Assessing Association Between Team Structure and Health Outcome and Cost by Social Network Analysis

Abstract

Background/Objective To assess the impact of team structure composition and degree of collaboration among various providers on process and outcomes of primary care. Design Cross‐sectional study. Setting Data from 20% randomly selected primary care service areas in the 2015 Medicare claims was used to identified primary care practices. Participants 449,460 patients with diabetes, heart failure, or chronic obstructive pulmonary disease cared for by the identified primary care practices. Measurements SNA network measures, including edge density, degree centralization, and betweenness centralization for each practice. Results When compared to practices with MDs and nurse practitioners (NPs) or/and physicians assistants (PAs), the practices with MDs only had lower degree of centralization and higher MD‐to‐MD connectedness. Within the primary care practices comprising MDs, NPs or/and PAs, the non‐physician providers were more connected (measured as edge density) to all providers in the practice but with higher degree of centralization compared to the MDs in the practice. After adjusting for patient characteristics and type of practice, higher edge density was associated with lower odds of hospitalization (odds ratio [OR]: 0.89, 95% Confidence Interval [CI]: 0.79–0.99), emergency department (ER) admission (OR: 0.80, 95% CI: 0.70–0.92), and total spending (cost ratio [CR]: 0.86, standard error of the mean [SE]: 0.038). Conversely, higher degree centralization was associated with higher rates of hospitalization (OR: 1.15, 95% CI: 1.03–1.28), ER admission (OR: 1.23, 95% CI: 1.08–1.40), and total spending (CR: 1.14, SE: 0.037). However, higher degree centralization was associated with lower rates of potentially inappropriate medications (OR: 0.90, 95% CI: 0.81, 0.99). Team leadership by an NP versus an MD were similar in the rate of ER admissions, hospitalizations, or total spending. Conclusion Our findings showed that highly connected primary care practices with high collaborative care and less top‐down MD‐centered authority have lower odds of hospitalization, fewer ER admissions, and less total spending; findings likely reflecting better communication and more coordinated care of older patients.

Information exchange networks for chronic diseases in primary care practices in Germany: a cross-sectional study

“…In their social network study, Mundt et al [ 24 ] found that high network density was associated with a 38% reduction in hospital days. Similar results were obtained by Kuo et al [ 34 ], who presented positive correlation between network density and hospitalization in the context of COPD, HF, and DM.…”

Using social network analysis methods to identify networks of physicians responsible for the care of specific patient populations

“…The degree centrality was defined as the ratio of edges and vertices per network. The edge density was calculated as the number of existing edges divided by the total number of possible edges per network and can be interpreted as the degree of collaborative care realized in the network [24]. The transitivity measures the interconnectedness of the physicians within a network, which relates to the existence of local clusters.…”

“…The methods for constructing these patient-sharing networks vary depending on the aims of the studies in which they are employed. Most studies of this nature have used routine data to identify all pairs of physicians who are connected through the patients they have in common, and to construct complex networks from these pairs [17][18][19][20][21][22][23][24][25]. Landon et al [18] used SNA to identify networks of physicians who would be suitable candidates for building Accountable Care Organizations (ACOs) in the United States because of their shared patient group.…”

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

“…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.…”