Economic Evaluation of Health Care Programs

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Cost-Utility Analysis: A Method of Quantifying the Value of Registered Nurses


Quality patient care and a
reduction in costs through careful management of resources are the
expectations consumers, insurers, regulatory agencies, and governmental
agencies have for professional nurses. Quality patient
care and a reduction in costs through careful management of resources
are the expectations consumers, insurers, regulatory agencies, and
governmental agencies have for professional nurses. Nurse executives are
continually challenged to demonstrate the value of registered nurses
(RNs) in providing quality care with limited resources. This article
will discuss several different mechanisms used to measure cost
effectiveness in health care today.

Nurse-sensitive indicators are one measure of the effectiveness of
professional nurses. The endeavor to link nursing care to patient
outcomes using nurse-sensitive indicators was undertaken by the American
Nurses Association (ANA) in 1994. The ANA efforts resulted in the
establishment of the National Database of Nursing Quality Indicators^TM (NDNQI^®) in 1998, housed at the University of Kansas School of Nursing (ANA, 2007).
The definitions and measurement strategies used in the NDNQI have been
reviewed and accepted by the National Quality Forum and The Joint
Commission. In addition, nurse executives have used the information to
improve the quality of patient care (Montalvo & Dunton, 2007).

The nursing profession has also been challenged to consider using
cost-utility analyses, such as quality-adjusted life years (QALY) and
disability-adjusted life years (DALY), to demonstrate desired patient
outcomes (Brosnan & Swint, 2001; Hirskyi, 2007; Siegel & Clancy, 2006; Stone, Lee, Giannini, & Bakken, 2004).
These methodologies can be employed to further define the impact of
nursing practice for such care issues as patient falls, urinary tract
infections, hospital acquired pneumonia, postoperative infections, and
hospital-acquired pressure ulcers, that are influenced either directly
or indirectly by nursing care. However, this has been challenging for
nursing because, although the hospital prevalence rate of these patient
care issues is important, the lasting health and economic consequences
of these events for the patient post discharge is yet to be fully
understood. Using cost-utility analysis will ultimately be most useful
to nurses when these analyses are able to provide even clearer advice
regarding the allocation of resources for patient care. Yet it is
important that nursing begin working now to gather data for cost-utility
analyses that will guide resource allocation decisions, even though
currently cost-utility analyses are not without controversy.

The purpose of this article is to present cost-utility analysis as a
relevant measure for describing the value of registered nurses. First
the article will present a short overview of cost effectiveness, along
with a discussion of two cost effective measures, cost-effective
analysis and cost-utility analysis. Then the measurement of
quality-adjusted life-years and disability-adjusted life years will be
presented. The article will conclude by challenging nurses to develop
cost-utility analyses into a meaningful and useful methodology that can
provide nursing with a process to measure the financial outcomes of our
nursing interventions.

Measuring Cost Effectiveness

In industry, cost-effectiveness is measured by comparing the cost of
production with the income from the manufactured product. Production
costs include materials, manpower, and management costs, such as manager
salaries, facility expenses, and employee benefits. As a product is
manufactured and prepared for the consumer, the quality and cost of a
manufactured item is amenable to objective measurement. In health care,
however, measuring the cost effectiveness of care and the quality of
patient outcomes is not as objective. Several common economic
evaluations used by both industry and health care are listed in Table 1.

Table 1. Common Economic Evaluations
Economic Evaluation	Definition
Cost analysis	Measurement of the cost of a product or service or intervention.
Cost-benefit analysis	Widely used technique to assist with decision making. The expected benefits of the project are subtracted from the total cost of implementation. The unit of measurement is monetary.
Cost-effective analysis	Costs spent per outcome achieved.
Cost-effectiveness ratio	Ratio of total costs to total benefits expressed in both dollars and benefit value.
Cost-utility analysis	A type of cost-effectiveness analysis that compares different procedures and outcomes relative to a person’s quality of life.
Cost-utility ratio	Comparison of interventions to achieve one quality-adjusted life year

Cost-Effective Analysis

The use of cost-effective analysis (CEA) in health care began in the
1960s as a means to determine the impact and/or the cost savings of the
decision to use a specific intervention, such as a medication, surgical
procedure, or counseling technique (American College of Physicians, 2000).
CEA is not only measured in monetary terms but is also calculated using
other health measurements, such as head injuries avoided through use of
bicycle helmets, sexually transmitted infection reduction through
condom use, and blood stream infections avoided by using chlorhexidine
gluconate dressings (Crawford, Fuhr, & Rao, 2004).

To calculate the cost of an intervention, monetary assignment is
determined by the cost of the care provided divided by a measure of the
benefits received, as assessed in terms of days, years, or incidence of
pathology, symptom management, disease management, or other measurable
indicators. This measurement is called the cost-effective ratio (C/E)
and is the sum of all benefits divided by the sum of all costs (Dixon & Lundeen, 2004). The lowerthe C/E, the more cost-effective is the intervention. Tsai, Chen, and Yin (2005)
used cost-effectiveness analysis to compare hospital-based home care
with traditional, outpatient therapy for patients with mental illness.
Tsai et al. measured outcome indicators of disease, psychotic symptoms,
social interaction, and satisfaction with the service to develop an
effectiveness score. The cost of care was then divided by the
effectiveness score to determine cost-effectiveness ratio (C/E). Thus,
the cost of program effectiveness score = the C/E Ratio.

Their findings suggested the cost of home health care (HHC) was more
cost effective (C/E ratio 4.3) than traditional outpatient therapy (C/E
ratio 13.5) (See Table 2).

Table 2. Example of the derivation of a C/E ratio
Comparison Groups	Costs of Care	Effectiveness Score	C/E Ratios
Home Health	$1,420.60	327.8	4.3
Usual Care	$3,208.20	238.0	13.5
Tsai, Chen, Yin (2005)

Cost-Utility Analysis

A cost-utility analysis is defined as a type of cost-effective
analysis that compares different procedures and outcomes relative to a
person's quality of life. Since the inception in the early 1990s of
cost-utility measurements, there has been much controversy over methods
used to determine these measures and the usefulness of these
measurements. Although over time some standardization of methods and
calculations, based on early, rudimentary studies, has been reported,
there continues discussion in the literature both for (Higginson & Carr, 2001) and against (McGregor, 2003)
using CUA as a method to measure health care costs and interventions.
Today cost-utility analysis is recommended for use by the United States
Public Health Services (USPHSs) Panel on Cost-Effectiveness in Health
and Medicine (USPHS Panel) when policies may impact resource allocation (Chapman et al., 2004).
In these analyses, patient outcomes are described by a single
measurement which reflects the health care outcome in terms of both of
the quality and the quantity of a life (Malek, 2001).
Two measures used to deduce CUA are costs per Quality-Adjusted Life
Years (QALY) and costs per Disability-Adjusted Life Years (DALY). Each
will be discussed in turn, but first an example of research using
cost-utility analysis will be provided.

Recent research has used CUA to demonstrate cost effectiveness in
medical and nursing interventions. Pignone, Earnshaw, Tice, and Pletcher
(2006)
used a metanalysis of the literature to demonstrate the value of a
combined aspirin and statin intervention for primary prevention of
coronary heart disease (CHD) in men. Their findings suggested that a
combination of aspirin and statin medications are a cost-effective
method of preventing heart disease events. In this study, the authors
compared the life-time effects of 10 years of either aspirin therapy, or
statin therapy, or a combination aspirin and statin therapy, or no
therapy in middle-aged men with a 7.5% risk of CHD. Their findings
suggested aspirin therapy was less costly than no therapy for men having
a CHD risk of 7.5% and greater. The addition of statin therapy
increased the cost-utility ratio but proved to be more cost effective
only for the men who had a greater than 10% risk of CHD.

Quality-Adjusted Life Years

Many instruments are readily available to measure quality of life
(QOL) globally, such as the Short Form Health Survey (SF-36) developed
by Ware, Snow, Kosinski, and Gandek (1993) and the Sickness Impact Profile by Gibson et al. (1975).
Additionally, QOL instruments specifically related to disease states
include the Arthritis Impact Measurement Scale by Meenan, Gertman, and
Mason (1980) and the Asthma Quality of Life Questionnaire by Juniper, Guyatt, Ferrie, and Griffith (1993). Also in common usage are the symptom states scales, such as the Faces Pain Scale (Wong & Baker, 1988), the Fatigue Scale (Chadler et al., 1993), and the Functional Independence Measures Scale (Keith, Grainger, Hamilton, & Sherwin, 1987).
Instruments may combine global QOL measures and health-related quality
of life measures to capture emotional, social, and physical well-being,
along with the effect a certain disease process has on the totality of a
life.

While each of these instruments allows researchers to describe and/or
quantify quality of life, none of them have expressed their measurement
in economic terms. This is not to say the measurements are not
important for analyses; nor to state these measurements do no contribute
to our understanding of a person's perception of life as perceived by
the individual. It merely says that ...health care researchers have not yet been able to quantify quality of life in monetary terms. health
care researchers have not yet been able to quantify quality of life in
monetary terms. Quality-adjusted life years (QALY) is a mathematical
measurement that combines quantity and quality of health to calculate
outcomes based on treatment or other activities that influence health (Bandolier, n.d.).
QALY has three key standardized components that support validity and
reliability. First, actuarial data, experimental data, or modeling is
used to study a given population (Graham, 2002).
Secondly, healthy life years are weighted the same; and lastly, the
weights for health states are derived from studies of individuals with
the specific condition in question (Graham).
The difference between QALY and QOL measures is the dynamic of
measurement. QALY attempts to provide a method of measurement for the
impact of disease or treatment on an individual's ability to function
which can be equated to an economic scale. QALY measures differ from the
QOL measures that provide subjective information describing
individuals' self-perception of their health status at a particular
point in time (Donald, 2001).
The QALY measure describes the cost of producing one year of quality
living existence. The scoring range of QALY is from 0 (death) to 1
(perfect health); however, a score that is a negative number may be
derived when a person is living with an extremely low quality of life (Malek, 2001).

Jacobsson, Lindholm, Waldau, and Engstrom (2000)
have demonstrated how CUA can be used to evaluate the effect of a
nursing intervention on patient outcomes, when one of these outcomes is
QOL. Jacobson et al. demonstrated that an eating-training program by
nurses for 11 post-stroke patients was a cost-effective intervention
that improved health-related QOL (HRQOL). This research team collected
data regarding the degree of change of the stroke survivors' feeding and
eating habits and the stroke survivors' HRQOL. In all but 2 cases, QALY
increased, with an average equal to one year of quality living
existence. The average cost per participant in the program was less than
$8000. The savings in this program, which resulted from eliminating the
need for nursing staff to feed the patient and the cost of the
nasogastric or gastrotomy feeding tubes, was $15,000 when compared to
conventional care. For patients without a feeding tube the cost per QALY
gained was $5500. The researchers also compared the cost of their
eating-training program for one QALY to the cost of a pharmaceutically
managed blood pressure program. When compared to hypertension
management, the feeding program for stroke survivors was very cost
effective.

This Jacobson et al. study (2000)
was very innovative in that it compared use of a nursing process
management with a disease process (hypertension) management. A similar
evaluation could be done by comparing changes in nursing practice that
promote patient safety and health outcomes with changes in blood
pressure management or other aspects of medical care. Thus ...the CUA measure can be used to assess cost utility for both medical interventions and nursing interventions the CUA measure can be used to assess cost utility for both medical interventions and nursing interventions (Siegel & Clancy, 2006). To capture accurate CUA for nursing interventions, current practice and the change in practice need to be compared.

It should be noted, however, that some scholars argue against using the QALY formula. Hirskyj (2007)
has argued that the formula for QALY could be considered unjust in a
world where there are limited health care dollars and a value is placed
on a life. Hehas added that in affluent nations, where health
care resources are readily available and expected by the public, this
method of analyzing effectiveness and efficiency could create conflict.
Yet, he encourages nurses to explore the potential of using QALY and
DALY.

Disability-Adjusted Life Years

Another CUA measure that could be considered by nursing is
disability-adjusted life years (DALY) which can be used to measure the
effect of ill health (i.e., hip fracture) in regard to function and
premature mortality (Hirskyj, 2007). In other words, one DALY is one lost year of healthy life (Murray & Lopez, 1996,
p. 7). The goal of measurement of DALY is to use an assessment of the
residual burden of disease and/or injury as an outcome measure (Fox-Rushby & Hanson, 2001). The World Health Organization defines disability-adjusted life years (DALY) as:

a health gap measure that extends the concept of potential years of
life lost due to premature death to include equivalent years of healthy
life lost by virtue of being in states of poor health or disability
(World Health Organization (n.d.).

DALY is a combined measure of years in disability and years of life lost due to premature death (from the disability) (Fox-Rushby & Hanson, 2001).
Two mathematical equations are used to calculate DALY, years of life
lost (YLL) and years lived with disability (YLD). YLL is the number of
years of life lost due to premature death. YLD is the number of healthy
years lost due to disability from the condition until remission or
death. These are then summed together to provide years living with
disability. The DALY scale range is the reverse of the QALY scale, with 1
indicating death and 0 indicating the best possible state of health.
Unlike QALY, DALY reverse scaling would not allow for negative values
because 0 is equivalent to perfect health.

To better understand DALY, consider this hypothetical example. Assume
that 150 eighteen-year-olds die as a result of motorcycle accidents in a
state with no helmet law. The life expectancy for the birth cohort of
1990 is 71.8 years (National Center for Health Statistics, 2006).
Therefore, YLL (for the total sample) was 8070 (150 X 53.8 years). For
YLD, lets assume these teenagers did not die, but sustained severe brain
trauma with disabilities similar to someone with severe cerebral palsy.
As a result, their life expectancy, due to this injury, is decreased to
31 years (Hutton & Pharoah, 2005).
YLD is the computation of number of incidence X disability weight X
average duration of disease or infirmary until death or remission.
Suppose the disability is weighted 0.8 (remember 0 is perfect health and
1 is death. The YLD is then 150 X 0.8 X 13 = 1560. Thus DALY (9630) =
YLL (8070) + YLD (1560). This is powerful when advocating for policy
change. Armed with this information
nurses could talk to their legislators about the number of years of lost
productivity from their constituents as a result of injuries .... Armed
with this information nurses could talk to their legislators about the
number of years of lost productivity from their constituents as a result
of injuries sustained from motorcycle-related health injuries. Adding
disability costs, costs of care, and deducting potential income of the
150 accident victims who would, for their age, be expected to have
worked until the age of 65 years if not prevented by their disability,
adds additional strength to the case for change of a state no helmet
law.

There is considerable debate about the use of DALY in cost-effective
analyses. Much of the debate has been centered on methodology (Fox-Rushby & Hanson, 2001), the lack of recognition of change in disability states over time (improvement or decline) (Jelsma, De Weerdt, & De Cock, 2002), and the limitations imposed by a single measurement (Barker & Green, 1996).
Additionally, Disability Peoples International (DPI) has issued an
opposition statement to DALY use for health policy. They present four
points:

1. DALY does not take into account social and environmental causes of disability
   
2. It assumes that any given disabling condition always has
   the same outcomes. That is, if you are diagnosed with a certain
   condition then the outcome must be x, y, or z, whereas the lived
   experience of disabled people shows clearly that is not the case.
   Outcomes are dependent on the environment and social impacts on the
   personal characteristics of the individual
   
3. The authors of DALY have relied on medical experts and ignored the disability community
   
4. The DALY puts the blame for low ratings in the global
   development measurement firmly on disabled people, instead of on lack of
   services, health care, equality, and justice. (Disabled People International, March 2006).
   

Advocates of using DALY argue that egalitarian principles are the
hallmark of this measurement. The calculations for DALY consider age and
sex when calculating the burden of the disability; there is no
consideration for economic status so that disability burden is measured
globally for all (Murray & Lopex, 1996).
They add that respectful consideration is given to DPI's position.
Because there is no other economic evaluation available to pursue policy
avenues to address concerns, such as lack of services, health care,
equality, and justice, using DALY to demonstrate the cost of ineffective
and inefficient care could provide support to enact policy changes that
would lessen the burden of disability.

Conclusion

The Nursing Report Card The
Nursing Report Card... has fueled nurse executives' abilities to
negotiate for a higher RN skill-mix in order to improve patient care
outcomes. has shown a reduction in undesired,
nurse-sensitive, patient outcomes, such as secondary pneumonia,
postoperative infection, hospital-acquired pressure ulcers, and urinary
tract infections, in hospitals having a higher proportion of RNs in the
nursing staff skill mix (Gallagher, & Rowell , 2003).
These findings emphasize the association of costs, processes, and
outcomes. This seminal work has fueled nurse executives' abilities to
negotiate for a higher RN skill-mix in order to improve patient care
outcomes.

Although the use of CUA, a measure which includes QOL, has yet to
become the industry standard for health care, it is increasingly being
tested (Neumann, Greenberg, Olchanski, Stone, & Rosen, 2005).
The methodology is becoming more sophisticated and a trend toward the
adaptation and adherence to the U.S. Panel on Cost-Effectiveness in
Health and Medicine is being noted in the literature (Neumann et al.). This is encouraging because all nursing care directly or indirectly impacts the patient's QOL. Hence ...there is a good match between CUA and the impact of nursing on patient care. there is a good match between CUA and the impact of nursing on patient care.

The question at this time is not whether CUA is a useful measurement
to show the value of nursing, but rather under what circumstances it is
most beneficial to use CUA to evaluate the benefits of nursing
interventions. Because interventions which prevent complications and/or
the advancement of an illness, such as managing congestive heart failure
and strengthening a diabetic patient's self care skills, have a
significant influence on the patients QOL, CUA could most profitably be
studied in these cases to demonstrate in economic terms the value of
nursing care.

Murray et al. (2003)
have already used CUA to demonstrate the value of nursing interventions
related to congestive heart failure. This team assessed the cost
effectiveness of interventions to lower blood pressure and cholesterol
levels. They demonstrated that a reduction of salt in processed foods
could ward off 21 million DALYs annually, worldwide, through the
reduction in vascular disease and its sequelae. Their conclusions
suggested the incidence of cardiovascular disease could be decreased by
50%.

Nurses could lead the charge to transform DALY into a measurement
that accounts for all causes of preventable disability, differentiating
disability outcomes and demonstrating how to translate data into action.
Nurses could start with small projects, such as defining the costs of
patient falls in a hospital and showing the value of a nursing
intervention that would prevent these falls. To enlarge their impact,
nurses could assist communities at the local, regional, and national
levels in using CUA to show the outcomes nurses can have on overall QOL
and costs of health care. ...nurses
could assist communities at the local, regional, and national levels in
using CUA to show the outcomes nurses can have on overall QOL and costs
of health care. For example, if the community has a high
diabetic population living in public housing, nurses could begin
working with the local public housing authority to research the
effectiveness of in-home education for diabetes management compared to
formal classroom group education that is routinely offered to the
general population through community diabetic educators. Using another
example, nurses could use the data from the CEA registry to assess the
impact of in-school prenatal care for teen pregnancy on premature births
and the costs of neonatal intensive care ($47,000/QALY for 0.5 -1 kg
infant and $6,800/QALY for 1-1.5 kg infant) versus routine care for
normal newborns. Other community health problems, such as smoking, motor
vehicle accidents, underage drinking, and injuries and falls in the
older adult are just a few of the opportunities in which nurses could be
involved in terms of assessing nursing interventions and improvement in
the health of their communities. See Table 3 for websites that provide information on CUA through QALYs and DALY.

Table 3. Websites offering information on CUA through QALY and DALY
Agency	Website
Centers for Disease Control and Prevention: Diabetes Cost Effectiveness Group	www.cdc.gov/diabetes/news/docs/cost.htm
World Health Organization: Global Burden of Disease Concept	www.who.int/quantifying_ ehimpacts/publications/en/9241546204chap3.pdf
National Institutes of Health Self-Study Course: Health Economics Information Resources	www.nlm.nih.gov/nichsr/edu/healthecon/glossary.html
Agency for Healthcare Research & Quality (AHRQ): Clinical Economics Research Database	http://cerd.ahrq.gov/
Tufts-New England Medical Center CEA Registry	www.tufts-nemc.org/cearegistry/

The challenge for nurses is develop CUA (using QALY and DALY studies)
into a meaningful and useful methodology that can provide the
profession with a process to measure the outcomes of nursings' holistic
interventions. Short term economic analyses provide information for
immediate needs, such as budgetary planning and compliance, meeting
established benchmarks, and regulatory compliance. Using a more holistic
approach, such as CUA, may assist nurse leaders to demonstrate the
unique value of professional nurses that care for patients. For example,
acute care nurse leaders could assess the patient costs related to a
reduction in man-hours. They could start by exploring the differences
between patient outcomes prior to and after the change using CUA. While
this may prove to be cumbersome due to the complexity of assessing QALY
and/or DALY, it is essential for nurse leaders to embrace the ultimate
cost of care over the continuum of life.

In summary, this article presented an overview of cost effectiveness,
along with a discussion of two cost-effectiveness measures,
cost-effective analysis and cost-utility analysis. Then two CUA
measures, quality-adjusted life years and disability-adjusted life
years, were discussed. The article concluded by challenging nurses to
develop cost-utility analyses into a meaningful and useful methodology
that can provide the profession with a process to demonstrate the
outcomes of our nursing interventions.

Author


Patricia M. Vanhook, PhD, APRN, BC
E-mail: Vanhook@etsu.edu

Dr. Vanhook is an Assistant Professor at East Tennessee State
University. She has been in practice since 1973, during which time she
has practiced clinically as a bedside nurse and nurse practitioner,
served as Magnet Coordinator for the first Magnet Hospital in Tennessee,
and spent over twenty-five years in nursing administration in the roles
of Nursing Director and Assistant to Chief Nursing Officers. These
experiences have provided various opportunities for involvement in both
quality outcomes and performance improvement. She recently received her
PhD from East Tennessee State University, Johnson City, Tennessee, where
her dissertation research focused on Appalachian women stroke
survivors. While serving as an acute care nurse practitioner, she
observed that hospitals' data interest centered primarily on short term
measurements that were linked to financial performance. She quickly
realized that short term performance does not demonstrate the full
picture of long-term outcomes and costs to either patients or to health
care systems. This led to her interest in using the public health model
of evaluating outcomes based on quality-adjusted life years or
disability-adjusted life years.

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