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National Healthcare Quality Report, 2007

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Chapter 6. Efficiency

Few issues within American health care policy today are as extensively debated as how to obtain better value for money. And the debate about how to improve efficiency is equally matched by the debate about how best to measure it. The existence of varying perspectives and definitions of "efficiency" in the health care market place and the lack of consensus on what constitutes appropriate measurement of efficiency have stymied efforts to report on this area. It is the only one of the Institute of Medicine's set of six quality aims1 that the NHQR and NHDR have not yet addressed.

The issue of how to improve efficiency in the Nation's health care system is at the heart of the mission of Secretary Mike Leavitt and the Department of Health and Human Services to increase transparency in health care with better information on quality and cost. In support of this mission, this year's NHQR provides an initial look at potential information sources and findings on efficiency in the U.S. health care system.

The focus on efficiency in this year's NHQR is a first attempt to outline the varying perspectives on efficiency and to offer potential methods for measuring efficiency at the national level that respond to the NHQR's mandate—that is, to provide information on health care performance for lawmakers in Congress. This chapter does not attempt to provide a definitive framework for efficiency, nor does it provide an exhaustive list of potential measures of efficiency. The examples provided should be viewed as preliminary, and no conclusions about efficiency in the U.S. health care system should be drawn. Rather, the Agency for Healthcare Research and Quality (AHRQ) hopes that this chapter will stimulate further productive discussions in the area of health care efficiency. AHRQ intends this chapter to be the first in an evolving national discussion on measuring efficiency in the U.S. health care system that will be reviewed, revised, and presented in future reports.

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Background and Measures

In its landmark report, Crossing the Quality Chasm: A New Health System for the 21st Century,1 the Institute of Medicine (IOM) presented six "aims" for the health care system: effectiveness, safety, timeliness, patient centeredness, equity, and efficiency. AHRQ, in its reauthorization legislation of 2001, was given the task of developing two national health care reports that would track quality and prevailing disparities in the Nation's health care.

IOM provided guidance2, 3 on the development of these two national health care reports and suggested that the framework for the reports be linked to the six aims presented in Crossing the Quality Chasm. At the same time, however, IOM stated that AHRQ should not try to address the issue of efficiency in the first national reports, but rather should examine its inclusion in future reports or in a stand-alone report.

With guidance from an HHS Interagency Work Group brought together to advise on the development of the reports, AHRQ developed the first NHQR and NHDR in 2003 without addressing the topic of efficiency. In 2004, the Interagency Work Group encouraged AHRQ to examine possible approaches to including efficiency in future reports. This followed advice by AHRQ's National Advisory Committee (NAC) of external experts from the private sector, academia, and the Federal sector. The NAC had, at AHRQ's request, formed a subcommittee, led by Dr. Don Berwick, that provided advice on the NHQR and NHDR. That subcommittee recommended that AHRQ develop a chapter on efficiency for the reports.

To respond to these NAC and Interagency Work Group requests, AHRQ formed a subgroup of its Interagency Work Group in 2004 to address the issue of efficiency. This subgroup held two meetings in 2005, during which it reviewed documents from previous reports and discussed possible ways to further this effort. The subgroup concluded at that time that there was insufficient consensus on the perspective from which to conceptualize and measure efficiency.

AHRQ had previously commissioned the RAND Corporation to systematically review measures of efficiency and their potential for tracking and reporting at various levels. The efficiency subgroup, therefore, decided to wait until that report was submitted to AHRQ to develop any further plans. The final version of this recently completed report summarizes the knowledge base on efficiency measures as follows:

  • Few analyses about the reliability and validity ("scientific soundness") of published and unpublished measures have been conducted.
  • Both the published literature measures and the vendor measures focus on intermediate outcomes (e.g., inpatient stays), not final outcomes (e.g., functional status, measures of health).
  • Consensus has yet to emerge on which approaches constitute acceptable measures of efficiency.4

The RAND report provides a typology of efficiency measures that emphasizes the multiple perspectives on efficiency and points out that measures must be considered from the standpoint of what the measuring organization is and what its goal is in assessing efficiency. The typology distinguishes between:

  • Society as a whole (i.e., the "population" level).
  • Health care firms (i.e., hospitals and other providers).
  • Individuals.

Another recent (2006) report examined the question of efficiency from the point of view of the cost of waste; in that report, the authors outline another common typology for efficiency measurement—the tracking of overuse, underuse, and misuse in the health care system.5

This chapter first presents a general set of trends on costs and quality levels in the U.S. health care system. Then a selection of potential measures on health care efficiency is presented that summarizes information at the population and provider level. The measures used are:

  • Change in expenditures and quality of care for cancer, diabetes, and heart disease (overview).
  • Trends in avoiding unnecessary hospitalizations and costs (population perspective).
  • Trends in hospital efficiency (provider perspective).

Because consensus has yet to emerge about the appropriate framework and acceptable measures of efficiency, the examples provided should be viewed as preliminary and designed to stimulate productive ongoing discussions about health care efficiency.

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Findings

Change in Expenditures and Quality of Care for Cancer, Diabetes, and Heart Disease

Data from AHRQ's Medical Expenditure Panel Survey (MEPS) are used to provide a preliminary overview and to suggest possible national trends in health care cost and quality. MEPS collects health care expenditures by all payers for nearly all types of health care utilization—including outpatient visits, hospital inpatient stays, emergency department visits, prescribed medicines, dental visits, and home health care—for the civilian noninstitutionalized population. Summary data are presented here on the rate of change in total annual expenditures for all persons and for persons with three high-priority conditions—cancer, diabetes, and heart disease—from 2001 to 2004. This presentation enables comparison of rates of expenditure change with the summary measure of percent change in quality that has been presented in previous NHQRs. The data presented here are summarized in terms of the annualized percent change in the NHQR measures from 2001 to 2004 nationally for the entire measure set and for each condition area.i

Figure 6.1. Overall example: Average annualized percent change in national health care expenditures and quality for all persons and persons with selected conditions, 2001-2004

Bar chart shows average annualized percent change in national health care expenditures and quality for all persons and persons with selected conditions. Overall: Annualized % Change in Expenditures, 7.6; Annualized % Change in Quality, 1.9. Heart disease: Annualized % Change in Expenditures, 12.9; Annualized % Change in Quality, 5.6. Cancer: Annualized % Change in Expenditures, 9; Annualized % Change in Quality, 3.6. Diabetes mellitus: Annualized % Change in Expenditures, 3.7; Annualized % Change in Quality, 0.6.

Source: Agency for Healthcare Research and Quality, Medical Expenditure Panel Survey, 2001 and 2004. Go to the Measure Specifications Appendix for list of measures included in each category.

Reference population: Civilian noninstitutionalized population.

Note: Average annualized percent change in total expenditures adjusted for inflation using the Gross Domestic Product implicit price deflator (Bureau of Economic Analysis).


i This annualized percent change is the same metric as is used in the Highlights section of this report and is explained in detail in Chapter 1, Introduction and Methods. A list of the measures used for these calculations is available in the NHQR Measure Specifications Appendix.


  • From 2001 to 2004, total annual health care expenditures have been increasing at a rate that is four times the rate of the increase in the summary measure of quality of care. Annual total health care expenditures rose 7.6% (in 2004 dollars). ii During this same time period, quality increased at a rate of 1.9%.
  • For heart disease, cancer, and diabetes individually, quality increased at a rate of 5.6%, 3.6%, and 0.6% annually. Expenditures increased at an annual rate of 12.9%, 9.0%, and 3.7%, respectively (Figure 6.1).

Figure 6.1 may seem to suggest that improvements in overall quality are outpaced by increases in expenditures. However, such a conclusion cannot be drawn and the statistics should be viewed with caution, as these are comparisons of percent changes of two very different measures. First, expenditures are comprehensively measured, but quality is not. Figure 6.1 presents a summary of all available quality measures in this report, rather than a catalog of all clinical care for all conditions and patients. The quality measures track both processes of care and outcomes of care. The indicators selected for inclusion in the NHQR/DR measure set are considered the most scientifically sound and clinically important markers of whether we are achieving appropriate performance in health care. However, many aspects of care are not captured in these indicators of quality. A comprehensive assessment may never be feasible, as technical aspects of care are changing more rapidly than can be captured through broad, consensus-based quality measurement vehicles such as the NHQR. Moreover, it would be difficult to collect measures of quality for rare conditions. In addition, the summary measure of quality is composed of measures calculated on a per person basis, but total annual expenditures increase in part due to population growth. Finally, these statistics are provided without estimates of variability (i.e., without confidence intervals). Statistical testing for these sorts of comparisons is complex, and future versions of the NHQR will examine more refinements to such statistical testing.iii

The statistics illustrated above suggest many questions about efficiency. They are not provided to suggest causation between costs and quality. Providing higher quality care may cost more than providing lower quality care, and achieving increasingly higher quality goals may require even higher expenditures to reach an additional person. Some types of quality care might reduce expenditures, particularly by reducing hospitalizations. Furthermore, the factors that caused the changes in expenditures may be different from the factors that caused improvement in quality. More research is needed to investigate these issues.


ii Expenditures in 2001 were adjusted to 2004 dollars using the Gross Domestic Product implicit price deflator.

iii The creation of confidence intervals for expenditures using MEPS data is possible and was conducted for this analysis. The estimates with their confidence intervals are: (a) heart disease 12.9% (3.7-22.1); (b) cancer 9.0% (−2.4-20.4); and (c) diabetes 3.7% (−4.2-11.6).


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Trends in Avoiding Potentially Unnecessary Hospitalizations and Costs

To address the population perspective of avoiding potentially unnecessary hospitalizations and costs, data on ambulatory-care-sensitive conditions are summarized here using the AHRQ Prevention Quality Indicators (PQIs). While not everyone of the hospitalizations tracked by the AHRQ PQIs is preventable, ambulatory-care-sensitive conditions are those for which good outpatient care can prevent the need for hospitalization or for which early intervention can prevent complications or more severe disease.6 The AHRQ PQIs track these conditions using hospital discharge data. For this analysis, total hospital charges were converted to costs using Healthcare Cost and Utilization Project (HCUP)iv cost-to-charge ratios based on hospital accounting reports from the Centers for Medicare & Medicaid Services.

Figure 6.2. Population example: National trends in potentially avoidable hospitalization rates, by type of hospitalization, 1997 and 2000-2004

Line graph shows national trends in potentially avoidable hospitalization rates, by type of hospitalization. Overall: 1997, 1,989; 2000, 1,993; 2001, 1,910; 2002, 1,988; 2003, 1,933; 2004, 1,844. Chronic: 1997, 1,294; 2000, 1,246; 2001, 1,191; 2002, 1,223; 2003, 1,198; 2004, 1,136. Acute: 1997, 695; 2000, 748; 2001, 720; 2002, 766; 2003, 735; 2004, 1,844.

Source: Agency for Healthcare Research and Quality, Healthcare Cost and Utilization Project, Nationwide Inpatient Sample, 1997 and 2000-2004.

Note: Data are for adults age 18 and over.


iv The Healthcare Cost and Utilization Project (HCUP) is a family of health care databases and related software tools and products developed through a Federal-State-industry partnership and sponsored by AHRQ. Additional information is provided in the NHQR Measure Specifications Appendix in the "Data Sources" section.


Figure 6.3 Population example: Total national costs associated with potentially avoidable hospitalizations, 1997 and 2000-2004

Bar chart shows total national costs associated with potentially avoidable hospitalizations in billions of 2004 dollars: 1997, $26.2; 2000, $28.4; 2001, $28.4; 2002, $30.5; 2003, $31; 2004, $28.9.

Source: Agency for Healthcare Research and Quality, Healthcare Cost and Utilization Project, Nationwide Inpatient Sample, 1997 and 2000-2004.

Note: Data are for adults age 18 and over.

  • Avoidable hospitalization rates have decreased gradually but significantly between 1997 and 2004 (Figure 6.2). Overall, Americans were hospitalized for conditions that can be effectively managed in the outpatient setting 7.75% less frequently in 2004 than in 1997 (1,989 hospitalizations per 100,000 in 1997 versus 1,844 hospitalizations per 100,000 in 2004).
  • Avoidable hospitalizations are more frequent for chronic conditions. However, avoidable hospitalizations for acute conditions have slightly increased since 1997 (695 per 100,000 in 1997 versus 708 per 100,000 in 2004).
  • Although avoidable hospitalization rates have decreased overall since 1997, total national hospital costs associated with avoidable hospitalizations have increased since 1997 (Figure 6.3). Avoidable hospitalizations cost the Nation's health care system nearly $29 billion in 2004, which was 10% greater than what they cost in 1997 when adjusted for inflation ($26.2 billion).v

These figures provide some preliminary measures of the potential for improvement in one dimension of efficiency.


v The inflation adjustment was done based on the change in Gross Domestic Product.


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Trends in Hospital Efficiency

Significant attention has been paid to cost variations across providers and across the country. Yet it is often difficult to separate out costs due to differences among providers in outputs, casemix, or quality of care. To address the provider perspective, hospital cost efficiency is examined using a technique from the field of econometrics that can account for such differences.vi This analysis uses data from the American Hospital Association Annual Survey, the Medicare Cost Reports, and quality indicators from the application of the AHRQ Quality Indicator software to data from the Healthcare Cost and Utilization Project.

Here, the efficiency of a hospital is defined as the ratio of best-practice costs to total observed costs. For example, given the types and quantities of outputs a hospital produces, the input prices it pays, its casemix, its quality, and the characteristics of its market, a theoretical best-practice hospital might incur expenses amounting to $90 million. A comparison hospital in an identical situation with total expenses of $100 million would have an estimated cost efficiency of 90%.

Cost efficiency estimates have been converted to index numbers with a base of 100 for the year 2000 as a way to place less emphasis on the specific magnitude of estimated cost efficiency than on its general trend.

Figure 6.4. Provider example: Average estimated relative hospital cost efficiency index for a selected sample of urban general, community hospitals, 2000-2004

Bar chart shows average estimated relative hospital cost efficiency index for a selected sample of urban general, community hospitals.  Relative index of hospital cost efficiency: 2000, 100; 2001, 100.08; 2002, 100.37; 2003, 100.64; 2004, 100.65.

Source: Agency for Healthcare Research and Quality. Analysis based on 1,266 urban general, community hospitals with data in the Healthcare Cost and Utilization Project, State Inpatient Databases. Go to Chapter 1, Introduction and Methods, for further details.


vi Stochastic frontier analysis (SFA) is the technique that is used in this analysis. SFA can estimate best-practice costs as the value total costs would be if full efficiency were attained. The hospital-level "cost efficiency" estimates produced by SFA measure whether output is obtained using the fewest inputs (i.e., technical efficiency), as well as whether output is produced using the optimal mix of inputs, given prices (i.e., allocative efficiency), the size of a hospital's operations (i.e., scale efficiency), and the range of a hospital's operations (i.e., scope efficiency), including possible overspecialization or overdiversification.7


  • Estimated urban hospital cost efficiency increased slightly from 2000 to 2004 for a selected sample of urban general, community hospitals (Figure 6.4).
  • The most cost-efficient hospitals (i.e., hospitals in the highest quartile of estimated cost efficiency) compared favorably with the least cost-efficient hospitals (i.e., hospitals in the lowest quartile of estimated cost efficiency) on a number of important variables. Cost-efficient hospitals had lower costs and fewer full-time equivalent employees per casemix-adjusted admission, as well as a shorter average length of stay (Table 6.1).
  • The most cost-efficient hospitals had a higher operating margin than the least cost-efficient hospitals (Table 6.1).
Table 6.1. Provider example: Correlates of hospital cost efficiency
Measure Estimate Standard deviation
Cost per casemix-adjusted admission:
 Top quartile of hospital cost efficiency $4,224.55 $1,212.55
 Bottom quartile of hospital cost efficiency $6,345.03 $2,652.23
Full-time equivalent employees per casemix-adjusted admission:
 Top quartile of hospital cost efficiency 0.042673 0.013120
 Bottom quartile of hospital cost efficiency 0.057556 0.022444
Average length of stay (days):
 Top quartile of hospital cost efficiency 5.45 2.36
 Bottom quartile of hospital cost efficiency 5.76 3.59
Operating margin:
 Top quartile of hospital cost efficiency 0.0123 0.1314
 Bottom quartile of hospital cost efficiency -0.0946 0.2603

It is important to note that the figures reported above are not national estimates and that no conclusions about national trends should be inferred. However, the hospitals in the analysis represent about 52% of all urban general, community hospitals and therefore provide an indication of the general trend that cost efficiency may be following.

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Next Steps on Efficiency Reporting

These brief examinations of efficiency clearly show that a significant amount of information about the study of efficiency and its measurement is not fully developed. In part, this is because the relationship between quality and efficiency is not straightforward. Past work examining variations in Medicare spending and its relationship to quality has shown clearly that higher cost providers do not necessarily provide higher quality care.8 The preliminary examination of efficiency in this chapter is only a first step. Tracking efficiency in the health care system over the long term will require ongoing and future efforts to improve the specificity of quality measures, as well as efficiency measures.

A number of major efforts are underway within both the public and private sectors in the U.S. health care system to advance our knowledge of efficiency. Since 2006, the National Committee on Quality Assurance (NCQA) has published measures of resource utilization for use in conjunction with quality measures for six chronic care conditions. Other private sector organizations, such as the Bridges to Excellence Program, the Leapfrog Group, and the Commonwealth Fund, have been active in supporting efforts to examine improved provider reporting on efficiency. Most recently, the National Quality Forum (NQF), as part of its Priority Setting Project, has developed a framework for efficiency measurement. The framework acknowledges the multiple perspectives on efficiency but concludes that the patient's perspective should be the focus of future work. This necessitates a focus across episodes of care, which presents distinct challenges from a data perspective. Current national data systems are extremely limited in their ability to produce the data needed to satisfy criteria developed for the NQF's efficiency framework. However, AHRQ plans to work closely with its Federal and private sector partners to develop the efficiency reporting in the NHQR to include, where possible, cross-episode accounting of efficiency.

One of the primary areas on which AHRQ and its HHS partners will be concentrating in the realm of improving efficiency measurement is the Secretary's Value-Driven Health Care Initiative. The Value-Driven Health Care Initiative is an effort by HHS Secretary Mike Leavitt and HHS to provide public information about the quality and cost of services delivered by health care providers. Such information is not widely available today. There is little information to help consumers compare doctors and hospitals based on measures of quality and cost. Providers themselves have limited information for comparing their performance based on accepted standards of care. Yet such information is crucial for delivering the best treatment and the best value in health care. As part of the initiative, volunteer participants commit to four objectives, called the "cornerstones" of value-driven health care. One of the cornerstones is "Reporting on Quality," whereby participants commit to public reporting on the performance of doctors, hospitals, and other providers. For more information about the Value-Driven Health Care Initiative, go to: http://www.hhs.gov/valuedriven/.

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References

1. Institute of Medicine, Committee on Quality of Health Care in America. Crossing the quality chasm: a new health system for the 21st century. Washington, DC: National Academy Press; 2001.

2. Institute of Medicine. Envisioning the national health care quality report. Washington, DC: National Academy Press; 2001.

3. Institute of Medicine, Committee on Guidance for Designing a National Healthcare Disparities Report. Guidance for the National Healthcare Disparities Report. (Swift EK, Ed.) Washington, DC: National Academies Press; 2002.

4. RAND Corporation. Identifying, categorizing, and evaluating healthcare efficiency measures. (Final report prepared for the Agency for Healthcare Research and Quality under Contract No. 282-00-0005-21); October 2007.

5. RTI International. Cost of poor quality or waste in integrated delivery system settings. (Final report prepared for the Agency for Healthcare Research and Quality under Contract No. 290-00-0018-11); September 2006.

6. Agency for Healthcare Research and Quality. Guide to prevention quality indicators: hospital admission for ambulatory care sensitive conditions. Version 3.1 (March 12, 2007). Available at: http://www.qualityindicators.ahrq.gov/pqi_download.htm.

7. Rosko M, Mutter R. Stochastic frontier analysis of hospital inefficiency: a review of empirical issues and an assessment of robustness. Med Care Res Rev. 2007. First published online November 28, 2007. Available at: http://mcr.sagepub.com/cgi/content/abstract/1077558707307580v1.

8. Fisher ES, Wennberg DE, Stukel TA, et al. The implications of regional variations in Medicare spending. Part 1: the content, quality, and accessibility of care. Ann Intern Med. 2003 Feb 18;138(4):273-87.

List of Core Report Measures Chapter 5.

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