Assessing the Impact of Hospital Characteristics on Outcomes of Outpatient Cardiac Procedures: An Analysis of the HCUP-NASS 2019 Database
Author(s)
Reeves C1, Mallow P2, Topmiller M2
1Xavier University, Windsor, ON, Canada, 2Xavier University, Cincinnati, OH, USA
Presentation Documents
OBJECTIVES: This research sought to evaluate the difference in adverse events in patients undergoing outpatient cardiac procedures based on hospital size after controlling for other hospital characteristics.
METHODS: Claims data from the HCUP-US Nationwide Ambulatory Surgery Sample (NASS) database for 2019 informed this retrospective analysis. Small/medium hospitals had 299-beds or less. Cardiac procedures were defined using the Clinical Classifications Software (CCS) designations 43, 48, and 49. Two statistical approaches were applied to understand the relationship between hospital size and adverse events: 1) multivariable logistic regression and 2) propensity score match (PSM) with regression. The odds of an adverse event following an outpatient cardiovascular procedure was calculated with each approach.
RESULTS: A total of 204,685 patients from 1,653 hospitals who had undergone a cardiac procedure. Small and medium hospitals constituted 66% (1084) of the hospitals and 33% (67,546) of the patients. There were statistically significant differences, p value <0.001, between small/medium and large hospitals for the following characteristics: US Census region of the hospital, urban or rural status, teaching status, public or private (not-for-profit or investor-owned). Odds ratios for small and medium hospitals from multivariable logistic regression before and after PSM were similar and associated with more adverse events after controlling for hospital characteristics and procedure type (1.79, 95% CI 1.55-2.07, p-value=<0.001 vs 1.84, 95% CI 1.59-2.12, p-value=<0.001).
CONCLUSIONS: This study demonstrated that an adverse event after an outpatient cardiac procedure is more likely to occur at small and medium facilities versus large facilities. Further studies are needed with more clinical information to assess whether this increase in risk is explainable due to some factor that is absent in an administrative claims database.
Conference/Value in Health Info
Value in Health, Volume 25, Issue 12S (December 2022)
Code
CO117
Topic
Clinical Outcomes, Real World Data & Information Systems
Topic Subcategory
Clinical Outcomes Assessment, Health & Insurance Records Systems
Disease
STA: Surgery