Gunn, Laura
Rios, Nancy
Oldiges, Paige
Lizano, Marcela
Martin, John
Korvink, Michael
Doucet Wadford, Danielle S.
Quick, David L.

Faculty

MDPI

1 online resource

2022

Journal article

articles

text

Variations in procedure coding intensity, defined as excess coding of procedures versus industry (instead of clinical) standards, can result in differentials in quality of care for patients and have additional implications for facilities and payors. The literature regarding coding intensity of procedures is limited, with a need for risk-adjusted methods that help identify over- and under-coding using commonly available data, such as administrative claims. Risk-adjusted metrics are needed for quality control and enhancement. We propose a two-step approach to risk adjustment, using a zero-inflated Poisson model, applied to a hip-knee arthroplasty cohort discharged during 2019 (n = 313,477) for patient-level risk adjustment, and a potential additional layer for adjustment based on facility-level characteristics, when desired. A 21.41% reduction in root-mean-square error was achieved upon risk adjustment for patient-level factors alone. Furthermore, we identified facilities that over- and under-code versus industry coding expectations, adjusting for both patient-level and facility-level factors. Excess coding intensity was found to vary across multiple levels: (1) geographically across U.S. Census regional divisions; (2) temporally with marked seasonal components; (3) by facility, with some facilities largely departing from industry standards, even after adjusting for both patient- and facility-level characteristics. Our proposed method is simple to implement, generalizable, it can be used across cohorts with different sets of information available, and it is not limited by the accessibility and sparsity of electronic health records. By identifying potential over- and under-coding of procedures, quality control personnel can explore and assess internal needs for enhancements in their health delivery services and monitor subsequent quality improvements.

Arthroplasty
Diagnosis
Medical care

Healthcare

English

doi:10.3390/healthcare10081368

https://www.mdpi.com/2227-9032/10/8/1368

http://hdl.handle.net/20.500.13093/work:689

This item may be protected by copyright and other related rights. Atkins Library provides access to this item for educational and research purposes only; other uses require the permission of the copyright holder.