Health Care Management Science最新文献_第10页

Optimal breast cancer risk reduction policies tailored to personal risk level. 针对个人风险水平量身定制的最佳乳腺癌风险降低政策。

IF 3.6 3区医学

Health Care Management Science Pub Date : 2022-09-01 DOI: 10.1007/s10729-022-09596-2

Mehmet A Ergun, Ali Hajjar, Oguzhan Alagoz, Murtuza Rampurwala

{"title":"Optimal breast cancer risk reduction policies tailored to personal risk level.","authors":"Mehmet A Ergun, Ali Hajjar, Oguzhan Alagoz, Murtuza Rampurwala","doi":"10.1007/s10729-022-09596-2","DOIUrl":"https://doi.org/10.1007/s10729-022-09596-2","url":null,"abstract":"Depending 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 enough resolution on the benefit-risk trade-off of an intervention policy as personal risk changes. In addressing this problem, we develop a discrete-time, finite-horizon Markov decision process (MDP) model with the objective of maximizing the patient's total expected quality-adjusted life years. We find several useful insights some of which contradict the existing national breast cancer risk reduction recommendations. For example, we find that mastectomy is the optimal choice for the border-line high-risk women who are between ages 22 and 38. Additionally, in contrast to the National Comprehensive Cancer Network recommendations, we find that exemestane is a plausible, in fact, the best, option for high-risk postmenopausal women.","PeriodicalId":12903,"journal":{"name":"Health Care Management Science","volume":null,"pages":null},"PeriodicalIF":3.6,"publicationDate":"2022-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10445480/pdf/nihms-1911145.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"10053555","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Homogeneity and Best Practice Analyses in Hospital Performance Management: An Analytical Framework. 同质性和最佳实践分析在医院绩效管理:一个分析框架。

IF 3.6 3区医学

Health Care Management Science Pub Date : 2022-09-01 Epub Date: 2022-02-22 DOI: 10.1007/s10729-022-09590-8

Mansour Zarrin, Jan Schoenfelder, Jens O Brunner

{"title":"Homogeneity and Best Practice Analyses in Hospital Performance Management: An Analytical Framework.","authors":"Mansour Zarrin, Jan Schoenfelder, Jens O Brunner","doi":"10.1007/s10729-022-09590-8","DOIUrl":"https://doi.org/10.1007/s10729-022-09590-8","url":null,"abstract":"Performance modeling of hospitals using data envelopment analysis (DEA) has received steadily increasing attention in the literature. As part of the traditional DEA framework, hospitals are generally assumed to be functionally similar and therefore homogenous. Accordingly, any identified inefficiency is supposedly due to the inefficient use of inputs to produce outputs. However, the disparities in DEA efficiency scores may be a result of the inherent heterogeneity of hospitals. Additionally, traditional DEA models lack predictive capabilities despite having been frequently used as a benchmarking tool in the literature. To address these concerns, this study proposes a framework for analyzing hospital performance by combining two complementary modeling approaches. Specifically, we employ a self-organizing map artificial neural network (SOM-ANN) to conduct a cluster analysis and a multilayer perceptron ANN (MLP-ANN) to perform a heterogeneity analysis and a best practice analysis. The applicability of the integrated framework is empirically shown by an implementation to a large dataset containing more than 1,100 hospitals in Germany. The framework enables a decision-maker not only to predict the best performance but also to explore whether the differences in relative efficiency scores are ascribable to the heterogeneity of hospitals.","PeriodicalId":12903,"journal":{"name":"Health Care Management Science","volume":null,"pages":null},"PeriodicalIF":3.6,"publicationDate":"2022-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9474503/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"39944294","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 8

Covid-19 infection risk on US domestic airlines. 美国国内航空公司的新冠肺炎感染风险。

IF 3.6 3区医学

Health Care Management Science Pub Date : 2022-09-01 Epub Date: 2022-07-02 DOI: 10.1007/s10729-022-09603-6

Arnold Barnett, Keith Fleming

{"title":"Covid-19 infection risk on US domestic airlines.","authors":"Arnold Barnett, Keith Fleming","doi":"10.1007/s10729-022-09603-6","DOIUrl":"10.1007/s10729-022-09603-6","url":null,"abstract":"Working with recent data and research findings, we estimate the probability that an air traveler in economy class would have contracted Covid-19 on a US domestic jet flight over the nine-month period June 2020 to February 2021. The estimates take account of the rates of confirmed Covid-19 infections in the US, flight duration, fraction of seats occupied, and some demographic differences between US air travelers and US citizens as a whole. Based on point estimates, the risk of contracting Covid-19 in-flight exceeded 1 in 1000 on a fully-loaded two-hour flight at the height of the pandemic over the nine months, but was about 1 in 6000 on a half-full flight when the pandemic was at a low ebb. However, these estimates are subject to substantial uncertainty, with the 10th percentiles of various risk distributions only about 1/7 as large as the medians, and the 90th percentiles about four times as large. Based on seat-occupancy levels on US flights for each month over June 2020 to February 2021, the median risk estimate for that period is 1 in 2250, while the mean risk estimate is 1 in 1450. Indirect effects arose because those who contracted Covid-19 on US airplanes could in turn infect others.","PeriodicalId":12903,"journal":{"name":"Health Care Management Science","volume":null,"pages":null},"PeriodicalIF":3.6,"publicationDate":"2022-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9474510/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"40565179","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 4

On the timing and probability of Presurgical Teledermatology: how it becomes the dominant strategy. 关于外科远程皮肤科的时机和可能性:它如何成为主导策略。

IF 3.6 3区医学

Health Care Management Science Pub Date : 2022-09-01 Epub Date: 2022-01-18 DOI: 10.1007/s10729-021-09574-0

Felipa de Mello-Sampayo

引用次数: 1

Excess deaths by sex and Age Group in the first two years of the COVID-19 pandemic in the United States. 美国 COVID-19 大流行头两年按性别和年龄组分列的超额死亡人数。

IF 2.3 3区医学

Health Care Management Science Pub Date : 2022-09-01 Epub Date: 2022-08-23 DOI: 10.1007/s10729-022-09606-3

Ian G Ludden, Sheldon H Jacobson, Janet A Jokela

{"title":"Excess deaths by sex and Age Group in the first two years of the COVID-19 pandemic in the United States.","authors":"Ian G Ludden, Sheldon H Jacobson, Janet A Jokela","doi":"10.1007/s10729-022-09606-3","DOIUrl":"10.1007/s10729-022-09606-3","url":null,"abstract":"The COVID-19 pandemic hastened hundreds of thousands of deaths in the United States. Many of these excess deaths are directly attributed to COVID-19, but others stem from the pandemic's social, economic, and health care system disruptions. This study compares provisional mortality data for age and sex subgroups across different time windows, with and without COVID-19 deaths, and assesses whether mortality risks are returning to pre-pandemic levels. Using provisional mortality reports from the CDC, we compute mortality risks for 22 age and sex subgroups in 2021 and compare against 2015-2019 using odds ratios. We repeat this comparison for the first twelve full months of the COVID-19 pandemic in the United States (April 2020-March 2021) against the next twelve full months (April 2021-March 2022). Mortality risks for most subgroups were significantly higher in 2021 than in 2015-2019, both with and without deaths involving COVID-19. For ages 25-54, Year 2 (April 2021-March 2022) was more fatal than Year 1 (April 2020-March 2021), whereas total mortality risks for the 65 + age groups declined. Given so many displaced deaths in the first two years of the COVID-19 pandemic, mortality risks in the next few years may fall below pre-pandemic levels. Provisional mortality data suggest this is already happening for the 75 + age groups when excluding COVID-19 deaths.","PeriodicalId":12903,"journal":{"name":"Health Care Management Science","volume":null,"pages":null},"PeriodicalIF":2.3,"publicationDate":"2022-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9395936/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"40633230","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

A tactical multi-week implicit tour scheduling model with applications in healthcare 一个战术多周隐式旅行调度模型及其在医疗保健中的应用

IF 3.6 3区医学

Health Care Management Science Pub Date : 2022-06-11 DOI: 10.1007/s10729-022-09601-8

M. Isken, Osman T. Aydas

引用次数: 0

Decision support algorithms for optimizing surgery start times considering the performance variation. 考虑性能变化优化手术开始时间的决策支持算法。

IF 3.6 3区医学

Health Care Management Science Pub Date : 2022-06-01 Epub Date: 2021-10-11 DOI: 10.1007/s10729-021-09580-2

Shing Chih Tsai, Wu Hung Lin, Chia Cheng Wu, Shao Jen Weng, Ching Fen Tang

引用次数: 1

Locating trauma centers considering patient safety. 考虑到病人的安全，确定创伤中心。

IF 3.6 3区医学

Health Care Management Science Pub Date : 2022-06-01 Epub Date: 2022-01-13 DOI: 10.1007/s10729-021-09576-y

Sagarkumar Hirpara, Monit Vaishnav, Pratik J Parikh, Nan Kong, Priti Parikh

{"title":"Locating trauma centers considering patient safety.","authors":"Sagarkumar Hirpara, Monit Vaishnav, Pratik J Parikh, Nan Kong, Priti Parikh","doi":"10.1007/s10729-021-09576-y","DOIUrl":"https://doi.org/10.1007/s10729-021-09576-y","url":null,"abstract":"Trauma continues to be the leading cause of death and disability in the U.S. for those under the age of 44, making it a prominent public health problem. Recent literature suggests that geographical maldistribution of Trauma Centers (TCs), and the resultant increase of the access time to the nearest TC, could impact patient safety and increase disability or mortality. To address this issue, we introduce the Trauma Center Location Problem (TCLP) that determines the optimal number and location of TCs in order to improve patient safety. We model patient safety through a surrogate measure of mistriages, which refers to a mismatch in the injury severity of a trauma patient and the destination hospital. Our proposed bi-objective optimization model directly accounts for the two types of mistriages, system-related under-triage (srUT) and over-triage (srOT), both of which are estimated using a notional tasking algorithm. We propose a heuristic based on the Particle Swarm Optimization framework to efficiently derive a near-optimal solution to the TCLP for realistic problem sizes. Based on 2012 data from the state of Ohio, we observe that the solutions are sensitive to the choice of weights for srUT and srOT, volume requirements at a TC, and the two thresholds used to mimic EMS decisions. Using our approach to optimize that network resulted in over 31.5% reduction in the objective with only 1 additional TC; redistribution of the existing 21 TCs led to 30.4% reduction.","PeriodicalId":12903,"journal":{"name":"Health Care Management Science","volume":null,"pages":null},"PeriodicalIF":3.6,"publicationDate":"2022-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"39931301","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 2

Beyond patient-sharing: Comparing physician- and patient-induced networks 超越病人分享:比较医生和病人诱导的网络

IF 3.6 3区医学

Health Care Management Science Pub Date : 2022-06-01 DOI: 10.1007/s10729-022-09595-3

Eva Kesternich, Olaf N. Rank

引用次数: 1

Bayesian prediction of emergency department wait time. 急诊等待时间的贝叶斯预测。

IF 3.6 3区医学

Health Care Management Science Pub Date : 2022-06-01 Epub Date: 2022-01-06 DOI: 10.1007/s10729-021-09581-1

Mani Suleiman, Haydar Demirhan, Leanne Boyd, Federico Girosi, Vural Aksakalli

{"title":"Bayesian prediction of emergency department wait time.","authors":"Mani Suleiman, Haydar Demirhan, Leanne Boyd, Federico Girosi, Vural Aksakalli","doi":"10.1007/s10729-021-09581-1","DOIUrl":"https://doi.org/10.1007/s10729-021-09581-1","url":null,"abstract":"Increasingly, 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 incorporates a priori information in government statistics and elicited expert opinion. This methodology is compared to frequentist quantile regression and Bayesian quantile regression with non-informative priors. The test set includes 1, 024 low acuity presentations, of which 457 (44%) are Category 3, 425 (41%) are Category 4 and 160 (15%) are Category 5. On the Huber loss metric, the proposed method performs best on the test data for both median and 90th percentile prediction compared to non-informative Bayesian quantile regression and frequentist quantile regression. We obtain a benefit in the estimation of model coefficients due to the value contributed by a priori information in the form of elicited expert guesses guided by government wait time statistics. The use of such informative priors offers a beneficial approach to ED wait time prediction with demonstrable potential to improve wait time quantile estimates.","PeriodicalId":12903,"journal":{"name":"Health Care Management Science","volume":null,"pages":null},"PeriodicalIF":3.6,"publicationDate":"2022-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"39790070","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 1