title: Hospital Characteristics Associated With Penalties in the Centers for Medicare & Medicaid Services Hospital-Acquired Condition Reduction Program.
abstract: OBJECTIVE
  In fiscal year (FY) 2015, the Centers for Medicare & Medicaid Services (CMS) instituted the Hospital-Acquired Condition (HAC) Reduction Program, which reduces payments to the lowest-performing hospitals. However, it is uncertain whether this program accurately measures quality and fairly penalizes hospitals.
  
  
  OBJECTIVE
  To examine the characteristics of hospitals penalized by the HAC Reduction Program and to evaluate the association of a summary score of hospital characteristics related to quality with penalization in the HAC program.
  
  
  METHODS
  Data for hospitals participating in the FY2015 HAC Reduction Program were obtained from CMS' Hospital Compare and merged with the 2014 American Hospital Association Annual Survey and FY2015 Medicare Impact File. Logistic regression models were developed to examine the association between hospital characteristics and HAC program penalization. An 8-point hospital quality summary score was created using hospital characteristics related to volume, accreditations, and offering of advanced care services. The relationship between the hospital quality summary score and HAC program penalization was examined. Publicly reported process-of-care and outcome measures were examined from 4 clinical areas (surgery, acute myocardial infarction, heart failure, pneumonia), and their association with the hospital quality summary score was evaluated.
  
  
  METHODS
  Penalization in the HAC Reduction Program.
  
  
  METHODS
  Hospital characteristics associated with penalization.
  
  
  RESULTS
  Of the 3284 hospitals participating in the HAC program, 721 (22.0%) were penalized. Hospitals were more likely to be penalized if they were accredited by the Joint Commission (24.0% accredited, 14.4% not accredited; odds ratio [OR], 1.33; 95% CI, 1.04-1.70); they were major teaching hospitals (42.3%; OR, 1.58; 95% CI, 1.09-2.29) or very major teaching hospitals (62.2%; OR, 2.61; 95% CI, 1.55-4.39; vs nonteaching hospitals, 17.0%); they cared for more complex patient populations based on case mix index (quartile 4 vs quartile 1: 32.8% vs 12.1%; OR, 1.98; 95% CI, 1.44-2.71); or they were safety-net hospitals vs non-safety-net hospitals (28.3% vs 19.9%; OR, 1.36; 95% CI, 1.11-1.68). Hospitals with higher hospital quality summary scores had significantly better performance on 9 of 10 publicly reported process and outcomes measures compared with hospitals that had lower quality scores (all P ≤ .01 for trend). However, hospitals with the highest quality score of 8 were penalized significantly more frequently than hospitals with the lowest quality score of 0 (67.3% [37/55] vs 12.6% [53/422]; P < .001 for trend).
  
  
  CONCLUSIONS
  Among hospitals participating in the HAC Reduction Program, hospitals that were penalized more frequently had more quality accreditations, offered advanced services, were major teaching institutions, and had better performance on other process and outcome measures. These paradoxical findings suggest that the approach for assessing hospital penalties in the HAC Reduction Program merits reconsideration to ensure it is achieving the intended goals.
authors.affiliation: Surgical Outcomes and Quality Improvement Center (SOQIC), Department of Surgery, Feinberg School of Medicine, Northwestern University, Chicago, Illinois2Center for Healthcare Studies in the Institute for Public Health and Medicine, Feinberg School of Medi.
authors.forename: Ravi
authors.initials: R
authors.lastname: Rajaram
authors.affiliation: Surgical Outcomes and Quality Improvement Center (SOQIC), Department of Surgery, Feinberg School of Medicine, Northwestern University, Chicago, Illinois.
authors.forename: Jeanette W
authors.initials: JW
authors.lastname: Chung
authors.affiliation: Surgical Outcomes and Quality Improvement Center (SOQIC), Department of Surgery, Feinberg School of Medicine, Northwestern University, Chicago, Illinois3Department of Surgery, Massachusetts General Hospital, Boston.
authors.forename: Christine V
authors.initials: CV
authors.lastname: Kinnier
authors.affiliation: Center for Healthcare Studies in the Institute for Public Health and Medicine, Feinberg School of Medicine, Northwestern University, Chicago, Illinois4Division of Quality, Northwestern Memorial HealthCare, Chicago, Illinois.
authors.forename: Cynthia
authors.initials: C
authors.lastname: Barnard
authors.affiliation: Department of Surgery, Henry Ford Hospital, Detroit, Michigan.
authors.forename: Sanjay
authors.initials: S
authors.lastname: Mohanty
authors.affiliation: Surgical Outcomes and Quality Improvement Center (SOQIC), Department of Surgery, Feinberg School of Medicine, Northwestern University, Chicago, Illinois.
authors.forename: Emily S
authors.initials: ES
authors.lastname: Pavey
authors.affiliation: Center for Healthcare Studies in the Institute for Public Health and Medicine, Feinberg School of Medicine, Northwestern University, Chicago, Illinois.
authors.forename: Megan C
authors.initials: MC
authors.lastname: McHugh
authors.affiliation: Surgical Outcomes and Quality Improvement Center (SOQIC), Department of Surgery, Feinberg School of Medicine, Northwestern University, Chicago, Illinois2Center for Healthcare Studies in the Institute for Public Health and Medicine, Feinberg School of Medi.
authors.forename: Karl Y
authors.initials: KY
authors.lastname: Bilimoria
mesh_terms: D000573:American Hospital Association; D014487:Centers for Medicare and Medicaid Services, U.S.; D006761:Hospitals / Q000592:standards* / Q000706:statistics & numerical data; D006801:Humans; D007349:Insurance, Health, Reimbursement / Q000191:economics / Q000331:legislation & jurisprudence*; D037141:Mandatory Programs; D006278:Medicare / Q000706:statistics & numerical data; D015397:Program Evaluation; D019984:Quality Indicators, Health Care / Q000706:statistics & numerical data*; D012044:Regression Analysis; D014481:United States