In addition, we considered the number of ambulatory visits as a potential confounder, because the number of ambulatory visits was weakly correlated with fragmentation score (Spearman correlation coefficient, 0.22 P <.0001).ĭescriptive statistics. 18,19 We considered beneficiary age and gender as potential confounders. 17 We also calculated a severity of illness index. We used ICD-9 codes to calculate the number of chronic conditions for each beneficiary (0, 1-2, 3-4, or ≥5) 3 of 26 unique chronic conditions defined by CMS ( eAppendix B). If an ED visit resulted in hospital admission, it was considered part of that admission and counted only as an admission. 14 An “ED visit” resulted in discharge to home or elsewhere. We identified ED visits and hospital admissions in the claims, using definitions from NCQA. We conducted sensitivity analyses with 2 other fragmentation indices, the Herfindahl-Hirschman Index and the Usual Provider Continuity Index (eAppendix A). Because the distribution of BBI scores is inherently skewed, we divided scores into quintiles, an approach we successfully used previously, 3 to maximize clarity of interpretation. Patterns of care that reflect high dispersion (many providers) and low density (a relatively low proportion of ambulatory visits by each provider) yield worse (higher) scores. 3,4,6,8,16 We reversed raw BBI scores, so that higher scores would reflect more fragmentation. Our base-case analysis measured fragmentation with the Bice-Boxerman Index (BBI) ( eAppendix A ), 15,16 a previously validated measure. Finally, we excluded those who were in the hospital on January 1, 2011, because they were not at risk of an ED visit or hospital admission at the start of follow-up. 8 We required that beneficiaries be continuously enrolled in Medicare for at least 1 more consecutive year, contributing data for 2 years (2010-2011) or 3 years (2010-2012). Next, we restricted the cohort to those with 4 or more ambulatory visits in the baseline year, because calculating fragmentation with 3 or fewer ambulatory visits can lead to statistically unstable estimates. Results: Among those with 1 to 2 or 3 to 4 chronic conditions, having the most (vs the least) fragmented care significantly increased the hazard of an ED visit and, separately, increased the hazard of an admission (adjusted P 99.9th percentile) for number of ambulatory visits or unique providers, because those observations may have been erroneous. We used Cox regression models to determine associations between fragmentation and ED visits and, separately, hospital admissions, stratifying by number of chronic conditions and adjusting for age, gender, number of ambulatory visits, and case mix. Methods: We calculated fragmentation scores using a modified Bice-Boxerman Index and, because scores were skewed, divided them into quintiles. Study Design: We conducted a cohort study over 3 years among 117,977 fee-for-service Medicare beneficiaries who were attributed to primary care physicians in a 7-county region of New York and had 4 or more ambulatory visits in the baseline year. Objectives: We sought to determine the associations between fragmented ambulatory care and subsequent emergency department (ED) visits and hospital admissions, while considering possible interactions between fragmentation and number of chronic conditions.
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