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Health Care Management Science

Samuel Davis, Nasser Fard
Failing to match the supply of resources to the demand for resources in a hospital can cause non-clinical transfers, diversions, safety risks, and expensive under-utilized resource capacity. Forecasting bed demand helps achieve appropriate safety standards and cost management by proactively adjusting staffing levels and patient flow protocols. This paper defines the theoretical bounds on optimal bed demand prediction accuracy and develops a flexible statistical model to approximate the probability mass function of future bed demand...
November 6, 2018: Health Care Management Science
Michael Fairley, David Scheinker, Margaret L Brandeau
The operating room is a major cost and revenue center for most hospitals. Thus, more effective operating room management and scheduling can provide significant benefits. In many hospitals, the post-anesthesia care unit (PACU), where patients recover after their surgical procedures, is a bottleneck. If the PACU reaches capacity, patients must wait in the operating room until the PACU has available space, leading to delays and possible cancellations for subsequent operating room procedures. We develop a generalizable optimization and machine learning approach to sequence operating room procedures to minimize delays caused by PACU unavailability...
November 1, 2018: Health Care Management Science
Saligrama Agnihothri, Leon Cui, Mohammad Delasay, Balaraman Rajan
Chronic conditions place a high cost burden on the healthcare system and deplete the quality of life for millions of Americans. Digital innovations such as mobile health (mHealth) technology can be used to provide efficient and effective healthcare. In this research we explore the use of mobile technology to manage chronic conditions such as diabetes and hypertension. There is ample empirical evidence in the healthcare literature showing that patients who use mHealth observe improvement in their health. However, an analytical study that quantifies the benefit of using mHealth is lacking...
October 31, 2018: Health Care Management Science
Matthew Herland, Richard A Bauder, Taghi M Khoshgoftaar
Quality and affordable healthcare is an important aspect in people's lives, particularly as they age. The rising elderly population in the United States (U.S.), with increasing number of chronic diseases, implies continuing healthcare later in life and the need for programs, such as U.S. Medicare, to help with associated medical expenses. Unfortunately, due to healthcare fraud, these programs are being adversely affected draining resources and reducing quality and accessibility of necessary healthcare services...
October 27, 2018: Health Care Management Science
Dina Bentayeb, Nadia Lahrichi, Louis-Martin Rousseau
With the growth of the population, access to medical care is in high demand, and queues are becoming longer. The situation is more critical when it concerns serious diseases such as cancer. The primary problem is inefficient management of patients rather than a lack of resources. In this work, we collaborate with the Centre Intégré de Cancérologie de Laval (CICL). We present a data-driven study based on a nonblock approach to patient appointment scheduling. We use data mining and regression methods to develop a prediction model for radiotherapy treatment duration...
October 11, 2018: Health Care Management Science
Habib Zare, Madjid Tavana, Abbas Mardani, Sepideh Masoudian, Mahyar Kamali Saraji
Performance measurement plays an important role in the successful design and reform of regional healthcare management systems. In this study, we propose a hybrid data envelopment analysis (DEA) and game theory model for measuring the performance and productivity in the healthcare centers. The input and output variables associated with the efficiency of the healthcare centers are identified by reviewing the relevant literature, and then used in conjunction with the internal organizational data. The selected indicators and collected data are then weighted and prioritized with the help of experts in the field...
September 17, 2018: Health Care Management Science
Ting-Yu Ho, Shan Liu, Zelda B Zabinsky
Dynamic resource allocation for prevention, screening, and treatment interventions in population disease management has received much attention in recent years due to excessive healthcare costs. In this paper, our goal is to design a model and an efficient algorithm to optimize sequential intervention policies under resource constraints to improve population health outcomes. We consider a discrete-time finite-horizon budget allocation problem with disease progression within a closed birth-cohort population...
September 7, 2018: Health Care Management Science
Ronald G McGarvey, Andreas Thorsen, Maggie L Thorsen, Rohith Madhi Reddy
Over 1300 federally-qualified health centers (FQHCs) in the US provide care to vulnerable populations in different contexts, addressing diverse patient health and socioeconomic characteristics. In this study, we use data envelopment analysis (DEA) to measure FQHC performance, applying several techniques to account for both quality of outputs and heterogeneity among FQHC operating environments. To address quality, we examine two formulations, the Two-Model DEA approach of Shimshak and Lenard (denoted S/L), and a variant of the Quality-Adjusted DEA approach of Sherman and Zhou (denoted S/Z)...
August 26, 2018: Health Care Management Science
Lauren E Cipriano, Thomas A Weber
We develop a general framework for optimal health policy design in a dynamic setting. We consider a hypothetical medical intervention for a cohort of patients where one parameter varies across cohorts with imperfectly observable linear dynamics. We seek to identify the optimal time to change the current health intervention policy and the optimal time to collect decision-relevant information. We formulate this problem as a discrete-time, infinite-horizon Markov decision process and we establish structural properties in terms of first and second-order monotonicity...
December 2018: Health Care Management Science
Sze-Chuan Suen, Margaret L Brandeau, Jeremy D Goldhaber-Fiebert
Effective treatment for tuberculosis (TB) patients on first-line treatment involves triaging those with drug-resistant (DR) TB to appropriate treatment alternatives. Patients likely to have DR TB are identified using results from repeated inexpensive sputum-smear (SS) tests and expensive but definitive drug sensitivity tests (DST). Early DST may lead to high costs and unnecessary testing; late DST may lead to poor health outcomes and disease transmission. We use a partially observable Markov decision process (POMDP) framework to determine optimal DST timing...
December 2018: Health Care Management Science
Zuraida Abal Abas, Mohamad Raziff Ramli, Mohamad Ishak Desa, Nordin Saleh, Ainul Nadziha Hanafiah, Nuraini Aziz, Zaheera Zainal Abidin, Abdul Samad Shibghatullah, Ahmad Fadzli Nizam Abdul Rahman, Haslinda Musa
The paper aims to provide an insight into the significance of having a simulation model to forecast the supply of registered nurses for health workforce planning policy using System Dynamics. A model is highly in demand to predict the workforce demand for nurses in the future, which it supports for complete development of a needs-based nurse workforce projection using Malaysia as a case study. The supply model consists of three sub-models to forecast the number of registered nurses for the next 15 years: training model, population model and Full Time Equivalent (FTE) model...
December 2018: Health Care Management Science
Vahab Vahdat, Jacqueline Griffin, James E Stahl
To address prolonged lengths of stay (LOS) in ambulatory care clinics, we analyze the impact of implementing flexible and dynamic policies for assigning exam rooms to providers. In contrast to the traditional approaches of assigning specific rooms to each provider or pooling rooms among all practitioners, we characterize the impact of alternate compromise policies that have not been explored in previous studies. Since ambulatory care patients may encounter multiple different providers in a single visit, room allocation can be determined separately for each encounter accordingly...
December 2018: Health Care Management Science
Sahar Ahmadvand, Mir Saman Pishvaee
Given the perennial imbalance and chronic scarcity between the demand for and supply of available organs, organ allocation is one of the most critical decisions in the management of organ transplantation networks. Organ allocation systems undergo rapid revisions for the sake of improved outcomes in terms of both equity and medical efficiency. This paper presents a Data Envelopment Analysis (DEA)-based model to evaluate the efficiency of possible patient-organ pairs for kidney allocation in order to enhance the fitness of organ allocation under inherent uncertainty in such problem...
December 2018: Health Care Management Science
Yin-Chi Chan, Eric W M Wong, Gavin Joynt, Paul Lai, Moshe Zukerman
An earlier article, inspired by overflow models in telecommunication systems with multiple streams of telephone calls, proposed a new analytical model for a network of intensive care units (ICUs), and a new patient referral policy for such networks to reduce the blocking probability of external emergency patients without degrading the quality of service (QoS) of canceled elective operations, due to the more efficient use of ICU capacity overall. In this work, we use additional concepts and insights from traditional teletraffic theory, including resource sharing, trunk reservation, and mutual overflow, to design a new patient referral policy to further improve ICU network efficiency...
December 2018: Health Care Management Science
Nisha Nataraj, Julie Simmons Ivy, Fay Cobb Payton, Joseph Norman
In the US, one in four adults has two or more chronic conditions; this population accounts for two thirds of healthcare spending. Comorbidity, the presence of multiple simultaneous health conditions in an individual, is increasing in prevalence and has been shown to impact patient outcomes negatively. Comorbidities associated with diabetes are correlated with increased incidence of preventable hospitalizations, longer lengths of stay (LOS), and higher costs. This study focuses on sex and race disparities in outcomes for hospitalized adult patients with and without diabetes...
December 2018: Health Care Management Science
Soovin Yoon, Laura A Albert
Emergency medical services provide immediate care to patients with various types of needs. When the system is congested, the response to urgent emergency calls can be delayed. To address this issue, we propose a spatial Hypercube approximation model with a cutoff priority queue that estimates performance measures for a system where some servers are reserved exclusively for high priority calls when the system is congested. In the cutoff priority queue, low priority calls are not immediately served-they are either lost or entered into a queue-whenever the number of busy ambulances is equal to or greater than the cutoff...
December 2018: Health Care Management Science
Xiang Zhong, Peter Hoonakker, Philip A Bain, Albert J Musa, Jingshan Li
To improve patient access to primary care, many healthcare organizations have introduced electronic visits (e-visits) to provide patient-physician communication through secure messages. However, it remains unclear how e-visit affects physicians' operations on a daily basis and whether it would increase physicians' panel size. In this study, we consider a primary care physician who has a steady patient panel and manages patients' office and e-visits, as well as other indirect care tasks. We use queueing-based performance outcomes to evaluate the performance of care delivery...
December 2018: Health Care Management Science
Ruben A Proano, Akshit Agarwal
Completing a residency program is a requirement for medical students before they can practice medicine independently. Residency programs in internal medicine must undergo a series of supervised rotations in elective, inpatient, and ambulatory units. Typically, a team of chief residents is charged to develop a yearly rotational schedule. This process is complex, as it needs to consider academic, managerial, regulatory, and legal restrictions while also facilitating the provision of patient care, ensuring a diverse educational experience, balancing the workload, and improving resident satisfaction...
December 2018: Health Care Management Science
Adam Diamant, Joseph Milner, Fayez Quereshy, Bo Xu
We investigate the inventory management practices for reusable surgical instruments that must be sterilized between uses. We study a hospital that outsources their sterilization services and model the inventory process as a discrete-time Markov chain. We present two base-stock inventory models, one that considers stockout-based substitution and one that does not. We derive the optimal base-stock level for the number of reusable instruments to hold in inventory, the expected service level, and investigate the implied cost of a stockout...
September 2018: Health Care Management Science
Lukas Kwietniewski, Jonas Schreyögg
This is the first study to use stochastic frontier analysis to simultaneously estimate the technical, cost and profit efficiency of physician practices for different physician specialist groups. We base our analysis on a unique panel data set of 4964 physician practices in Germany for the years 2008 to 2010. The data contains information on practice costs and revenues, services provided, as well as physician characteristics and practice characteristics. Additionally we consider a wide range additional variables not previously analyzed in this context (e...
September 2018: Health Care Management Science
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