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Health Systems and Efficient Matching of Patients to Hospitals
Context
The choice of hospital for a particular patient depends on many factors (e.g. patient characteristics, reason for the admission, distance to hospitals, types of services available at area hospitals). Multiple reasons may explain why a patient might not be admitted to the hospital best able to efficiently meet the patient’s needs (e.g. incomplete information about the patient, payment incentives, hospital capacity, and hospital affiliation of the clinician making the hospital selection decision). Health systems that include community hospitals and teaching hospitals may be able to improve upon the allocation of patients to hospitals, and alternative payment models (e.g. Accountable Care Organizations) may realign incentives to reward more efficient triage of patients to the optimal care setting.
Research Questions
Do community hospitals’ acquisition by health systems with teaching hospitals lead to: 1) an increase in the proportion of patients in community hospitals’ service area that are admitted to teaching hospitals for conditions that can be treated more efficiently at a community hospital? 2) an increase in the proportion of patients admitted to teaching hospitals for conditions more appropriately treated at a teaching hospital? 3) an increase in the proportion of patients in the teaching hospital service area that are admitted to a community hospital for community-appropriate conditions?
Data and Methods
We use a unique relational database containing information on physicians, physician practices, hospitals, and health systems in 2010-2016 that draws from and integrates data from many different sources. All providers can be linked to commercial and Medicare claims data. Our database of health systems enables us to identify hospitals that are part of the same system. We also identify a set of community hospitals that were acquired in each year, 2011-2015.
Our study population includes hospitalized patients living in the primary service areas of short term general acute care hospitals in the United States. We define hospital primary service areas (PSA) for rural and suburban community hospitals (urban and teaching hospitals) as all ZIP code tabulation areas (ZCTA) whose centroid coordinate falls within 25 (45) miles of each hospital’s address. We stratify patients into groups based on the patient’s complexity (HCC scores, CCW diagnoses and previous admissions) and the reason for admission (principle diagnosis code).
We estimate two difference in differences models at the patient admission level using Medicare claims data for inpatient care to examine the changes in the hospital’s proportion of admissions originating from their own PSA before and after acquisition. First, we estimate the proportion of admissions for patients residing in a community hospital PSA who are admitted to a teaching hospital. Second, we estimate the proportion of admissions for patients residing in a teaching hospital PSA who are admitted to a community hospital.
We include hospital, year, and market fixed effects, controls for patient characteristics, and relative distance measures. We also investigate heterogeneous effects for patient type, admission type, and acquired hospital characteristics (e.g. capacity, system employment of acquired community hospital physicians).
