Geographic Variation in Diagnosis Frequency and Risk of Death Among Medicare Beneficiaries

By H. Gilbert Welch, MD, MPH, Sandra M. Sharp, SM, Dan J. Gottlieb, MS, Jonathan S. Skinner, PhD, John E. Wennberg, MD, MPH
JAMA
March 16, 2011

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.

http://jama.ama-assn.org/content/305/11/1113.abstract

This study from the Dartmouth Institute confirms the intuitive observation that the number of diagnoses of serious chronic conditions in Medicare beneficiaries has a positive correlation with case-fatality rates. The greater number of serious problems a person has, the greater the risk of death. But observation of the regional distribution of these serious diagnoses provides troubling results.

In this study, hospital referral regions varied in the average number of diagnoses per patient of these serious chronic conditions. There is an inverse relationship between the regional frequency of diagnoses and the case-fatality rate. As an example, if you had multiple serious diagnoses, your chances of dying are less if your diagnoses were made in a region where more people have a greater number of diagnoses than if the same diagnoses were made in a region where not as many people received multiple diagnoses.

The authors discuss possible explanations, but I’ll go out on a limb, and a very solid one at that, and give my opinion.  Assigning a greater number of serious diagnoses to a patient permits greater remuneration from upcoding, and it provides rewards for favorable quality and outcomes results since the patient is not as ill as the list of diagnoses would otherwise imply.

It is very difficult to differentiate a list of well documented diagnoses from an embellished list that may include some poorly substantiated notations in the record allegedly supporting the diagnoses. It would be very difficult to ferret out the claims that do not warrant additional consideration based on complexity or quality outcomes.

Reform was supposed to bring us higher quality at a lower cost, but it appears that continued gaming of the system will bring us higher costs with spurious results on quality and outcome assessments.

Much more work needs to be done before we could rely on these observations to improve quality and reduce costs. In the meantime, we could certainly tackle the issue of costs head on by the well proven method of enacting a single payer national health program. Quality and efficiency will be a continual work in progress.