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Using clinical data to predict high-cost performance coding issues associated with pressure ulcers: a multilevel
William V Padula1, Robert D Gibbons2,3, Peter J Pronovost4,5
1Department of Health Policy & Management, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA.
Insights
Hospital-acquired pressure ulcers (HAPUs) are a significant concern. Inaccurate coding, particularly for spinal cord injuries, leads to penalties and affects patient care quality.
Area of Science:
- Healthcare Informatics
- Patient Safety
- Medical Coding Accuracy
Background:
- Hospital-acquired pressure ulcers (HAPUs) are associated with high mortality rates (11.6%), significant treatment costs, and Medicare reimbursement penalties.
- Accurate coding of HAPUs, as defined by Agency for Healthcare Research and Quality Patient-Safety Indicator 3 (PSI-03), is crucial for hospital performance metrics.
Purpose of the Study:
- To leverage electronic health records (EHRs) for predicting pressure ulcer development in hospitalized patients.
- To identify specific coding inaccuracies that contribute to inappropriate PSI-03 flags and potential Medicare penalties.
Main Methods:
- Analysis of EHR data from an academic medical center (2011-2014), including demographics, diagnoses, medications, and provider orders.
- Utilized random forests for data dimensionality reduction and multilevel logistic regression to assess HAPU incidence predictors.
- Defined HAPUs based on PSI-03 criteria, excluding cases present on admission or related to paralysis.
Main Results:
- Identified spinal cord injury (ICD-9 907.2) as a major risk factor for HAPUs (OR = 14.3), with 71% of these cases inappropriately coded without paralysis, triggering PSI-03 flags.
- Other significant risk factors included bed confinement (ICD-9 V49.84, OR = 3.1) and provider-ordered pre-albumin lab tests (OR = 2.5).
- The study analyzed 21,153 patients, identifying 1549 PSI-03 cases.
Conclusions:
- Spinal cord injuries represent a high-risk group for HAPUs and are frequently miscoded, leading to erroneous PSI-03 designations.
- The developed statistical model shows potential for predicting HAPUs during hospitalization.
- Inaccurate medical coding practices negatively impact hospital performance evaluations and financial reimbursements.
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.
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