On designing of a low leakage patient-centric provider network

Yuchen Zheng,Kun Lin,Thomas White,Gigi Yuen-Reed,Jeremy Pickreign

doi:10.1186/s12913-018-3038-5

Abstract

BackgroundWhen a patient in a provider network seeks services outside of their community, the community experiences a leakage. Leakage is undesirable as it typically leads to higher out-of-network cost for patient and increases barrier for care coordination, which is particularly problematic for Accountable Care Organization (ACO) as the in-network providers are financially responsible for quality of care and outcome. We aim to design a data-driven method to identify naturally occurring provider networks driven by diabetic patient choices, and understand the relationship among provider composition, patient composition, and service leakage pattern. By doing so, we learn the features of low service leakage provider networks that can be generalized to different patient population.MethodsData used for this study include de-identified healthcare insurance administrative data acquired from Capital District Physicians’ Health Plan (CDPHP) for diabetic patients who resided in four New York state counties (Albany, Rensselaer, Saratoga, and Schenectady) in 2014. We construct a healthcare provider network based on patients’ historical medical insurance claims. A community detection algorithm is used to identify naturally occurring communities of collaborating providers. For each detected community, a profile is built using several new key measures to elucidate stakeholders of our findings. Finally, import-export analysis is conducted to benchmark their leakage pattern and identify further leakage reduction opportunity.ResultsThe design yields six major provider communities with diverse profiles. Some communities are geographically concentrated, while others tend to draw patients with certain diabetic co-morbidities. Providers from the same healthcare institution are likely to be assigned to the same community. While most communities have high within-community utilization and spending, at 85% and 86% respectively, leakage still persists. Hence, we utilize a metric from import-export analysis to detect leakage, gaining insight on how to minimize leakage.ConclusionsWe identify patient-driven provider organization by surfacing providers who share a large number of patients. By analyzing the import-export behavior of each identified community using a novel approach and profiling community patient and provider composition we understand the key features of having a balanced number of PCP and specialists and provider heterogeneity.

Highlights

When a patient in a provider network seeks services outside of their community, the community experiences a leakage
The implication is amplified with Accountable Care Organization (ACO) since provider revenues are typically tied to patient outcome
We focus on analyzing data from diabetic patients who were enrolled in any one of the commercial insurance products from Capital District Physicians’ Health Plan (CDPHP), such as individual affordable plans, Table 1 Description of acronyms and abbreviations

Summary

Introduction

When a patient in a provider network seeks services outside of their community, the community experiences a leakage. ACOs are groups of physicians, facilities and other healthcare providers, who come together voluntarily to provide coordinated high- quality care to their patients. Another example is payer-driven value network, known as narrow network, which intends to have smaller number of innetwork providers but tighter control on cost and quality. The narrow network concept is gaining popularity for network targeted at specific patient populations, for example network that services specific employee population Service leakage in these less traditional network types is even less desirable, as it undermines the premise of ability to facilitate care coordination, streamline care delivery, and manage patient outcome and quality. The implication is amplified with ACO since provider revenues are typically tied to patient outcome

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