Physician network position and patient outcomes following implantable cardioverter defibrillator therapy

Abstract

Objective To evaluate two novel measures of physician network centrality and their associations with implantable cardioverter defibrillator (ICD) procedure volume and health outcomes. Data Sources Medicare claims and the National Cardiovascular Data Registry data from 2007 to 2011. Study Design We constructed a national cardiovascular disease patient‐sharing physician network and used network analysis to characterize physician network centrality with two measures: within‐hospital degree centrality (number of connections within a hospital) and across‐hospital degree centrality (number of connections across hospitals). The primary outcome was risk‐adjusted 2‐year case fatality. Hierarchical logistic regression estimated the effects of physician's within‐hospital and across‐hospital degree centrality on case fatality. We included 105 109 ICD therapy patients and 3474 ICD implanting physicians in our analyses. Principal Findings After controlling for other physician and hospital characteristics, we observed greater risk‐adjusted case fatality among patients treated by physicians in the highest across‐hospital degree tertile compared to lowest tertile (OR [95% CI] = 1.10 [1.04‐1.16], P = 0.001) and lowest tertile volume physicians compared with highest volume (OR [95% CI] = 0.90 [0.84‐0.95], P < 0.001). Physician's within‐hospital degree tertile was inversely associated with case fatality but not statistically significant. Conclusions Degree centrality measures capture information independent of procedure volume and raise questions about the quality of physicians with networks that predict worse health outcomes.

Regional medical inter-institutional cooperation in medical provider network constructed using patient claims data from Japan

“…We calculated the µ G (s) of medical providers hospitalized by a patient in each case from the strength s of individual medical providers using Eq. (11). We used µ G (s) as an input variable.…”

“…Researchers have proposed various methods to construct physician and medical provider networks to share or transfer patients [3]. Previous studies on physician networks have examined the relationship between network features and medical cost [4-9], quality of care [10],and mortality [11] as a patient-level medical outcome measure and the relationship between various medical outcomes and network features at the regional level [12].Physician networks contain information about medical cooperation and the quality of healthcare.Compared with studies on physician networks, few reports of studies on medical provider networks exist. The extent to which medical cooperation, extracted from the medical provider network, affects the quality of health care provision is an interesting question.…”

“…and mortality [11] as a patient-level medical outcome measure and the relationship between various medical outcomes and network features at the regional level [12].…”

Regional medical inter-institutional cooperation in medical provider network constructed using patient claims data from Japan

“…Both tails are similar to power law distribution. We calculated the μ G (s) of medical providers hospitalized by a patient in each case from the strength s of individual medical providers using Eq (11). We used μ G (s) as an input variable.…”

“…Researchers have proposed various methods to construct physician and medical provider networks to share or transfer patients [ 3 ]. Previous studies on physician networks have examined the relationship between network features and medical cost [ 4 – 9 ], quality of care [ 10 ], and mortality [ 11 ] as a patient-level medical outcome measure and the relationship between various medical outcomes and network features at the regional level [ 12 ]. Physician networks contain information about medical cooperation and the quality of healthcare.…”