Unsupervised learning methods for efficient geographic clustering and identification of disease disparities with applications to county-level colorectal cancer incidence in California
AbstractMany public health policymaking questions involve data subsets representing application-specific attributes and geographic location. We develop and evaluate standard and tailored techniques for clustering via unsupervised learning (UL) algorithms on such amalgamated (dual-domain) data sets. The aim of the associated algorithms is to identify geographically efficient clusters that also maximize the number of statistically significant differences in disease incidence and demographic variables across top clusters. Two standard UL approaches, k means with k++ initialization (k++) and the standard self-organizing map (S...
Source: Health Care Management Science - June 23, 2022 Category: Hospital Management Source Type: research
Non-linear missing data imputation for healthcare data via index-aware autoencoders
In this study, we assess the shortcomings of autoencoder models for data imputation and propose modified models to improve imputation performance. To evaluate, we compare the performance of the proposed model with five well-known imputation techniques on six medical datasets and five classification methods. Through extensive experiments, we demonstrate that the proposed non-linear imputation model outperforms the other models for all degrees of missing ratios and leads to the highest disease classification accuracy for all datasets. (Source: Health Care Management Science)
Source: Health Care Management Science - June 23, 2022 Category: Hospital Management Source Type: research
Unsupervised learning methods for efficient geographic clustering and identification of disease disparities with applications to county-level colorectal cancer incidence in California
AbstractMany public health policymaking questions involve data subsets representing application-specific attributes and geographic location. We develop and evaluate standard and tailored techniques for clustering via unsupervised learning (UL) algorithms on such amalgamated (dual-domain) data sets. The aim of the associated algorithms is to identify geographically efficient clusters that also maximize the number of statistically significant differences in disease incidence and demographic variables across top clusters. Two standard UL approaches, k means with k++ initialization (k++) and the standard self-organizing map (S...
Source: Health Care Management Science - June 23, 2022 Category: Health Management Source Type: research
A tactical multi-week implicit tour scheduling model with applications in healthcare
AbstractIn many healthcare tactical scheduling analyses, we need to solve large tour scheduling problems in which required staffing levels vary by time of day and day of week. A tour is a set of shift start times and shift lengths worked over a scheduling horizon of one or more weeks. As the degree of scheduling flexibility increases, the resulting tour scheduling problems get larger and this increase in size is exacerbated when the scheduling horizon is longer than one week. In this article, we present a tactical multi-week implicit tour scheduling model intended to complement operational scheduling systems. The implicit ...
Source: Health Care Management Science - June 11, 2022 Category: Hospital Management Source Type: research
Optimal breast cancer risk reduction policies tailored to personal risk level
AbstractDepending on personal and hereditary factors, each woman has a different risk of developing breast cancer, one of the leading causes of death for women. For women with a high-risk of breast cancer, their risk can be reduced by two main therapeutic approaches: 1) preventive treatments such as hormonal therapies (i.e., tamoxifen, raloxifene, exemestane); or 2) a risk reduction surgery (i.e., mastectomy). Existing national clinical guidelines either fail to incorporate or have limited use of the personal risk of developing breast cancer in their proposed risk reduction strategies. As a result, they do not provide enou...
Source: Health Care Management Science - June 10, 2022 Category: Hospital Management Source Type: research
On the use of partitioning for scheduling of surgeries in the inpatient surgical department
AbstractIn hospitals, the efficient planning of the operating rooms (ORs) is difficult due to the uncertainty inherent to surgical services. This is especially true for the inpatient surgical department where complex and long surgeries are often performed along with surgeries on emergency patients. This paper aims to improve the scheduling of the inpatient department by partitioning the elective surgeries into the more predictable surgeries (MPS) group and the less predictable surgeries (LPS) group, based on surgery duration variability, and by scheduling each of the two surgery groups in different ORs. Through a simulatio...
Source: Health Care Management Science - June 2, 2022 Category: Hospital Management Source Type: research
Bayesian prediction of emergency department wait time
AbstractIncreasingly, many hospitals are attempting to provide more accurate information about Emergency Department (ED) wait time to their patients. Estimation of ED wait time usually depends on what is known about the patient and also the status of the ED at the time of presentation. We provide a model for estimating ED wait time for prospective low acuity patients accessing information online prior to arrival. Little is known about the prospective patient and their condition. We develop a Bayesian quantile regression approach to provide an estimated wait time range for prospective patients. Our proposed approach incorpo...
Source: Health Care Management Science - June 1, 2022 Category: Hospital Management Source Type: research
Balancing control and autonomy in master surgery scheduling: Benefits of ICU quotas for recovery units
We present an extension to the master surgery schedule, where the capacity for surgeries on ICU patients is controlled by introducing downstream-dependent block types – one for both ICU and ward patients and one where surgeries on ICU patients must not be performed. The goal is to provide better control over post-surgery patient flows through the hospital while preserving each medical specialty’s autonomy over its operational surgery scheduling. We propose a mixed-integer program to determine the allocation of the new block types within either a given or a new master surgery schedule to minimize the maximum workload in...
Source: Health Care Management Science - June 1, 2022 Category: Hospital Management Source Type: research
The importance of peer imitation on smoking initiation over time: a dynamical systems approach
AbstractA recent Institute of Medicine Report calls for explicit modeling of smoking initiation, cessation and addiction processes. We introduce a model of smoking initiation that explicitly teases out the percentage of initiation due to social pressures, which we call “peer-imitation,” and the percentage due to other factors, such as media ads, family smoking, and psychological factors, which we call “self-initiation.” We propose a dynamic non-linear behavioral contagion model of smoking initiation and employ data from the National Survey on Drug Use and Health to estimate the relative contributions of imitation a...
Source: Health Care Management Science - June 1, 2022 Category: Hospital Management Source Type: research
Towards a more efficient healthcare system: Opportunities and challenges caused by hospital closures amid the COVID-19 pandemic
AbstractA substantial number of United States (U.S.) hospitals have closed in recent years. The trend of closures has accelerated during the COVID-19 pandemic, as hospitals have experienced financial hardship from reduced patient volume and elective surgery cases, as well as the thin financial margins for treating patients with COVID-19. This trend of hospital closures is concerning for patients, healthcare providers, and policymakers. In this current opinion piece, we first describe the challenges caused by hospital closures and discuss what policymakers should know based on the existing research. We then discuss unique o...
Source: Health Care Management Science - June 1, 2022 Category: Hospital Management Source Type: research
