2012 National Healthcare Quality Report

Chapter 7. Efficiency

Health care cost increases continue to outpace the rise in wages, inflation, and economic growth. One approach to containing the growth of health care costs is to improve the efficiency of the health care delivery system. This approach would allow finite health care resources to be used in ways that best support high-quality care.

Recent work examining variations in Medicare spending and quality shows that higher cost providers do not necessarily provide higher quality care, illustrating the potential for improvement (Fisher, et al., 2003). Improving efficiency in the Nation's health care system is an important component of Department of Health and Human Services (HHS) efforts to support a better health care system.

Measures

Part of the discussion about how to improve efficiency involves the question about how best to measure it. Varying perspectives and definitions of health care efficiency exist; although consensus has not yet emerged on what constitutes appropriate measurement of efficiency, the Agency for Healthcare Research and Quality (AHRQ) has supported development in this area.

This chapter has been largely shaped by a number of documents that have developed the field of health care efficiency measurement. One major contributor is an AHRQ-commissioned report by RAND Corporation. This report systematically reviewed efficiency measures, assessed their tracking potential, and provided a typology that emphasizes the multiple perspectives on health care efficiency (McGlynn, 2008).

This chapter of the National Healthcare Quality Report is organized around the concepts of overuse and misuse. As noted in the National Strategy for Quality Improvement in Health Care,i Achieving optimal results every time requires an unyielding focus on eliminating patient harms from health care, reducing waste, and applying creativity and innovation to how care is delivered."

The measures this year are presented in the following layout:

  • Inappropriate medication use:
    • Adults age 65 and over who received potentially inappropriate prescription medications.
  • Preventable emergency department visits:
    • Potentially avoidable emergency department visit rates.
    • Emergency treatment for mental illness or substance abuse.
    • Emergency treatment for dental conditions.
  • Preventable hospitalizations:
    • Potentially avoidable hospitalization rates for adults.
    • Potentially avoidable hospitalization costs.
    • Potentially avoidable hospitalizations among Medicare home health and nursing home patients.
  • Perforated appendixes.
  • Trends in hospital cost efficiency.

Findings

Inappropriate Medication Use

Some drugs are potentially harmful for older patients but nevertheless are prescribed to them (Zhan, et al., 2001)ii Using inappropriate medications can be life threatening and may result in hospitalization, as well as increased costs of pharmaceutical services (Lau, et al., 2005). To measure inappropriate medication use, we have followed the Beers criteria, which have been generally accepted by the medical community and by expert opinion, although there is still some disagreement. This disagreement relates to the many factors that must be considered when identifying what constitutes inappropriate use by certain populations (Zhan, et al., 2001).

Figure 7.1. Adults age 65 and over who received potentially inappropriate prescription medications in the calendar year, by age and insurance, 2002-2009

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Source: Agency for Healthcare Research and Quality, Medical Expenditure Panel Survey, 2002-2009.
Denominator: Civilian noninstitutionalized population age 65 and over.
Note: For this measure, lower rates are better. Prescription medications received include all prescribed medications initially purchased or otherwise obtained, as well as any refills. Medicare and public are individuals with Medicare and some other public insurance (e.g., Medicaid).

  • In 2009, there were no statistically significant differences by age or insurance in the percentage of adults age 65 and over who received potentially inappropriate medications (Figure 7.1).
  • From 2002 to 2009, the overall percentage of adults age 65 and over who received potentially inappropriate medications decreased.

Also, in the NHDR:

  • In 2009, the percentage of adults age 65 and over who received potentially inappropriate medications was higher for females than for males.

Preventable Emergency Department Visits

Potentially Avoidable Emergency Department Visit Rates for Adults

Potentially preventable, high-cost encounters with the medical system occur not only in hospitals, but also in emergency departments (EDs). There were more than 125 million ED encounters in 2008 (AHRQ, 2008). ED crowding, boarding (i.e., holding patients until an inpatient bed is available), and ambulance diversion have become more prevalent and have given rise to increasing concerns about the quality of care delivered in EDs.

Some hospitalizations and ED encounters cannot be avoided, but appropriate ambulatory care can help keep some patients from having to visit an ED or from being hospitalized. Reducing potentially avoidable ED encounters, in particular, holds promise for reducing cost, improving quality, and enhancing efficiency.

For this analysis, the AHRQ Prevention Quality Indicators software was applied to the Healthcare Cost and Utilization Project (HCUP) Nationwide Emergency Department Sample (NEDS). The overall potentially avoidable ED visit rate includes visits for acute conditions such as dehydration and pneumonia and chronic conditions such as diabetes and congestive heart failure.

Figure 7.2.Potentially avoidable emergency department rates, by age and residence location, 2007-2009

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Source: Agency for Healthcare Research and Quality, Healthcare Cost and Utilization Project, Nationwide Emergency Department Sample, 2007-2009.
Denominator: Adults age 18 and over.
Note: Annual rates are adjusted for age and gender.

  • In 2009, the rate of ED visits for potentially avoidable conditions was 3,681 per 100,000 adults (Figure 7.2).
  • In all years, adults ages 45-64 and age 65 and over had higher rates of potentially avoidable ED visits compared with adults ages 18-44.
  • In all years, residents of small metropolitan, micropolitan, and noncore areas had higher potentially avoidable ED visit rates compared with residents of large metropolitan areas.

Also, in the NHDR:

  • Women had a higher rate of potentially avoidable ED visits compared with men.
  • Residents of the highest income quartile had a lower rate of potentially avoidable ED visits compared with residents of lower income quartiles.

Emergency Treatment for Mental Illness or Substance Abuse

When high-quality mental health care is not available in the community, patients with mental illness tend to rely on emergency rooms for care (Alakeson, et al., 2010). EDs are often not staffed or equipped to provide optimal psychiatric care, and patients with mental illness often wait long periods before receiving appropriate care. ED staff observing patients waiting for psychiatric care cannot care for patients with other medical emergencies. This measure provides information on the quality of the local mental health care system and the degree to which EDs function as safety net providers for people with mental health and substance abuse problems.

Figure 7.3. Rate of emergency department visits with a principal diagnosis related to mental health and alcohol or substance abuse, per 100,000 population, by age and residence location, 2009

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Source: Agency for Healthcare Research and Quality, Healthcare Cost and Utilization Project, Nationwide Emergency Department Sample, 2009.
Denominator: U.S. population.
Note: For this measure, lower rates are better. Substance abuse includes visits for co-occurring substance abuse and mental health disorders.

  • In 2009, the rate of ED visits for mental health was 1,170 per 100,000 population, and the rate of ED visits for substance abuse (including co-occurring substance abuse and mental health disorders) was 518 per 100,000 (Figure 7.3).
  • Children ages 0-17 and adults age 65 and over had lower rates of ED visits for mental health and for substance abuse compared with adults ages 18-44.
  • Residents of large central metropolitan, medium metropolitan, small metropolitan, micropolitan, and noncore areas had higher rates of ED visits for mental health compared with residents of large fringe metropolitan areas (suburbs). Residents of large central and medium metropolitan areas also had higher rates of ED visits for substance abuse compared with residents of large fringe metropolitan areas.

Also, in the NHDR:

  • Compared with males, females had a higher rate of ED visits for mental health but a lower rate of ED visits for substance abuse.
  • Residents of the highest income quartile had lower rates of ED visits both for mental health and for substance abuse compared with residents of lower income quartiles.

Emergency Treatment for Dental Conditions

Dental health requires periodic oral exams and timely treatment of tooth decay and gum disease. When patients do not access outpatient dental services, dental disease may progress and necessitate emergent treatment and even hospitalization. EDs often cannot provide definitive dental treatment and can only provide medication for pain and infection. Hence, use of EDs for dental conditions may reflect system inefficiency in the delivery of dental care.

Figure 7.4. Rate of emergency department visits with a principal diagnosis related to dental issues, per 100,000 population, by age and residence location, 2009

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Source: Agency for Healthcare Research and Quality, Healthcare Cost and Utilization Project, Nationwide Emergency Department Sample, 2009.
Denominator: U.S. population.
Note: For this measure, lower rates are better.

  • In 2009, the rate of ED visits for dental conditions was 307 per 100,000 population (Figure 7.4).
  • Children ages 0-17 and adults age 45 and over had lower rates of ED visits for dental conditions compared with adults ages 18-44.
  • Residents of small metropolitan, micropolitan, and noncore areas had higher rates of ED visits for dental conditions compared with residents of large metropolitan areas.

Also, in the NHDR:

  • Residents of the highest income quartile had lower rates of ED visits for dental conditions compared with residents of lower income quartiles.

Preventable Hospitalizations

Potentially Avoidable Hospitalization Rates for Adults

Hospitalization is expensive. Preventing avoidable hospitalizations could improve the efficiency of health care delivery. To address potentially avoidable hospitalizations from the population perspective, data on ambulatory care-sensitive conditions are summarized here using the AHRQ Prevention Quality Indicators (PQIs). Not all hospitalizations that the AHRQ PQIs track are preventable. But 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.

The AHRQ PQIs track these conditions using hospital discharge data. Hospitalizations for acute conditions, such as dehydration or pneumonia, are distinguished from hospitalizations for chronic conditions, such as diabetes or congestive heart failure. Results presented this year apply a modified version 4.1 of the AHRQ Quality Indicators and are not comparable to results from previous years.

Figure 7.5. Potentially avoidable hospitalization rates for adults, by type of hospitalization, 2000-2009

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Source: Agency for Healthcare Research and Quality (AHRQ), Healthcare Cost and Utilization Project, Nationwide Inpatient Sample, and AHRQ Quality Indicators, modified version 4.1, 2000-2009.
Denominator: Civilian noninstitutionalized adults age 18 and over.
Note: For this measure, lower rates are better. Annual rates are adjusted for age and gender.

  • From 2000 to 2009, the overall rate of avoidable hospitalizations fell from 1,657 to 1,395 per 100,000 population (Figure 7.5). Declines in avoidable hospitalizations were observed for both acute and chronic conditions.
  • In 2008, the top 3 State achievable benchmark for all potentially avoidable hospitalizations was 818 per 100,000 population. iii The overall achievable benchmark could not be attained for 18 years.
  • The top 3 State achievable benchmark for acute potentially avoidable hospitalizations was 387 per 100,000 population. iv The acute achievable benchmark also could not be attained for 18 years.
  • The top 3 State achievable benchmark for potentially avoidable hospitalizations for chronic conditions was 394 per 100,000 population.v The chronic achievable benchmark could not be attained for 21 years.

Also, in the NHDR:

  • In all years, rates of potentially avoidable hospitalizations were lower among Asians and Pacific Islanders compared with Whites. Rates were higher among Blacks compared with Whites.
  • In all years, rates of potentially avoidable hospitalizations were higher among residents of areas in the lowest and second income quartiles compared with residents of the highest income quartile.

Potentially Avoidable Hospitalization Costs

The costs associated with potentially avoidable hospitalizations can be calculated to estimate how much money could be saved by eliminating such services. For this analysis, total hospital charges were converted to costs using HCUP cost-to-charge ratios based on hospital accounting reports from the Centers for Medicare & Medicaid Services. Therefore, cost estimates in this section refer to hospital costs for providing care but do not include either payers' costs or costs for physician care that are billed separately.

Figure 7.6. Total national costs associated with potentially avoidable hospitalizations, 2000-2009

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Source: Agency for Healthcare Research and Quality (AHRQ), Healthcare Cost and Utilization Project, Nationwide Inpatient Sample, and AHRQ Quality Indicators, modified version 4.1, 2000-2009.
Denominator: Civilian noninstitutionalized adults age 18 and over.
Note: For this measure, lower rates are better. Annual rates are adjusted for age and gender. Costs are adjusted for inflation and are represented in 2009 dollars.

  • From 2000 to 2003, total national hospital costs associated with potentially avoidable hospitalizationsvi increased from $25.1 billion to $28.3 billion. Since then, costs have been gradually declining, to $26.0 billion in 2009 (Figure 7.6).
  • These changes are largely attributable to avoidable hospitalizations for chronic conditions, with national hospital costs that increased from $14.5 billion to $16.4 billion between 2000 and 2003 and then declined to $15.3 billion in 2009.
  • Changes in avoidable hospitalizations for acute conditions also contributed, with national hospital costs that increased from $10.7 billion to $11.9 billion between 2000 and 2003 and then declined to $10.7 billion in 2009.

Potentially Avoidable Hospitalizations Among Medicare Home Health and Nursing Home Patients

Many patients are hospitalized while receiving care from home health agencies and nursing homes, with resulting high costs and care transition problems. A number of these hospitalizations are appropriate. However, some hospital admissions could be prevented with better primary care and monitoring in these settings, or the patient could receive appropriate treatment in a less resource-intense setting.

Using the AHRQ PQIs, we track potentially avoidable hospitalizations among Medicare patients occurring within 30 days of the start of home health or nursing home care. These patients may differ from patients discussed earlier in this chapter who are predominantly admitted for avoidable conditions from home. At home, some are receiving appropriate primary care and others have not visited a health care provider for years.

In contrast, Medicare home health and nursing home patients have regular contact with health providers, which should reduce rates of avoidable hospitalization. However, these patients are also more acutely ill, may become seriously ill when affected by a new illness, and may have multiple comorbidities. Medicare patients in these settings often have been hospitalized recently.

Therefore, an avoidable hospitalization may represent a return to the hospital, perhaps against the expectation that the patient no longer needed acute care.

For application to home health and nursing home settings, the potentially avoidable stays are identified within a defined time period, 30 days, from the home health or nursing home admission date. If a patient is hospitalized more than once in that period, only the first stay is recognized for the measure.

Data on home health patients come from Medicare fee-for-service (FFS) home health claims and Outcome and Assessment Information Set patient assessment information. Data on nursing home patients come from Medicare skilled nursing facility FFS claims and Minimum Data Set patient assessment information. These data are linked with Medicare Part A acute care hospital claims to determine hospitalizations for potentially avoidable conditions. The maps below show State performance in quartiles for home health patients and nursing home patients.

Figure 7.7. Home health patients with potentially avoidable hospitalizations within 30 days of start of care, by State, 2008

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Source: Centers for Medicare & Medicaid Services, Outcome and Assessment Information Set linked with Medicare Part A claims (100%), 2008.
Denominator: Adult nonmaternity patients starting an episode of home health care.
Note: For this measure, lower numbers are better.

  • The percentage of home health patients with potentially avoidable hospitalizations ranged from 2.3% to 5.7%.
  • Potentially avoidable hospitalizations account for 28% of all-cause hospitalizations among home health patients.
  • All-cause hospitalizations ranged from 9% to 17.4%.

Figure 7.8. Residents with skilled nursing facility stays with potentially avoidable hospitalizations within 30 days of admission, by State, 2008

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Source: Centers for Medicare & Medicaid Services, Minimum Data Set 2.0, linked with Medicare Part A claims (100%), 2008.
Denominator: Residents who met the skilled nursing facility criteria for nursing home admission.
Note: For this measure, lower numbers are better.

  • The percentage of SNF residents with potentially avoidable hospitalizations ranged from 0.7% to 2.3 %.
  • Potentially avoidable hospitalizations accounted for 35% of all-cause hospitalizations among SNF residents.
  • All-cause hospitalizations ranged from 3.5% to 8.8%.

Perforated Appendixes

Perforation is a severe complication of appendicitis that allows intestinal contents to spill into the abdominal cavity. Patients with a perforated appendix have a worse prognosis and require longer recovery times after surgery than patients whose appendix does not rupture. More timely detection and treatment of appendicitis can reduce the percentage of appendicitis admissions in which rupture has occurred.

Figure 7.9. Perforated appendixes per 1,000 admissions for appendicitis, by age and gender, 2004, 2005, and 2007-2009

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Source: Agency for Healthcare Research and Quality, Healthcare Cost and Utilization Project, State Inpatient Databases disparities analysis file, 2004, 2005, and 2007-2009.
Note: For this measure, lower rates are better. Data for 2006 are not included, because a new version of the PQI software was used to calculate rates and 2006 was not included in the calculation.

  • In 2009, the rate of perforated appendixes was higher for those age 65 and over and those ages 45-64 than for those ages 18-44 (510.2 and 385.5 per 1,000 admissions, respectively, compared with 197.7; Figure 7.9).
  • Also in 2009, there were no statistically significant differences by gender.

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 that reflect differences among providers in outputs, patient burden of illness,vii or care quality.viii To address the provider perspective, hospital cost efficiency is examined using a technique from the field of econometrics that can account for such differences. This analysis uses data from the American Hospital Association Annual Survey and from Medicare Cost Reports, as well as data derived from the application of AHRQ Quality Indicators software and the Comorbidity Software to HCUP data.

Here, hospital efficiency 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 case mix, its quality, and its market characteristics, 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 2005 as a way to place less emphasis on the specific magnitude of estimated hospital efficiency than on its general trend (Mutter, et al., 2008).

Figure 7.10. Average estimated relative hospital cost efficiency index for a selected sample of urban general community hospitals (with confidence interval brackets), 2005-2009

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Source:Agency for Healthcare Research and Quality.
Note: Analysis based on 1,552 urban general community hospitals with data in the Healthcare Cost and Utilization Project, State Inpatient Databases. See Chapter 1, Introduction and Methods, for further details.

  • The highest level of efficiency occurred in 2005. Changes in cost efficiency were essentially flat during the period and none of the year means was significantly different than the index year mean of 100 (Figure 7.10).
  • 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. The most cost-efficient hospitals had lower costs and fewer full-time-equivalent employees per case-mix-adjusted admission, compared with the least cost-efficient hospitals. The most cost-efficient hospitals also had a shorter average length of stay, although the difference was not statistically significant (Table 7.1).
  • The most cost-efficient hospitals had a higher operating margin than the least cost-efficient hospitals (Table 7.1).

Table 7.1. Correlates of hospital cost efficiency

MeasureEstimateStandard deviationStandard error mean
Cost per case mix-adjusted admission:
Top quartile of hospital cost efficiency8,242.212,737.80138.99
Bottom quartile of hospital cost efficiency12,160.845,244.72266.26
Full-time equivalent employees per case-mix-adjusted admission
Top quartile of hospital cost efficiency0.580.160.01
Bottom quartile of hospital cost efficiency0.770.240.01
Average length of stay (days)
Top quartile of hospital cost efficiency4.871.150.06
Bottom quartile of hospital cost efficiency5.041.630.08
Operating margin
Top quartile of hospital cost efficiency0.040.130.01
Bottom quartile of hospital cost efficiency-0.040.160.01

Source:Agency for Healthcare Research and Quality.
Note: Analysis based on 2009 values for 1,552 urban general community hospitals.

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 60% of all non-Federal urban general community hospitals and therefore provide an indication of the general trend that cost efficiency may be following.

References

Weighted national estimates from HCUP Nationwide Emergency Department Sample. Rockville, MD: Agency for Healthcare Research and Quality; 2008. Available at: http://hcupnet.ahrq.gov.

Alakeson V, Pande N, Ludwig M. A plan to reduce emergency room ‘boarding' of psychiatric patients. Health Aff (Millwood) 2010 Sep;29(9):1637-42.

Elixhauser A, Steiner C, Harris DR, et al. Comorbidity measures for use with administrative data. Med Care 1998 Jan;36(1):8-27.

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.

Lau DT, Kasper JD, Potter DE, et al. Hospitalization and death associated with potentially inappropriate medication prescriptions among elderly nursing home residents. Arch Intern Med 2005 Jan 10;165(1):68-74.

McGlynn E. Identifying, categorizing, and evaluating health care efficiency measures. Rockville, MD: Agency for Healthcare Research and Quality; 2008. AHRQ Publication No. 08-0030. Available at: http://www.ahrq.gov/research/findings/final-reports/efficiency/. Accessed December 8, 2009.

Mutter RL, Rosko MD, Wong HS. Measuring hospital inefficiency: the effects of controlling for quality and patient burden of illness. Health Serv Res 2008 Dec;43(6):1992-2013. Epub 2008 Sep 8.

Zhan C, Sangl J, Bierman AS, et al. Potentially inappropriate medication use in the community-dwelling elderly: findings from the 1996 Medical Expenditure Panel Survey. JAMA 2001 Dec 12;286(22):2823-9.


i. Available at http://www.ahrq.gov/workingforquality/nqs/nqs2011annlrpt.htm.
ii. Drugs that should always be avoided for older patients include barbiturates, flurazepam, meprobamate, chlorpropamide, meperidine, pentazocine, trimethobenzamide, belladonna alkaloids, dicyclomine, hyoscyamine, and propantheline. Drugs that should often or always be avoided for older patients include carisoprodol, chlorzoxazone, cyclobenzaprine, metaxalone, methocarbamol, amitriptyline, chlordiazepoxide, diazepam, doxepin, indomethacin, dipyridamole, ticlopidine, methyldopa, reserpine, disopyramide, oxybutynin, chlorpheniramine, cyproheptadine, diphenhydramine, hydroxyzine, promethazine, and propoxyphene.
iii. The top 3 States that contributed to the overall achievable benchmark are Hawaii, Utah, and Washington.
iv. The top 3 States that contributed to the acute achievable benchmark are Hawaii, Utah, and Washington.
v. The top 3 States that contributed to the chronic achievable benchmark are Utah, Vermont, and Washington.
vi. Adjusted for inflation. The inflation adjustment was done using the gross domestic product implicit price deflator.
vii. This analysis controls for the following components that Elixhauser, et al. (1998) contend are part of patient burden of illness: (1) primary reason for admission to the hospital, (2) severity of the principal diagnosis, (3) iatrogenic complications, and (4) comorbidities that are unrelated to the primary diagnosis but have a substantial impact on both the resources used to treat the patient and the outcomes of the care provided.
viii. To control for quality, this analysis uses risk-adjusted rates of the following AHRQ Quality Indicators: in-hospital mortality for (1) acute myocardial infarction, (2) congestive heart failure, (3) stroke, (4) gastrointestinal hemorrhage, (5) hip fracture, and (6) pneumonia; failure to rescue; iatrogenic pneumothorax; infection due to medical care; and accidental puncture and laceration (Mutter, et al., 2008).
ix. Stochastic frontier analysis (SFA) is the technique 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 SFA produces 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 (McGlynn, 2008).
x. Operating margin is a commonly used measure of profitability from operations or the excess of revenue over expenses. It is calculated by the following formula: Operating margin = (total net patient revenue−total operating expenses)/ total net patient revenue.
 

Current as of May 2013
Internet Citation: 2012 National Healthcare Quality Report: Chapter 7. Efficiency. May 2013. Agency for Healthcare Research and Quality, Rockville, MD. http://www.ahrq.gov/research/findings/nhqrdr/nhqr12/chap7.html