An analysis of patient-sharing physician networks and implantable cardioverter defibrillator therapy

Abstract

The application of social network analysis to the organization of healthcare delivery is a relatively new area of research that may not be familiar to health services statisticians and other methodologists. We present a methodological introduction to social network analysis with a case study of physicians’ adherence to clinical guidelines regarding use of implantable cardioverter defibrillators (ICDs) for the prevention of sudden cardiac death. We focus on two hospital referral regions (HRRs) in Indiana, Gary and South Bend, characterized by different rates of evidence-based ICD use (86% and 66%, respectively). Using Medicare Part B claims, we construct a network of physicians who care for cardiovascular disease patients based on patient-sharing relationships. Approaches for weighting physician dyads and aggregating physician dyads by hospital are discussed. Then, we obtain a set of weighted network statistics for the positions of hospitals in their referral region, global statistics for the physician network within each hospital, and of the network positions of individual physicians within hospitals, providing the mathematical specification and sociological intuition underlying each measure. We find that adjusting for network measures can reduce the observed differences between referral regions for evidence-based ICD therapy. This study supports previous reports on how variation in physician network structure relates to utilization of care, and motivates future work using physician network measures to examine variation in evidence-based medicine.

Virtuelle Behandlernetzwerke

“…Die präzise mathematische Berechnungsformel findet sich zum Beispiel bei Newman [23, S. 8578]. [24] wenden in einer Fallstudie das netzwerktheoretische Analyseinstrumentarium auf die von Bynum et al [14] gebildeten krankenhauszentrierten Netzwerke an, um Eigenschaften zu bestimmen, die eine Leitlinienadhärenz bei der Implantierung von Defibrillatoren unterstützen. Sie suchen nach Faktoren zur Gewichtung der Verbindungen zwischen Ärzten und Krankenhäusern und zwischen den Ärzten innerhalb eines krankenhauszentrierten Netzwerks.…”

Bayesian exponential random graph modelling of interhospital patient referral networks

“…With the exceptions mentioned at the outset, available studies of interhospital networks are almost exclusively descriptive , or concerned with the transfer of critically ill patients where decentralised dyadic interorganisational relations are less important because of the overwhelming presence of formalised patient‐transfer routines . Studies based on ERGMs are beginning to appear that have looked at patient‐sharing relations among physicians , but we are not aware of the studies of interhospital patient referral networks that have exploited the empirical advantage offered by Bayesian approaches. Hence, the secondary contribution of the paper is to the healthcare literature on interhospital collaboration with special reference to interhospital patient referral relations.…”

Physician network position and patient outcomes following implantable cardioverter defibrillator therapy

“…Using national Medicare claims, physician networks can be inclusive of the entire nation or bounded using previously developed algorithms to assign physicians to “groups” (eg, hospitals or hospital referral regions) . Degree centrality is a measure of the number of ties a physician has to other physicians within the network boundary.…”

“…Using national Medicare claims, physician networks can be inclusive of the entire nation 19 or bounded using previously developed algorithms to assign physicians to "groups" (eg, hospitals or hospital referral regions). 15,20 Degree centrality is a measure of the number of ties a physician has to other physicians within the network boundary. A mathematically appealing feature of degree centrality is that it perfectly partitions into the sum of the measure evaluated for a subnetwork and on the complement of the subnetwork.…”