Output of the Healthcare Sector
1. Describe the product medical care and its components.
2. Define the concepts of risk and risk shifting and show why they are relevant to medical care.
3. Describe health care and its components.
4. Describe the concept of health outcome.
5. Explain the theoretical relationship between health and medical care, and demonstrate the meaning
of the term flat-of-the-curve medicine.
In this chapter, we introduce the descriptive elements in the study of the healthcare system. This
involves identifying the phenomena with which we are concerned, defining them so we can know their
nature precisely, and measuring them so we can obtain an understanding of their magnitude. At this
stage, we wish only to discover what phenomena exist, not what causes them (explanation) or in what
quantities they should exist (evaluation).
The processes generated within the healthcare system can be looked at in two ways. The first approach
is to directly examine factors that influence health. These health-influencing factors can be classified as
lifestyle elements, such as diet, sleep, and other individual behaviors; environmental factors, such as air
and water purification; genetic factors; and medical care, such as examinations and treatments. Section
1.2 focuses on the definition and measurement of medical care. It identifies and defines the phenomena
associated with medical care and discusses measures that indicate how much medical care is provided.
Section 1.3 describes another aspect of the healthcare system: risk shifting. Because most medical
expenditures do not occur with certainty, individuals will place a value on buying insurance to cover
possible losses. Risk shifting provides benefits to consumers and is an important output of the
The second approach stems from the assertion that the true end of the healthcare sector is not the care
itself, but rather the health that results from this care. When measuring the output of health care,
according to this approach, the measure should be how much health is being produced. If it is believed
that the volume of medical care provided is not necessarily a good indicator of the benefits provided, a
more fundamental approach would be to measure what medical care is ideally supposed to produce,
that is, health. Section 1.4 examines issues of definition and measurement associated with health.
Section 1.5 focuses on the output of the healthcare system derived from the education of healthcare
personnel. The healthcare system includes the training of the professionals who work within the system,
and these individuals will produce output (health care) during their training and after it is completed. In
economic terms, the output of the education and training production process is called “human capital.”
1.2 MEDICAL CARE
Medical care is a process during which certain inputs, or factors of production (e.g., healthcare provider
services, medical instrument and equipment services, and pharmaceuticals), are combined in varying
quantities, usually under a physician’s supervision, to yield an output. An individual visiting a physician’s
office receives an examination involving the services of the physician or a nurse practitioner, nurse, or
medical technician, and the use of some equipment. The inputs vary from one visit to another. One
patient may receive more friendly treatment than another, and healthcare providers vary in their
thoroughness, knowledge, and technique. Thus, the quality of one visit may differ considerably from the
quality of another.
Much of the difficulty in measuring the medical care process stems from the issue of quality. If physician
care is measured by the number of patient visits to a physician’s office, two cursory examinations count
as two visits. But one cursory examination followed by a thorough examination involving a battery of
tests also counts as two visits, even though more medical care was provided.
It should be stressed that quality is a very broad term, and its meaning is elusive (Donabedian, 1988).
For example, organizations providing medical care can have substantially different characteristics. To
begin with, they can differ in terms of structure, that is, the amount and type of training of the care
providers and the type of medical equipment used. Further, differences in structure are associated with
the use of different techniques in the provision of care. For example, a computerized axial tomography
(CAT) scan machine that takes cross-sectional radiographs is generally considered to provide a higher
quality product than a standard radiology machine (Sisk, Dougherty, Ehrenhaft, Ruby, & Mitchner,
1990). A second aspect of the quality of care involves the process of providing care, in particular, the
amount of personal attention providers devote to consumers, and incorporates what is actually done in
the provision and receipt of care. Examples of quality-of-care measures that reflect the degree of
personal attention given to consumers include the volume of services performed per individual and
patient evaluations of physician performance.
Another set of characteristics is associated with outcomes, or the effects of care on the health status of
the individual or the populations. In this instance, the measure of outcomes deals with the accuracy of
diagnoses and the effectiveness of treatments in producing health. Examples of measures reflecting this
set of characteristics include hospital mortality rates adjusted for patient condition, the rates of other
adverse events in hospitals, such as postsurgical infections, or the reduction in influenza because of
All of these characteristics, as well as others, have been identified as aspects of quality. The challenge of
measuring quality, then, derives from the fact that there are many ways of viewing quality and many
different ideas as to what constitutes quality. For this reason, the raw measure “visits” should be only
guardedly used as a measure of physician care.
The measurement of hospital care requires the same caution. Hospital output has frequently been
measured by bed days or by the number of cases admitted to the hospital. Over time, however, the
typical admitted patient receives a greater intensity of services as a result of advances in technology. To
count an admission in 1965 as having the same output as an admission in 2011 (given the type of case)
would be to neglect the greater intensity of services likely to be provided at the later date.
Despite these objections, physician visits as a measure of the output of medical care and hospital
admissions or bed days as a measure of the output of hospital care have frequently been used because
of their immediate availability. Recently, efforts have been made to develop additional measures that
incorporate the changing quality of inputs per admission or per bed day.
Output measurements are usually conducted to make comparisons, either against other output
measures or against some standard. There are two types of output comparisons: time series and crosssectional comparisons. A time series comparison measures the output of the same good or service at
different times. A cross-sectional comparison measures the output of the good or service among
different groups at the same time (e.g., the medical care provided to consumers in different age groups,
ethnic groups, or geographic areas, or with different diagnoses).
Medical care output can be measured at three sources:
1. The providers can be surveyed to determine how much medical care they have produced.
2. The payers for medical care can be surveyed to determine for how much medical care they have
3. The consumers can be surveyed to determine the quantity of consumption or utilization.
With perfect measurement, all three sources will yield the same results; however, because of
measurement difficulties, considerable differences will arise. A continuing source of data on medical
care received by consumers is the National Health Interview Survey, an annual nationwide sample
survey of households on health-related matters compiled for the U.S. Public Health Service. Much of the
information from this survey is summarized in the Public Health Service’s annual compendium of healthrelated data, Health United States (www.cdc.gov/nchs/hus.htm).
The National Health Interview Survey (www.cdc.gov/nchs/nhis.htm) is also the major source of data on
medical care administered by physicians outside the hospital. This care is measured by the number of
visits to physicians (the numbers of visits are often adjusted for the size of the relevant populations to
yield utilization rates), with utilization defined as the amount of services consumed. As an illustration of
the use of time series data, comparisons were made of physician’s office visits per year for individuals in
the 65 and over age group. For this group, visits per person were 4.5 in 1975, also 4.5 in 1985, 5.3 in
1995, and 6.9 in 2008. These numbers indicate that there was no increase in the output of physician
office care for this group between 1975 and 1985, but that a marked increase did occur in the following
decades (see U.S. Department of Health and Human Services, 1994, 1999, 2011). Also, one visit in 1975
was counted as the equivalent of one visit in 2008 because quality-difference adjustments were not
made. It is very likely that quality did increase in this period because of new technology, better
equipment, and better training. Unfortunately, this aspect of output is usually neglected in data
collection efforts (Freiman, 1985).
An alternative way of measuring physician output is to focus on procedures or services. Procedures (e.g.,
an appendectomy) can be measured in a number of dimensions (e.g., average time of performance,
complexity, overhead expenses), and based on these dimensions, comparable weights can be developed
for each procedure (Hsiao & Stason 1979; Hsiao et al., 1992). This approach better captures the
differences among various physician tasks.
There are several different measures of hospital output. One way of measuring output is to examine the
number of admissions on a per-population basis. In 1964, there were 190 admissions per 1,000
population, while in 2007 there were 114 admissions. However, the length of stay per admission has
changed radically in this time period, from 12 days per admission to 4.8 days. As a result, total days in
hospital per 1,000 population fell from 2,292 to 540. The number of days is a better measure of
resources used than admissions, but even days does not tell the whole story, as it leaves out the
consideration of quality (U.S. Department of Health and Human Services, 1999, 2011).
Because of the vast differences in types of illnesses, in disease severity, and in medical treatment
patterns (including quality of care), hospital output is difficult to characterize from an economic
viewpoint. One method of doing so that captures a mixture of illness types and severities, as well as
treatment patterns, is the diagnosis-related group (DRG) classification system. The DRG system has
many variants, but all of them are simply patient classification systems. In the 1998 version of the DRG
system, which was used by the Health Care Financing Administration to reimburse hospitals, hospital
inpatient output was divided into 511 different groups based on the major reason for hospitalization,
whether the case was medical or surgical, patient age, and the presence of significant complications and
comorbidities (conditions in addition to the primary). In 2007, the Centers for Medicare and Medicaid
introduced the Medicare Severity Diagnosis-Related Groups (MS-DRG), expanding the number of groups
to 745. While the MS-DRGs do not measure quality, they do incorporate more data on the severity of
illness of the patients within the diagnosis.
In a nationwide study of hospital costs conducted at the Agency for Health Care Policy and Research
(AHCPR), average annual charges for specific DRGs were as follows: normal delivery, $3,094; craniotomy
without complications, $32,594; liver transplant, $204,000 (Agency for Healthcare Research and Quality,
1997). Despite the fact that the DRG system develops average costs among groups, the range of costs
within, as well as between, DRGs was considerable; this variation is reduced, but not eliminated, with
the MS-DRG system.
DRGs do not measure “quality of care.” To gather a picture of hospital product quality, we must look at
data collected from hospitals. Hospital output data are available from Vital and Health Statistics (Series
13), published by the Public Health Service; Hospital Statistics, the annual compendium of the American
Hospital Association (AHA), and various issues of Hospitals: Journal of the American Hospital Association.
The Hospital Compare website (http://www.hospitalcompare.hhs.gov) provides another source of
quality measures in hospitals, including patients’ perceptions regarding their hospital stays.
The AHA formerly published a series of indexes that extensively covered the concept of measuring
quality changes in hospital care over time (Phillip, 1977). This index attempted to measure the quality
change of a day of care by changes in service intensity, which was defined as the quantity of real
services that go into one typical day of hospitalization. The AHA’s Hospital Intensity Index (HII)
incorporated 46 services, including the number of dialysis treatments, obstetric unit worker hours, and
pharmacy worker hours. A weighted average of these 46 services was calculated annually on data from a
sample of hospitals to derive an average number of services per patient day offered during the year.
With the calculation for 1969 as a baseline (the value for that year equals 100), the annual averages
formed an index that measured changes in the service intensity component of output over time.
Although these data are no longer published, they did provide an excellent illustration of how important
service intensity is as a component of medical care output. While intensity of service has been
associated with quality of hospital services, there is no evidence that increased intensity always results
in increased quality of care. There are a number of other factors impacting actual quality of care
In Table 1-1, national data are shown for three components of hospital utilization between 1980 and
2007. The three general measures are hospital patient days per 10,000 population, hospital discharges
per 10,000 population, and average lengths of stay (ALOS) in days. These three categories are then
presented as crude rates and as age-adjusted rates. The crude rates are simply numbers of events that
occurred. The age-adjusted rates are statistical calculations to adjust the population to a “standard”
distribution. Age-adjusted rates enable better comparisons among populations with different age
distributions, which is particularly important in health care, because there are substantial differences in
health simply because of the aging process. For example, if there is interest in comparing hospital
utilization across different areas, and one area has a high rate of younger individuals (possibly because
of a college town within its borders), compared to another area with an older population, the ageadjusted rate can be used to reduce the confounding impact of age differentials.
Table 1-1 Output in Short-term, Acute Care Hospitals in the United States
As can be seen in Table 1-1, the utilization of hospitals has been declining since 1980. The decline was
large in the 1980s and early 1990s, and has leveled off somewhat in recent years, especially in terms of
the length of stay of individuals admitted to hospitals. The age-adjusted number of days of care per
10,000 population in 2007 was only about 40% of what it was in 1980. The decline in days of care reflect
both a decrease in the number of times individuals were admitted/discharged from the hospitals and
the average length of time they stayed in the hospital once admitted.
1.3 RISK SHIFTING AND HEALTH INSURANCE
Another type of healthcare sector output is risk shifting through the purchase of health insurance.
Illnesses are often unexpected and accompanied by monetary losses. These losses can be in the form of
medical expenses, lost earnings from work, and other expenses. Individuals can be said to face a risk of
losing some of their wealth, which means that the existence of the loss and its amount are uncertain.
This risk creates concern on the part of the consumers, and they are usually willing to pay something to
avoid the risk.
One way of dealing with the risk is to shift it to someone else. Insurers are organizations that specialize
in accepting risk. When an insurer accepts a large amount of risk, the average loss to the insurer
becomes predictable. Of course, there are costs of operating such a risk-sharing organization. These
include the administrative expenses associated with determining probabilities, setting prices, selling
policies, and adjudicating claims. The owners also expect a return on their investment (profits). These
expenses and profits are included in the fee (called a premium) that each individual must pay to obtain
insurance. The essential point here is that, in its own right, risk shifting is an additional output that is
distinct from the output called medical care. Someone can obtain medical care without risk shifting (by
paying for it when the product is received). Such an individual is still faced with the risk of incurring
losses, but has done nothing to shift the risk. It is the additional activity of shifting the risk in advance—
taking action to reduce the loss should illness occur—that is the output.
There are a variety of ways in which risk can be shifted. It can be done privately, by the purchase of
insurance. Insurance organizations, such as Blue Cross Blue Shield, Prudential, and Aetna, sell health
insurance policies, either directly to individuals (individual policies) or through groups, such as
employers and professional associations (group policies). In addition, health maintenance organizations
(HMOs) act as both insurers and providers of care. The government also acts as a payer of healthcare
bills for large numbers of individuals, although, strictly speaking, it is not an insurer; most of its revenues
are in the form of taxes, not premiums, and often the covered individuals are not the ones who pay
these taxes. Thus, the government does not manage its healthcare related expenditures on an insurance
(risk assessment) basis. Government-style risk sharing is referred to as risk pooling.
Health insurance can cover all an individual’s expenses. Full insurance has become quite costly, and so
insurers have come to resort to “cost-sharing” provisions, in which insured persons pay a portion of
their healthcare bills and the insurer covers the rest. These provisions allow the insurers to limit
expected payouts and charge the insured persons lower premium rates. In cost-sharing arrangements,
the risk shifting is not complete.
Cost sharing can be done in several ways. The insurance policy can require the individual to cover the
first dollars of expenses—a deductible—and the insurer then pays all, or a portion, of the rest. For
example, the individual might be required to pay a deductible of $100 before the insurer begins to kick
in. The insurer can also specify a limit above which payments will cease. For example, it might cover
expenses up to a lifetime limit of $1,000,000. Beyond that, the individual would again bear the risk. Socalled catastrophic insurance can be obtained to cover very large losses.
The amount and type of insurance coverage is inextricably tied to the workings of the medical care
market. T ...
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