Physician network position and patient outcomes following implantable cardioverter defibrillator therapy

Detecting Variation in Clinical Practice Patterns for Geriatric Trauma Care Using Social Network Analysis

OBJECTIVE

To characterize hospital-level professional networks of physicians caring for older trauma patients as a function of trauma patient age distribution.

BACKGROUND

The causal factors associated with between-hospital variation in geriatric trauma outcomes are poorly understood. Variation in physician practice patterns reflected by differences in professional networks might contribute to hospital-level differences in outcomes for older trauma patients.

METHODS

This is a population-based, cross-sectional study of injured older adults (age 65 or above) and their physicians from January 1, 2014, to December 31, 2015, using Health Care Cost and Utilization Project inpatient data and Medicare claims from 158 hospitals in Florida. We used social network analyses to characterize the hospitals in terms of network density, cohesion, small-worldness, and heterogeneity, then used bivariate statistics to assess the relationship between network characteristics and hospital-level proportion of trauma patients who were aged 65 or above.

RESULTS

We identified 107,713 older trauma patients and 169,282 patient-physician dyads. The hospital-level proportion of trauma patients who were aged 65 or above ranged from 21.5% to 89.1%. Network density, cohesion, and small-worldness in physician networks were positively correlated with hospital geriatric trauma proportions ( R =0.29, P <0.001; R =0.16, P =0.048; and R =0.19, P <0.001, respectively). Network heterogeneity was negatively correlated with geriatric trauma proportion ( R =0.40, P <0.001).

CONCLUSIONS

Characteristics of professional networks among physicians caring for injured older adults are associated with the hospital-level proportion of trauma patients who are older, indicating differences in practice patterns at hospitals with older trauma populations. Associations between interspecialty collaboration and patient outcomes should be explored as an opportunity to improve the treatment of injured older adults.

Optimal Physician Shared-Patient Networks and the Diffusion of Medical Technologies

Social network analysis has created a productive framework for the analysis of the histories of patient-physician interactions and physician collaboration. Notable is the construction of networks based on the data of "referral paths" - sequences of patient-specific temporally linked physician visits - in this case, culled from a large set of Medicare claims data in the United States. Network constructions depend on a range of choices regarding the underlying data. In this paper we introduce the use of a five-factor experiment that produces 80 distinct projections of the bipartite patient-physician mixing matrix to a unipartite physician network derived from the referral path data, which is further analyzed at the level of the 2,219 hospitals in the final analytic sample. We summarize the networks of physicians within a given hospital using a range of directed and undirected network features (quantities that summarize structural properties of the network such as its size, density, and reciprocity). The different projections and their underlying factors are evaluated in terms of the heterogeneity of the network features across the hospitals. We also evaluate the projections relative to their ability to improve the predictive accuracy of a model estimating a hospital's adoption of implantable cardiac defibrillators, a novel cardiac intervention. Because it optimizes the knowledge learned about the overall and interactive effects of the factors, we anticipate that the factorial design setting for network analysis may be useful more generally as a methodological advance in network analysis.

Physician Network Connections Associated With Faster De-Adoption of Dronedarone for Permanent Atrial Fibrillation

BACKGROUND

Physicians' professional networks are an important source of new medical information and have been shown to influence the adoption of new treatments, but it is unknown how physician networks impact the de-adoption of harmful practices.

METHODS

We analyzed changes in physicians' use of dronedarone after the PALLAS trial (Palbociclib Collaborative Adjuvant Study; November 2011) showed that dronedarone increased the risk of death from cardiovascular events among patients with permanent atrial fibrillation. Deidentified administrative claims from the OptumLabs Data Warehouse were combined with physicians' demographic information from the Doximity database and publicly available data on physicians' patient-sharing relationships compiled by the Centers for Medicare and Medicaid Services. We used a linear probability model with an interrupted linear time trend specification to model the impact of the PALLAS trial on physicians' dronedarone usage between 2009 and 2014.

RESULTS

Before the PALLAS trial, the use of dronedarone was increasing by 0.22 percentage points per quarter (95% CI, 0.19-0.25) in our Medicare Advantage sample (N=343 429 patient-quarter observations) and 0.63 percentage points per quarter (95% CI, 0.52-0.75) in our commercially insured sample (N=44 402 patient-quarter observations). After the PALLAS trial and subsequent United States Food and Drug Administration black box warning, physicians in the Medicare Advantage sample with an above-median number of network connections to other physicians decreased their quarterly usage of dronedarone by 0.12 percentage points more per quarter (95% CI, -0.20 to -0.04; P=0.031) than physicians with equal to or below the median number of network connections. Similar patterns existed in the commercially insured sample (P=0.0318).

CONCLUSIONS

After controlling for a wide range of patient, physician, and geographic characteristics, physicians with a greater number of network connections were faster de-adopters of dronedarone for patients with permanent atrial fibrillation after the PALLAS trial and subsequent United States Food and Drug Administration black box warning detailed the harmfulness of dronedarone for these patients. Policies for improving physicians' responsiveness to new medical information should consider utilizing the influence of these important professional network relationships.

A measure of local uniqueness to identify linchpins in a social network with node attributes

Network centrality measures assign importance to influential or key nodes in a network based on the topological structure of the underlying adjacency matrix. In this work, we define the importance of a node in a network as being dependent on whether it is the only one of its kind among its neighbors' ties. We introduce linchpin score, a measure of local uniqueness used to identify important nodes by assessing both network structure and a node attribute. We explore linchpin score by attribute type and examine relationships between linchpin score and other established network centrality measures (degree, betweenness, closeness, and eigenvector centrality). To assess the utility of this measure in a real-world application, we measured the linchpin score of physicians in patient-sharing networks to identify and characterize important physicians based on being locally unique for their specialty. We hypothesized that linchpin score would identify indispensable physicians who would not be easily replaced by another physician of their specialty type if they were to be removed from the network. We explored differences in rural and urban physicians by linchpin score compared with other network centrality measures in patient-sharing networks representing the 306 hospital referral regions in the United States. We show that linchpin score is uniquely able to make the distinction that rural specialists, but not rural general practitioners, are indispensable for rural patient care. Linchpin score reveals a novel aspect of network importance that can provide important insight into the vulnerability of health care provider networks. More broadly, applications of linchpin score may be relevant for the analysis of social networks where interdisciplinary collaboration is important.

Physician network connections to specialists and HIV quality of care

OBJECTIVE

To estimate novel measures of generalist physicians' network connectedness to HIV specialists and their associations with two dimensions of HIV quality of care.

DATA SOURCES

Medicare and Medicaid claims and the American Medical Association Masterfile data on people living with HIV (PLWH) and the physicians providing their HIV care in California between 2007 and 2010.

STUDY DESIGN

I construct regional patient-sharing physician networks from the shared treatment of PLWH and calculate (a) measures of network connectedness to all physician types and (b) specialty-weighted measures to describe connectedness to HIV specialists. Two HIV quality of care outcomes are then evaluated: medication quality (prescribing antiretroviral drugs from at least two drug classes) and monitoring quality (at least two annual HIV virus monitoring scans). Linear probability models estimate the associations between network statistics and the two dimensions of HIV quality of care, and a policy simulation demonstrates the importance of these statistical relationships. These analyses include 16 124 PLWH, 3240 generalists, and 1031 HIV specialists.

DATA COLLECTION/EXTRACTION METHODS

PLWH are identified from claims for patients with any indication of HIV using an existing algorithm from the literature.

PRINCIPAL FINDINGS

Generalists' network connectedness to HIV specialists is positively related with their own HIV medication quality; one additional HIV specialist connection is associated with a 1.46 percentage point (SE 0.42, P < .01) increase in generalist's medication quality. Based on the estimated associations, a simulated policy that increases connectedness between generalists and HIV specialists reduces the annual rate of HIV infections by up to 6%, roughly 290 fewer infections per year. Only network connectedness to all physician types is associated with improved monitoring quality.

CONCLUSIONS

Network connectedness to HIV specialists is positively associated with generalists' HIV medication quality, which suggests that specialists provide clinical support through patient-sharing for complex treatment protocol.

Surgeon and medical oncologist peer network effects on the uptake of the 21-gene breast cancer recurrence score assay

BACKGROUND

Drivers behind the adoption of gene expression profiling in breast cancer oncology have been shown to include exposure to physician colleagues' use of a given genomic test. We examined adoption of the Oncotype DX 21-gene breast cancer recurrence score assay (ODX) in the United States after its incorporation into clinical guidelines. The influence of patient-sharing ties and co-location with prior adopters and the role of these potential exposures across medical specialties on peers' adoption of the test were examined.

METHODS

We conducted a retrospective cohort study of women with incident breast cancer using a 100% sample of fee-for-service Medicare enrollee claims over 2008-2011. Peer networks connecting medical oncologists and surgeons treating these patients were constructed using patient-sharing and geographic co-location. The impact of peer connections on the adoption of ODX by physicians and testing of patients was modeled with multivariable hierarchical regression.

RESULTS

Altogether, 156,229 women identified with incident breast cancer met criteria for cohort inclusion. A total of 7689 ODX prescribing physicians were identified. Co-location with medical oncologists who adopted the test in the early period (2008-2009) was associated with a 1.38-fold increase in the odds of a medical oncologist adopting ODX in 2010-2011 (95% CI = 1.04-1.83), as was co-location with early-adopting surgeons (odds ratio [OR] = 1.25, 95% CI = 1.00-1.58). Patients whose primary medical oncologist was linked to an early-adopting surgeon through co-location (OR = 1.17, 95% CI = 1.04-1.32) or both patient-sharing and co-location (OR = 1.17, 95% CI = 1.03-1.34) were more likely to receive ODX.

CONCLUSIONS

Exposure to surgeon early adopters through peer networks and co-location was predictive of ODX uptake by medical oncologists and testing of patients. Interventions focused on the role of surgeons in molecular testing may improve the implementation of best practices in breast cancer care.

Physician network position and patient outcomes following implantable cardioverter defibrillator therapy

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.