Does state malpractice environment affect outcomes following spinal fusions? A robust statistical and machine learning analysis of 549,775 discharges following spinal fusion surgery in the United States release_ofvubynfwrazjnesbhzuhionsm

by Andrew K. Chan, Michele Santacatterina, Brenton Pennicooke, Shane Shahrestani, Alexander M. Ballatori, Katie O. Orrico, John F. Burke, Geoffrey T. Manley, Phiroz E. Tarapore, Michael C. Huang, Sanjay S. Dhall, Dean Chou (+2 others)

Published in Neurosurgical Focus by Journal of Neurosurgery Publishing Group (JNSPG).

Volume 49E18 (2020)

Abstract

<jats:sec><jats:title>OBJECTIVE</jats:title>Spine surgery is especially susceptible to malpractice claims. Critics of the US medical liability system argue that it drives up costs, whereas proponents argue it deters negligence. Here, the authors study the relationship between malpractice claim density and outcomes.</jats:sec><jats:sec><jats:title>METHODS</jats:title>The following methods were used: 1) the National Practitioner Data Bank was used to determine the number of malpractice claims per 100 physicians, by state, between 2005 and 2010; 2) the Nationwide Inpatient Sample was queried for spinal fusion patients; and 3) the Area Resource File was queried to determine the density of physicians, by state. States were categorized into 4 quartiles regarding the frequency of malpractice claims per 100 physicians. To evaluate the association between malpractice claims and death, discharge disposition, length of stay (LOS), and total costs, an inverse-probability-weighted regression-adjustment estimator was used. The authors controlled for patient and hospital characteristics. Covariates were used to train machine learning models to predict death, discharge disposition not to home, LOS, and total costs.</jats:sec><jats:sec><jats:title>RESULTS</jats:title>Overall, 549,775 discharges following spinal fusions were identified, with 495,640 yielding state-level information about medical malpractice claim frequency per 100 physicians. Of these, 124,425 (25.1%), 132,613 (26.8%), 130,929 (26.4%), and 107,673 (21.7%) were from the lowest, second-lowest, second-highest, and highest quartile states, respectively, for malpractice claims per 100 physicians. Compared to the states with the fewest claims (lowest quartile), surgeries in states with the most claims (highest quartile) showed a statistically significantly higher odds of a nonhome discharge (OR 1.169, 95% CI 1.139–1.200), longer LOS (mean difference 0.304, 95% CI 0.256–0.352), and higher total charges (mean difference [log scale] 0.288, 95% CI 0.281–0.295) with no significant associations for mortality. For the machine learning models—which included medical malpractice claim density as a covariate—the areas under the curve for death and discharge disposition were 0.94 and 0.87, and the R<jats:sup>2</jats:sup> values for LOS and total charge were 0.55 and 0.60, respectively.</jats:sec><jats:sec><jats:title>CONCLUSIONS</jats:title>Spinal fusion procedures from states with a higher frequency of malpractice claims were associated with an increased odds of nonhome discharge, longer LOS, and higher total charges. This suggests that medicolegal climate may potentially alter practice patterns for a given spine surgeon and may have important implications for medical liability reform. Machine learning models that included medical malpractice claim density as a feature were satisfactory in prediction and may be helpful for patients, surgeons, hospitals, and payers.</jats:sec>
In application/xml+jats format

Archived Files and Locations

application/pdf  2.0 MB
file_7ad246y7tfg2zaznvxdwfsqpqu
web.archive.org (webarchive)
thejns.org (publisher)
Read Archived PDF
Archived
Type  article-journal
Stage   published
Year   2020
Container Metadata
Open Access Publication
Not in DOAJ
In ISSN ROAD
In Keepers Registery
ISSN-L:  1092-0684
Work Entity
access all versions, variants, and formats of this works (eg, pre-prints)
Catalog Record
Revision: 487e3ce4-259b-4098-ac09-be0df7ae1007
API URL: JSON