James T Bernatz1,2, Jonathan L Tueting3, Scott Hetzel4, Paul A Anderson3. 1. University of Wisconsin School of Medicine and Public Health, Madison, WI, USA. jbernatz@wisc.edu. 2. UW Medical Foundation Centennial Building, 1685 Highland Avenue, 6th Floor, Madison, WI, 53705-2281, USA. jbernatz@wisc.edu. 3. University of Wisconsin School of Medicine and Public Health, Madison, WI, USA. 4. Department of Biostatistics and Medical Informatics, University of Wisconsin-Madison, Madison, WI, USA.
Abstract
BACKGROUND: The Centers for Medicare & Medicaid Services (CMS) now include hip and knee replacements in the Hospital Readmission Reduction Program. The 30-day readmission rate is an important quality metric; however, the incidence has not yet been defined across the numerous orthopaedic subspecialties. Elucidating the readmission rate for each subspecialty may indicate that certain services are being disincentivized by the CMS reimbursement program. Furthermore, the "planned" and "unplanned" definitions of readmission have not been well examined to determine their clinical relevance and representation of safe patient care. Therefore, reducing the 30-day readmission rate has become a top priority in orthopaedic quality assurance. QUESTIONS/PURPOSES: (1) What are the 30-day readmission rates for the different orthopaedic subspecialties? (2) What are the risk factors associated with readmission within 30 days? (3) What are the causes of 30-day readmissions? (4) What is the interrater agreement among CMS, hospital, and clinician definitions of planned and unplanned readmissions? METHODS: We retrospectively examined one tertiary care academic hospital's quality improvement database and identified 4792 discharges from the department of orthopaedics during a continuous 24-month period. Discharges were divided and analyzed according to the subspecialty of orthopaedic care. Demographics and comorbidities were extracted from the database and subjected to univariate and multivariate analysis to determine risk factors for 30-day readmission. Further chart review was conducted on all cases of 30-day readmission to identify causes. The authors' determination of planned versus unplanned was compared with two other definitions (hospital and CMS) and analyzed for agreement by using Fleiss' kappa for multiple rater. RESULTS: The all-cause 30-day readmission rate was 4% (95% confidence interval [CI], 3.8-4.8). The unplanned readmission rate was 3% (95% CI, 2.8-3.8). After controlling for relevant confounding variables, we found that length of stay (odds ratio [OR], 1.10 per day; p < 0.001), American Society of Anesthesiologists score (OR, 1.89 per point; p < 0.001), and care under trauma (OR, 2.55; p < 0.001) or "other" (OR, 1.65; p = 0.009) as compared with joint subspecialty were associated with increased risk of readmission. Of the 160 unplanned readmissions, 93 (58%) were surgical and 67 (42%) were medical. The most common surgical cause was surgical site infection (38% of surgical readmissions) and the most common medical causes were gastrointestinal bleed, pulmonary embolus, and unrelated trauma (each 9% of medical readmissions). There was poor agreement (Fleiss' kappa = 0.120) among the three definitions of planned readmission. CONCLUSIONS: There are important differences in the risk of readmission by subspecialty across orthopaedics and the CMS-driven disincentives may be applied unequally across these subspecialties. This could result in hospitals deemphasizing those service lines and could potentially limit access to care for the patients most in need. Avenues of readmission reduction should be further studied including telephone followup programs and outpatient management of threatened wounds. Clinical, hospital, and CMS definitions of planned readmission have poor agreement, suggesting that hospitals are being unnecessarily penalized. The CMS should develop a more clinically relevant definition of 30-day readmission to more accurately evaluate the rate of readmissions. LEVEL OF EVIDENCE: Level III, therapeutic study.
BACKGROUND: The Centers for Medicare & Medicaid Services (CMS) now include hip and knee replacements in the Hospital Readmission Reduction Program. The 30-day readmission rate is an important quality metric; however, the incidence has not yet been defined across the numerous orthopaedic subspecialties. Elucidating the readmission rate for each subspecialty may indicate that certain services are being disincentivized by the CMS reimbursement program. Furthermore, the "planned" and "unplanned" definitions of readmission have not been well examined to determine their clinical relevance and representation of safe patient care. Therefore, reducing the 30-day readmission rate has become a top priority in orthopaedic quality assurance. QUESTIONS/PURPOSES: (1) What are the 30-day readmission rates for the different orthopaedic subspecialties? (2) What are the risk factors associated with readmission within 30 days? (3) What are the causes of 30-day readmissions? (4) What is the interrater agreement among CMS, hospital, and clinician definitions of planned and unplanned readmissions? METHODS: We retrospectively examined one tertiary care academic hospital's quality improvement database and identified 4792 discharges from the department of orthopaedics during a continuous 24-month period. Discharges were divided and analyzed according to the subspecialty of orthopaedic care. Demographics and comorbidities were extracted from the database and subjected to univariate and multivariate analysis to determine risk factors for 30-day readmission. Further chart review was conducted on all cases of 30-day readmission to identify causes. The authors' determination of planned versus unplanned was compared with two other definitions (hospital and CMS) and analyzed for agreement by using Fleiss' kappa for multiple rater. RESULTS: The all-cause 30-day readmission rate was 4% (95% confidence interval [CI], 3.8-4.8). The unplanned readmission rate was 3% (95% CI, 2.8-3.8). After controlling for relevant confounding variables, we found that length of stay (odds ratio [OR], 1.10 per day; p < 0.001), American Society of Anesthesiologists score (OR, 1.89 per point; p < 0.001), and care under trauma (OR, 2.55; p < 0.001) or "other" (OR, 1.65; p = 0.009) as compared with joint subspecialty were associated with increased risk of readmission. Of the 160 unplanned readmissions, 93 (58%) were surgical and 67 (42%) were medical. The most common surgical cause was surgical site infection (38% of surgical readmissions) and the most common medical causes were gastrointestinal bleed, pulmonary embolus, and unrelated trauma (each 9% of medical readmissions). There was poor agreement (Fleiss' kappa = 0.120) among the three definitions of planned readmission. CONCLUSIONS: There are important differences in the risk of readmission by subspecialty across orthopaedics and the CMS-driven disincentives may be applied unequally across these subspecialties. This could result in hospitals deemphasizing those service lines and could potentially limit access to care for the patients most in need. Avenues of readmission reduction should be further studied including telephone followup programs and outpatient management of threatened wounds. Clinical, hospital, and CMS definitions of planned readmission have poor agreement, suggesting that hospitals are being unnecessarily penalized. The CMS should develop a more clinically relevant definition of 30-day readmission to more accurately evaluate the rate of readmissions. LEVEL OF EVIDENCE: Level III, therapeutic study.
Authors: Rutledge Carter Clement; Peter B Derman; Danielle S Graham; Rebecca M Speck; David N Flynn; Lawrence Scott Levin; Lee A Fleisher Journal: J Arthroplasty Date: 2013-08-13 Impact factor: 4.757
Authors: Francis Lovecchio; Wellington K Hsu; Timothy R Smith; George Cybulski; Bobby Kim; John Y S Kim Journal: Spine (Phila Pa 1976) Date: 2014-01-15 Impact factor: 3.468
Authors: Richard A McCormack; Tracey Hunter; Nicholas Ramos; Ryan Michels; Lorraine Hutzler; Joseph A Bosco Journal: Spine (Phila Pa 1976) Date: 2012-06-15 Impact factor: 3.468
Authors: Elizabeth M Hechenbleikner; Martin A Makary; Daniel V Samarov; Jennifer L Bennett; Susan L Gearhart; Jonathan E Efron; Elizabeth C Wick Journal: J Am Coll Surg Date: 2013-04-11 Impact factor: 6.113
Authors: William W Schairer; Alexandra Carrer; Vedat Deviren; Serena S Hu; Steven Takemoto; Praveen Mummaneni; Dean Chou; Christopher Ames; Shane Burch; Bobby Tay; Aenor Sawyer; Sigurd H Berven Journal: Spine (Phila Pa 1976) Date: 2013-09-01 Impact factor: 3.468
Authors: Beejal Y Amin; Tsung-Hsi Tu; William W Schairer; Lumine Na; Steven Takemoto; Sigurd Berven; Vedat Deviren; Christopher Ames; Dean Chou; Praveen V Mummaneni Journal: J Neurosurg Spine Date: 2012-11-27
Authors: Elizabeth A Dailey; Amy Cizik; Jesse Kasten; Jens R Chapman; Michael J Lee Journal: J Bone Joint Surg Am Date: 2013-06-05 Impact factor: 5.284
Authors: Daniel R Evans; Alexander L Lazarides; Mark M Cullen; Julia D Visgauss; Jason A Somarelli; Dan G Blazer; Brian E Brigman; William C Eward Journal: Ann Surg Oncol Date: 2021-05-20 Impact factor: 5.344
Authors: Iahn Cajigas; Anil K Mahavadi; Ashish H Shah; Veronica Borowy; Nathalie Abitbol; Michael E Ivan; Ricardo J Komotar; Richard H Epstein Journal: J Neurooncol Date: 2019-10-22 Impact factor: 4.130
Authors: Elizabeth Y Killien; Roel L N Huijsmans; Monica S Vavilala; Anneliese M Schleyer; Ellen F Robinson; Rebecca G Maine; Frederick P Rivara Journal: J Surg Res Date: 2021-04-10 Impact factor: 2.417
Authors: Felix Rohrer; David Haddenbruch; Hubert Noetzli; Brigitta Gahl; Andreas Limacher; Tanja Hermann; Jan Bruegger Journal: Perioper Med (Lond) Date: 2021-12-15
Authors: Connor R Crutchfield; Jack R Zhong; Nathan J Lee; Thomas A Fortney; Christopher S Ahmad; T Sean Lynch Journal: Arthrosc Sports Med Rehabil Date: 2022-06-13