Background Context: Whereas the costs of primary surgery, revisions, and selected complications for adult spinal deformity (ASD) have been individually reported in the literature, the total costs over several years after surgery have not been assessed. The determinants of such costs are also not well understood in the literature.
Purpose: This study analyzes the total hospital costs and operating room (OR) costs of ASD surgery through extended follow-up.
Study Design/setting: Single-center retrospective analysis of consecutive surgical patients.
Patient Sample: Four hundred eighty-four consecutive patients undergoing surgical treatment for ASD from January 2005 through January 2011 with minimum three levels fused.
Outcome Measures: Costs were collected from hospital administrative data on the total hospital costs incurred for the operation and any related readmissions, expressed in 2010 dollars and discounted at 3.5% per year. Detailed data on OR costs, including implants and biologics, were also collected.
Methods: We performed a series of paired t tests and Wilcoxon signed-rank tests for differences in total hospital costs over different follow-up periods. The goal of these tests was to identify a time period over which average costs plateau and remain relatively constant over time. Generalized linear model regression was used to estimate the effect of patient and surgical factors on hospital inpatient costs, with different models estimated for different follow-up periods. A similar regression analysis was performed separately for OR costs and all other hospital costs.
Results: Patients were predominantly women (n=415 or 86%) with an average age of 48 (18-82) years and an average follow-up of 4.8 (2-8) years. Total hospital costs averaged $120,394, with primary surgery averaging $103,143 and total readmission costs averaging $67,262 per patient with a readmission (n=130 or 27% of all patients). Operating room costs averaged $70,514 per patient, constituting the majority (59%) of total hospital costs. Average total hospital costs across all patients significantly increased (p<.01) after primary surgery, from $111,807 at 1-year follow-up to $126,323 at 4-year follow-up. Regression results also revealed physician preference as the largest determinant of OR costs, accounting for $14,780 of otherwise unexplained OR cost differences across patients, with no significant physician effects on all other non-OR costs (p<.05).
Conclusions: The incidence of readmissions increased the average cost of ASD surgery by more than 70%, illustrating the financial burden of revisions/reoperations; however, the cost burden resulting from readmissions appeared to taper off within 5 years after surgery. The estimated impact of physician preference on OR costs also highlights the variation in current practice and the opportunity for large cost reductions via a more standardized approach in the use of implants and biologics.
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http://dx.doi.org/10.1016/j.spinee.2014.01.032 | DOI Listing |
Eur J Obstet Gynecol Reprod Biol
January 2025
Division of Gynecologic Oncology, Department of Obstetrics and Gynecology, University of Southern California, Los Angeles, CA, USA; Division of Gynecologic Oncology, Department of Obstetrics and Gynecology, Los Angeles General Medical Center, Los Angeles, CA, USA; Norris Comprehensive Cancer Center, University of Southern California, Los Angeles, CA, USA. Electronic address:
Objective: To assess clinical and obstetric characteristics associated with pregnant patients with a diagnosis of attention-deficit hyperactivity disorder (ADHD).
Methods: This serial cross-sectional study queried the Agency of Healthcare Research and Quality's Healthcare Cost and Utilization Project National Inpatient Sample. The study population was 16,759,786 hospital deliveries from 2016 to 2020.
Knee
January 2025
Department of Orthopaedics, Juntendo University, Faculty of Medicine, Bunkyo-ku, Tokyo, Japan.
Purpose: The purpose of this study was to compare the distribution of the coronal plane alignment of the knee (CPAK) phenotype between the healthy population and the arthritic population in Japan.
Methods: The retrospective cross-sectional study included 1049 knees. There were 256 healthy individuals with a total of 512 knees and 310 individuals with a total of 537 arthritic knees who underwent around-knee osteotomy between June 2010 and January 2024.
Knee
January 2025
IULS-University Institute for Locomotion and Sports, Pasteur 2 Hospital, University Côte d'Azur, Nice, France; ICARE Team, Côte d'Azur University, Inserm, CNRS, Valrose Institute of Biology, Nice, France. Electronic address:
Background: Several studies have demonstrated the interest in patient-specific custom cutting guides in total knee arthroplasty (TKA), but clinical improvement remains debated. The purpose of this study was to evaluate the functional outcomes (Forgotten Joint Score, FJS) of patients undergoing individualized TKA compared with those receiving off-the-shelf (OTS) implants, both using patient-specific cutting guides with personalized alignment over a minimum follow up period of 12 months. We hypothesized that individualized TKA demonstrates significantly better functional outcomes than OTS TKA (FJS and percentage of patients reaching the minimum clinically important difference).
View Article and Find Full Text PDFGeriatr Nurs
January 2025
Ordine delle Professioni Infermieristiche di Bergamo, via Pietro Rovelli 45, Bergamo 24125, Italy.
Introduction/objective: The relationship between staffing levels and skill mix in nursing homes is poorly documented in Italy. This study aimed to investigate nursing staffing levels and skill mix in Northern Italian nursing homes.
Methods: A cross-sectional observational study was conducted using a questionnaire sent to several nursing homes.
Int J Med Inform
January 2025
Rheumatology and Allergy Clinical Epidemiology Research Center and Division of Rheumatology, Allergy, and Immunology, and Mongan Institute, Department of Medicine, Massachusetts General Hospital Boston MA USA. Electronic address:
Background: ANCA-associated vasculitis (AAV) is a rare but serious disease. Traditional case-identification methods using claims data can be time-intensive and may miss important subgroups. We hypothesized that a deep learning model analyzing electronic health records (EHR) can more accurately identify AAV cases.
View Article and Find Full Text PDFEnter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!