Literature DB >> 27539199

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

William V Padula1, Robert D Gibbons2,3, Peter J Pronovost4,5, Donald Hedeker3, Manish K Mishra6, Mary Beth F Makic7, John Fp Bridges1, Heidi L Wald8, Robert J Valuck9, Adam J Ginensky10, Anthony Ursitti10, Laura Ruth Venable10, Ziv Epstein11, David O Meltzer12.   

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.
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.
© The Author 2016. Published by Oxford University Press on behalf of the American Medical Informatics Association. All rights reserved. For Permissions, please email: journals.permissions@oup.com

Entities:  

Keywords:  Braden Scale; Medicare; electronic health record; mixed-effects regression model; predictive modeling; pressure ulcer; spinal cord injury

Mesh:

Year:  2017        PMID: 27539199      PMCID: PMC7651933          DOI: 10.1093/jamia/ocw118

Source DB:  PubMed          Journal:  J Am Med Inform Assoc        ISSN: 1067-5027            Impact factor:   4.497


  30 in total

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Authors:  William V Padula; Mary Beth F Makic; Manish K Mishra; Jonathan D Campbell; Kavita V Nair; Heidi L Wald; Robert J Valuck
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Authors:  William V Padula; Manish K Mishra; Mary Beth F Makic; Patrick W Sullivan
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6.  Friction and shear highly associated with pressure ulcers of residents in long-term care - Classification Tree Analysis (CHAID) of Braden items.

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7.  Risk assessment and prevention of pressure ulcers: a clinical practice guideline from the American College of Physicians.

Authors:  Amir Qaseem; Tanveer P Mir; Melissa Starkey; Thomas D Denberg
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8.  Hospital-acquired pressure ulcers: results from the national Medicare Patient Safety Monitoring System study.

Authors:  Courtney H Lyder; Yun Wang; Mark Metersky; Maureen Curry; Rebecca Kliman; Nancy R Verzier; David R Hunt
Journal:  J Am Geriatr Soc       Date:  2012-09       Impact factor: 5.562

9.  Factors associated with pressure ulcer risk in spinal cord injury rehabilitation.

Authors:  Gerben DeJong; Ching-Hui J Hsieh; Patrick Brown; Randall J Smout; Susan D Horn; Pamela Ballard; Tara Bouchard
Journal:  Am J Phys Med Rehabil       Date:  2014-11       Impact factor: 2.159

10.  CAPriCORN: Chicago Area Patient-Centered Outcomes Research Network.

Authors:  Abel N Kho; Denise M Hynes; Satyender Goel; Anthony E Solomonides; Ron Price; Bala Hota; Shannon A Sims; Neil Bahroos; Francisco Angulo; William E Trick; Elizabeth Tarlov; Fred D Rachman; Andrew Hamilton; Erin O Kaleba; Sameer Badlani; Samuel L Volchenboum; Jonathan C Silverstein; Jonathan N Tobin; Michael A Schwartz; David Levine; John B Wong; Richard H Kennedy; Jerry A Krishnan; David O Meltzer; John M Collins; Terry Mazany
Journal:  J Am Med Inform Assoc       Date:  2014-05-12       Impact factor: 4.497

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  4 in total

1.  Patient-specific factors associated with pressure injuries revealed by electronic health record analyses.

Authors:  Megan W Miller; Rebecca T Emeny; Jennifer A Snide; Gary L Freed
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2.  Pressure injury identification, measurement, coding, and reporting: Key challenges and opportunities.

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Review 3.  Recent technological advances in the management of chronic wounds: A literature review.

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Journal:  BMJ Qual Saf       Date:  2018-08-10       Impact factor: 7.035

  4 in total

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