Using clinical data to predict high-cost performance coding issues associated with pressure ulcers: a multilevel cohort model.
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.


Materials and 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).


Discussion
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.


Conclusion
Inappropriate coding of conditions leads to poor hospital performance measures and Medicare reimbursement penalties.
['Padula|William V|WV|', 'Gibbons|Robert D|RD|', 'Pronovost|Peter J|PJ|', 'Hedeker|Donald|D|', 'Mishra|Manish K|MK|', 'Makic|Mary Beth F|MB|', 'Bridges|John Fp|JF|', 'Wald|Heidi L|HL|', 'Valuck|Robert J|RJ|', 'Ginensky|Adam J|AJ|', 'Ursitti|Anthony|A|', 'Venable|Laura Ruth|LR|', 'Epstein|Ziv|Z|', 'Meltzer|David O|DO|']
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 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 D018570:Risk Assessment D012307:Risk Factors D013119:Spinal Cord Injuries D014481:United States D055815:Young Adult
pressure ulcer Medicare electronic health record spinal cord injury Braden Scale mixed-effects regression model predictive modeling