JAMA: Regions with more chronic conditions diagnoses have lower death rates
Regions that have a greater frequency of diagnoses have a lower case fatality rate for certain chronic conditions, a March 16 study in the Journal of the American Medical Association (JAMA) revealed.
H. Gilbert Welch, MD, MPH, of the Department of Veterans Affairs Medical Center in White River Junction, Vt., and colleagues conducted a study examining data for more than 5.15 million Medicare beneficiaries in 2007 to determine the association between frequency of diagnoses for chronic conditions in geographic areas and case fatality rate.
The study included an analysis of the average number of nine serious chronic conditions diagnosed in 306 hospital referral regions (HRRs) in the U.S. The nine chronic conditions were cancer with poor prognosis, 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.
In 2007, the mean number of chronic conditions diagnosed among Medicare beneficiaries across 306 HRRs was 0.90; median, 0.87. The frequency of diagnosis varied substantially with geography, according to the study. The average number of chronic conditions diagnosed per Medicare beneficiary ranged from 0.58 in Grand Junction, Colo., and Idaho Falls, Idaho, to 1.23 in Miami and McAllen, Texas.
Across the 306 HRRs, diagnosis frequency had a strong positive correlation with measures of physician encounters and diagnostic testing. In addition, the number of conditions diagnosed was related to risk of death, the authors wrote. Among patients diagnosed with 0, one, two, and three conditions, the case-fatality rates were 16, 45, 93, and 154 per 1000, respectively.
“As the number of diagnoses of chronic conditions increased in individual patients, there was an associated increased risk of death. However, as the number of diagnoses increased among geographically defined populations (i.e., across quintiles of diagnosis frequency), there was little relationship with population-based mortality. These apparently paradoxical findings were explained by a third observation: Among patient subgroups with a given number of chronic conditions, there was a consistent stepwise decrement in case fatality as diagnosis frequency increased.
“As with all observational data, causality cannot be directly tested. Our analysis could be limited by residual confounding—i.e., from variables that could explain increased diagnosis frequency as well as declining case fatality. The conventional explanation for our findings would be that the geographic variation in diagnosis frequency reflects underlying differences in disease burden, [thus] regions with high diagnosis frequencies must have sicker patients,” wrote Welch and colleagues. “However, this explanation fails to explain why population-based mortality is stable across quintiles of diagnosis frequency.”
The authors cited a number of limitations in their analysis. For example, “although Medicare claims are the most complete population-based data available in the U.S., they are not entirely complete. Specifically, beneficiaries enrolled in plans outside of fee-for-service (plans that receive capitated payments from Medicare, such as Medicare Advantage) are not included in claims data,” they wrote. In addition, the logistic regression models’ ability to adequately isolate the effect of each individual condition from others may be limited; and coding could vary across regions, according to the study.
“Future research must further evaluate the contribution of the process of observation to diagnosis frequency and explore mechanisms to better measure disease burden,” the authors concluded.
H. Gilbert Welch, MD, MPH, of the Department of Veterans Affairs Medical Center in White River Junction, Vt., and colleagues conducted a study examining data for more than 5.15 million Medicare beneficiaries in 2007 to determine the association between frequency of diagnoses for chronic conditions in geographic areas and case fatality rate.
The study included an analysis of the average number of nine serious chronic conditions diagnosed in 306 hospital referral regions (HRRs) in the U.S. The nine chronic conditions were cancer with poor prognosis, 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.
In 2007, the mean number of chronic conditions diagnosed among Medicare beneficiaries across 306 HRRs was 0.90; median, 0.87. The frequency of diagnosis varied substantially with geography, according to the study. The average number of chronic conditions diagnosed per Medicare beneficiary ranged from 0.58 in Grand Junction, Colo., and Idaho Falls, Idaho, to 1.23 in Miami and McAllen, Texas.
Across the 306 HRRs, diagnosis frequency had a strong positive correlation with measures of physician encounters and diagnostic testing. In addition, the number of conditions diagnosed was related to risk of death, the authors wrote. Among patients diagnosed with 0, one, two, and three conditions, the case-fatality rates were 16, 45, 93, and 154 per 1000, respectively.
“As the number of diagnoses of chronic conditions increased in individual patients, there was an associated increased risk of death. However, as the number of diagnoses increased among geographically defined populations (i.e., across quintiles of diagnosis frequency), there was little relationship with population-based mortality. These apparently paradoxical findings were explained by a third observation: Among patient subgroups with a given number of chronic conditions, there was a consistent stepwise decrement in case fatality as diagnosis frequency increased.
“As with all observational data, causality cannot be directly tested. Our analysis could be limited by residual confounding—i.e., from variables that could explain increased diagnosis frequency as well as declining case fatality. The conventional explanation for our findings would be that the geographic variation in diagnosis frequency reflects underlying differences in disease burden, [thus] regions with high diagnosis frequencies must have sicker patients,” wrote Welch and colleagues. “However, this explanation fails to explain why population-based mortality is stable across quintiles of diagnosis frequency.”
The authors cited a number of limitations in their analysis. For example, “although Medicare claims are the most complete population-based data available in the U.S., they are not entirely complete. Specifically, beneficiaries enrolled in plans outside of fee-for-service (plans that receive capitated payments from Medicare, such as Medicare Advantage) are not included in claims data,” they wrote. In addition, the logistic regression models’ ability to adequately isolate the effect of each individual condition from others may be limited; and coding could vary across regions, according to the study.
“Future research must further evaluate the contribution of the process of observation to diagnosis frequency and explore mechanisms to better measure disease burden,” the authors concluded.