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Which patient factors are most strongly associated with 30-day readmission after primary total hip arthroplasty, and is there a difference between predictors of all-cause, surgical, and return-to-theater readmissions?
In this study of 514 455 patients from the UK National Health Service, we found that key predictors of each type of total hip arthroplasty readmission were different.
All-cause readmission is the only metric in widespread use but overlooks important information that enables readmission risk to be understood; focus on surgical and return-to-theater readmission may facilitate risk reduction and cost savings.
Thirty-day readmission to hospital after total hip arthroplasty (THA) has significant direct costs and is used as a marker of hospital performance. All-cause readmission is the only metric in current use, and risk factors for surgical readmission and those resulting in return to theater (RTT) are poorly understood.
To determine whether patient-related predictors of all-cause, surgical, and RTT readmission after THA differ and which predictors are most significant.
Design, Setting, and Participants
Analysis of all primary THAs recorded in the National Health Service (NHS) Hospital Episode Statistics database from 2006 to 2015. The effect of patient-related factors on 30-day readmission risk was evaluated by multilevel logistic regression analysis. The analysis comprised all acute NHS hospitals in England and all patients receiving primary THA.
Main Outcomes and Measures
Thirty-day readmission rate for all-cause, surgical (defined using International Statistical Classification of Diseases and Related Health Problems, Tenth Revision primary admission diagnoses), and readmissions resulting in RTT.
Across all hospitals, 514 455 procedures were recorded. Seventy-nine percent of patients were older than 60 years, 40.3% were men, and 59.7% were women. There were 30 489 all-cause readmissions (5.9%), 16 499 surgical readmissions (3.2%), and 4286 RTT readmissions (0.8%); 54.1% of readmissions were for surgical causes. Comorbidities with the highest odds ratios (ORs) of RTT included those likely to affect patient behavior: drug abuse (OR, 2.22; 95% CI, 1.34-3.67; P = .002), psychoses (OR, 1.83; 95% CI, 1.16-2.87; P = .009), dementia (OR, 1.57; 95% CI, 1.11-2.22; P = .01), and depression (OR, 1.52; 95% CI, 1.31-1.76; P < .001). Obesity had a strong independent association with RTT (OR, 1.46; 95% CI, 4.45-6.43; P < .001), with one of the highest population attributable fractions of the comorbidities (3.4%). Return to theater in the index episode was associated with a significantly increased risk of RTT readmission (OR, 5.35; 95% CI, 4.45-6.43; P < .001). Emergency readmission to the hospital in the preceding 12 months increased the risk of readmission significantly, with the association being most pronounced for all-cause readmission (for >2 emergency readmissions, OR, 2.33; 95% CI, 2.11-2.57; P < .001). Hip resurfacing was associated with a lower risk of RTT when compared with cemented implants (OR, 0.69; 95% CI, 0.54-0.88; P = .002) but for other types of readmission, implant type had no significant association with readmission risk. Increasing age and length of stay were strongly associated with all-cause readmission.
Conclusions and Relevance
Many patient-related risk factors for surgical and RTT readmission differ from those for all-cause readmission despite the latter being the only measure in widespread use. Clinicians and policy makers should consider these alternative readmission metrics in strategies for risk reduction and cost savings.
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Corresponding Author: Adam M. Ali, BMBCh, MA(Cantab), MRCS(Eng); St Mary’s Hospital, Praed St, London W2 1NY, United Kingdom (firstname.lastname@example.org).
Accepted for Publication: July 22, 2017.
Correction: This article was corrected on November 15, 2017, to correct errors in the Introduction, Methods, and Discussion sections.
Published Online: October 4, 2017. doi:10.1001/jamasurg.2017.3949
Author Contributions: Dr Bottle had full access to all the data in the study and takes responsibility for the integrity of the data and the accuracy of the data analysis.
Concept and design: Ali, Loeffler, Bottle.
Acquisition, analysis, or interpretation of data: Ali, Aylin, Bottle.
Drafting of the manuscript: Ali, Aylin, Bottle.
Critical revision of the manuscript for important intellectual content: All authors.
Statistical analysis: Ali, Bottle.
Obtained funding: Aylin, Bottle.
Administrative, technical, or material support: Aylin.
Conflict of Interest Disclosures: None reported.
Funding/Support: The Dr Foster Unit at Imperial College London is partially funded by a grant from Dr Foster Intelligence, an independent healthcare information company. Drs Aylin and and Bottle declare that they are partially funded by this grant. The Dr Foster Unit at Imperial is affiliated with the National Institute of Health Research Imperial Patient Safety Translational Research Centre. The National Institute of Health Research Imperial Patient Safety Translational Centre is a partnership between the Imperial College Healthcare National Health Services Trust and Imperial College London.
Role of the Funder/Sponsor: The funding organizations were not involved in the design and conduct of the study; collection, management, analysis, and interpretation of the data; preparation, review, or approval of the manuscript; or decision to submit the manuscript for publication.
Disclaimer: The views expressed in this publication are those of the authors and not necessarily those of the UK National Health Service, the National Institute of Health Research, or the Department of Health.
Additional Contributions: We thank Rukhsana Kamal, MBBS, Chelsea and Westminster Hospital NHS Foundation Trust Clinical Coding Manager, for her assistance with clinical coding. No financial compensation was associated with this.
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