An observational study of health care provider collaboration networks and heterogenous hospital cost efficiency and quality outcomes

Sebastian Linde, Hajime Shimao

Research output: Contribution to journalArticlepeer-review

Abstract

Provider network structure has been linked to hospital cost, utilization, and to a lesser degree quality, outcomes; however, it remains unknown whether these relationships are heterogeneous across different acute care hospital characteristics and US states. The objective of this study is to evaluate whether there are heterogeneous relationships between hospital provider network structure and hospital outcomes (cost efficiency and quality); and to assess the sources of measured heterogeneous effects. We use recent causal random forest techniques to estimate (hospital specific) heterogeneous treatment effects between hospitals' provider network structures and their performance (across cost efficiency and quality). Using Medicare cost report, hospital quality and provider patient sharing data, we study a population of 3061 acute care hospitals in 2016. Our results show that provider networks are significantly associated with costs efficiency (P <.001 for 7/8 network measures), patient rating of their care (P <.1 in 5/8 network measures), heart failure readmissions (P <.01 for 3/8 network measures), and mortality rates (P <.02 in 5/8 cases). We find that fragmented provider structures are associated with higher costs efficiency and patient satisfaction, but also with higher heart failure readmission and mortality rates. These effects are further found to vary systematically with hospital characteristics such as capacity, case mix, ownership, and teaching status. This study used an observational design. In summary, we find that hospital treatment responses to different network structures vary systematically with hospital characteristics.

Original languageEnglish (US)
Pages (from-to)E30662
JournalMedicine (United States)
Volume101
Issue number39
DOIs
StatePublished - Sep 30 2022

All Science Journal Classification (ASJC) codes

  • General Medicine

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