Evaluating increasing hospital closure rates in U.S.: A model framework and a Lean Six Sigma deployment approach for quality improvement initiatives to prevent further closures in rural and disadvantaged locations

Hospital Closures occur from time to time. Several rural hospitals were closed in the U.S. recently in an unprecedented manner and hundreds of others are at the risk of closing. The Patient Protection and Affordable Care Act (PPACA) which was amended in 2010, has brought sea of changes in the healthcare industry right from changing the way how hospitals receive reimbursements by introducing several new programs targeting hospitals' quality of care to expanding health insurance for millions of poor and underprivileged populations in the country.;The goal of this study is to understand the closure of rural hospitals in line with the recent reform changes and identifying counter measures to prevent further closures in the future.;The first section of the research identifies and evaluates the factors behind the closures by creating a binary logistic model to predict closures of hospitals. Three models were created, first using patient and market characteristics factors (Financial Importance), second using hospitals core measure processes (Operational Importance) and a final model combining the above both models.;The second section of the research identifies and evaluates process improvement initiatives by deploying Lean Six Sigma projects in the hospitals. A Hospital Enterprise System (HES) which encompass three hospitals is used for the study. A 0-1 Integer Linear Programming method (Knapsack Method) is proposed for the selection of projects. Two scenarios are created in which the first scenario optimizes the cost savings by selecting projects among three hospitals. In the second scenario, one among the three hospitals are assumed to be present in a disadvantaged location and few core measure projects are mandatorily implemented to improve the performance of processes to avoid penalties, reimbursement cuts and achieve cost savings to prevent closures in the future.