A population health approach to reducing observational intensity bias in health risk adjustment: cross sectional analysis of insurance claims.

OBJECTIVE: To compare the performance of two new approaches to risk adjustment that are free of the influence of observational intensity with methods that depend on diagnoses listed in administrative databases. SETTING: Administrative data from the US Medicare program for services provided in 2007 among 306 US hospital referral regions. DESIGN: Cross sectional analysis. PARTICIPANTS: 20% sample of fee for service Medicare beneficiaries residing in one of 306 hospital referral regions in the United States in 2007 (n = 5,153,877). MAIN OUTCOME MEASURES: The effect of health risk adjustment on age, sex, and race adjusted mortality and spending rates among hospital referral regions using four indices: the standard Centers for Medicare and Medicaid Services--Hierarchical Condition Categories (HCC) index used by the US Medicare program (calculated from diagnoses listed in Medicare's administrative database); a visit corrected HCC index (to reduce the effects of observational intensity on frequency of diagnoses); a poverty index (based on US census); and a population health index (calculated using data on incidence of hip fractures and strokes, and responses from a population based annual survey of health from the Centers for Disease Control and Prevention). RESULTS: Estimated variation in age, sex, and race adjusted mortality rates across hospital referral regions was reduced using the indices based on population health, poverty, and visit corrected HCC, but increased using the standard HCC index. Most of the residual variation in age, sex, and race adjusted mortality was explained (in terms of weighted R2) by the population health index: R2=0.65. The other indices explained less: R2=0.20 for the visit corrected HCC index; 0.19 for the poverty index, and 0.02 for the standard HCC index. The residual variation in age, sex, race, and price adjusted spending per capita across the 306 hospital referral regions explained by the indices (in terms of weighted R2) were 0.50 for the standard HCC index, 0.21 for the population health index, 0.12 for the poverty index, and 0.07 for the visit corrected HCC index, implying that only a modest amount of the variation in spending can be explained by factors most closely related to mortality. Further, once the HCC index is visit corrected it accounts for almost none of the residual variation in age, sex, and race adjusted spending. CONCLUSION: Health risk adjustment using either the poverty index or the population health index performed substantially better in terms of explaining actual mortality than the indices that relied on diagnoses from administrative databases; the population health index explained the majority of residual variation in age, sex, and race adjusted mortality. Owing to the influence of observational intensity on diagnoses from administrative databases, the standard HCC index over-adjusts for regional differences in spending. Research to improve health risk adjustment methods should focus on developing measures of risk that do not depend on observation influenced diagnoses recorded in administrative databases.

Observational intensity bias associated with illness adjustment: cross sectional analysis of insurance claims.

OBJECTIVE: To determine the bias associated with frequency of visits by physicians in adjusting for illness, using diagnoses recorded in administrative databases. SETTING: Claims data from the US Medicare program for services provided in 2007 among 306 US hospital referral regions. DESIGN: Cross sectional analysis. PARTICIPANTS: 20% sample of fee for service Medicare beneficiaries residing in the United States in 2007 (n=5,153,877). MAIN OUTCOME MEASURES: The effect of illness adjustment on regional mortality and spending rates using standard and visit corrected illness methods for adjustment. The standard method adjusts using comorbidity measures based on diagnoses listed in administrative databases; the modified method corrects these measures for the frequency of visits by physicians. Three conventions for measuring comorbidity are used: the Charlson comorbidity index, Iezzoni chronic conditions, and hierarchical condition categories risk scores. RESULTS: The visit corrected Charlson comorbidity index explained more of the variation in age, sex, and race mortality across the 306 hospital referral regions than did the standard index (R(2)=0.21 v 0.11, P<0.001) and, compared with sex and race adjusted mortality, reduced regional variation, whereas adjustment using the standard Charlson comorbidity index increased it. Although visit corrected and age, sex, and race adjusted mortality rates were similar in hospital referral regions with the highest and lowest fifths of visits, adjustment using the standard index resulted in a rate that was 18% lower in the highest fifth (46.4 v 56.3 deaths per 1000, P<0.001). Age, sex, and race adjusted spending as well as visit corrected spending was more than 30% greater in the highest fifth of visits than in the lowest fifth, but only 12% greater after adjustment using the standard index. Similar results were obtained using the Iezzoni and the hierarchical condition categories conventions for measuring comorbidity. CONCLUSION: The rates of visits by physicians introduce substantial bias when regional mortality and spending rates are adjusted for illness using comorbidity measures based on the observed number of diagnoses recorded in Medicare's administrative database. Adjusting without correction for regional variation in visit rates tends to make regions with high rates of visits seem to have lower mortality and lower costs, and vice versa. Visit corrected comorbidity measures better explain variation in age, sex, and race mortality than observed measures, and reduce observational intensity bias.

Fewer hospitalizations result when primary care is highly integrated into a continuing care retirement community.

Meeting the medical and social needs of elderly people is likely to be costly, disruptive, and at odds with personal preferences if efforts to do so are not well coordinated. We compared two different models of primary care in four different continuing care retirement communities. In the first model, used in one community, the physicians and two part-time nurse practitioners delivered clinical care only at that site, covered all settings within it, and provided all after-hours coverage. In the second model, used in three communities, on-site primary care physician hours were limited; the same physicians also had independent practices outside the retirement community; and after-hours calls were covered by all members of the practices, including physicians who did not practice on site. We found that residents in the first model had two to three times fewer hospitalizations and emergency department visits. Only 5 percent of those who died did so in a hospital, compared to 15 percent at the other sites and 27 percent nationally. These findings provide insight into what is possible when medical care is highly integrated into a residential retirement setting.

Geographic variation in diagnosis frequency and risk of death among Medicare beneficiaries.

CONTEXT: Because diagnosis is typically thought of as purely a patient attribute, it is considered a critical factor in risk-adjustment policies designed to reward efficient and high-quality care. OBJECTIVE: To determine the association between frequency of diagnoses for chronic conditions in geographic areas and case-fatality rate among Medicare beneficiaries. DESIGN, SETTING, AND PARTICIPANTS: Cross-sectional analysis of the mean number of 9 serious chronic conditions (cancer, chronic obstructive pulmonary disease, coronary artery disease, congestive heart failure, peripheral artery disease, severe liver disease, diabetes with end-organ disease, chronic renal failure, and dementia) diagnosed in 306 hospital referral regions (HRRs) in the United States; HRRs were divided into quintiles of diagnosis frequency. Participants were 5,153,877 fee-for-service Medicare beneficiaries in 2007. MAIN OUTCOME MEASURES: Age/sex/race-adjusted case-fatality rates. RESULTS: Diagnosis frequency ranged across HRRs from 0.58 chronic conditions in Grand Junction, Colorado, to 1.23 in Miami, Florida (mean, 0.90 [95% confidence interval {CI}, 0.89-0.91]; median, 0.87 [interquartile range, 0.80-0.96]). The number of conditions diagnosed was related to risk of death: among patients diagnosed with 0, 1, 2, and 3 conditions the case-fatality rate was 16, 45, 93, and 154 per 1000, respectively. As regional diagnosis frequency increased, however, the case fatality associated with a chronic condition became progressively less. Among patients diagnosed with 1 condition, the case-fatality rate decreased in a stepwise fashion across quintiles of diagnosis frequency, from 51 per 1000 in the lowest quintile to 38 per 1000 in the highest quintile (relative rate, 0.74 [95% CI, 0.72-0.76]). For patients diagnosed with 3 conditions, the corresponding case-fatality rates were 168 and 137 per 1000 (relative rate, 0.81 [95% CI, 0.79-0.84]). CONCLUSION: Among fee-for-service Medicare beneficiaries, there is an inverse relationship between the regional frequency of diagnoses and the case-fatality rate for chronic conditions.

Regional variations in diagnostic practices.

BACKGROUND: Current methods of risk adjustment rely on diagnoses recorded in clinical and administrative records. Differences among providers in diagnostic practices could lead to bias. METHODS: We used Medicare claims data from 1999 through 2006 to measure trends in diagnostic practices for Medicare beneficiaries. Regions were grouped into five quintiles according to the intensity of hospital and physician services that beneficiaries in the region received. We compared trends with respect to diagnoses, laboratory testing, imaging, and the assignment of Hierarchical Condition Categories (HCCs) among beneficiaries who moved to regions with a higher or lower intensity of practice. RESULTS: Beneficiaries within each quintile who moved during the study period to regions with a higher or lower intensity of practice had similar numbers of diagnoses and similar HCC risk scores (as derived from HCC coding algorithms) before their move. The number of diagnoses and the HCC measures increased as the cohort aged, but they increased to a greater extent among beneficiaries who moved to regions with a higher intensity of practice than among those who moved to regions with the same or lower intensity of practice. For example, among beneficiaries who lived initially in regions in the lowest quintile, there was a greater increase in the average number of diagnoses among those who moved to regions in a higher quintile than among those who moved to regions within the lowest quintile (increase of 100.8%; 95% confidence interval [CI], 89.6 to 112.1; vs. increase of 61.7%; 95% CI, 55.8 to 67.4). Moving to each higher quintile of intensity was associated with an additional 5.9% increase (95% CI, 5.2 to 6.7) in HCC scores, and results were similar with respect to laboratory testing and imaging. CONCLUSIONS: Substantial differences in diagnostic practices that are unlikely to be related to patient characteristics are observed across U.S. regions. The use of clinical or claims-based diagnoses in risk adjustment may introduce important biases in comparative-effectiveness studies, public reporting, and payment reforms.

Variations in hospital resource use for Medicare and privately insured populations in California.

The amount of resources used in the care of chronically ill Medicare fee-for-service (FFS) patients varies widely across hospitals. We studied variations across California hospitals in hospital resource use for chronically ill patients covered by Medicare health maintenance organizations (HMOs) and private insurers and found substantial variation in all of the coverage groups studied. Resource-use measures based on Medicare FFS data often reflect patterns evident for other payers. Previous estimates of savings if the most resource-intensive hospitals more closely resembled less resource-intensive hospitals, based on just Medicare FFS spending, could underestimate possible savings when other payers are taken into account.

Extending the P4P agenda, part 1: how Medicare can improve patient decision making and reduce unnecessary care.

The decision to undergo many discretionary medical treatments should be based on informed patient choice. Shared decision making is an effective strategy for achieving this goal. The Centers for Medicare and Medicaid Services (CMS) should extend its pay-for-performance (P4P) agenda to assure that all Americans have access to a certified shared decision-making process. This paper outlines a strategy to achieve informed patient choice as the standard of practice for preference-sensitive care.

Extending the P4P agenda, part 2: how Medicare can reduce waste and improve the care of the chronically ill.

The care of Americans with severe chronic illnesses is disorganized, unnecessarily costly, and undisciplined by sound clinical science. The federal government should invest in a crash program to improve the scientific basis of managing chronic illness, and the Centers for Medicare and Medicaid Services (CMS) should extend its pay-for-performance (P4P) agenda to ensure that within ten years all Americans with severe chronic illnesses have access to accountable health care organizations providing evidence-based prospective care. This paper recommends a strategy for achieving this goal.

End-of-life care at academic medical centers: implications for future workforce requirements.

The expansion of U.S. physician workforce training has been justified on the basis of population growth, technological innovation, and economic expansion. Our analyses found threefold differences in physician full-time-equivalent (FTE) inputs for Medicare cohorts cared for at academic medical centers (AMCs); AMC inputs were highly correlated with the number of physician FTEs per Medicare beneficiary in AMC regions. Given the apparent inefficiency of current physician practices, the supply pipeline is sufficient to meet future needs through 2020, with adoption of the workforce deployment patterns now seen among AMCs and regions dominated by large group practices.

Bereaved family member perceptions of quality of end-of-life care in U.S. regions with high and low usage of intensive care unit care.

OBJECTIVES: To compare the quality of end-of-life care of persons dying in regions of differing practice intensity. DESIGN: Mortality follow-back survey. SETTING: Geographic regions in the highest and lowest deciles of intensive care unit (ICU) use. PARTICIPANTS: Bereaved family member or other knowledgeable informants. MEASUREMENTS: Unmet needs, concerns, and rating of quality of end-of-life care in five domains (physical comfort and emotional support of the decedent, shared decision-making, treatment of the dying person with respect, providing information and emotional support to family members). RESULTS: Decedents in high- (n=365) and low-intensity (n=413) hospital service areas (HSAs) did not differ in age, sex, education, marital status, leading causes of death, or the degree to which death was expected, but those in the high-intensity ICU HSAs were more likely to be black and to live in nonrural areas. Respondents in high-intensity HSAs were more likely to report that care was of lower quality in each domain, and these differences were statistically significant in three of five domains. Respondents from high-intensity HSAs were more likely to report inadequate emotional support for the decedent (relative risk (RR)=1.2, 95% confidence interval (CI)=1.0-1.4), concerns with shared decision-making (RR=1.8, 95% CI=1.0-2.9), inadequate information about what to expect (RR=1.5, 95% CI=1.3-1.8), and failure to treat the decedent with respect (RR=1.4, 95% CI=1.0-1.9). Overall ratings of the quality of end-of-life care were also significantly lower in high-intensity HSAs. CONCLUSION: Dying in regions with a higher use of ICU care is not associated with improved perceptions of quality of end-of-life care.

Postmarketing surveillance of medical devices using Medicare claims.

The current system of postmarketing surveillance of high-risk medical devices could be improved by taking advantage of the administrative billing data collected by the Centers for Medicare and Medicaid Services (CMS) to systematically monitor for adverse events that may signal device-related problems. In this paper we use the current concern about the excess risk associated with drug-eluting coronary stents to highlight the strengths and weaknesses of claims data for postmarketing surveillance and propose a pilot collaboration between government, industry, and academe to systematically explore the use of Medicare claims data for this purpose.

Unwarranted variations in the quality of health care: can the law help medicine provide a remedy/remedies?

This Article reviews the essential findings of studies of variations in quality of care according to three categories of care: effective care, preference-sensitive care, and supply-sensitive care. It argues that malpractice liability and informed consent laws should be based on standards of practice that are appropriate to each category of care. In the case of effective care, the legal standard should be that virtually all of those in need should receive the treatment, whether or not it is currently customary to provide it. In the case of preference-sensitive care, the law should recognize the failure of the doctrine of informed consent to assure that patient preferences are respected in choice of treatment; we suggest that the law adopt a standard of informed patient choice in which patients are invited, not merely to consent to a recommended treatment, but to choose the treatment that best advances their preferences. In the case of supply-sensitive care, we suggest that physicians who seek to adopt more conservative patterns of practice be protected under the "respectable minority" or "two schools of thought" doctrine.

Use of Medicare claims data to monitor provider-specific performance among patients with severe chronic illness.

This study illustrates that Medicare claims can be used to measure population-based, provider-specific rates of resource inputs, utilization, and Medicare spending. The target populations are seventy-seven cohorts of chronically ill Medicare enrollees who received most of their care from seventy-seven well-known U.S. hospitals. Striking variations are documented in resource inputs and use of services during the last six months of life. The patterns of care seen in the progression of chronic illness correlate highly with care received during previous periods. We believe that hospital-specific measures can be helpful in identifying providers with acceptable quality indices who are also relatively efficient in managing chronic illness.

Who you are and where you live: how race and geography affect the treatment of medicare beneficiaries.

The existence of overall racial and ethnic disparities in health care is well documented, but this average effect masks variation across regions and types of care. Medicare claims data are used to document the extent of these variations. Regions with high racial disparities in one procedure are not more likely to be high in other procedures. Unusually large racial disparities in surgery are often the result of high white rates rather than low black rates. Differences in end-of-life care are driven more by residence than by race. Policies should focus on getting the rates right, rather than solely on racial differences.

Practice variations and health care reform: connecting the dots.

Unwarranted variation is a ubiquitous feature of U.S. health care. Remedies for variations exist, and several are described in the current collection of Health Affairs papers. Several obstacles stand in the way of widespread adoption of these remedies: (1) a quality agenda that has yet to focus on improving the quality of patient decision making; (2) economic incentives that do not reward exemplary practice; and (3) the poor state of clinical science. Medicare reform legislation creates the opportunity for a demonstration project to redesign health care to address these barriers. We also must grapple with the cultural bias that more care is better and that physicians must know best.

Use of hospitals, physician visits, and hospice care during last six months of life among cohorts loyal to highly respected hospitals in the United States.

OBJECTIVE: To evaluate the use of healthcare resources during the last six months of life among patients of US hospitals with strong reputations for high quality care in managing chronic illness. DESIGN: Retrospective cohort study based on claims data from the US Medicare programme. PARTICIPANTS: Cohorts receiving most of their hospital care from 77 hospitals that appeared on the 2001 US News and World Report "best hospitals" list for heart and pulmonary disease, cancer, and geriatric services. MAIN OUTCOME MEASURES: Use of healthcare resources in the last six months of life: number of days spent in hospital and in intensive care units; number of physician visits; percentage of patients seeing 10 or more physicians; percentage enrolled in hospice. Terminal care: percentage of deaths occurring in hospital; percentage of deaths occurring in association with a stay in an intensive care unit. RESULTS: Extensive variation in each measure existed among the 77 hospital cohorts. Days in hospital per decedent ranged from 9.4 to 27.1 (interquartile range 11.6-16.1); days in intensive care units ranged from 1.6 to 9.5 (2.6-4.5); number of physician visits ranged from 17.6 to 76.2 (25.5-39.5); percentage of patients seeing 10 or more physicians ranged from 16.9% to 58.5% (29.4-43.4%); and hospice enrollment ranged from 10.8% to 43.8% (22.0-32.0%). The percentage of deaths occurring in hospital ranged from 15.9% to 55.6% (35.4-43.1%), and the percentage of deaths associated with a stay in intensive care ranged from 8.4% to 36.8% (20.2-27.1%). CONCLUSION: Striking variation exists in the utilisation of end of life care among US medical centres with strong national reputations for clinical care.

Racial, ethnic, and geographic disparities in rates of knee arthroplasty among Medicare patients.

BACKGROUND: There are large variations in the use of knee arthroplasty among Medicare enrollees according to race or ethnic group and sex. Are racial and ethnic disparities more pronounced in some regions than in others, and if so, why? METHODS: We used all Medicare fee-for-service claims data for 1998 through 2000 to determine the incidence of knee arthroplasty according to Hospital Referral Region, sex, and race or ethnic group. A total of 430,726 knee arthroplasties were performed during the three-year study period. RESULTS: At the national level, the annual rate of knee arthroplasty was higher for non-Hispanic white women (5.97 procedures per 1000) than for Hispanic women (5.37 per 1000) and black women (4.84 per 1000). The rate for non-Hispanic white men (4.82 procedures per 1000) was higher than that for Hispanic men (3.46 per 1000) and more than double that for black men (1.84 per 1000). The rates were significantly lower for black men than for non-Hispanic white men in nearly every region of the country (P<0.05). For the Hispanic population and for black women, racial or ethnic disparities at the national level were due in part to geographic differences rather than to differences in the rates for different racial and ethnic groups within geographic areas. Residential segregation and low income levels contributed to racial and ethnic disparities in arthroplasty rates. CONCLUSIONS: In the Medicare population, the rate of surgical treatment for osteoarthritis of the knee varies dramatically according to sex, race or ethnic group, and region. These variations underscore the importance of geography and sex in determining racial or ethnic barriers to health care.

The more things change...: the federal government's role in the evaluative sciences.

The unfortunate political history of the Agency for Health Care Policy and Research (AHCPR) illustrates the risks to the agencies attempting to evaluate the common practices of medicine and reform clinical decision making to take account of patients' preferences. The evaluative sciences have yet to regain the congressional attention they had when Senators George Mitchell and David Durenberger championed their cause. But the fundamental problems remain, and they are getting worse. Sooner or later Congress will need to revisit the debate over where in the federal government the evaluative sciences should find their base, and questions concerning the role of the National Institutes of Health (NIH) will be raised once again, as they were at the time of AHCPR's founding.