HCS 490 week 4 assignment

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Resource: Demographic Paper grading criteria located on the student website

You have been designated by the senior management team at a community hospital to write a summary on the effects of changes in population demographics on the needs and services for a selected population.

Identify the population on which your case study will focus, such as the aging population, patients with a particular chronic disease, children, patients with AIDS, patients requiring long-term care, or emergency management.

Write a 1,050- to 1,400-word paper about the demographic you selected. Include the following in your paper:

·  Identify the targeted population.

·  Gather data about the population demographics.

·  Describe the general impact that changing demographics may have on the health care market.

·  Why and how will changes in the demographics of this population affect health care?

·  Identify two key health care-related challenges to this population, such as increases in health care costs, increases in prescription drug costs, or the need for in-home medical care.

·  Describe how a chronic disease wellness program may affect the costs for this demographic.

·  What do the demographics tell you about the marketing needs or services needed for this population?

·  How can the individual patient, the community, and society as a whole address these challenges?

Include a minimum of three peer-reviewed references, not including the textbook.

Format your paper consistent with APA guidelines.


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FROM THE EDITOR we have the technology I was surrounded by obstetricians—at least 3o of them. No. this was not an anxiety dream about childbirth. I was sitting in a hotel conference room, and these obstetricians were talking about what could go wrong and what should go right in obstetrical care. It was ig86, and this group was one of several gathered by the Joint Commission on Accreditation of Healthcare Organizations and charged with recommending indicators of quality. Robert From berg Edilor-in-Chief This was a turning point in the history of quality improvement in health care. Avedis Donabedian had just published the third and final volume of Explorations in Quality Assessment and Monitoring. or questions about HFMA publications to Hromberg@hfma.org. electronic health record. The EHR is key to afoiding The Joint Commission was putting these concepts to work as part of a truly visionary strategy: identiiying a core set of clinical quality indicators for hospitals nationwide that would be used internally and externally to monitor performance and identify situations requiring further evaluation. Fast-fon\'ard 19 years. I am sitting in another hotel conference room. Gary Mecklenburg, president and CEO of Northwestern Memorial HealthCare, is speaking to several hundred people at the Nonprofit Health Care Investors Conference put on by Citigroup, the American Hospital Association, and HFMA. He says, "For my entire career, the electronic health record has heen right around the corner." The audienee chuckles in agreement. He continues, "Well, the time is now, because the electronic health record is just around the corner." Less than tbree years later, Donald Berwick published "Continuous Improvement as an Ideal in Health Care," a commentaiy in the New England Journal of Medicine that drew on tbe tenets of Edwards Demingto suggest, with stunning common sense, tbat problems with healthcare quality had more to do with good people trapped in bad processes than with inept people. Soon you could barely enter a bospital conference room without seeing an Ishikawa diagram or a clinical path on a flip chart. The local and national efforts to improve quality were fervent, smart, and necessary. But they 38 In the years that followed, the means of addressing quality have evolved, and the intensity of attention to quality has waned and waxed {the latter most recently catalyzed by two Institute of Medicine reports on patient safety). But the need for technology support has never lessened. The three words that best capture that support are offering a framework for defining quaUty, identi fying criteria of quality, and using those criteria to monitor and improve pertbrmance. Perhaps tbe most memorable aspect of Donabedian's work was tbe division of quality indicators into three categories: structure, process, and outcome. LET US K N O W Send your commenis lacked supporting technology. Too often, retrospective monitoring meant sifting through stacks of paper patient records and recording on a paper check sheet the presence or absence of a quality indicator. Too often, concurrent monitoring meant glancing at a paper clinical path clipped to a patient's chart. FEBRUARY 2006 healthcare linancial management problems by using decision-support tools and is key to having the necessary information to truly monitor healthcare processes and outcomes within a hospital or externally through national accreditation or pay for performance. And, as a result, so is truly effective quality improvement. I hope tbe next time I'm sitting in a conference room full of obstetricians, they will be comparing quality success stories. Or perhaps this time I will be having an anxiety dream ahout childbirth.* A C C E S S I N t i l t Access To Specialty Care And Medical Services In Community Health Centers Lack of access to specialty services is a more important problem for CHCs than previously thought. by Nakela L. Cook, LeRoi S. Hicks, A. James O'Malley, Thomas Keegan, Edward Guadagnoli, and Bruce E. Landon ABSTRACT: Although community health centers (CHCs) provide primary health services to the medically underserved and poor, limited access to off-site specialty services may lead to poorer outcomes among underinsured CHC patients. This study evaluates access to specialty health services for patients receiving care in CHCs, using a survey of medical directors of all federally qualified CHCs in the United States in 2004. Respondents reported that uninsured patients had greater difficulty obtaining access to off-site specialty services, including referrals and diagnostic testing, than did patients with Medicaid, Medicare, or private insurance. [Health Affairs 26, no. 5 (2007): 1459-1468; 10.1377/hlthaff.26.5.1459] D EFICIENCIES IN THE QUALITY OF HEALTH CARE and disparities in quality according to patients' race and socioeconomic status are salient issues for community health centers (CHCs), which provide a safety net of support for underserved and uninsured Americans.' CHCs were first funded in 1965 and are required to provide a defined set of medical services for all residents of their service areas, regardless of their ability to pay- More than 1,000 federally qualified CHCs nationwide at more than 5,000 sites collectively serve more than fifteen million people, many of whom are racial or ethnic minorities, low income, uninsured, or insured through Medicaid.^ The Bush administration began an initiative in 2002 to expand CHC sites nationwide, to improve access to medieal eare for uninsured people/ As CHCs assume responsibility for a greater proportion of the care of the unin- Nakela Cook is a clinical and research fellow in medieine in the Cardiology Division, Massachusetts General Hospital and a health services research fellow in the Health Care Policy Department, Harvard Medical School, both in Boston. LeRoi Hicks (hieks&hcp.med.harvard.edu) is an assistant professor of medicine in the Department of Medicine, Brigham and Women's Hospital, in Boston, andan instructor of heakh carcpolicy in Harvard Medical Schools Health Care Policy Department. James O'Mallcy is an associate professor of statistics in the Health Cart Policy Department. Thomas Keegan is a project manager in the department. Edward Guadagnoli is a professor of health care policy there, and Bruce Landon is an associate professor of health carepolicy. H E A L T H A F F A I R S - Volume 26, Number 5 DOU0.\i77/h\lhaR.26.5.l459 ^2007 Pro,m HOPE-Thc People to-PcopUUcahh Foundation Jnc. I459 D A I A W A 1 C H sured, many are concerned that the capacity of the nation's CHCs to care for them beyond primary services will be inadequate.^ In particular, quahtative studies suggest that some CHC patients have difficulty accessing services that are not provided directly hy the CHC, such as specialty care or diagnostic testing.^ These data suggest that some specialty service providers refuse to provide services to uninsured or Medicaid patients or require up-front payment for their services. Lack of access to specialty services among CHC patients might contribute to poorer outcomes among the uninsured.' However, few empirical data exist on access to specialty services for CHC patients. We surveyed the medical directors of federally qualified health centers (FQHCs) in 2004, to better understand the challenges they face in obtaining access to off-site specialty services. We address two important questions: First, what is the relationship between perceived access to specialty medical and mental health services and patients' insurance status? Second, what other factors are associated with better or worse access to off-site specialty services for uninsured and Medicaid patients? ,, , „ ^ , Study Data And Methods ' • Survey sample and administration. Using data supphed in 2002 to collaborators at the National Association of Community Health Centers (NACHC), we identified 814 FQHCs nationally.^ Of these, eighty-nine centers were new grantees in 2002, estabhshed under President Bush's health center initiative, and 725 were previously established grantees. Surveys were mailed to the medical director, fol lowed by reminder cards and a second copy of the survey. Nonresponders were then contacted by phone. Data collection took place during March-July 2004. • Survey questionnaire. The survey instrument elicited closed-ended responses on a scries of topics related to access to specialty services. We adapted vahdated questions from a prior survey of CHCs associated with academic medical centers and created additional items based on discussions with key informants and a review of the literature.^ We first requested information about the centers, such as whether or not the CHC participated in a referral network or had affiliations with a medical school or hospital. The survey then asked directors for responses according to three insurance status categories (no insurance, Medicaid, or private insurance/ Medicare). For each category, we asked a series of questions about three dimensions of access to specialty care: the need for medically necessary referrals, access to specialty services, and barriers to referral. Medical directors were first asked the percentage of visits to the CHC that resulted in medically necessary referrals for specialty services not provided by the CHC for each insurance category. We then asked them to rate how often they were able to obtain the following seven major services for patients in each of the insurance categories: diagnostic tests, referrals to medical specialists, specialized services (for example, cancer care), nonemergency hospital admissions, high-technology services (for example, cardiac catheterization), mental 1 4 6 {1 September/Ot:l:nber2007 A C C E S S I N C H C S health services, and substance abuse services. Responses were collected on a fivepoint Likert scale that ranged from "never" to ''always." We then asked directors to rate the extent to which the following six factors served as barriers to referral for patients in each insurance category: distance, wait times, poor quality of specialty providers, unwilhngness of providers to accept patients of a certain insurance status, requirements that patients pay up front at specialty appointments, and insurance plan/CHC financial coverage of the needed services. Responses ranged across a fivepoint scale from "not at all" to "a great deal." Questions about access were grouped separately by insurance category to avoid leading the respondent to explicitly compare the different insurance status groups. Finally, medical directors answered questions about themselves, including their age, race, sex, ethnicity, profession, years in current position, and hours spent providing patient care. • Uniform Data System (UDS). We obtained additional data on each CHC from the 2004 UDS, including size, region, location, racial/ethnic and insurance distribution of patients, and revenue sources. In addition, we ascertained whether mental health, diagnostic testing, and diagnostic x-ray services were provided on site. • Anaiysis. We compared respondents to nonrespondents using t-tests or chisquare tests as appropriate. Based on the pattern of responses, we dichotomized response items from the survey related to access and barriers to specialty services as difficult access (yes/no) and significant barrier (yes/no). Bivariate analyses were performed to determine the impact of CHC characteristics on the individual response items, stratified by insurance status. Additionally, we compared responses for newstart grantees with those of established CHCs. We used factor analysis to group the seven access-to-specialty-service items into meaningful categories."-' The factor analysis revealed two underlying dimensions: (1) specialty medical care and admissions (including referrals to medical specialists, hospital admissions, high-tech services, specialized services, and diagnostic tests) and (2) mental health and substance abuse services. Composite dependent variables for specialty medical services and specialty mental health services were defined as the sum of the items in each dimension. For analyses we dichotomized these composite variables by defining difficult access as the lower quartile of the summed responses. We then estimated separate hierarchical logistic regression models for each composite outcome to determine the independent effect of insurance status on difficult access to specialty services, controlling for CHC characteristics." Study Results • CHC characteristics. We received completed surveys from 439 (54 percent) of the 814 directors surveyed, including 47 from new grantees. Respondent health centers were representative of CHCs nationally (Fxhibit 1). About 75 percent of CHCs had on-site mental health services. Diagnostic testing services were available HEALTH AFFAIRS - Volume 26. Numtcr 5 1461 D A T A W A T C H EXHIBIT 1 Characteristics Of Study Community Heaith Centers (CHCs) Compared With All CHCs Nationally, 2004 Health center characteristic Respondent CHCs (n = 439)^ All CHCs {n =• 814)" p value*^ Center-level characteristics, mean N (SD) Service delivery sites Total users 4.6 (4.8) 15,593 (15,624) 4,5 (4.6) 15.167 (15,233) 0.80 0,39 Patient-level characterfstics". mean N (%) Black/African American Wfiite Hlspar^icor Latino Best served in language other than English Uninsured 3.056 (19.6%) 5.491 (35,2) 5.466 (35.1) 4,767 (30.3) 6,217 (39.5) 3.374 (22.2%) 5.227 (34.5) 5,151 (34,0) 4.418 (28,7) 6,119 (39.7) 0,11 0.20 0.31 0,19 0,65 Location. N (%) Urban Rural 209 (47.6%) 230 (52.4%) 401 (48,6%) 413 (51,4) 0.31 0.31 Census region, N [%) Northeast Southeast Mtdwest West 93 (21.2%) 145 (33.0) 83 (18.9) 118 (26,9) 175 (21.5%) 284 (34.9) 146 (17.9) 209 (25.7) 0.81 0.23 0,43 0,40 Funding sources, mean dotiar amount (%) Funding from BPHC grants Funding from Medicaid revenue Funding from Medicare revenue Funding from commercial insurance 1.670.294 (21.6%) 3,284,354 (24.2) 654.016 (6.4) 902,791(9.1) 1.652,649 (15,5%) 3.314.574 (31,0) 643,080 (6.0) 864.124 (8-0) 0.70 0,89 0.82 0.73 Services available on site, N (%) Mentai health Substance abuse Diagnostic testing Diagnostic x-ray 327 (75.3%) 221 (50.9) 345 (79.5) 206 (47.5) 582 (72,8%) 388 (48,5) 625 (78.1) 371 (46.4) 0.07 0,14 0.31 0,50 SOURCE: Bureau of Primary Health Care Uniform Data System (UDS). 2004. ' N varies between 432 and 439 based upon the number of respondents to each individual UDS Item. "N represents the total number of federally qualified health centers (FQHCs) included in the sample. N varies between 800 and 814 based upon the number of respondents to each individual UDS item. "All significance tests are for respondent versus nonrespondent health centers. " Race and ethnicity categories as defined by the 2004 UDS. on site at about 80 percent of CHCs, and diagnostic x-ray services were available at about half. • Respondents' characteristics. Most of the respondents were white, and 77 percent were male.'^ On average, medical directors had been in their positions for 6.3 years and practiced clinicLilly 28 hours each week. • Access to speciaity care. Medical directors reported that about 25 percent of visits to their CHC resulted in medically necessary referrals for services not provided by the center. This rate did not vary for uninsured patients compared to those with Medicare/private insurance (p ~ 0.41). For Medicare or privately insured patients, respondents reported that they rarely had difficulty obtaining access to specialty medical services, ranging from 0 percent of the time (for diagnostic tests) to 10 percent of the time (for high-tech 1462 September/October 2007 A C C E S S I N C H C S services) (Exhibit 2). In contrast, significantly higher proportions of respondents reported difficult access for Medicaid and uninsured patients. These problems were more pronounced for access to specialty mental health and substance abuse services (Exhibit 3). In general, there were no differences in reported difficult access for new centers started in 2002 compared to established centers for both specialty medical services and specialty mental health services.'^ In adjusted models, these findings remained unchanged (Exhibit 4). CHCs with medical school or hospital affiliation reported less difficult access to specialty medical services than nonaffiliated CHCs; similarly, CHCs with on site mental health services reported less difficulty with access to specialty mental health services compared to CHCs without on-site mental health services. In light of federal policy increasing the number of access points and new CHCs beginning in 2002, we examined whether the availability of on-site diagnostic and mental health services changed between 2002 and 2004 using the UDS. Based on summary data, we found minimal changes in the overall percentage of centers that reported having diagnostic and mental health services on site." • Barriers to access. The most frequent barriers that medical directors reported were that providers outside of the center were unwilhng to take patients of certain insurance type; patients couldn't meet the requirement to pay up front for services; and patients lacked full coverage by the insurance pian or health center for needed services. The effects of these barriers varied significantly by insurance status (Exhibit 5). EXHIBIT 2 Percentage Of Community Health Center (CHC) Directors Reporting Difficult Access To Specialty Medicai Services, By insurance Category, 2 0 0 4 Percent of patients with difficult access • Private insurance Medicaid • Uninsured 50 SOURCE: All information was derived from the authors' computations using survey response data. NOTES: -Difficult access" means that patients were "never" or "rarely" able to obtain access. ' For private insurance compared with Medicaid, p < 0.05. For private insurance compared with uninsured and Medicaid compared with uninsured, p < 0.001. ° For pnvate insurance compared wtth uninsured and for Medicaid compared with uninsured, p < 0.001. HEALTH AFFAIRS -Vinfume 2 6 , Number 5 146i D A T A W A T C H EXHIBIT 3 , . . Percentage Of Community Health Center (CHC) Directors Reporting Difficult Access To Specialty Mental Health Services, By Insurance Category, 2004 Percenlof patients with difficult access • Private insurance ' Medicaid • Uninsured 50 Substance abuse Mental health SOURCE: All information was derived from the authors' computations using survey response data. NOTE: "Difficult access" means that patients were 'never' or "rarely" abie to obtain access. " For private insurance compared with Medicaid, private insurance compared with uninsured, and Medtcaid compared with uninsured, p< 0.001. EXHIBIT 4 Adjusted Results Of Hierarchicai Regression Model Predicting Difficuit Access To Specialty Medical Services And Speclaity Mentai Heaith Services CHC characteristic Specialty medical services: odds ratio (95% Ci) Speclaity mental liealth services: odds ratio (95% Ci) Insurance category Private/Medicare Medicaid Uninsured 1.00 2.83(2.12,3.77) 109.88 (82.54, 146.26) 1.00 7.61(5.10, 11.35) 96.13 (62.04.148.95) 1.00 0.83 {0.38.1.85) 0.47 (0.22,1.01) 0.66 (0.31, 1.42) 1.00 0.38(0.12,1.16) 0.13(0.04,0.40) 0.43(0.15.1.27) Total users^ 0.89 (0.72, 1.09) 1.27(0.94.1,71) Local Rurai Urban 1.00 0.68(0.37,1.24) 1.00 1.02 (0.43, 2.41) Affiliation with medical school or hospital 0.37 (0.20,0.67) 0.91(0.38,2.18) Services on site Diagnostic lab Diagnostic tests Case management Mental heaith Substance abuse 1.27 (0.62. 2.59) 0.49(0.27. 0.91) 0.72 (0.38.1.37) 1.51(0.81.2.83) 1.10(0.65,1.88) 0.47 (0.17.1.30) 1.47 (0.60, 3.61) 0.46(0.18.1.19) 0.22 (0.09. 0.54) 1.09(0.51.2.36) Census region West Midwest Northeast Southeast SOURCE: All information derived from authors' computations. NOTES: Adjusted for region, rural or urban location, numtser of sites, number of users, affiliation with medical school or hospital, percentage of racial and ethnic minorities, percentage of non-English-speaking patients, percentage of health center funding from grants and clinical care revenue, and on-site secondary services, p < 0.0001 for overall model to predict the effect of insurance status as a predictor of access to specialty medical services and specialty mental health services. •Per increase of 10,000 users. S e p t e m b e r / O c t o b e r 2007 AccESi IN EXHiBiT 5 Percentage Of Community Heaith Center (CHC) Directors Reporting Significant Access Barriers, By insurance Category, 2004 Percent of patients encountering barrier • Private insurance r. Medicaid • Uninsured 75 Provider won't accept insurance t y p e ' Provider requires payment upfront" Insurance does notcover' SOURCE: Ail information was derived from the authors' computations using survey response data. NOTE: "Significant barner" limits ability to refer "a fair amount' or "a great deal." ' For private insurance compared with Medicaid. private insurance compared with uninsured, and Medicaid compared with uninsured, p < 0.001. ' For private insurance compared with uninsured and Medicaid compared with uninsured, p < 0.001. ' For private Insurance compared with Medicaid, private insurance compared wfth uninsured, and Medicatd compared wUh uninsured. p< 0.05. Discussion ' ' Our findings suggest that lack of access to specialty services is a more important problem for CHCs than previously thought. Referrals to off site specialty services are frequently needed, yet medical directors reported major problems obtaining access to specialized medical and mental health services for uninsured patients and those covered by Medicaid. Particularly for the uninsured, these reported problems are pervasive and affect sizable numbers of patients. Given that federal policies expanding the number of CHC sites have not led to a substantial increase in the availability of many on-site specialty services, the problem of difficult access for services may increase if additional resources and planning are not devoted to assuring access to outside specialty services or bringing a greater array of services into CHCs.'^ • Consistency with previous studies. Our finding that CHC physicians report difficulty in access for uninsured and Medicaid patients at CHCs is consistent with prior reports in other health care settings.'^ For example, in an analysis of the patients from the Community Tracking Survey, uninsured adults were found to have significantly worse access to substance abuse and mental health services than Medicaid and privately insured patients.'^ Christopher Forrest and colleagues reported that payer status is a significant predictor of obtaining a referral from the primary care setting, with the uninsured having 0.58 times lower odds of referral than the privately insured.'*' Our findings of frequent need for services off-site from the CHC are much HEALTH A F F A I R S ^ ^'cilnmc 2e>, N u m b e r 5 1463 D A T A W A T C H greater than previously reported figures for referrals outside of CHCs. For instance, studies usitig disposition surveys have reported referral rates of just over 5 percent among CHC patients.''' Some possible explanations for this discrepancy suggest that our survey findings might be a better reflection of the actual need for referrals services at CHCs. First, the visit disposition surveys capture referrals actually completed, compared to services that are needed but not always obtained, as perceived by the medical directors of our study centers. Second, diagnostic services were included in the off site referral rate in our survey, whereas visit disposition surveys accounted for such diagnostic services separately. Finally, because of difficulties accessing services, CHC physicians might choose to substitute less optimal services (for example, screening for colorectal cancer using fecal occult blood testing in place of colonoscopy) that can be obtained at the CHC, and such substitutions would also not be captured in disposition surveys. Our findings relating to the need for specialty services are also consistent with prior research that suggests that visits to hospital outpatient departments are more commonly associated with additional services and referrals when compared to patients receiving care in community-based locations.-^ Although part of this difference tnight be explained by a lower threshold to use services that are offered on site, difficulties with access to specialty services in community-based settings because of insurance issues likely explain part of this discrepancy. Even among academic health centers, where hospital resources for ancillary and specialty services are available, providers report that access to specialty care can be very difficult for uninsured patients relative to privately insured patients.-' This problem is likely to be worse for patients at centers without a hospital affiliation. • Policy implications. Our results suggest some potential strategies to improve access to specialty services. First, medical directors report that requirements for upfront payment arc major access barriers for uninsured patients. Explicit underwriting of specialty services is one potential mechanism for addressing this barrier, but it will require additional resources. Earmarking additional funds for CHCs to use for such payments and contractually obligating a defined amount of specialty care for CHC patients are potential mechanisms by which this care could be underwritten. Second, we found that CHCs affiliated with a medical school or hospital reported much greater access to specialty medical services, while CHCs with mental health services on site reported greater access to specialty mental health services. Policymakers should encourage these affiliations and expansion of on-site services while supporting future research to explore other aspects of CHCs associated with referral success. For example, exploring the feasibility of creating and improving locally integrated outpatient referral networks that include CHCs would be a step toward improving quality of care for the under- and uninsured. • Study iimltations. Our study is subject to several limitations. Like ail surveys, ours relies on self-reported data, and our survey respondents might not have had accurate knowledge about all of the issues covered in the survey. We did, however, tar- 1466 S e p t e m b e r / O c t o b e r 2007 A C C E S S I N C H C S get the most knowledgeable respondent at the health center regarding these issues. Some of the directors' tendency to report a rate of access lower for uninsured patients or higher for privately insured patients might be attributable to prevailing assumptions about the problems of the uninsured. However, medical directors of CHCs are more likely than anyone else to have firsthand knowledge of this situation, and in the survey design we grouped questions about access separately by insurance category to prevent respondents from directly comparing insurance groups. Lastly, our response rate to the survey was 54 percent, and we must be cautious in generalizing to all CHCs; however, this percentage is in keeping with average response rates of physician surveys, and the centers in our survey appear to be representative of CHCs nationally.-' O UR FINDINGS SUGGEST THAT IF POLICYMAKERS p l a n t o e x t e n d a c c e s s to primary care for the uninsured by increasing the number of CHCs and CHC clinic sites, they must also address the problem of access to secondary and tertiary levels of care. Furthermore, given that uninsured and Medicaid patients receiving care in CHCs are disproportionately minority and low-income, the improvements suggested here could have a strong impact on the persistent disparities in health outcomes across racial and socioeconomic groups in the United States Prchminary results from this study were previously presented at the Office of Minority Heaith National Leaders.hip Summit on Eliminating Racial and Ethnic Disparities in Health in Washington, D.C, 9 January 2006. Thisproject was supported by the Har\'ard Medical School Office for Diversity and Community Partnership Bridge Award The authors acknowledge the Commonwealth Fund for educational and salary support for Nakela Cook during the conduct of this research. They thank YangXu for statistical programming, Rebecca Gregory for assistance with project manageman, Mary Ly and Lynn Huynh [or research assistance, and the many directors at community health centers nationwide for thar time inproviding the data for this analysis. They also ackmvikdge Michelle Proset; Thomas Curtain, and Daniel Hawkins at the National Association o/Communiry Health Centers for their collaboration on the survey design and key input on cuntnt issues affecting health centers. N O T E S • • • . , , • • • ' ' ' • ' ^ ',"• •' '•• 1, J, Hadley, Sicka- and Rwrrr The Consequences of Being Umnsitred: A Review of the Rmarth on the Relationship between Health Insurance, Health, Work, Income, and Education (Washington; Kaiser Commission on Medicaid and the Linin.sured, 2002); A, Markus, D. Roby. and S. Rosenbaum, A Profile of federally funded Heahh CciKcrs Scr^vig a Higher Proportion of Uninsured Patiairs (Washington: Kaiser Commission, 2002); and D. Rowland. "Uninsured in America: Testimony for U.S. House Ways and Means Subcommittee on Health" (Washington: Kaiser Commission. 2004). 2, Bureau of Primary Health Care, "About Health Centers," 16 May 2006, hrtp://bphc.hrsa.gov/about/health centcrs.htm (accessed 29 January 2007). 3. Ibid,; Markus et al., A Profile of Federally Funded Health Ca\ters\ Rowland, "Uninsured in America"; S. Rosenbaum et al.. Health Centers' Role as Safety Ncr Pro\'idersfor Medicaid Patiaas and the Unimuivd (Washington: Kaiser Commission, 2000); S. Rosenbaum and P. Shin, Health Ccmas as Safety Net Pamderi: An Oven-jew and Assessment ofMedicaid's Role (Washington: Kaiser Commission, 2003); and BPHC. 2005 Unifomi Data System (Washington: Health Resources and Scr\'ices Administration. 2005). 4. P. Cunningham and J. Hadley, "Expanding Care versus Expanding Coverage: How to Improve Access to Care," Health Affairs 23, no. 4 (2004): 234-244. H E A L T H A F F A I R S - Volume 26. Numhcr 5 1467 D A T A W A T C H 5. Ibid.; and M.K. Gusmano, G. Fairbrother, and H, Park, "Exploring the Limits of the Safety Net; Community Health Centers and Care for the Uninsured," Health Affairs 21, no. 6 (2002): 188-194. 6. S. Felt'Iisk, M. McHugh, and E. Howell, "Monitoring Local Safety-Net Providers: Do They Have Adequate Capacity?" Health Affairs 21. no, 5 (2002); 277-283; Gusmano et al,, "Exploring the Limits of the Safety Net"; and J,S. Weissman et aL, "Limits to the Safety Net: Teaching Hospital Faculty Report on Their Patients' Access to Care." Heahh Affairs 22. no. 6 (2003): 156-166, 7. J,Z, Ayanian ct al., "Specialty of .Ambulatory Care Physicians and Mortality' among Elderly Patients after Myocardial Infarction," New Fngland Journal of Medicine 347, no, 21 (2002): 1678-1686; and A- Ahmed et al,. "Association of Consultation between Generalists and Cardiologists with Quality and Outcomes of Heart Failure Care." American Mean journal 145, no. 6 (2003): 1086--1093, 8, In March 2004, when the survey was conducted, data from 2002 were the most current available to the National As.sociation of Community Health Centers. There were 817 CHCs with active medical directors. Three CHCs subsequently reported that they no longer functioned as CHCs and were removed from the data set. leaving 814 health centers with medical directors as potential respondents, 9, Weissman et al,. "Limits to the Safety Net," 10, The number of factors was determined by as,sessing how many eigenvalues of the reduced correktion matrix exceeded the mean eigenvalue (an adapted version of Guttman's criterion), L. Guttman, "Some Necessary Conditions for Common-Factor Analyses," Psychometrika 19 (1954): 149-161, 11. Each model included health center region; number of sites; number of users; location; percentage of black. Hispanic, and other minority patients; percentage of uninsured patients; percentage of non-Englishspeaking patients; percentage of revenue by payer; percentage of revenue from grants; presence of on-site second^ services; and affiliation with a hospital or medical school. 12. See Appendix Table 1. online at http://content.healthaffairs.Org/cgt/content/full/26/5/1459/DCl. 13. See Appendix Table 2. ibid. 14, See Appendix Table 3. ibid, 15, Gusmano ct al,. "Exploring the Umits of the Safety Net"; A.S. O'Malley et aL. "Health Center Trends, 19942001: What Do They Portend for the Eederal Growth Initiadve?" Health Affairs 24, no. 2 (2005): 465-472; and BPHC. 2005 Uniform Data System. 16, L. Shi and G,D. Stevens, "VulnerabiUty and Unmet Health Care Needs: The Influence of Multiple Risk Factors," Jouma/o/General internal Medicine 20. no, 2 (2005): 148-134; K,B. Wells et al,. "Alcohol. Drug Abuse, and Mental Health Care for Uninsured and Insured Adults," Health Services Rcsearcli 37. no. 4 (2002): 10551066; j,Z, Ayanian et al,. "Unmet Health Needs of Uninsured Adults in the United States." journal of the American Medical Association 284. no, 16 (2000): 2061-2069; and C.B. Forrest et al., "Primary Care Physician Specialty Referral Decision Making: Padent. Physician, and Health Care System Determinants," Medical Decision Making 26, no, 1 (2006): 76-85. 17 Wells et al., "Alcohol, Drug Abuse, and Mental Health Care." 18. Forrest et al,, "Primary Care Physician Specialty Referral Decision Making." 19. C.B, Forrest and E,M, Whelan, "Primary Care Safety-Net Delivery Sites in the United States: A Comparison of Community Health Centers. Hospital Outpatient Departments, and Physicians" Offices," Journal of the American Medical Association 284. no. 16 (2000): 2077-2083, 20. Ibid, 21. Weissman et al,, "Umits to the Safety Net," 22. !bid,;J,S, Weissman et al,. "Resident Physicians' Preparedness to Provide Cross Cultural Care." Jouma! of the American Medical Association 294, no. 9 (2005): 1058-1067; and B.E, Landon. J. Reschovsky. and D. Blumenthal, "Changes in Career Satisfaction among Primary Care and Specialist Physicians. 1997-2001," JoHiTiaf of the American Medical Association 289, no. 4 (2003): 442-449, 23. Markus et al., A Pwfik of Federally Funded Health Centers; Rowland. UninsurEd in America; BPHG, "About Health Centers"; Rosenbaum et al,. "Health Centers' Role as Safety Net Providers"; Rosenbaum and Shin, "Health Centers as Safety Net Providers"; and BPHC. 2005 Uniform Data System. M68 ' September/October 2007 RESEARCH IN HEALTHCARE FINANCIAL MANAGEMENT Vol. 12, No. 1, 93–111. © 2009, isRHFM, Ltd. CONSUMER CONCERNS FOR HEALTHCARE INFORMATION PRIVACY: A COMPARISON OF US AND CANADIAN PERSPECTIVES Michael V. Laric University of Baltimore Dennis A. Pitta University of Baltimore Lea Prevel Katsanis Concordia University (Canada) ABSTRACT T his paper explores privacy concerns of consumers in the area of healthcare services. Concerns with privacy can affect consumers’ search, choice and consumption of those services. This study compares US and Canadian citizens’ concerns with privacy and perceptions of issues surrounding various medical conditions or treatments. We postulate that concerns are a function of the health condition treated and three individual characteristics: age, race and gender. Furthermore, the nature of the individual’s healthcare insurance coverage might affect his or her concern for privacy. If a person has healthcare coverage, he or she might be willing to barter privacy for saving money. The particular governmental healthcare system an individual enjoys is important since it creates expectations of the ambient level of privacy one will experience. Though other individual characteristics like demographics, psychographics, and purchasing behaviors might play a role in the concern for privacy, they were not examined in this study. W hen consumers keep information private, they do so to avoid some negative consequence (Gelman & McCandish, 1998; Pitta et al., 2003). The underlying reason for keeping information private depends on the nature of the information. Individuals tend to keep identifying data like date of birth and social security number private to avoid a particular consequence: identity theft with Acknowledgement: The authors wish to thank the Senior Editor and two anonymous reviewers for their helpful comments on this paper. Address for correspondence: Michael V. Laric, Department of Management & Marketing, Merrick School of Business, University of Baltimore, 1420 North Charles Street, Baltimore, MD 21201 USA, mlaric@ubalt.edu. 94 Laric, Pitta & Katsanis consequent economic loss (Kieke, 2009; Eisenstein, 2008). Reports in the media are sensitizing consumers to the grave economic consequences of identify theft. In fact, the US Department of Justice reports that in 2004: “The estimated loss during the 6month period was about $3.2 billion” (US DOJ, 2006). In other arenas, political leanings and the values held regarding a woman’s right to choose and the right to life may have serious social consequences. Health information may have a variety of emotional and other consequences, but this article focuses on social and economic ones. The current research first reviews briefly what privacy is in general and what it is in the healthcare area. A brief overview of private and public healthcare systems is described next juxtaposing the Canadian and US systems. The article then describes the pathways of medical information about patients among the providers and insurers in the healthcare system, and explores what types of healthcare information consumers are concerned about and conversely, what types are of little or no concern. It next examines the effect of these on the level of privacy concerns comparing US and non-US consumers. The research sheds light upon the correlation between privacy concerns and the types of medical information involved. Suggestions for safeguarding information that should be kept confidential and for marketing healthcare services will be explored. LITERATURE OVERVIEW Consumers’ concern for health privacy focuses on the impact of disclosure on their daily social and economic interactions in society. The information of interest is often covert in the sense that it may be hidden from the casual observer. Employment opportunities, social acceptance and individual relationships affect the quality of life and can be affected by the degree to which information about one’s health is kept confidential (Rice, 2003). The cost of revealing such information varies with the severity of the medical condition. Thus, we postulate that the degree of concerns would vary based on the nature of the medical condition. Some medical conditions are so benign or commonplace that they merit scant attention. Others, especially those which are contagious, can cause others to avoid those so afflicted. There are references to social ostracism of HIV-positive patients that prompted federal legislation regarding their rights (Buchanan, 2002). In some cases, disclosing certain health conditions can prevent or even terminate employment. Even ordinary conditions like pregnancy have caused female workers problems (Suplido & Ong, 2000). For example, General Motors fired pregnant women working in an automobile battery fabrication shop because of the fear that lead used in the shop would affect the unborn child leading to birth defects. Those birth defects would make the company liable for a lawsuit and significant damages. Women who wanted to continue working in the shop and earn the shop’s higher pay rate hid their condition for as long as possible. It appears that perceived risk and cost are the most important factors in a patient’s desire to protect the privacy of his or her health information (Dowling & Staelin, 1994). The complexity of daily living forces consumers to focus on the more pressing RESEARCH IN HEALTHCARE FINANCIAL MANAGEMENT, Vol. 12, No. 1, 2009 CONSUMER CONCERNS FOR HEALTHCARE INFORMATION PRIVACY 95 elements, ignoring those that are less important. When losing privacy has a significant cost, consumers will be more active in protecting confidentiality (Luna, 2004). As noted above, the two relevant cost components of the privacy of medical information are social and economic cost (Schwartz, 1997). Divulging personal health information that might result in loss of a job or a promotion has a significant economic cost. Similarly divulging certain mental or physical health states may result in social ostracism or possible harassment. In both cases, the more rigorous the consequences, the more vigilant patients may be. Moreover, the risk perceptions would vary among individuals and for a given individual it would vary by the medical condition involved. PRIVACY AND THE MEDICAL SYSTEM Privacy Privacy has been defined as “the ability of an individual or group to stop information about themselves from becoming known to people other than those they choose to give the information to.” Privacy is sometimes related to the desire to be in control of one’s information and personal health related data, thereby retaining a degree of anonymity and protection. Privacy, especially in the aftermath of the 9/11 terrorist attacks has been seen as an aspect of ‘security’—where trade-offs between the interests of one group and another can become particularly clear. The Patriot Act and the debate about its renewal exemplify the public debate about privacy issues vs. national security in the US. As increased computerization of healthcare records progresses, the speed and ease with which data can be transferred among the many participants of the healthcare system increases dramatically. The result is to make invasion of privacy much easier. Anticipating the increased risk to privacy from this advance in information technological, the Organization for Economic Cooperation and Development (OECD, 2004) published ‘Guidelines on the Protection of Privacy and Trans-border Flows of Personal Data’ which were enacted because of the “…development of automatic data processing, which enables vast quantities of data to be transmitted within seconds across national frontiers, and indeed across continents, has made it necessary to consider privacy protection in relation to personal data.” As mentioned above, privacy may be voluntarily sacrificed by a patient, normally in exchange for perceived benefits, as is the case with third party payers in healthcare. In some cases, the information that is voluntarily shared, may get stolen or misused, as in the case of identity theft. Many countries support the privacy of information concerning a person’s health. The patient must grant access to the healthcare information before anyone other than the directly related healthcare organization clinical or staff personnel may view the information. The reasons for keeping medical information private may include possible discrimination against individuals with certain medical conditions. There are exceptions to the rule, as is the case with infectious diseases, when healthcare providers must report cases of Avian Flu, or other highly communicable diseases to medical authorities such as the Center for Disease Control (CDC) in the US. There are also some cases where the law may require disclosure of an individual’s information. RESEARCH IN HEALTHCARE FINANCIAL MANAGEMENT, Vol. 12, No. 1, 2009 96 Laric, Pitta & Katsanis For example, it may be illegal to fail to disclose medical information in the US and UK of individuals found guilty of “culpable and reckless” conduct in failing to tell their partners they are HIV positive before having sexual relationships. There is wide agreement that a person’s right to privacy is important and subordinate only to the safety rights of the larger community. The Medical System The focus of medical privacy is on the information in a patient’s file, i.e., the medical record. The medical record has historically been a paper file of the entire medical history of the patient, which resided in the doctor’s office (Etzioni, 1999). Records in doctors’ offices have been for the most part not integrated with records in hospitals, pharmacies or insurance providers. The lack of technological integration facilitated privacy. However, the greatly increased use of electronic medical records and telecommunications to transmit the records has the potential to decrease privacy. Electronic data sharing between different payer and providers including prescription and medical insurance records, laboratory test results, MRI, X-Ray images and others, are examples of the rapidly changing environment and increasing integration (Henderson, 1999a, 1999b). While a patient’s General Practitioner (GP) generated much of the medical information—other health providers who were consulted also had files. While such files were held in the providers’ offices, copies could end up being produced and reproduced at hospitals, pharmacies, laboratories and other healthcare facilities. Many records were also kept by third party payers and the potential for errors or leakage of information increases with the number of transmissions and copies made. It is reasonable to postulate that the type of medical system a country has would influence the level and kind of privacy concerns among those using the system. For example if everyone in a county is automatically enrolled in and covered by the country’s universal coverage system, its citizens would have less, if any, concerns about the possibility of getting turned down for general medical coverage based on their medical record. That would not be the case in the present US healthcare system. While the US healthcare system is largely a combination of public (Medicare, Medicaid, Veterans Health Administration, Tricare, etc.) and private payers, the majority of developed countries, including Canada, have some form of a publicly funded medical system with universal coverage. Critics refer to it as “socialized medicine.” While the reasons are diverse and the subject of vigorous public debate, the US healthcare system stands virtually alone among developed nations in not establishing a publicly funded, national healthcare system. INFORMATION FLOWS AND PATHWAYS IN HEALTHCARE Most marketing exchanges involve interactions between two parties: the buyer and seller. In healthcare that is between the uninsured patient and the healthcare provider. When the patient has health insurance the dyadic exchange becomes a tripartite one. Initiating a request for payment from a third party insuring organization requires processing by one or both parties to the initial exchange: the patient or the physician, RESEARCH IN HEALTHCARE FINANCIAL MANAGEMENT, Vol. 12, No. 1, 2009 CONSUMER CONCERNS FOR HEALTHCARE INFORMATION PRIVACY 97 or both. Exhibit 1 shows the tripartite relationships. That tripartite relationship is markedly different from traditional marketing transactions and is prevalent in the healthcare industry. EXHIBIT 1 INFORMATION PATHWAYS IN A TRIPARTITE HEALTHCARE EXCHANGE ENVIRONMENT Patients Physicians Payer During the information exchange, the insuring organization may require that the insured pre-authorize the recommended procedure. In most health maintenance organizations, treatment by specialists requires another “gate keeper” physician’s referral. In other cases, the insuring organization limits the level of reimbursement, or the network of specific providers that are pre-approved as participating members. All these financial arrangements impact consumers’ search for, choice of, and consumption of healthcare services. The tripartite relationships are often complicated further by the participation of other members of the healthcare network. The healing process often requires the use of prescription medications, or ambulatory care. Pharmacies, hospitals, providers of medical equipment and supplies, physical or other therapists may all be added as participants in the process. This is compounded when international outsourcing of services, such as radiology readings or surgeries, is included. Exhibit 2 shows some of the information pathways through which medical records and data pass in the extended global model of information exchange. Exhibit 2 shows both the private and public flows of information in a typical healthcare system. The traditional dyad: doctor-patient is at the heart of the model, and is numbered as 1 – patient and 2 – physician. When there is no need for prescriptions, the simple dyad is a robust and private relationship. As the need to add more healthcare elements grows, the privacy of the information flows becomes less robust. For example, including the third element, the pharmacy, (3 in Exhibit 2) opens a new participant whose RESEARCH IN HEALTHCARE FINANCIAL MANAGEMENT, Vol. 12, No. 1, 2009 98 Laric, Pitta & Katsanis employees might disclose information about the patient’s condition. Even secure pharmacy information systems cannot protect the information contained on a prescription bottle label. In fact, discarded pill bottles have disclosed healthcare information about individuals, including celebrities. As additional elements of the healthcare delivery system come into play, the threats to the privacy of information increase exponentially. When a hospital (4 in Exhibit 2) is involved the amount of information increases. Exhibit 2 also shows the variety that exists within the major groupings. While tracing each complex interaction is beyond the scope of this discussion, some elements stand out. Within the pharmacy circle there are medical equipment and supply providers (3a), ancillary providers and others who handle information. The Insurance circle includes other financially responsible parties such as worker’s compensation payers or auto insurers (5a) who pay for required treatments resulting from accidents. The Government circle, (7) has offices dealing with security (7a) like the Center for Disease Control, which requires that certain medical information be sent to it. EXHIBIT 2: GLOBAL INFORMATION PATHWAYS IN THE HEALTHCARE SYSTEM 1. Patient 2. Physicians 3. Pharmacies 4. Hospitals 6. Employers 3b. Medical service vendors 3a. Medical equipment vendors 5. Health Insurers 5a. Financially responsible parties 3c. Ancillary providers 7. Government insurance 5b. Governmental payers/transfer plans, military plans 5c. Life/disability insurers 7c. Governmental planning 7a. Governmental security 7b. Governmental licensing & certification 8. Pharmaceutical manufacturers Finally, all the above parties interact with insurance organizations (5) further multiplying the information pathways. The multiplicity of information transferred has RESEARCH IN HEALTHCARE FINANCIAL MANAGEMENT, Vol. 12, No. 1, 2009 CONSUMER CONCERNS FOR HEALTHCARE INFORMATION PRIVACY 99 often been cited as a cause for delays in payment and a significant overhead cost in the healthcare industry. In a recent New York Times editorial (2009) the editors commented on the drive to digitize healthcare records as a means of making the information pathways less costly. As part of the stimulus package, planned by the current administration, it is expected that up to $20 billion dollars will be invested in accelerating the use of electronic health records. While the goal is to improve quality and lower costs, it also: “…raises important questions about how to ensure the privacy of patients.” The pressure to find healthcare economies will increase significantly over time. The editorial also comments on the relative security offered by paper records compared to the electronic one. It notes that the American Civil Liberties Union, in a recent letter to Congress, notes employers who obtain medical records of an individual might reject a job candidate who could be relatively expensive to insure. Drug companies may use the information to solicit buyers or try to switch patients to their products. Data brokers might mine, or buy personal health records and sell them to marketers. The bills pending in Congress could go a long way toward preventing such abuses. They could outlaw the sale of any personal health information without the patient’s permission, mandate audit trails to help detect inappropriate access, and require that patients be notified whenever their records are lost or used for an unauthorized purpose. They would also increase the penalties for noncompliance and allow state attorneys general to help enforce the rules—a useful approach in case the federal government is less able to prosecute a case. They could also encourage the use of protective technologies, like encryption, to protect personal medical information that will be transmitted as part of the electronic medical record. Health insurance plans and some disease management groups counter that such new requirements would impose administrative burdens that could impede the use of electronic records and interfere with the coordination of care. They want to ease the marketing restrictions, notify patients only if security breaches are harmful, and keep the attorneys general out of the enforcement role. It should be possible through implementing regulations to fine-tune the privacy requirements so that they do not disrupt patient care. The New York Times editors argue that the Congress should make every effort to ensure that patients’ privacy is protected (New York Times, 2009). IMPORTANCE TO MARKETING The terms of healthcare benefits packages provided by employers through third party payers stipulate that providers of these benefits are entitled to information about the individuals’ health condition and the nature of the services rendered to them. Having medical insurance involves sharing information with the third party payer, a largely anonymous entity to the patient. Where a nationalized health system exists as in the UK and Canada, the information can be shared, through service providers, with the government authorities who pay for the different procedures through tax levies. Their situation is somewhat similar to that of the Medicare and Medicaid systems in the US. RESEARCH IN HEALTHCARE FINANCIAL MANAGEMENT, Vol. 12, No. 1, 2009 100 Laric, Pitta & Katsanis The information shared affects privacy concerns with respect to individuals’ behavior in the marketplace. Those concerns, in turn, impact their search for, choice of, purchase and consumption of healthcare services. There are also marketing implications for each of the steps leading to buying and the post purchase behavior, such as loyalty to providers, repurchase, and ease of applying for and the amounts of reimbursements. Healthcare providers must be aware of these concerns and behaviors when developing their marketing strategies. The consumer behavior elements outlined above affect many elements of the healthcare markets. Ambulatory care, the pharmaceuticals prescribed, the diagnostic tests provided and the services rendered by physicians and others, all require healthcare information sharing. Each of these may in turn disclose the nature of the illness to third party payers and to the other participants in the healthcare system. Exhibit 2 showed some of the information pathways in the healthcare system. The result is an extended set of relationships and information flows that are more challenging in the effort to safeguard personal information. The effect of different health conditions and treatments, along with privacy concerns on consumers’ behavior are of great interest to many concerned with the healthcare market. They are also relatively unexplored in the marketing field. VULNERABILITIES AND FINANCIAL ASPECTS OF HEALTH INFORMATION Healthcare information resides in the medical history and the patient’s medical history is arguably the foundation of modern medical care. Once a medical record is established for a patient it is updated with each visit to a provider such as a physician, dentist, psychiatrist or nurse practitioner. In the words of a former Secretary of Health and Human Services: “The days when the family doctor kept our records sealed away in a locked cabinet are gone. Information about patients—their illnesses and medical histories, the drugs they have taken—is now stored electronically and transferred quickly from doctor to doctor or insurer to pharmacist” (Fridel, 2004). Often, the patient history contains background information in addition to the biological symptoms and designation related to medical illnesses. Such background information includes lifestyle information like smoking or alcohol consumption, sedentary life style, obesity, domestic relationships, involvement in high-risk activities and family medical and mental history. The history often includes information like the results of laboratory tests and other diagnostic tests, copies of X-Ray films or radiology reports—all with information about the individual’s health conditions. The history details each medication prescribed and medical procedure performed and thereby discloses additional information about potential medical conditions or diagnoses. Medical insurers use the records of past treatments and medical conditions as the basis for evaluating admissibility and coverage of new members. When a person is no longer eligible for an employer’s group health insurance, he or she must seek individual private insurance—which is often far more expensive, if it can be obtained at all. The change makes pre-existing medical conditions very important. With as many as 60 million individuals needing to buy their own health insurance, some 8% are rejected because of pre-existing conditions (Fuhrmans, 2005). RESEARCH IN HEALTHCARE FINANCIAL MANAGEMENT, Vol. 12, No. 1, 2009 CONSUMER CONCERNS FOR HEALTHCARE INFORMATION PRIVACY 101 Garfinkel (2000) writes: “Privacy isn’t just about hiding things. It’s the right of people to control what details about their lives stay inside their houses and what leaks to the outside.” As medical practice progresses, new types of private information are included. Genetic testing is now becoming much more common and such information can be stored in the patient history and used for profiling susceptibility to illnesses such as certain types of cancer. Other information such as participation in pharmaceutical clinical trials, exposure to environmental hazards, or even applications for life, disability or accident insurance can be included. Medical records are attractive to persons and organizations outside the healthcare field. Like credit information—they have a market value, and many have sought to make this information legally available to those who could benefit from it. An advertising agency, for example might be interested in knowing the demographics (age, ethnicity, and economic background) of the users of antidepressants, if their pharmaceutical company client sells antidepressants (Scarf, 2001). Employers might want to know the medical history of a present or potential employee. Insurers could (and do) make use of detailed mental health records to exclude specific applicants from their pool (Lueck, 2005). If the information is online, with the proper access, it can be obtained at the touch of a button (Fridell, 2004). HEALTH INFORMATION PRIVACY AND THE LAW Recent changes in the US government’s approach to safeguarding the privacy of patients’ healthcare information have generated a considerable increase in information disclosure requirements (HIPAA, 1996). Since the Health Insurance Portability and Accountability Act (HIPAA) went into effect, a patient visiting a doctor’s office or picking up a prescription has to sign a statement regarding information privacy. While many patients simply sign the statement, the result has been heightened consumer awareness about what health information is held privately and what is not (Davis & Silver-Malyska, 2003). In the US, the Medical Information Privacy and Security Act (MIPSA, 1999) is the new development. MISPA contains important provisions which require that any access to data automatically generate an audit trail. Patients are able to partition their data so sensitive information is safeguarded. For example genetic information might not be revealed as part of the medical record when they go for a flu injection. Individuals have a right to access, copy, edit and augment their information. The consumer’s ability to manage partitions has not been established, and many issues regarding not just the privacy but also the integrity of the information are yet to be addressed. While HIPAA was enacted for a variety of reasons, one underreported effect of the act is a reduction in the security of patients’ healthcare information. As a result, the literature has changed its focus to the structure of information exchange inherent in marketing relationships (Mercuri, 2004). Consequently, the emphasis has shifted from individual transactions to a more comprehensive view of the environment. To our knowledge, no marketing research study, focusing on consumers’ privacy concerns with respect to healthcare, has appeared in the literature. The federal government’s institution of HIPAA has generated considerable concern on the part of consumer RESEARCH IN HEALTHCARE FINANCIAL MANAGEMENT, Vol. 12, No. 1, 2009 102 Laric, Pitta & Katsanis advocates who recognize the potential breach of privacy problems inherent in the extended information model. The question is whether consumers recognize the extent of threats to their privacy. Finally, privacy concerns are not unique to patients. There are implications of privacy issues for physicians as well. However, this study focuses on the patients’ perspective. PRELIMINARY RESEARCH QUESTIONS The two questions we address are presented in the form of research propositions: RP1: Does the level of a consumer’s concern for the privacy of healthcare information vary as a function of the health condition or malady? RP2: Does the level of a consumer’s concern for the privacy of healthcare information vary as a function of the individual characteristics such as gender, age, race or national origin? METHODOLOGY Data Collection Data collection was based on a questionnaire, shown in the Appendix. Initial draft versions of the instrument were pretested during the spring semester of 2005. The instruments were refined and two final versions were used in data collection. Two separate questionnaires were required due to the differences in demographics and healthcare public policies of Canada and the US. The survey asks respondents to indicate how concerned they are with the privacy of their information with respect to specific health conditions and medical procedures. It further seeks to identify underlying factors that account for a consumer’s concern for privacy. We collected a total of 225 responses—a 100 percent response rate—from MBA students enrolled in a university in Canada (N = 45) and a university in the US (N = 180). The study’s dependent variables included a variety of common ailments as well as serious conditions. They included contagious and non-contagious ailments. The survey included conditions that generate varying degrees of potential social stigma. The study’s four independent variables included age, gender, race and whether or not the patient was covered by health insurance. The specific racial categories used in each version of the survey instrument reflect official terminology pertinent to either Canada or the US. Pretesting the instrument uncovered the need for specific changes. For example, the term used to describe Canada’s native peoples is “Aboriginal.” The equivalent term for the US’s native population is “Native Americans.” Several other categories were modified between the samples to reflect the demographics more accurately. Data Analysis The data analysis plan incorporated ANOVA to discern statistically significant differences. In addition, a means analysis was performed to learn more about any RESEARCH IN HEALTHCARE FINANCIAL MANAGEMENT, Vol. 12, No. 1, 2009 CONSUMER CONCERNS FOR HEALTHCARE INFORMATION PRIVACY 103 significant relationship. Because of minor differences in the Canadian and US data sets, two separate analyses were performed, and are reported separately. US SAMPLE Initial data analysis revealed several significant differences, presented in Exhibit 3. EXHIBIT 3 STATISTICALLY SIGNIFICANT RESULTS US SAMPLE (N = 180) 4. 5. 6. 8. 9. 10. 11. 15. 18. 21. 23. 25. 26. 27. 28. 30. 31. 32. 33. 34. 35. 37. 38. 41. 42. 43. Type of Patient Health Information Standard Physicals Follow up visits with a GP Cholesterol testinga Flu or common colda Standard vision care Standard dental care Mammogramsa Injury requiring PTa Complications from std. ailment Plastic surgery—liposuction Plastic surgery—tummy tuck Diabetes Ambulatory carea Cancer required surgerya Cancer—chemotherapya Cardiac surgerya Mastectomy Organ transplanta Tumors—benigna Tumor malignant HIV testinga Sexually transmitted herpes Curable STD Substance abusea Eating disordersa Depressiona 50. GENDER Independent Variables 52. RACE 53. INSURANCE 0.010 0.028 0.034 0.036 0.021 0.021 0.014 0.062 0.061 0.001 54. AGE 0.022 0.010 0.041 0.006 0.012 0.010 0.014 0.006 0.037 0.031 0.008 0.035 0.049 0.000 0.035 0.027 0.004 0.002 0.058 0.049 0.002 0.005 0.030 0.004 0.005 Note: Variables are significant at the p ≤ 0.10 level. a Type of information is not significant in the Canadian sample. Gender Differences Most of the dependent variables showed no statistical differences in a patient’s concern for privacy for most of the procedures or conditions. There were a total of 10 RESEARCH IN HEALTHCARE FINANCIAL MANAGEMENT, Vol. 12, No. 1, 2009 104 Laric, Pitta & Katsanis statistical differences based on gender. The two statistically significant plastic surgery related concerns: liposuction (0.062) and tummy tuck (0.061) likely reflect potential embarrassment if these elective procedures were publicized. Means analysis showed that female subjects in general had a higher concern for privacy for each of these procedures than males. That finding may reflect a larger number of females who might elect such procedures, in addition to greater sensitivity to their disclosure. There was another cluster of significant differences in privacy concerns dealing with ailments which consumers feel are sensitive. HIV testing (0.049), sexually transmitted herpes (0.002), curable sexually transmitted disease (0.055), substance abuse (0.030), eating disorders (0.004) and depression (0.005) showed significant differences. Consistently, females had higher means than males. One other finding related to gender is that malignant tumors showed a significant difference (0.058). The mean concern for privacy was higher with females. Age Age showed a majority (19 information types) of significant differences in concern for privacy. In general, subjects in the 45 and over age category showed higher concerns for privacy than younger subjects. The higher means for older subjects were remarkably consistent. The results may reflect the fact that younger people suffer from fewer ailments or conditions and therefore have perhaps thought less about issues related to keeping their health information private. Race There was a selection of racial differences in privacy concerns linked with eight specific information types. Black Americans tend to be consistently more concerned about the privacy of the healthcare information than white or Asian Americans. The significant differences between the races were clustered in the more commonplace dependent variables like standard physical examinations (0.010), follow up visits to a general practitioner (0.028), cholesterol testing (0.034), the flu (0.036) or even standard vision (0.021) or dental care (0.021). Significantly, the means for black Americans were high overall. In comparison, whites and Asians concerns increased as the importance or sensitivity of the visit increased. In that case, there were no significant differences between the races on more ‘important’ issues. One other condition, plastic surgery— tummy tuck (0.061) was significantly different by race. Whites had a lower concern for privacy than other races. Insurance Insurance coverage did not seem to affect the level of concern for privacy. Individuals with coverage and those without had concerns for privacy that were not significantly different. CANADA SAMPLE Identical methods were used to analyze the Canadian data set. Exhibit 4 shows the significant relationships found in the Canadian sample. RESEARCH IN HEALTHCARE FINANCIAL MANAGEMENT, Vol. 12, No. 1, 2009 CONSUMER CONCERNS FOR HEALTHCARE INFORMATION PRIVACY 105 EXHIBIT 4 STATISTICALLY SIGNIFICANT RESULTS CANADA SAMPLE (N = 45) 4. 5. 7. 9. 10. 13. 18. 20. 21. 23. 25. 31. 34. 37. 38. 44. Type of Patient Health Information Standard Physicals Follow up visits with a GP Inoculation for travela Standard vision care Standard dental care Colonoscopy or similar testsa Complications from std. ailment Plastic surgery—nosea Plastic surgery—liposuction Plastic surgery—tummy tuck Diabetes Mastectomy Tumor malignant Sexually transmitted herpes Curable STD Schizophrenia (bi-polar disorder)a 50. Gender Independent Variables 52. Race 53. Insurance 54. Age 0.010 0.059 0.053 0.042 0.034 0.020 0.002 0.035 0.040 0.043 0.069 0.021 0.058 0.052 0.028 0.078 Note: Variables are significant at the p ≤ 0.10 level. Type of information is not significant in the US sample. a Gender Differences Most of the dependent variables showed no statistical differences in a patient’s concern for privacy for most of the procedures or conditions. There were a total of six statistical differences based on gender. The three statistically significant plastic surgery related concerns: rhinoplasty (0.035), liposuction (0.040) and tummy tuck (0.043) again likely reflect potential embarrassment if these elective procedures were publicized. Means analysis showed that female subjects in general had a higher concern for privacy for each of these procedures than males. That finding may reflect a larger number of females who might elect such procedures, in addition to greater sensitivity to their disclosure. Mastectomy showed a significant difference in concern for privacy in the Canadian data. Again, females responded with higher means than males. Another finding in the Canadian data related to gender is that malignant tumors showed a significant difference (0.058). The mean concern for privacy was higher with females. Also, research has documented that males and females develop schizophrenia in about equal numbers (Miller, 2005). Generally, females develop the disorder later in life than males, and since our sample population is relatively young, it RESEARCH IN HEALTHCARE FINANCIAL MANAGEMENT, Vol. 12, No. 1, 2009 106 Laric, Pitta & Katsanis is possible that the females were less concerned about the condition, which we found to differ significantly by gender (0.078). Age There were fewer age related significant differences in concern for privacy in Canada than in the US. There were four significant differences: standard physicals (0.010), follow up visits with a general practitioner (0.059), and standard vision (0.042) and dental care (0.034) In general, as in the US, subjects in the 45 and over age category showed higher concerns for privacy than younger subjects. Race There were five significant differences in privacy concerns linked with race. In the Canadian survey instrument, the racial categories differ from the US instrument with the substitution of Middle Eastern for the Hispanic category. The significant differences between the races were clustered in the more commonplace dependent variables like the privacy of colonoscopy (0.020), complications from standard ailment (0.002), and diabetes (0.069). Two of the sensitive items: sexually transmitted herpes (0.052), and curable sexually transmitted disease (0.028) showed significant differences. The means for non-white were higher overall than for whites. The means for Aboriginals (Indians) was the highest for diabetes and may possibly reflect a disproportionate incidence of this disease among native North American people. Insurance Insurance coverage did not seem to affect the level of concern for privacy. Most Canadians have provincial healthcare coverage so that eliminates a potentially significant within group difference. While inoculations for travel showed a significant difference regarding insurance coverage, one might speculate this could be due to the travel connection rather than a current disease. Further research would be necessary to more fully examine this result. FINDINGS This paper presented a number of postulates to be verified. The first, “Does the level of a consumer’s concern for the privacy of healthcare information vary as a function of the health condition or malady?” In each country, mean responses for concerns for privacy rose from lower levels for the more everyday ailments to higher levels for the more severe, sensitive, or contagious conditions. One example is the significant results for HIV positive testing. In our cross-border survey, there were several differences in consumer’s concern for the privacy of healthcare information. The US results included 14 significant dependent variables that were not significant in the Canada sample (nos. 6, 8, 11, 15, 26, 27, 28, 30, 32, 33, 35, 41, 42 and 43), while the Canada results included four significant dependent variables that were not significant in the US sample (nos. 7, 13, 20 and 44). Future comparisons may examine the reasons for these differences in RESEARCH IN HEALTHCARE FINANCIAL MANAGEMENT, Vol. 12, No. 1, 2009 CONSUMER CONCERNS FOR HEALTHCARE INFORMATION PRIVACY 107 more detail. However, one important finding is that insurance coverage in both countries is not significantly related to concerns for healthcare privacy. In Canada, the effect is not likely due to universal healthcare coverage—few, if any, Canadian citizens have no health insurance coverage. Canada significantly differed only on information type no. 7 Inoculation for Travel. In the US it may be that private HIPAA privacy regulation apply to all Americans so, again, there is little variation in the data. The study did identify some differences that relate to the perceived importance of healthcare privacy. In general, females consistently ranked their concerns for privacy higher than males. Age differences were shown to be important across countries. While the specific maladies were different, older subjects were more concerned with the privacy of their health information than younger people. That finding may reflect older subjects increasing experience with healthcare and associated issues compared to the healthy younger subjects. The racial differences were revealing in that minorities were more concerned about privacy regarding everyday procedures like standard physical examinations. It is reported that minorities in the US have less access to and utilization of healthcare than whites (Fiscella et al., 2000), which may have some relation to their increased concern for privacy. SUMMARY In general terms, the study showed that females are more concerned about privacy than males. Further research is needed to explore the reasons why these gender differences exist. In addition, older people are more concerned about healthcare privacy than younger people. It is possible that experience with the healthcare system sensitizes the older more experienced patient compared to the younger patient. This result also needs to be studied further. Experience may also play a part when the effect of race is considered. Minorities are more concerned about the privacy than the majority for common procedures. This finding may reflect minorities’ lower access to the healthcare system and needs further study. LIMITATIONS AND DIRECTIONS FOR FUTURE RESEARCH The results of the study represent a limited sample (N = 225). As noted above, Canada and the US are quite similar in many ways and the public policy differences may not be different enough to significantly affect consumer concerns for privacy. Our finding that inoculations for travel showed a significant difference regarding insurance coverage was a surprise. One might speculate that the result may be due to the travel connection, not directly related to a current disease. Further research would be necessary to replicate or explore this finding. In addition, while the study provided insight into some of the factors affecting concern for the privacy of healthcare information, examining the underlying reasons for and dimensions of privacy concern were beyond the scope of this paper. RESEARCH IN HEALTHCARE FINANCIAL MANAGEMENT, Vol. 12, No. 1, 2009 108 Laric, Pitta & Katsanis Conceptually, social, economic and cultural factors may be associated with privacy concerns. Future research will address this question empirically. Our results point to future work that may be done to validate a privacy concern scale. Questionnaire development in the current study helped uncover qualitative relationships among maladies and privacy. Quantifying the association of specific disease entities and conditions with concern for privacy may help in refining our understanding of the underlying factors that operate to sensitize individuals to privacy concerns. Finally, on a broader scale, it would be helpful to repeat the study in a few years after more of the nation’s medical records become digitized. Will US consumers perceive privacy threats differently? Will their perception change if a national healthcare system were to be implemented? The New York Times editorial (2009), comments on the financial stimulus package and its impact on healthcare. There are bills pending in the Congress that address preventing abuses of medical privacy and outlaw the sale of any personal health information. They would also mandate audit trails to help detect inappropriate access, and further require that patients be notified when their records are lost or misused. Penalties for noncompliance would be imposed and state attorneys general would help enforce the rules. At the same time, insurance plans and other industry participants express concerns that the new requirements would impose administrative burdens and interfere with coordination of care. They advocate easing the marketing restrictions, notify patients only if security breaches are harmful, and keeping the state attorneys general out of the enforcement role. It would be useful to try and assess the issue of the cost-benefit aspects of protecting individual privacy. Such analysis would need to identify a balance between the benefits of implementing the privacy safeguards and the costs of disrupting patient care. REFERENCES Buchanan, R.J. (2002). Ryan White CARE Act and eligible metropolitan areas. Health Care Financing Review, 23(4): 149–157. Davis, V., & Silver-Malyska, T. (2003). Employer’s liability for use and disclosure of individual health information: HIPAA privacy and employer functions. Benefits Law Journal, 16(2): 29–47. Dowling, G.R., & Staelin, R. (1994). A model of perceived risk and intended risk-handling activity. Journal of Consumer Research, 21(June): 119–134. Eisenstein, E.M. (2008). Identity theft: An exploratory study with implications for marketers. Journal of Business Research, 61(11): 1160–1172. Etzioni, A. (1999). The limits of privacy. New York, NY: Basic Books. Fiscella, K., Franks, P., Gold, M.R., & Clancy, C.M. (2000). Inequality in quality: Addressing socioeconomic, racial, and ethnic disparities in health care. The Journal of the American Medical Association, 283(19): 2579–2584. Fridell, R. (2004). Your Rights in Conflict: Privacy vs. Security. Berkeley Heights, NJ: Enslow Publishers, Inc. Fuhrmans, V. (2005). Health insurers’ new target. Wall Street Journal, (May 31): B1, B4. RESEARCH IN HEALTHCARE FINANCIAL MANAGEMENT, Vol. 12, No. 1, 2009 CONSUMER CONCERNS FOR HEALTHCARE INFORMATION PRIVACY 109 Garfinkel, S. (2000). Database Nation: The Death of Privacy in the 21st Century, Sebastopol, CA: O’Reilly & Associates, Inc. Gelman, R.B., & McCandish, S. (1998). Protecting Yourself Online. New York, NY: Harper Edge. Henderson, H. (1999a. Issues in the Information Age. San Diego, CA: Lucent Books. Henderson, H. (1999b). Privacy in the Information Age. New York, NY: Facts on File, Inc. HIPPA. (1996). Understanding HIPAA Privacy, US Department of Health & Human Services. Accessed Jun. 8, 2009 at: www.hhs.gov/ocr/privacy/hipaa/understanding/index.html. Kieke, R.L. (2009). Although a relatively new risk area, medical identity theft should not be taken lightly. Journal of Health Care Compliance, (Jan.–Feb.): 51–74. Lueck, S. (2005). Seeking insurance, individuals face many obstacles. Wall Street Journal, (May 31): A1, A8. Luna, J.J. (2004). How to Be Invisible, New York, NY: Thomas Dunne Books. Mercuri, R. (2004). The HIPAA-potamus in health care data security. Communications of the ACM, 47(7): 25–29. Miller, J.L. (2005). Schizophrenia, Athealth.com, Accessed Jun. 12, 2009 at: www.athealth.com/Consumer/disorders/Schizophrenia.html. MIPSA. (1999). The Medical Information Privacy and Security Act (MIPSA), Setting Information-Age Parameters for Medical Privacy, Accessed Jun. 8, 2009) at: http://leahy.senate.gov/press/199903/990310b.html. New York Times Editorial, (2009). Your e-health records. New York Times (New York ed.), (Feb. 1): WK8. Organization for Economic Cooperation & Development. (2004). OECD Guidelines on the Protection of Privacy and Trans-border Flows of Personal Data, OECD, Accessed Feb.11, 2009 at: www.oecd.org/document/18/0,3343,en_2649_34255_1815186_1_1_1_1,00.html. Pitta, D., Franzak, F., & Laric, M. (2003). Privacy and one-to-one marketing: Resolving the conflict. Journal of Consumer Marketing. 20(7): 616–682. Rice, B. (2003). To tell or not to tell. Medical Economics, 80(9): 35–38. Scarf, M. (2001). Secrets for sale. Social Research, 68(1): 333–339. Schwartz, P.M. (1997). Privacy and the economics of health care information. Texas Law Review. 76(1): 1–75. Suplido, M.L., & Ong, C.N. (2000). Lead exposure among small-scale battery recyclers, automobile radiator mechanics, and their children in Manila, The Philippines. Environmental Research. 82(3): 231–238. US Department of Justice. (2006). 3.6 Million U.S. Households Learned they were Identity Theft Victims During a Six-Month Period in 2004, (Apr. 2). Accessed Feb. 11, 2009 at: www.ojp.usdoj.gov/bjs/pub/press/it04pr.htm. RESEARCH IN HEALTHCARE FINANCIAL MANAGEMENT, Vol. 12, No. 1, 2009 110 Laric, Pitta & Katsanis APPENDIX SURVEY INSTRUMENT Healthcare Information Privacy Survey This survey is intended to learn more about how you feel about the confidentiality of your healthcare information. Sharing some types of health information may cause no embarrassment or harm. You may feel less comfortable divulging other types of health information. Please consider each type of health information below. Please rate each type of health information on the basis of how you feel about its sensitivity. Please rate the sensitivity of the information from 1 (not sensitive at all) to 5 (highly sensitive) by circling the appropriate number. If you have no basis for rating the information, please circle NR for no basis for rating. Type of patient health information 1. 2. 3. 4. 5. 6. 7. 8. 9. 10. 11. 12. 13. 14. 11. 15. 16. 17. 18. 19. 20. 21. 22. 23. 24. 25. 26. 27. 28. 29. 30. A planned or welcome pregnancy Unwelcome pregnancy Well child care Standard physicals Follow-up visits with a general practitioner Cholesterol test Inoculation shots for travel Flu or common cold Standard vision care Standard dental care Mammograms Prostate screening Colonoscopy or similar diagnostic tests Joint surgery like rotator cuff Hip or knee replacement Injury requiring physical therapy Outpatient surgeries Routine surgeries requiring hospitalization Complications arising from a standard ailment Unexpected diagnostic results Plastic surgery—rhinoplasty (nose) Plastic surgery—liposuction (fat removal) Plastic surgery—face lift Plastic surgery—tummy tuck Sports injury requiring long term physical therapy Diabetes Ambulatory care Cancer requiring surgery Cancer requiring surgery and chemotherapy Cancer requiring surgery, chemotherapy, and radiation Cardiac surgery RESEARCH IN HEALTHCARE FINANCIAL MANAGEMENT, Vol. 12, No. 1, 2009 How sensitive is the information? Please circle: 1- (not sensitive at all) to 5- (highly sensitive) or NR- no basis for answering. 1 2 3 4 5 NR 1 2 3 4 5 NR 1 2 3 4 5 NR 1 2 3 4 5 NR 1 2 3 4 5 NR 1 2 3 4 5 NR 1 2 3 4 5 NR 1 2 3 4 5 NR 1 2 3 4 5 NR 1 2 3 4 5 NR 1 2 3 4 5 NR 1 2 3 4 5 NR 1 2 3 4 5 NR 1 2 3 4 5 NR 1 2 3 4 5 NR 1 2 3 4 5 NR 1 2 3 4 5 NR 1 2 3 4 5 NR 1 2 3 4 5 NR 1 2 3 4 5 NR 1 2 3 4 5 NR 1 2 3 4 5 NR 1 2 3 4 5 NR 1 2 3 4 5 NR 1 2 3 4 5 NR 1 2 3 4 5 NR 1 2 3 4 5 NR 1 2 3 4 5 NR 1 2 3 4 5 NR 1 2 3 4 5 NR 1 2 3 4 5 NR CONSUMER CONCERNS FOR HEALTHCARE INFORMATION PRIVACY 111 31. 32. 33. 34. 35. 36. 37. 38. 39. 40. 41. 42. 43. 44. 45. 46. Mastectomy Organ transplants Tumors, benign Tumors, malignant HIV Testing Hansen’s disease (leprosy) Sexually transmitted Herpes Curable sexually transmitted diseases Alcoholism diagnosis Alcoholism treatment Substance abuse Eating disorders Depression Schizophrenia (bi-polar disorder) Dissociative syndrome (multiple personalities) Antisocial personality disorder (sociopathy) 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 NR NR NR NR NR NR NR NR NR NR NR NR NR NR NR NR Please indicate the strength of your agreement with the following (1-strongly disagree to 5strongly agree) 47. Healthcare information can be safely handled by my family physician. 48. Hospitals take adequate precautions with healthcare information. 49. Except to physicians and hospitals, my personal healthcare information is not readily available. 1 2 3 4 5 1 2 3 4 5 1 2 3 4 5 Please check or circle the correct response. 50. Your gender MALE __________ FEMALE _________ 51. Are you a US citizen YES ______ NO _____ 52. Your racial/ethnic heritage WHITE ___ BLACK ___ NATIVE AMERICAN ___ ASIAN ___ HISPANIC ___ OTHER ___ 53. Do you have health insurance YES ______ NO _____54. Your age 18 and under 19–24 34 35–44 45 and over 25– Thank you for completing this survey. RESEARCH IN HEALTHCARE FINANCIAL MANAGEMENT, Vol. 12, No. 1, 2009 63 CONSUMER PRIVACY ISSUES ASSOCIATED WITH THE USE OF ELECTRONIC HEALTH RECORDS Irvine Clarke III, James Madison University Theresa B. Flaherty, James Madison University Stacy M. Hollis, James Madison University Mark Tomallo, James Madison University ABSTRACT A growing number of organizations use technology to communicate medical information and store electronic health records in order to best serve their patients and customers. However technological advancements do not come without some risks to consumer welfare. This paper examines the emerging use of electronic health records (EHRs) to store patient data and the subsequent impact on consumer privacy issues. A discussion of the practices, problems, and methods to mitigate consumer risks will be provided. INTRODUCTION The use of technology for the communication and storage of medical information has experienced a significant increase over the past several years due to the many benefits experienced. For example, the ability to maintain patient information and health data electronically can increase the convenience and feasibility of health care administration for practitioners and patients (Freeman, 2006). The reduction of repetitive tests, cross checking, and collaboration of collected data could help eliminate human errors associated with diagnosis and prescriptions (Fricke, 2008). Increased operational efficiencies could control costs, expedite insurance claims and reimbursements, and ultimately have a positive effect on shareholder value (Lowder, 2008). However, these benefits are drawn with the inclusion of many risks. For instance, the confidentiality, integrity, and availability of patient data may be at risk when stored on a web server, and the privacy of the patient’s health information could be compromised. Confidentiality, integrity, and AHCMJ, Volume 5, Number 2, 2009 64 availability of information may also become issues if the electronic storage systems are unreliable, breached, or not kept up-to-date. Norberg, Horne, and Horne (2007) contend that the consumer’s sense of personal privacy will continue to deteriorate unless they have a good understanding of how their information is being collected, used, and stored. Therefore, the purpose of this paper is to take a closer look at one area of privacy that notably can affect many consumers – the use of electronic health records (EHR). OVERVIEW OF ELECTRONIC HEALTH RECORDS There are many components of a health information management system and there are hundreds of health information management system vendors on the market running on various hardware and operating system platforms. This health information management system industry continues to grow and serve every aspect of healthcare—from day-to-day tasks that a practice management system handles like scheduling, demographic, and insurance information of patients to niche specialties such as operating room preferences of surgeons and laboratory and pharmaceutical applications (Fricke, 2008). Before discussing specific features of electronic health records, it will be helpful to imagine a scenario. Imagine walking into an emergency room in another state and a team of doctors is able to access your entire medical history, make informed decisions, and cure you of whatever ails you. As you register at the reception desk, your demographic information such as blood type, height, weight, and medical history and diagnosis such as allergies, cancer, and broken leg are immediately uploaded from the Internet to the hospital’s health information management system. When your blood work is processed, results are automatically sent to the system so all clinicians who need access can view it. As you move to radiology, your exact procedures are documented and films are uploaded to the system to be viewed by your attending physician and other clinicians. After the doctor has diagnosed your illness, it is entered into the system and proper medications are recommended by the pharmacy based on the diagnosis, your demographic information, and health insurance. As the nurse administers the medication, your bar coded wristband and the medication are scanned to ensure that proper dosage and AHCMJ, Volume 5, Number 2, 2009 65 administration is taking place. When your hospital stay ends, an itemized bill is prepared and immediately sent to your insurer upon discharge. Returning to your home state and primary care physician, follow-up visits can be either an on-site check-up or, due to the documentation in your electronic medical record, a conversation via e-mail, or phone as to your well-being. The above scenario, although very attractive from a patient perspective and highly probable over the next ten years, is not very realistic in today’s healthcare system. Traditionally, the recording of patient health histories and patient care has been accomplished through the use of paper medical records and charts. When a patient visits a new doctor’s office, the patient typically fills out a health history form to report previous diagnoses and other health information such as current prescriptions and family medical history. When the doctor examines the patient, data relating to the patient’s condition and general health is recorded on paper records. These source records, including lab results, are then placed in the patient’s medical record to build a history of the patient’s health problems and care provided. Many hospitals and medical practices today still utilize a paper system to record and store patient data. However, these records are typically stored on a shelf or in a drawer, and are not given to the patient when the patient changes practitioners. Thus, the historical record is “lost” and a patient’s new doctor must start from scratch to begin building the patient’s record. As technology advances, hospitals and practices are moving toward paperless systems to provide better access to patient data and better care. An electronic medical record (EMR) is an application used by healthcare practitioners to document, monitor, and manage health care delivery within a care delivery organization (CDO). The data in the EMR is the legal record of what happened to the patient during their encounter at the CDO and is owned by the CDO (Garets & Davis 2006). According to Garets and Davis (2006), EMR applications are installed in approximately 61% of the U.S. hospitals and the majority of these are still in the early stages of adoption. The EMR may provide convenience to practitioners, as patient data can be easily and quickly accessed and will not be subject to risks of paper records, such as physical damage or misplacement. However, the EMR is only used by the specific medical practice or hospital in which it was created and the patient has very limited access, if any, to the information contained within the record (Garets & Davis 2006). AHCMJ, Volume 5, Number 2, 2009 66 In addition, The Health Information Technology for Economic and Clinical Health Act (HITECH Act) could further accelerate EMR adoption by providing incentives to healthcare practitioners through Medicare reimbursements. Hospitals and physicians who demonstrate “meaningful” use of “certified electronic health record technology” will be eligible for significant financial incentives. After 2014, these incentives are scheduled to be removed with Medicare payment reductions applied to those who do not comply with EMR standards. The overall goal of the HITECH Act is to further the utilization of EMRs (Klein & Cohn 2009). The electronic health record (EHR) consists of component data derived of the EMR and addresses some of the limitations of the EMR. For example, a very important distinction is that the EHR is owned by the patient, rather than the health care provider (Garets & Davis 2006). Thus, the record is mobile so that when a patient switches medical practices or hospital systems, the EHR can be carried along and can be utilized by the new provider organization. The EHR would allow the new practitioner to view the patient’s medical background and the details of care provided by other practitioners, and the patient would be able to add information to the record as well (Garets & Davis 2006). Table 1: Differences Between Electronic Medical Records (EMR) and Electronic Health Records (EHR) Source: Garets and Davis, 2006 The terms EHR and EMR systems are commonly confused and used interchangeably in the medical and technological communities, so a distinction between each was made. Table 1 provides a detailed comparison between the EHR and EMR. This manuscript is not meant to debate or define specific categories of AHCMJ, Volume 5, Number 2, 2009 67 software, hardware, or systems used to store patient data nor to critique, promote, or disparage any one vendor or their system. For this paper, electronic medical record and electronic health record refer to an electronic medical record in digital format which resides in one or many health provider computers. We will use EHR throughout the remainder of this paper. CONSUMER PRIVACY CONCERNS WITH EHRs Using EHRs to store, track, and transmit patient protected health information has stirred significant debate. Given the risks and privacy concerns, many consumers remain skeptical of EHR technology, do not fully understand how EHRs work, and/or question the ethics of using such electronic records. There are a number of privacy issues that could be faced by consumers if their medical information is included in an EHR. These include: a) Privacy and Integrity of Health Related Data, b) Security Breaches, and c) Medical Identity Theft. Privacy and Integrity of Health Related Data A major risk which concerns consumers relates to the privacy of healthrelated data. Most patients desire to keep their medical problems confidential, not only to eliminate embarrassment regarding the condition but also to protect against legal troubles. For instance, if a medical record was exposed and revealed that the patient has AIDS, the patient could face trouble acquiring health insurance or obtaining a new job. To address such risks, the Health Insurance Portability and Accountability Act (HIPAA) Privacy Rule was enacted to protect the confidentiality of patient protected health information from improper use or disclosure (HHS OCR 2003). A supplement to HIPAA, known as the Security Rule, was implemented to assure the confidentiality of electronic protected health information by specifying a series of administrative, technical, and physical security procedures (HHS CMS 2007). However, laws cannot prevent the possibility of human errors or the persistence of hackers. The integrity of the patient data stored in the EHR may also be at risk of corruption or inaccuracy if a glitch exists in the software, or if an unauthorized user alters the data. Proponents of EHR technology argue that electronic records will reduce medical errors, improve patient care through better tracking of prescriptions and procedures, reduce costs associated with healthcare management, and improved communication between practitioners (HC Pro 2008). However, other analysts AHCMJ, Volume 5, Number 2, 2009 68 believe that EHR technology will produce opposite effects. Experts in the policy and legal professions report an increase in adverse events in health care facilities after adoption of EHR technology due to the increased time practitioners spend using the EHR system in lieu of attending to patients, prompting concerns over malpractice liability (Korin & Quattrone, 2007). Some practitioners also oppose the use of electronic records, citing limitations to data entry and inability to document patient information in useful, narrative formats (Walsh 2004). Vendors are working with experts in the healthcare industry to address some of the current limitations of electronic health record technology to help accelerate future implementation (Monegain, 2007). Additionally, the positive potential of EHR technology has been demonstrated by pioneers such as the Veterans Health Administration, which has experienced a 6% annual increase in productivity since successful implementation of its VistA software (Evans, Nichol, & Perlin 2006). However, given the present limitations of electronic health records and the criticism from consumers and practitioners, widespread adoption of EHR technology at the current time appears to carry risks. Security Breaches Another consumer privacy concern pertains to moving sensitive medical records from paper to a d...
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