title: Using clinical data to predict high-cost performance coding issues associated with pressure ulcers: a multilevel cohort model.
abstract: OBJECTIVE
  Hospital-acquired pressure ulcers (HAPUs) have a mortality rate of 11.6%, are costly to treat, and result in Medicare reimbursement penalties. Medicare codes HAPUs according to Agency for Healthcare Research and Quality Patient-Safety Indicator 3 (PSI-03), but they are sometimes inappropriately coded. The objective is to use electronic health records to predict pressure ulcers and to identify coding issues leading to penalties.
  
  
  METHODS
  We evaluated all hospitalized patient electronic medical records at an academic medical center data repository between 2011 and 2014. These data contained patient encounter level demographic variables, diagnoses, prescription drugs, and provider orders. HAPUs were defined by PSI-03: stages III, IV, or unstageable pressure ulcers not present on admission as a secondary diagnosis, excluding cases of paralysis. Random forests reduced data dimensionality. Multilevel logistic regression of patient encounters evaluated associations between covariates and HAPU incidence.
  
  
  RESULTS
  The approach produced a sample population of 21 153 patients with 1549 PSI-03 cases. The greatest odds ratio (OR) of HAPU incidence was among patients diagnosed with spinal cord injury (ICD-9 907.2: OR = 14.3; P  < .001), and 71% of spinal cord injuries were not properly coded for paralysis, leading to a PSI-03 flag. Other high ORs included bed confinement (ICD-9 V49.84: OR = 3.1, P  < .001) and provider-ordered pre-albumin lab (OR = 2.5, P  < .001).
  
  
  CONCLUSIONS
  This analysis identifies spinal cord injuries as high risk for HAPUs and as being often inappropriately coded without paralysis, leading to PSI-03 flags. The resulting statistical model can be tested to predict HAPUs during hospitalization.
  
  
  CONCLUSIONS
  Inappropriate coding of conditions leads to poor hospital performance measures and Medicare reimbursement penalties.
authors.affiliation: Department of Health Policy & Management, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA.
authors.forename: William V
authors.initials: WV
authors.lastname: Padula
authors.affiliation: Department of Medicine, University of Chicago, Chicago, IL, USA.|Department of Public Health Sciences, University of Chicago, Chicago, IL, USA.
authors.forename: Robert D
authors.initials: RD
authors.lastname: Gibbons
authors.affiliation: Department of Anesthesiology, Johns Hopkins School of Medicine, Baltimore, MD, USA.|Department of Critical Care and Surgery, Johns Hopkins School of Medicine, Baltimore, MD, USA.
authors.forename: Peter J
authors.initials: PJ
authors.lastname: Pronovost
authors.affiliation: Department of Public Health Sciences, University of Chicago, Chicago, IL, USA.
authors.forename: Donald
authors.initials: D
authors.lastname: Hedeker
authors.affiliation: Department of Community & Family Medicine, The Geisel School of Medicine at Dartmouth, Hanover, NH, USA.
authors.forename: Manish K
authors.initials: MK
authors.lastname: Mishra
authors.affiliation: College of Nursing, University of Colorado, Aurora, CO, USA.
authors.forename: Mary Beth F
authors.initials: MB
authors.lastname: Makic
authors.affiliation: Department of Health Policy & Management, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA.
authors.forename: John Fp
authors.initials: JF
authors.lastname: Bridges
authors.affiliation: School of Medicine, University of Colorado, Aurora, CO, USA.
authors.forename: Heidi L
authors.initials: HL
authors.lastname: Wald
authors.affiliation: Department of Clinical Pharmacy, Skaggs School of Pharmacy and Pharmaceutical Sciences, University of Colorado, Aurora, CO, USA.
authors.forename: Robert J
authors.initials: RJ
authors.lastname: Valuck
authors.affiliation: The Graham School, University of Chicago, Chicago, IL, USA.
authors.forename: Adam J
authors.initials: AJ
authors.lastname: Ginensky
authors.affiliation: The Graham School, University of Chicago, Chicago, IL, USA.
authors.forename: Anthony
authors.initials: A
authors.lastname: Ursitti
authors.affiliation: The Graham School, University of Chicago, Chicago, IL, USA.
authors.forename: Laura Ruth
authors.initials: LR
authors.lastname: Venable
authors.affiliation: Pomona College, Claremont, CA, USA.
authors.forename: Ziv
authors.initials: Z
authors.lastname: Epstein
authors.affiliation: Section of Hospital Medicine, University of Chicago, Chicago, IL, USA.
authors.forename: David O
authors.initials: DO
authors.lastname: Meltzer
mesh_terms: D000046:Academic Medical Centers; D000293:Adolescent; D000328:Adult; D000368:Aged; D000369:Aged, 80 and over; D059019:Clinical Coding; D015331:Cohort Studies; D057286:Electronic Health Records; D006760:Hospitalization; D006801:Humans; D007049:Iatrogenic Disease / Q000453:epidemiology; D015994:Incidence; D038801:International Classification of Diseases; D016015:Logistic Models; D006278:Medicare; D008875:Middle Aged; D010043:Outcome and Process Assessment, Health Care; D003668:Pressure Ulcer / Q000145:classification* / Q000453:epidemiology / Q000209:etiology; D018570:Risk Assessment / Q000379:methods; D012307:Risk Factors; D013119:Spinal Cord Injuries / Q000145:classification* / Q000150:complications; D014481:United States; D055815:Young Adult
keywords: Braden Scale; Medicare; electronic health record; mixed-effects regression model; predictive modeling; pressure ulcer; spinal cord injury