The association between patient sharing network structure and healthcare costs

Geissler, Kimberley H.; Lubin, Benjamin; Ericson, Keith M. Marzilli

doi:10.1371/journal.pone.0234990

Cited by 13 publications

(13 citation statements)

References 45 publications

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“…The great power of networks to describe real-world systems has attracted growing interest, and this modelling approach has been used in many research areas in recent decades. Several studies have introduced networks as helpful tools to investigate specific questions, even in the field of health and medical information analysis [ 19 , 20 , 21 , 22 ]. However, to date, only a few studies have dealt with network models to study drug prescription [ 10 , 11 , 23 ].…”

Section: Discussionmentioning

confidence: 99%

A Network Approach for the Study of Drug Prescriptions: Analysis of Administrative Records from a Local Health Unit (ASL TO4, Regione Piemonte, Italy)

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Armando

et al. 2021

IJERPH

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In a Drug Prescription Network (DPN), each drug is represented as a node and two drugs co-prescribed to the same patient are represented as an edge linking the nodes. The use of DPNs is a novel approach that has been proposed as a means to study the complexity of drug prescription. The aim of this study is to demonstrate the analytical power of the DPN-based approach when it is applied to the analysis of administrative data. Drug prescription data that were collected at a local health unit (ASL TO4, Regione Piemonte, Italy), over a 12-month period (July 2018–June 2019), were used to create several DPNs that correspond to the five levels of the Anatomical Therapeutic Chemical classification system. A total of 5,431,335 drugs prescribed to 361,574 patients (age 0–100 years; 54.7% females) were analysed. As indicated by our results, the DPNs were dense networks, with giant components that contain all nodes. The disassortative mixing of node degrees was observed, which implies that non-random connectivity exists in the networks. Network-based methods have proven to be a flexible and efficient approach to the analysis of administrative data on drug prescription.

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Section: Discussionmentioning

confidence: 99%

A Network Approach for the Study of Drug Prescriptions: Analysis of Administrative Records from a Local Health Unit (ASL TO4, Regione Piemonte, Italy)

Miglio

Basso

Armando

et al. 2021

IJERPH

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“…First, our analysis is based in Massachusetts, which may limit generalizability. However, most network analysis is done in highly local areas (e.g., hospital referral regions) (Landon et al 2012) or using a single insurer (Trogdon et al 2019) and so using a state-level dataset is of value to measure both geographically close and distant patient-sharing patterns (Geissler et al 2020a;O'Malley et al 2020). We include fixed effects for patient 3-digit ZIP code to account for geographic differences in patient care and physician patient-sharing network measures in areas with fewer physicians.…”

Section: Discussionmentioning

confidence: 99%

“…Our analysis makes an important contribution in showing referrals are to physicians -including overall and specialists only -with differing positions in the physician patientsharing network in terms of network connections and centrality, which have been shown to be associated with healthcare costs (Landon et al 2012;Agha et al 2019;Geissler et al 2020a). Similar to previous findings (Geissler et al 2016;Landon et al 2013), our results suggest policy choices in the insurance and delivery system that change physician…”

Section: Discussionmentioning

confidence: 99%

“…PCPs have a major role in patient treatment, as well as in selecting and coordinating specialist care (Bodenheimer et al 1999;Barnett et al 2019;Mehrotra et al 2011;Agha et al 2019;Geissler et al 2020a;Geissler 2020;Geissler and Zeber 2020;Geissler et al 2020b) -and their patterns may particularly vary based on patient insurance type (Agha et al 2019;Barnett et al 2018;Forrest et al 1997). Accordingly, we develop measures for directly measuring the extent to which a PCP works with highly connected specialists who may have access to more information flow due to their network position.…”

Section: Physician Patient-sharing Network Constructionmentioning

confidence: 99%

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The association of insurance plan characteristics with physician patient-sharing network structure

Geissler

Lubin

Ericson

2021

Int J Health Econ Manag.

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Professional and social connections among physicians impact patient outcomes, but little is known about how characteristics of insurance plans are associated with physician patientsharing network structure. We use information from commercially insured enrollees in the 2011 Massachusetts All Payer Claims Database to construct and examine the structure of the physician patient-sharing network using standard and novel social network measures. Using regression analysis, we examine the association of physician patient-sharing network measures with an indicator of whether a patient is enrolled in a health maintenance organization (HMO) or preferred provider organization (PPO), controlling for patient and insurer characteristics and observed health status. We find patients enrolled in HMOs see physicians who are more central and densely embedded in the patient-sharing network. We find HMO patients see PCPs who refer to specialists who are less globally central, even as these specialists are more locally central. Our analysis shows there are small but significant differences in physician patient-sharing network as experienced by patients with HMO versus PPO insurance. Understanding connections between physicians is essential and, similar to previous findings, our results suggest policy choices in the insurance and delivery system that change physician connectivity may have important implications for healthcare delivery, utilization and costs.

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“…In the pre-analysis, we performed 20 iterations with five-fold cross-validation and used the average value of RMSE as the evaluation value of the regression performance. As a result, we used the parameter (t, l, w, d) = (7,60,13,75), where the mean value of RMSE is the minimum value of each parameter. The results for this pre-analysis are shown in S3 Figure.…”

Section: Rmse = (Dmentioning

confidence: 99%

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

Ohki

Ikeda

Kunisawa

et al. 2022

Preprint

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The aging world population requires a sustainable and high-quality healthcare system. To examine the efficiency of medical cooperation, medical provider and physician networks were constructed using patient claims data. Previous studies have shown that these networks contain information on medical cooperation. However, the usage patterns of multiple medical providers in a series of medical services have not been considered. In addition, these studies used only general network features to represent medical cooperation, but their expressive ability was low. To overcome these limitations, we analyzed the medical provider network to examine its overall contribution to the quality of healthcare provided by cooperation between medical providers in a series of medical services. This study focused on: i) the method of feature extraction from the network, ii) incorporation of the usage pattern of medical providers, and iii) expressive ability of the statistical model. Femoral neck fractures were selected as the target disease. To build the medical provider networks, we analyzed the patient claims data from a single prefecture in Japan between January 1, 2014 and December 31, 2019. We considered four types of models: a model using node strength and linear regression to a model using feature representation by node2vec and regression tree ensemble, which is a machine learning method. The results showed that a stronger medical provider reduces the duration of hospital stay. The overall contribution of the medical cooperation to the duration of hospital stay extracted from the medical provider network using node2vec is approximately 20%, which is approximately 20 times higher than the model using strength.

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The association between patient sharing network structure and healthcare costs

Cited by 13 publications

References 45 publications

A Network Approach for the Study of Drug Prescriptions: Analysis of Administrative Records from a Local Health Unit (ASL TO4, Regione Piemonte, Italy)

A Network Approach for the Study of Drug Prescriptions: Analysis of Administrative Records from a Local Health Unit (ASL TO4, Regione Piemonte, Italy)

The association of insurance plan characteristics with physician patient-sharing network structure

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

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