OBJECTIVES: To assess the relationship between care fragmentation and both quality and costs of care for commercially insured, chronically ill patients. STUDY DESIGN: We used claims data from 2004 to 2008 for 506,376 chronically ill, privately insured enrollees of a large commercial insurance company to construct measures of fragmentation. We included patients in the sample if they had chronic conditions in any of the following categories: cardiovascular disease, diabetes, asthma, arthritis, or migraine. METHODS: We assigned each patient a fragmentation index based on the patterns of care of their primary care provider (PCP), with care patterns spread across a higher number of providers considered to be more fragmented. We used regression analysis to examine the relationship between fragmentation and both quality and cost outcomes. RESULTS: Patients of PCPs in the highest quartile of fragmentation had a higher chance of having a departure from clinical best practice (32.8%, vs 25.9% among patients of PCPs in the lowest quartile of fragmentation; P < .001). Similarly, patients of PCPs with high fragmentation had higher rates of preventable hospitalizations (9.1% in highest quartile vs 7.1% in lowest quartile; P < .001). High fragmentation was associated with $4542 higher healthcare spending ($10,396 in the highest quartile vs $5854 in the lowest quartile; P < .001). We found similar or larger effects on quality and costs among patients when we examined the most frequently occurring disease groups individually. CONCLUSIONS: Chronically ill patients whose primary care providers offer highly fragmented care more often experience lapses in care quality and incur greater healthcare costs.
OBJECTIVES: To assess the relationship between care fragmentation and both quality and costs of care for commercially insured, chronically ill patients. STUDY DESIGN: We used claims data from 2004 to 2008 for 506,376 chronically ill, privately insured enrollees of a large commercial insurance company to construct measures of fragmentation. We included patients in the sample if they had chronic conditions in any of the following categories: cardiovascular disease, diabetes, asthma, arthritis, or migraine. METHODS: We assigned each patient a fragmentation index based on the patterns of care of their primary care provider (PCP), with care patterns spread across a higher number of providers considered to be more fragmented. We used regression analysis to examine the relationship between fragmentation and both quality and cost outcomes. RESULTS:Patients of PCPs in the highest quartile of fragmentation had a higher chance of having a departure from clinical best practice (32.8%, vs 25.9% among patients of PCPs in the lowest quartile of fragmentation; P < .001). Similarly, patients of PCPs with high fragmentation had higher rates of preventable hospitalizations (9.1% in highest quartile vs 7.1% in lowest quartile; P < .001). High fragmentation was associated with $4542 higher healthcare spending ($10,396 in the highest quartile vs $5854 in the lowest quartile; P < .001). We found similar or larger effects on quality and costs among patients when we examined the most frequently occurring disease groups individually. CONCLUSIONS: Chronically ill patients whose primary care providers offer highly fragmented care more often experience lapses in care quality and incur greater healthcare costs.
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