Dataset Information

Do illness rating systems predict discharge location, length of stay, and cost after total hip arthroplasty?

ABSTRACT: Background:As procedure rates and expenditures for total hip arthroplasty (THA) rise, hospitals are developing models to predict discharge location, a major determinant of total cost. The predictive value of existing illness rating systems such as the American Society for Anesthesiologists (ASA) Physical Classification System, Severity of Illness (SOI) scoring system, or Mallampati (MP) rating scale on discharge location remains unclear. This study explored the predictive role of ASA, SOI, and MP scores on discharge location, lengths of stay, and total costs for THA patients. Methods:A retrospective analysis of patients undergoing elective primary or revision THA was conducted at a single institution. Multivariable regressions were utilized to assess the significant predictive factors for lengths of stay, total costs, and discharge to skilled nursing facilities (SNFs), rehabilitation centers, and home. Controls included demographic factors, insurance coverage, and the type of procedure. Results:ASA scores ?3 are the only significant predictors of discharge to SNFs (odds ratio [OR] = 1.69, confidence interval [CI] = 1.04-2.74) and home (OR = 0.57, CI = 0.34-0.98). Medicaid coverage (OR = 2.61, CI = 1.37-4.96) and African-American race (OR = 2.60, CI = 1.59-4.25) were additional significant predictors of discharge to SNF. SOI scores are the only significant predictors of length of stay (? = 1.36 days, CI = 0.53-2.19) and total cost for an episode (? = $6,234, CI = $3577-$8891). MP scores possess limited predictive power over lengths of stay only. Conclusions:These findings suggest that although ASA classifications predict discharge location and SOI scores predict length of stay and total costs, other factors beyond illness rating systems remain stronger predictors of discharge for THA patients.

SUBMITTER: Rudasill SE

PROVIDER: S-EPMC5994639 | biostudies-literature | 2018 Jun

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Do illness rating systems predict discharge location, length of stay, and cost after total hip arthroplasty?

Rudasill Sarah E SE Dattilo Jonathan R JR Liu Jiabin J Nelson Charles L CL Kamath Atul F AF

Arthroplasty today 20180321 2

<h4>Background</h4>As procedure rates and expenditures for total hip arthroplasty (THA) rise, hospitals are developing models to predict discharge location, a major determinant of total cost. The predictive value of existing illness rating systems such as the American Society for Anesthesiologists (ASA) Physical Classification System, Severity of Illness (SOI) scoring system, or Mallampati (MP) rating scale on discharge location remains unclear. This study explored the predictive role of ASA, SO ...[more]

PMID: 29896555

Similar Datasets

Project description:BACKGROUND: The steady rise in demand for total hip arthroplasty constitutes a significant and increasing burden on health care resources. The biggest contributors to the total cost of hip replacement procedures other than the price of the implant are hospital stay and postoperative rehabilitation. Blood management is one of the most adjustable factors that can impact length of stay and cost-efficiency while improving patient safety. QUESTIONS/PURPOSES: The primary purpose of this retrospective study was to assess the potential impact of blood management interventions on length of hospital stay after primary unilateral total hip arthroplasty. This was achieved by first identifying which patient and surgical factors are associated with an increased risk of prolonged hospital stay. Subsequently, the significant factors were controlled for through a multivariate regression analysis to quantify the association between blood transfusions and increased hospital stay. METHODS: Retrospectively, the study included 2,104 primary total hip replacements. Eight hundred eighty-eight procedures were performed on males and 1,216 on females, with a mean age of 64 years at the time of the surgery (range 18-94 years) and BMI of 28.6 kg/m(2) (range 12-51.5 kg/m(2)). The correlation between each factor and length of stay was analyzed separately using univariate regression analysis. Those variables with p???0.05 in the univariate model were selected for inclusion in the multivariate logistic regressions. Multiple linear regression was used to analyze the effect of each significant factor and derive odds ratios with adjustment for the other variables. RESULTS: Multivariate Poisson regression revealed that increased length of stay was significantly correlated to patient age (p?=?0.05), the use of coumadin (p?=?0.02) or lovenox/heparin (p?=?0.007) as opposed to aspirin for anticoagulation, and allogeneic blood transfusion (p?<?0.0001). The data shows that allogeneic blood transfusion is associated with a longer hospital stay regardless of absolute drop in hemoglobin level postoperatively or at discharge or the number of units transfused (OR?=?1.18, 95% CI?=?1.09 to 1.28, p?<?0.001). CONCLUSION: Transfusion of allogeneic blood is independently associated with increased hospital stay after total hip arthroplasty. Blood management modalities that can significantly reduce transfusion risk could impact length of stay as well as the total cost of hip replacement procedures.

Dataset Information

Do illness rating systems predict discharge location, length of stay, and cost after total hip arthroplasty?

Publications

Do illness rating systems predict discharge location, length of stay, and cost after total hip arthroplasty?

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets