# Fulfilling the Promise of Hospital Consolidation to Improve Clinical Quality and Costs

> **NIH AHRQ R01** · UNIVERSITY OF MICHIGAN AT ANN ARBOR · 2022 · $376,414

## Abstract

PROJECT SUMMARY ABSTRACT
The healthcare policy and financing environment since the Affordable Care Act has increased pressure on
hospitals to consolidate into larger hospital systems. Annual hospital merger activity has doubled over the last
decade, and over two-thirds of US hospitals are now part of a hospital system. The presumed benefits of
hospital consolidation include concentrating volume and expertise, care integration, and investment in quality
improvement. If done correctly, they would translate to both quality and cost improvements. The limited data on
hospital system performance shows significant variation in achieving the purported benefits of consolidation.
While hospital consolidation may impact a broad spectrum of service lines, changes to surgical services may
be the most informative. Surgical care has known variation in well-defined outcomes and short-term costs. As
such, surgical care may be a “leading indicator” to understand the effects of hospital consolidation on
healthcare quality and costs. In order to better understand this phenomenon, we propose the following aims:
Aim 1: To examine the relationship between hospital network optimization and outcomes. Using claims
and publicly reported data on an inclusive range of surgical procedures from public and private payers, we will
assess hospital systems on rationalization of site of care, including centralization of complex procedures,
avoidance of low-volume surgery, and selective referral of high-risk patients to tertiary centers. Aim 2: To
examine the relationship between hospital network optimization and healthcare costs. Again using
claims and publicly reported data, we will empirically assess variation between and within hospital systems in
risk-adjusted 30-day episode costs for the same surgical procedures. We will then analyze the relationship
between care rationalization and average system costs as well as within-system cost variation. Aim 3: To
understand characteristics of high-performing networks in order to identify best practices. We will use
qualitative methods to identify effective system strategies not observable in claims data. Using a positive
deviance approach, we will identify hospital systems that exhibit the most longitudinal improvement in
outcomes and costs and perform in-depth interviews of hospital system leaders, reviews of policies and
protocols, and site visits in order to define the differentiating characteristics. Our work will allow policymakers
and the public to evaluate hospital system performance in care rationalization. Our work will also provide
insights that will help hospital system leaders improve the performance of their organizations.

## Key facts

- **NIH application ID:** 10518443
- **Project number:** 1R01HS028606-01A1
- **Recipient organization:** UNIVERSITY OF MICHIGAN AT ANN ARBOR
- **Principal Investigator:** Andrew Mounir Ibrahim
- **Activity code:** R01 (R01, R21, SBIR, etc.)
- **Funding institute:** AHRQ
- **Fiscal year:** 2022
- **Award amount:** $376,414
- **Award type:** 1
- **Project period:** 2022-08-01 → 2027-05-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10518443

## Citation

> US National Institutes of Health, RePORTER application 10518443, Fulfilling the Promise of Hospital Consolidation to Improve Clinical Quality and Costs (1R01HS028606-01A1). Retrieved via AI Analytics 2026-05-24 from https://api.ai-analytics.org/grant/nih/10518443. Licensed CC0.

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