Health Care Management Science最新文献

{"title":"Optimal breast cancer risk reduction policies tailored to personal risk level.","authors":"Mehmet A Ergun,&nbsp;Ali Hajjar,&nbsp;Oguzhan Alagoz,&nbsp;Murtuza Rampurwala","doi":"10.1007/s10729-022-09596-2","DOIUrl":"https://doi.org/10.1007/s10729-022-09596-2","url":null,"abstract":"<p><p>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.</p>","PeriodicalId":12903,"journal":{"name":"Health Care Management Science","volume":"25 3","pages":"363-388"},"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}

{"title":"A tactical multi-week implicit tour scheduling model with applications in healthcare","authors":"M. Isken, Osman T. Aydas","doi":"10.1007/s10729-022-09601-8","DOIUrl":"https://doi.org/10.1007/s10729-022-09601-8","url":null,"abstract":"","PeriodicalId":12903,"journal":{"name":"Health Care Management Science","volume":"25 1","pages":"551 - 573"},"PeriodicalIF":3.6,"publicationDate":"2022-06-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42045335","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}

{"title":"Beyond patient-sharing: Comparing physician- and patient-induced networks","authors":"Eva Kesternich, Olaf N. Rank","doi":"10.1007/s10729-022-09595-3","DOIUrl":"https://doi.org/10.1007/s10729-022-09595-3","url":null,"abstract":"","PeriodicalId":12903,"journal":{"name":"Health Care Management Science","volume":"25 1","pages":"498 - 514"},"PeriodicalIF":3.6,"publicationDate":"2022-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44732005","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}

{"title":"The importance of peer imitation on smoking initiation over time: a dynamical systems approach.","authors":"Carl Simon, David Mendez","doi":"10.1007/s10729-021-09583-z","DOIUrl":"10.1007/s10729-021-09583-z","url":null,"abstract":"<p><p>A 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 and self-initiation to the overall smoking initiation process. Although the percent of total smoking due to peer imitation has been trending downward over time, it remains higher than the percent due to self-initiation. We note unexpected changes for the 2007 cohort, and we discuss possible implications for intervention and for the spread of e-cigarettes.</p>","PeriodicalId":12903,"journal":{"name":"Health Care Management Science","volume":"25 2","pages":"222-236"},"PeriodicalIF":2.3,"publicationDate":"2022-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"9754948","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}

{"title":"What is the value of explicit priority setting for health interventions? A simulation study","authors":"E. Barlow, A. Morton, S. Dabak, Sven Engels, W. Isaranuwatchai, Y. Teerawattananon, K. Chalkidou","doi":"10.1007/s10729-022-09594-4","DOIUrl":"https://doi.org/10.1007/s10729-022-09594-4","url":null,"abstract":"","PeriodicalId":12903,"journal":{"name":"Health Care Management Science","volume":"25 1","pages":"460 - 483"},"PeriodicalIF":3.6,"publicationDate":"2022-05-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"47391908","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}

{"title":"A multi-product multi-period stochastic model for a blood supply chain considering blood substitution and demand uncertainty","authors":"Yuan Xu, Joseph G. Szmerekovsky","doi":"10.1007/s10729-022-09593-5","DOIUrl":"https://doi.org/10.1007/s10729-022-09593-5","url":null,"abstract":"","PeriodicalId":12903,"journal":{"name":"Health Care Management Science","volume":"25 1","pages":"441 - 459"},"PeriodicalIF":3.6,"publicationDate":"2022-05-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"45932906","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}

{"title":"A dynamic sequential decision-making model on MRI real-time scheduling with simulation-based optimization","authors":"Bowen Pang, Xiaolei Xie, Feng Ju, J. Pipe","doi":"10.1007/s10729-022-09592-6","DOIUrl":"https://doi.org/10.1007/s10729-022-09592-6","url":null,"abstract":"","PeriodicalId":12903,"journal":{"name":"Health Care Management Science","volume":"25 1","pages":"426 - 440"},"PeriodicalIF":3.6,"publicationDate":"2022-04-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"41384570","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}

{"title":"Towards a more efficient healthcare system: Opportunities and challenges caused by hospital closures amid the COVID-19 pandemic","authors":"S. Saghafian, Lina Song, A. Raja","doi":"10.1007/s10729-022-09591-7","DOIUrl":"https://doi.org/10.1007/s10729-022-09591-7","url":null,"abstract":"","PeriodicalId":12903,"journal":{"name":"Health Care Management Science","volume":"25 1","pages":"187 - 190"},"PeriodicalIF":3.6,"publicationDate":"2022-03-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46174782","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}

{"title":"The effect of correlation and false negatives in pool testing strategies for COVID-19.","authors":"Leonardo J Basso,&nbsp;Vicente Salinas,&nbsp;Denis Sauré,&nbsp;Charles Thraves,&nbsp;Natalia Yankovic","doi":"10.1007/s10729-021-09578-w","DOIUrl":"https://doi.org/10.1007/s10729-021-09578-w","url":null,"abstract":"<p><p>During the current COVID-19 pandemic, active testing has risen as a key component of many response strategies around the globe. Such strategies have a common denominator: the limited availability of diagnostic tests. In this context, pool testing strategies have emerged as a means to increase testing capacity. The efficiency gains obtained by using pool testing, derived from testing combined samples simultaneously, vary according to the spread of the SARS-CoV-2 virus in the population being tested. Motivated by the need for testing closed populations, such as long-term care facilities (LTCFs), where significant correlation in infections is expected, we develop a probabilistic model for settings where the test results are correlated, which we use to compute optimal pool sizes in the context of two-stage pool testing schemes. The proposed model incorporates the specificity and sensitivity of the test, which makes it possible to study the impact of these measures on both the expected number of tests required for diagnosing a population and the expected number and variance of false negatives. We use our experience implementing pool testing in LTCFs managed by SENAMA (Chile's National Service for the Elderly) to develop a simulation model of contagion dynamics inside LTCFs, which incorporates testing and quarantine policies implemented by SENAMA. We use this simulation to estimate the correlation of test results among collected samples when following SENAMA's testing guidelines. Our results show that correlation estimates are high in settings representative of LTCFs, which validates the use of the proposed model for incorporating correlation in determining optimal pool sizes for pool testing strategies. Generally, our results show that settings in which pool testing achieves efficiency gains, relative to individual testing, are likely to be found in practice. Moreover, the results show that incorporating correlation in the analysis of pool testing strategies both improves the expected efficiency and broadens the settings in which the technique is preferred over individual testing.</p>","PeriodicalId":12903,"journal":{"name":"Health Care Management Science","volume":"25 1","pages":"146-165"},"PeriodicalIF":3.6,"publicationDate":"2022-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1007/s10729-021-09578-w","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"39361862","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}

{"title":"Prospective adverse event risk evaluation in clinical trials.","authors":"Abhishake Kundu,&nbsp;Felipe Feijoo,&nbsp;Diego A Martinez,&nbsp;Manuel Hermosilla,&nbsp;Timothy Matis","doi":"10.1007/s10729-021-09584-y","DOIUrl":"https://doi.org/10.1007/s10729-021-09584-y","url":null,"abstract":"<p><p>Proactive and objective regulatory risk management of ongoing clinical trials is limited, especially when it involves the safety of the trial. We seek to prospectively evaluate the risk of facing adverse outcomes from standardized and routinely collected protocol data. We conducted a retrospective cohort study of 2860 Phase 2 and Phase 3 trials that were started and completed between 1993 and 2017 and documented in ClinicalTrials.gov. Adverse outcomes considered in our work include Serious or Non-Serious as per the ClinicalTrials.gov definition. Random-forest-based prediction models were created to determine a trial's risk of adverse outcomes based on protocol data that is available before the start of a trial enrollment. A trial's risk is defined by dichotomic (classification) and continuous (log-odds) risk scores. The classification-based prediction models had an area under the curve (AUC) ranging from 0.865 to 0.971 and the continuous-score based models indicate a rank correlation of 0.6-0.66 (with p-values < 0.001), thereby demonstrating improved identification of risk of adverse outcomes. Whereas related frameworks highlight the prediction benefits of incorporating data that is highly context-specific, our results indicate that Adverse Event (AE) risks can be reliably predicted through a framework of mild data requirements. We propose three potential applications in leading regulatory remits, highlighting opportunities to support regulatory oversight and informed consent decisions.</p>","PeriodicalId":12903,"journal":{"name":"Health Care Management Science","volume":"25 1","pages":"89-99"},"PeriodicalIF":3.6,"publicationDate":"2022-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"39445784","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}