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Clinical Features - Original Research

30-Day readmission following outpatient rotator cuff repair: an analysis of 18,061 cases

, , , , &
Pages 466-470 | Received 16 Apr 2018, Accepted 17 Jul 2018, Published online: 27 Jul 2018
 

ABSTRACT

Objectives: The purpose of this study is to identify patient characteristics that increase risk for unplanned readmission within 30 days of an initial hospital stay after outpatient rotator cuff repair (RCR).

Methods: A retrospective cohort study was performed utilizing the National Surgical Quality Improvement Program (ACS NSQIP) datasets from 2012 to 2015. Patients were preliminarily included in the study based on the presence of a primary Common Procedural Terminology code for RCR (23410, 23412, 23420, and 29827). Only non-emergent, outpatient, and elective procedures performed on patients with American Society of Anesthesiologists (ASA) ≤4 were considered. The primary outcome variables were 30-day unplanned readmission after outpatient surgery. Secondary analyses were implemented to establish reason and timing of readmission.

Results: A total of 18,061 cases were reviewed, and 199 (1%) patients experienced 30-day unplanned readmission. Age ≥80 (OR = 2.13, p = 0.0276), COPD (OR = 1.75, p = 0.0354), hypertension requiring medication (OR = 1.67, p = 0.0027), dialysis (OR = 13.46, p < 0.0001) and an ASA classification of 3 (OR = 2.78, p = 0.0143) or ASA 4 (OR = 6.15, p = 0.0012) were identified as major prognosticators for readmission. Female sex was associated with lower odds of readmission (OR = 0.54, p = 0.0001). The most common complications associated with readmission were cardiovascular (29%), infection (19%), and respiratory (17%).

Conclusions: The rate of 30-day unplanned inpatient readmission following outpatient RCR using the NSQIP data was found to be 1%, with advanced age and preexisting medical comorbidities contributing to the highest odds of readmission. Cardiovascular, infectious, and respiratory complications contributed to the majority of readmissions. The ability to identify patients with these risk factors will be of utility in optimizing outcomes and cost-effectiveness of RCR.

Level of evidence: Level III

Declaration of interest

BD Owens declares Consulting for MTF/CONMED, Mitek. The authors have no other relevant affiliations or financial involvement with any organization or entity with a financial interest in or financial conflict with the subject matter or materials discussed in the manuscript. This includes employment, consultancies, honoraria, stock ownership or options, expert testimony, grants or patents received or pending, or royalties. Peer reviewers on this manuscript have no relevant financial relationships to disclose.

Additional information

Funding

This manuscript was not funded.

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