Incremental Cost-effectiveness Analysis on Length of Stay of an Enhanced Recovery After Spine Surgery Program: A Single-center, Retrospective Cohort Study.

BACKGROUND: Enhanced recovery after spine surgery (ERAS) is increasingly utilized to improve postoperative outcomes and reduce cost. There are limited data on the monetary benefits of ERAS when incorporating the costs of developing, operationalizing, and maintaining ERAS programs. The objective of this study was to calculate the incremental cost-effectiveness of a spine surgery ERAS program, modeling hospital and operational cost and length of stay (LOS). METHODS: The study included adult patients undergoing spine surgery before and after implementation of an ERAS program. Variables included individual patient-level and ERAS personnel costs, with LOS as the outcome utility of interest. Propensity score matching was used to create a quasi-experimental design to equate the standard care and ERAS groups. RESULTS: Four hundred and nine patients were included in the unmatched group, with 54 patients each in the standard care and ERAS groups after matching. In the matched cohort, the only imbalance in predictors (standard mean difference [SMD] >0.2) were race (SMD, 0.21), American Society of Anesthesiologist (ASA) physical status (SMD, 0.32), fluid balance in the operating room (SMD, 0.21), median (interquartile range) LOS (standard care, 2.0 [1.0, 3.75] days vs. ERAS, 4.0 [3.0, 5.0]; SMD, 0.81) and mean (±SD) total cost (standard care, $19,291.57±13,572.24 vs. ERAS, $24,363.45±26,352.45; SMD, 0.24). In the incremental cost effectiveness analysis, standard care was the dominant strategy in both 1-way and 2-way sensitivity analysis. CONCLUSIONS: We report a real-world, cost-effectiveness analysis following implementation of an ERAS program for spine surgery at a quaternary medical center. Our study demonstrated that considering LOS as the sole determinant, standard care is the dominant cost-effective strategy compared with the ERAS protocol.

Evaluating the Costs of Nurse Burnout-Attributed Turnover: A Markov Modeling Approach.

OBJECTIVE: Burnout is a public health crisis that impacts 1 in 3 registered nurses in the United States and the safe provision of patient care. This study sought to understand the cost of nurse burnout-attributed turnover using hypothetical hospital scenarios. METHODS: A cost-consequence analysis with a Markov model structure was used to assess nurse burnout-attributed turnover costs under the following scenarios: (1) a hospital with "status quo" nurse burnout prevalence and (2) a hospital with a "burnout reduction program" and decreased nurse burnout prevalence. The model evaluated turnover costs from a hospital payer perspective and modeled a cohort of nurses who were new to a hospital. The outcome measures were defined as years in burnout among the nurse cohort and years retained/employed in the hospital. Data inputs derived from the health services literature base. RESULTS: The expected model results demonstrated that at status quo, a hospital spends an expected $16,736 per nurse per year employed on nurse burnout-attributed turnover costs. In a hospital with a burnout reduction program, such costs were $11,592 per nurse per year employed. Nurses spent more time in burnout under the status quo scenario compared with the burnout reduction scenario (1.5 versus 1.1 y of employment) as well as less time employed at the hospital (2.9 versus 3.5 y of employment). CONCLUSIONS: Given that status quo costs of burnout are higher than those in a hospital that invests in a nurse burnout reduction program, hospitals should strongly consider proactively supporting programs that reduce nurse burnout prevalence and associated costs.

Effects of a proposed rural dental school on regional dental workforce and access to care.

INTRODUCTION: Southwest Virginia is a rural, low-income region with a relatively small dentist workforce and poor oral health outcomes. The opening of a dental school in the region has been proposed by policy-makers as one approach to improving the size of the dentist workforce and oral health outcomes. METHODS: A policy simulation was conducted to assess how a hypothetical dental school in rural Southwest Virginia would affect the availability of dentists and utilization levels of dental services. The simulation focuses on two channels through which the dental school would most likely affect the region. First, the number of graduates who are expected to remain in the region was varied, based on the extensiveness of the education pipeline used to attract local students. Second, the number of patients treated in the dental school clinic under different dental school clinical models, including the traditional model, a patient-centered clinic model and a community-based clinic model, was varied in the simulation to obtain a range of additional dentists and utilization rates under differing dental school models. RESULTS: Under a set of plausible assumptions, the low yield scenario (ie private school with a traditional clinic) would result in three additional dentists residing in the region and a total of 8090 additional underserved patients receiving care. Under the high yield scenario (ie dental pipeline program with community based clinics) nine new dentists would reside in the region and as many as 18 054 underserved patients would receive care. Even with the high yield scenario and the strong assumption that these patients would not otherwise access care, the utilization rate increases to 68.9% from its current 60.1%. CONCLUSIONS: While the new dental school in Southwest Virginia would increase the dentist workforce and utilization rates, the high cost combined with the continued low rate of dental utilization suggests that there may be more effective alternatives to improving oral health in rural areas. Alternative policies that have shown considerable promise in expanding access to disadvantaged populations include virtual dental homes, enhanced Medicaid reimbursement programs, and school-based dental care systems.