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.

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.

Outcomes following coronary stenting in the era of bare-metal vs the era of drug-eluting stents.

CONTEXT: Although drug-eluting stents reduce restenosis rates relative to bare-metal stents, concerns have been raised that drug-eluting stents may also be associated with an increased risk of stent thrombosis. Our study focused on the effect of stent type on population-based interventional outcomes. OBJECTIVE: To compare outcomes of Medicare beneficiaries who underwent nonemergent coronary stenting before and after the availability of drug-eluting stents. DESIGN, SETTING, AND PATIENTS: Observational study of 38,917 Medicare patients who underwent nonemergent coronary stenting from October 2002 through March 2003 when only bare-metal stents were available (bare-metal stent era cohort) and 28,086 similar patients who underwent coronary stenting from September through December 2003, when 61.5% of patients received a drug-eluting stent and 38.5% received a bare-metal stent (drug-eluting stent era cohort). Follow-up data were available through December 31, 2005. MAIN OUTCOME MEASURES: Coronary revascularization (percutaneous coronary intervention, coronary artery bypass surgery), ST-elevation myocardial infarction, survival through 2 years of follow-up. RESULTS: Relative to the bare-metal stent era, patients treated in the drug-eluting stent era had lower 2-year risks for repeat percutaneous coronary interventions (17.1% vs 20.0%, P < .001) and coronary artery bypass surgery (2.7% vs 4.2%, P < .01). The difference in need for repeat revascularization procedures between these 2 eras remained significant after risk adjustment (hazard ratio, 0.82; 95% confidence interval, 0.79-0.85). There was no difference in unadjusted mortality risks at 2 years (8.4% vs 8.4%, P =.98 ), but a small decrease in ST-elevation myocardial infarction existed (2.4% vs 2.0%, P < .001). The adjusted hazard of death or ST-elevation myocardial infarction at 2 years was similar (hazard ratio, 0.96; 95% confidence interval, 0.92-1.01). CONCLUSION: The widespread adoption of drug-eluting stents into routine practice was associated with a decline in the need for repeat revascularization procedures and had similar 2-year risks for death or ST-elevation myocardial infarction to bare-metal stents.

Evaluating the efficiency of california providers in caring for patients with chronic illnesses.

In this paper we compare the relative efficiency of health care providers in managing patients with severe chronic illnesses over fixed periods of time. To minimize the contribution of differences in severity of illness to differences in care management, we evaluate performance over fixed intervals prior to death for patients who died during a five-year period, 1999-2003. Medicare spending, hospital bed and full-time equivalent (FTE) physician inputs, and utilization varied extensively between regions, among hospitals located within a given region, and among hospitals belonging to a given hospital system. The data point to important opportunities to improve efficiency.

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.

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.

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.

The Quality of Medical Care in the United States: A Report on the Medicare Program: the Dartmouth Atlas of Health Care 1999

The United States leads the world, by a substantial measure, in its monetary commitment to medical care. If, as we have long believed, more care is better care, then American medicine must surely be the best in the world. But where is the "best" of American medicine? Previous editions of the Atlas have demonstrated conclusively that in American health care, geography is destiny. Both the amounts and kinds of care provided to residents of the United States are highly dependent on two factors: the capacity of the local health care system (which influences how much care is provided) and the practice style of local physicians (which determines what kind of care is provided). Variations in the intensity of use of hospitals, the striking differences in care at the end of life, and the nearly random patterns of elective surgery all raise questions about the outcomes and value of care­about quality. Is more in fact better? What is the value received for the money spent? What, as Joseph Juran asked, is the cost of poor quality? These questions are receiving increasing public attention. The National Academy of Sciences convened the National Roundtable on Health Care Quality to assess the problem of quality of care. Reporting its findings in the American Journal of Medicine, the Roundtable concluded: "Serious and widespread quality problems exist throughout American medicine. These problems, which may be classified as underuse, overuse and misuse, occur in small and large communities alike, in all parts of the country and with approximately equal frequency in managed care and fee-for-service systems of care." The Roundtable estimated that "very large numbers of Americans are harmed as a direct result" of poor quality care: "Millions of Americans are not reached by proven effective interventions that can save lives and prevent disability. Perhaps an equal number suffer needlessly because they are exposed to the harms of unnecessary health services. Large numbers are injured because preventable complications are not averted." The concern about quality is not restricted to experts or to those who speak on the part of patients or the American public. Ordinary citizens are concerned. The American Hospital Association's "Reality✓" investigation revealed that patients have significant problems with "The way the 'system' works (or fails to work), and the way decisions are made about their care." Patients interviewed by the Picker Institute for this study reported that they "see a confusing, expensive, unreliable and often impersonal dis-assembly of medical professionals and institutions." Moreover, patients expressed a strong concern over their own roles in making health care decisions. Asked who should control decisions about health care in an "ideal world," AHA focus group participants answered that they, themselves, should call the shots, along with their doctors. Patients are more aware than they have been in the past about the variations and alternatives in treatments for many disorders, and they are more likely to question doctors about decisions regarding their treatment ... [a] senior citizen who had recently drawn up a living will with the help of her seniors' group commented, "I didn't know before that I could refuse! Now I know!" These findings call into question the underlying assumption that more care is better care, and that access and cost are the most fundamental problems of the American health care system. Patients as well as health services researchers have begun to ask whether more really is better, and whether the "system" really is a system. Until we can answer those questions with any certainty, we will not be able to achieve real quality in American medical care.