Health care management science
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Health Care Manag Sci · Jun 2017
A stochastic model of acute-care decisions based on patient and provider heterogeneity.
The primary cause of preventable death in many hospitals is the failure to recognize and/or rescue patients from acute physiologic deterioration (APD). APD affects all hospitalized patients, potentially causing cardiac arrest and death. Identifying APD is difficult, and response timing is critical - delays in response represent a significant and modifiable patient safety issue. ⋯ Clustering methods identified provider clusters considering RRT-activation preferences and estimation of stabilization-related resource needs. Providers with conservative resource estimates preferred waiting over activating RRT. This study provides simple practical rules for personalized acute care delivery.
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Health Care Manag Sci · Mar 2017
Scheduling elective surgeries: the tradeoff among bed capacity, waiting patients and operating room utilization using goal programming.
Scheduling of surgeries in the operating rooms under limited competing resources such as surgical and nursing staff, anesthesiologist, medical equipment, and recovery beds in surgical wards is a complicated process. A well-designed schedule should be concerned with the welfare of the entire system by allocating the available resources in an efficient and effective manner. In this paper, we develop an integer linear programming model in a manner useful for multiple goals for optimally scheduling elective surgeries based on the availability of surgeons and operating rooms over a time horizon. ⋯ A numerical study is conducted to illustrate the optimal master-surgery schedule obtained from the models. The numerical results demonstrate that when the available number of surgeons and operating rooms is known without error over the planning horizon, the proposed models can produce good schedules and priority levels and preference weights of four goals affect the resulting schedules. The results quantify the tradeoffs that must take place as the preemptive-weights of the four goals are changed.
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Health Care Manag Sci · Mar 2017
Contextual, organizational and ecological effects on the variations in hospital readmissions of rural Medicare beneficiaries in eight southeastern states.
The enactment of the Patient Protection and Affordable Care Act (ACA) has been expected to improve the coverage of health insurance, particularly as related to the coordination of seamless care and the continuity of elder care among Medicare beneficiaries. The analysis of longitudinal data (2007 through 2013) in rural areas offers a unique opportunity to examine trends and patterns of rural disparities in hospital readmissions within 30 days of discharge among Medicare beneficiaries served by rural health clinics (RHCs) in the eight southeastern states of the Department of Health & Human Services (DHHS) Region 4. The purpose of this study is twofold: first, to examine rural trends and patterns of hospital readmission rates by state and year (before and after the ACA enactment); and second, to investigate how contextual (county characteristic), organizational (clinic characteristic) and ecological (aggregate patient characteristic) factors may influence the variations in repeat hospitalizations. ⋯ The sixteen predictors accounted for 21.52 % of the total variability in readmissions. This study contributes to the literature in health disparities research from the contextual, organizational and ecological perspectives in the analysis of longitudinal data. The synergism of multiple contextual, organizational and ecological factors, as shown in this study, should be considered in the design and implementation of intervention studies to address the problem of hospital readmissions through prevention and enhancement of disease management of rural Medicare beneficiaries.
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Health Care Manag Sci · Dec 2016
The operating room case-mix problem under uncertainty and nurses capacity constraints.
Surgery is one of the key functions in hospitals; it generates significant revenue and admissions to hospitals. In this paper we address the decision of choosing a case-mix for a surgery department. The objective of this study is to generate an optimal case-mix plan of surgery patients with uncertain surgery operations, which includes uncertainty in surgery durations, length of stay, surgery demand and the availability of nurses. ⋯ A computational experiment is presented to demonstrate the performance of the proposed method. The results show that the stochastic model solution outperforms the expected value problem solution. Additional analysis is conducted to study the effect of varying the number of ORs and nurses capacity on the overall ORs' performance.
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Operating rooms (ORs) in US hospitals are costly to staff, generate about 70 % of a hospital's revenues, and operate at a staffed-capacity utilization of 60-70 %. Many hospitals allocate blocks of OR time to individual or groups of surgeons as guaranteed allocation, who book surgeries one at a time in their blocks. The booking procedure frequently results in unused time between surgeries. ⋯ A key feature of our approach is that we allow hospitals to have two shift lengths. Our analytical results form the basis of a branch-and-bound algorithm, which we test on data obtained from three hospitals. Experiments show that rescheduling saves significant staffing costs.