R28 Assessing Risk-Factors for Hospital-Acquired Pressure Injuries and Impact to Cost and Outcomes in U.S. Hospitals

Jill Dreyfus, PhD, MPH1, Julie Gayle, MPH1, Paul Trueman2, Gary Delhougne, JD, MHA3 and Aamir Siddiqui, MD4, (1)Premier, Inc., Charlotte, NC, (2)Smith & Nephew, Inc., Hull, East Yorkshire, United Kingdom, (3)Smith & Nephew, Inc, Fort Worth, TX, (4)Henry Ford Hospital, Detroit, MI
Background: Hospital-acquired pressure injuries (HAPI) are a societal burden with approximately 2.5 million pressure ulcers treated annually in the U.S., amounting to $11 billion in healthcare costs. The emergence of large-scale population level data from electronic medical records and claims data, offers the potential to generate further insight into risk factors through predictive modeling. Increasingly, the availability of such ‘big-data’ allow decision makers to move towards more evidence-based solutions to health system problems such as HAPI.

Methods: This study of inpatients from the 2009-2014 U.S. Premier Healthcare Database identified HAPI using ICD-9 diagnosis codes 707.xx. Comparisons of outcomes were made after 1:3 propensity score matching of HAPI to non-HAPI patients. Conditional logistic regression models compared odds for inpatient readmissions and generalized estimating equations models compared mean index visit LOS and costs.

Results: The study identified 16,967,687 adult inpatients (47,365 HAPI) during the study period. The matched sample included 110,808 patients (27,702 HAPI). Strong risk factors for HAPI included prior PU (OR=12.52, 95% CI 11.93-13.15), prior diabetic foot ulcer (OR=3.43, 95% CI 3.20-3.68), and malnutrition (OR=3.11, 95% CI 3.02-3.20). Adjusted mean LOS was 3.7 days longer (p<.0001), and total hospitalization cost $8,014 higher (p<.0001) for HAPI vs. non-HAPI patients. HAPI patients had greater odds of readmissions through 180-days follow-up (OR=1.60, 95% CI 1.55-1.65).

Conclusions: This study identified novel risk factors and highlighted the burden of HAPIs. In a dynamic and evolving healthcare system where the availability and usefulness of data advances daily, providers and policy-makers have an opportunity to leverage their own data on risk factors for HAPIs and the economic burden they place on society.