’s domain during the design.The objective is to replace the following report / spreadsheet with a relational database. The submission will consist of a word compatible document to record the design process, and an Access DB. (A matching Excel spreadsheet is attached. This is provided to reduce typos - do not assume the spreadsheet is a table in the normalized design.)Here is the un-normalized (UNF) relational schema (table) notation for the above report:BloodDraws (DrawNum, Date, Nvials, PatID, fName, lName, DOB)The functional dependencies are:DrawNum - - > Date, Nvials, PatID, fName, lName, DOBPatID - - > fName, lName, DOBThe specific tasks to perform are listed below, the percentage corresponds to the grade weight for each task: Organize your document to match the tasks.Name your document Last Name_TermProject (i.e. Smith_TermProject). When you are asked to provide an explanation or description, you must include sufficient content to demonstrate that you understand the definition, term, concept, etc. and how it applies to this exercise.SUGGESTION: Review the Terms and Concepts Forum, especially the Normalization One-To-Many example. There is also a normalization MP4 file that can be downloaded from the Resources section.Follow the below outline in your submission – include the section numbers – and a portion of each question in the submission.1) Review the existing report, functional dependencies and sample data (consider field domains and common knowledge) then document any assumptions you feel are appropriate (beyond those in the key points) and identify the initial entities (person, place, thing). (10%)2 Describe functional dependency and explain each row of the functional dependencies provided above (use field names and values). (15%) (you do not need to describe full, partial or transitive dependency in this task)3) Based on multiplicity – in plain English explain the relationship between the Entities provided in the above description – (either one-to-many, or many-to-many). (15%) 4) Design: all tables and fields must be specified at each normal form levela) First Normal Forum (1NF) assessment / action10%- Copy the 1NF definition from the text (include quotes and page number)- Assess the UNF table provided and if necessary, make the changes needed to conform to the 1NF definition. Explain any action taken and why.- Specify all 1NF table(s) using relational schema notation or spreadsheet format (see - the above example or page 111 Figure 4.2.6 of the text). Ensure primary keys are identified.- Explain how each table(s) meets the 1NF definition (use field names and values)b) Second Normal Form (2NF) assessment / action10%- Copy the 2NF definition from the text (include quotes and page number)- Assess the 1NF table(s) in the previous section and if necessary, make the changes needed to conform to the 2NF definition. Explain any action taken and why.- Specify all 2NF table(s) using relational schema notation or spreadsheet format. Ensure primary keys are identified.- Explain how each table meets the 2NF definition (use field names and values)c) Third Normal Form (3NF) assessment / action10%- Copy the 3NF definition from the text (include quotes and page number)- Assess the 2NF table(s) in the previous section and if necessary, make the changes needed to conform to the 3NF definition. Explain any action taken and why.- Specify all 3NF table(s) using relational schema notation or spreadsheet format. Ensure primary keys are identified.- Explain how each table meets the 3NF definition (use field names and values)5) Using the 3NF tables in your design, create an new MS Access database, load the sample data provided, and ensure any table relationship are established.Name your database Last Name_TermProject (i.e. Smith_TermProject). (5%).6) Create a Query, for the following request: List each Patient and their blood draws; include the following fields PatID, fName, lName, DrawNum, date, and Nvials, sort Ascending by lName. Name the Query BloodDraws. (5%)7) Create a Form: for New Patient Input, name the form NewPatient. (5%)8) Create a Report: List all Blood Draws (5%)Upload the database to the assignment area as one of the deliverables9) Submission content organization, clarity, spelling and grammar (10%) Contact the instructor with any questions.<o:p>
Portland Community College The Tri State Book Festival Thesis Paper
any thing is in the file look at it, when you understand you can start and I'm using a Mac so is better you are using appl ...
Portland Community College The Tri State Book Festival Thesis Paper
any thing is in the file look at it, when you understand you can start and I'm using a Mac so is better you are using apple computer when you get the question I will upload the word so you can correct what the directions say , and look for a long term tutor to help
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