Skip to main page content
U.S. flag

An official website of the United States government

Dot gov

The .gov means it’s official.
Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site.

Https

The site is secure.
The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

Access keys NCBI Homepage MyNCBI Homepage Main Content Main Navigation
. 2011 Mar 16;305(11):1113-8.
doi: 10.1001/jama.2011.307.

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

Affiliations

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

H Gilbert Welch et al. JAMA. .

Abstract

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.

PubMed Disclaimer

Conflict of interest statement

Conflict of Interest Disclosures: All authors have completed and submitted the ICMJE Form for Disclosure of Potential Conflicts of Interest. Dr Wennberg reported serving as a paid consultant to the Foundation for Informed Medical Decision Making and Health Dialog and receiving royalties from Health Dialog. No other authors reported disclosures.

Figures

Figure 1
Figure 1
Variation in Number of Chronic Conditions Diagnosed Among Medicare Beneficiaries in the United States, 2007 aValues in parentheses indicate range for each quintile.
Figure 2
Figure 2
Distribution of Chronic Conditions Among Medicare Beneficiaries Across Regions With Varying Diagnosis Frequency See Table 1 for denominator data used to calculate diagnosis frequency. aValues in parentheses indicate range for each quintile.
Figure 3
Figure 3
Population-Based Mortality and Case Fatality Across Regions With Varying Diagnosis Frequency Error bars indicate 95% confidence intervals. Relative rates of death in regions with very high vs very low diagnosis frequency: relative rate, 1.07 (95% CI, 1.06–1.08 [P=.31 for trend]) for entire population; 0.97 (95% CI, 0.94–1.00 [P=.46 for trend]) for no chronic conditions; 0.74 (95% CI, 0.72–0.76 [P=.006 for trend]) for 1 chronic condition; 0.76 (95% CI, 0.74–0.78 [P=.007 for trend]) for 2 chronic conditions; 0.81 (95% CI, 0.79–0.84 [P=.01 for trend]) for 3 chronic conditions. Entire population, N=5 153 877; no chronic conditions, n=2 611 646; 1 chronic condition, n=1 318 809; 2 chronic conditions, n=665 093; 3 chronic conditions, n=331 999; not shown are 226 300 persons with 4 or more conditions. aQuintiles indicate mean number of chronic conditions per beneficiary. Values in parentheses indicate range for each quintile.
Figure 4
Figure 4
Relative Rates of Death in Regions With Very High vs Very Low Diagnosis Frequency Among Beneficiaries Diagnosed With Each of 9 Chronic Conditions Relative rates were calculated using logistic regression adjusted for age/sex/race and number of coexisting chronic conditions and are not calculable from raw counts of numbers of deaths and numbers with each condition. CAD indicates coronary artery disease; CHF, congestive heart failure; COPD, chronic obstructive pulmonary disease; PVD, peripheral vascular disease.

References

    1. Song Y, Skinner J, Bynum J, Sutherland J, Wennberg JE, Fisher ES. Regional variations in diagnostic practices. N Engl J Med. 2010;363(1):45–53. - PMC - PubMed
    1. Iezzoni LI, Heeren T, Foley SM, Daley J, Hughes J, Coffman GA. Chronic conditions and risk of in-hospital death. Health Serv Res. 1994;29(4):435–460. - PMC - PubMed
    1. Welch WP, Welch HG. Fee-for-data: a strategy to open the HMO black box. Health Aff (Millwood) 1995;14(4):104–116. - PubMed
    1. Morreim EH. Gaming the system: dodging the rules, ruling the dodgers. Arch Intern Med. 1991;151 (3):443–447. - PubMed
    1. Pine M, Jordan HS, Elixhauser A, et al. Modifying ICD-9-CM coding of secondary diagnoses to improve risk-adjustment of inpatient mortality rates. Med Decis Making. 2009;29(1):69–81. - PubMed

Publication types

LinkOut - more resources