Forecasting healthcare service volumes with machine learning algorithms
As an efficacious solution to remedying the imbalance of medical resources, the online medical platform has burgeoned expeditiously. Apt allotment of medical resources on the medical platform can facilitate patients in reasonably selecting physicians and time slots, coordinating doctors' clinic...
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| Veröffentlicht in: | Journal of forecasting Jg. 43; H. 6; S. 2358 - 2377 |
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| Sprache: | Englisch |
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Chichester
Wiley Periodicals Inc
01.09.2024
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| ISSN: | 0277-6693, 1099-131X |
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| Abstract | As an efficacious solution to remedying the imbalance of medical resources, the online medical platform has burgeoned expeditiously. Apt allotment of medical resources on the medical platform can facilitate patients in reasonably selecting physicians and time slots, coordinating doctors' clinical arrangements, and generating precise projections of medical platform service volume to enhance patient satisfaction and alleviate physicians' workload. To this end, grounded in the data‐driven method, this paper assembles an exhaustive feature set encompassing hospital features, physician features, and patient features. Through feature selection, appropriate features are screened, and machine learning algorithms are leveraged to accurately forecast doctors' online consultation volume. Subsequently, to glean the influence relationship between online medical services and offline medical services, this paper introduces features of offline medical services such as hospital registration volume and regional gross domestic product (GDP) to solve the prediction of offline medical service volume using online medical information. The findings signify that online data feature prediction can pinpoint superior machine learning models for online medical platform service volume (with the optimal accuracy up to 96.89%). Online features exert a positive effect on predicting offline medical service volume, but the accuracy declines to some degree (the optimal accuracy is 73%). Physicians with favorable reputations on the online platform are more susceptible to attain higher offline appointment volumes when online consultation volume is a vital feature impacting offline appointment volume. |
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| AbstractList | As an efficacious solution to remedying the imbalance of medical resources, the online medical platform has burgeoned expeditiously. Apt allotment of medical resources on the medical platform can facilitate patients in reasonably selecting physicians and time slots, coordinating doctors' clinical arrangements, and generating precise projections of medical platform service volume to enhance patient satisfaction and alleviate physicians' workload. To this end, grounded in the data‐driven method, this paper assembles an exhaustive feature set encompassing hospital features, physician features, and patient features. Through feature selection, appropriate features are screened, and machine learning algorithms are leveraged to accurately forecast doctors' online consultation volume. Subsequently, to glean the influence relationship between online medical services and offline medical services, this paper introduces features of offline medical services such as hospital registration volume and regional gross domestic product (GDP) to solve the prediction of offline medical service volume using online medical information. The findings signify that online data feature prediction can pinpoint superior machine learning models for online medical platform service volume (with the optimal accuracy up to 96.89%). Online features exert a positive effect on predicting offline medical service volume, but the accuracy declines to some degree (the optimal accuracy is 73%). Physicians with favorable reputations on the online platform are more susceptible to attain higher offline appointment volumes when online consultation volume is a vital feature impacting offline appointment volume. |
| Author | Zhu, Ke‐Hui Yang, Dong‐Hui Wang, Ruo‐Nan |
| Author_xml | – sequence: 1 givenname: Dong‐Hui orcidid: 0000-0002-9447-3161 surname: Yang fullname: Yang, Dong‐Hui email: dhyang@seu.edu.cn organization: Southeast University – sequence: 2 givenname: Ke‐Hui surname: Zhu fullname: Zhu, Ke‐Hui organization: Southeast University – sequence: 3 givenname: Ruo‐Nan surname: Wang fullname: Wang, Ruo‐Nan organization: Southeast University |
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| Cites_doi | 10.3389/fpsyg.2022.886077 10.2196/jmir.2003 10.3389/fpubh.2022.986933 10.3390/ijerph192013293 10.1080/10864415.2016.1171977 10.1016/j.indmarman.2018.01.004 10.2196/16765 10.1016/j.ijmedinf.2022.104781 10.1038/s41598-022-11607-9 10.1080/16549716.2023.2179163 10.21037/qims-22-268 10.1002/for.2953 10.3390/healthcare9101401 10.1038/s42256-022-00538-9 10.1007/978-3-319-08416-9_11 10.1016/j.dss.2015.05.006 10.1287/isre.2017.0749 10.1111/j.1365-2753.2009.01297.x 10.1287/isre.2019.0836 10.3389/fpubh.2014.00095 10.1186/s12911-016-0386-0 10.1016/j.dss.2012.10.047 10.2196/21892 10.1108/INTR-07-2020-0379 10.1007/s12652-019-01434-8 10.1016/j.omega.2022.102784 10.1016/j.dss.2013.01.003 10.2196/jmir.6423 |
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| Copyright | 2024 John Wiley & Sons Ltd. 2024 John Wiley & Sons, Ltd. |
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| References_xml | – volume: 16 issue: 1 year: 2023 article-title: Utilization of telehealth services in low‐ and middle‐income countries amid the COVID‐19 pandemic: A narrative summary publication-title: Global Health Action – volume: 9 issue: 10 year: 2021 article-title: The utilization and benefits of telehealth services by health care professionals managing breast cancer patients during the COVID‐19 pandemic publication-title: Healthcare – volume: 13 issue: 4 year: 2022 article-title: The effects of online text comments on patients' choices: The mediating roles of comment sentiment and comment content publication-title: Frontiers in Psychology – volume: 16 start-page: 1215 issue: 6 year: 2010 end-page: 1220 article-title: How do patients choose their doctors for primary care in a free market? publication-title: Journal of Evaluation in Clinical Practice – volume: 57 start-page: 417 year: 2014 end-page: 427 article-title: Factors influencing online health information search: An empirical analysis of a national cancer‐related survey publication-title: Decision Support Systems – volume: 163 year: 2022 article-title: The effect of interactive factors on online health consultation review deviation: An empirical investigation publication-title: International Journal of Medical Informatics – volume: 115 year: 2023 article-title: Physician selection based on user‐generated content considering interactive criteria and risk preferences of patients publication-title: Omega‐International Journal of Management Science – volume: 8 issue: 2 year: 2020 article-title: Analysis of massive online medical consultation service data to understand physicians' economic return: Observational data mining study publication-title: JMIR Medical Informatics – volume: 14 issue: 1 year: 2012 article-title: A changing landscape of physician quality reporting: Analysis of patients' online ratings of their physicians over a 5‐year period publication-title: Journal of Medical Internet Research – volume: 11 start-page: 2925 year: 2020 end-page: 2942 article-title: Mining patient opinion to evaluate the service quality in healthcare: A deep‐learning approach publication-title: Journal of Ambient Intelligence and Humanized Computing – volume: 30 start-page: 872 issue: 3 year: 2019 end-page: 891 article-title: When a doctor knows, it shows: An empirical analysis of doctors' responses in a Q&A Forum of an online healthcare portal publication-title: Information Systems Research – volume: 55 start-page: 941 issue: 4 year: 2013 end-page: 947 article-title: Digital health communities: The effect of their motivation mechanisms publication-title: Decision Support Systems – volume: 29 start-page: 849 issue: 4 year: 2018 end-page: 870 article-title: Exit, voice, and response on digital platforms: An empirical investigation of online management response strategies publication-title: Information Systems Research – volume: 71 start-page: 203 issue: 2 year: 2018 end-page: 214 article-title: Offline retailers expanding online to compete with manufacturers: Strategies and channel power publication-title: Industrial Marketing Management – volume: 32 start-page: 454 year: 2022 end-page: 476 article-title: Doctor recommendation on healthcare consultation platforms: An integrated framework of knowledge graph and deep learning publication-title: Internet Research – volume: 4 start-page: 814 issue: 10 year: 2022 article-title: Forecasting SARS‐CoV‐2 transmission and clinical risk at small spatial scales by the application of machine learning architectures to syndromic surveillance data publication-title: Nature Machine Intelligence – volume: 23 issue: 3 year: 2021 article-title: Effectiveness of interactive tools in online health care communities: Social exchange theory perspective publication-title: Journal of Medical Internet Research – volume: 15 start-page: 68 issue: 3 year: 2022 end-page: 74 article-title: The relationship between the level of trust and self‐efficacy of hospitalized patients and the behavior of medical decision‐making: Using physician‐patient interactions as the mediator publication-title: Chinese Journal of Health Policy – volume: 18 issue: 10 year: 2016 article-title: The impact of the internet on health consultation market concentration: An econometric analysis of secondary data publication-title: Journal of Medical Internet Research – year: 2022 – volume: 19 issue: 20 year: 2022 article-title: Internal or external word‐of‐mouth (WOM), why do patients choose doctors on online medical services (OMSs) single platform in China? publication-title: International Journal of Environmental Research and Public Health – volume: 11 start-page: 1 issue: 1 year: 2022 end-page: 23 article-title: What affects patients' choice of consultant: An empirical study of online doctor consultation service publication-title: Electronic Commerce Research – volume: 13 start-page: 1957 issue: 3 year: 2022 end-page: 1971 article-title: A systematic review of the modelling of patient arrivals in emergency departments publication-title: Quantitative Imaging in Medicine and Surgery – volume: 20 start-page: 551 issue: 4 year: 2016 end-page: 577 article-title: The impact of individual and organizational reputation on physicians' appointments online publication-title: International Journal of Electronic Commerce – volume: 42 start-page: 1245 year: 2023 end-page: 1260 article-title: A deep learning model for online doctor rating prediction publication-title: Journal of Forecasting – volume: 12 start-page: 7603 issue: 1 year: 2022 article-title: Analyzing historical and future acute neurosurgical demand using an AI‐enabled predictive dashboard publication-title: Scientific Reports – volume: 10 year: 2022 article-title: Patient's behavior of selection physician in online health communities: Based on an elaboration likelihood model publication-title: Frontiers in Public Health – volume: 16 start-page: 151 year: 2016 article-title: Exploring the impact of word‐of‐mouth about physicians' service quality on patient choice based on online health communities publication-title: BMC Medical Informatics and Decision Making – start-page: 111 year: 2014 end-page: 126 – volume: 2 start-page: 95 year: 2014 end-page: 95 article-title: Establishing an independent mobile health program for chronic disease self‐management support in Bolivia publication-title: Frontiers in Public Health – volume: 78 start-page: 113 year: 2015 end-page: 121 article-title: Exploring the influence of the online physician service delivery process on patient satisfaction publication-title: Decision Support Systems – ident: e_1_2_9_4_1 doi: 10.3389/fpsyg.2022.886077 – ident: e_1_2_9_6_1 doi: 10.2196/jmir.2003 – volume: 15 start-page: 68 issue: 3 year: 2022 ident: e_1_2_9_3_1 article-title: The relationship between the level of trust and self‐efficacy of hospitalized patients and the behavior of medical decision‐making: Using physician‐patient interactions as the mediator publication-title: Chinese Journal of Health Policy – ident: e_1_2_9_22_1 doi: 10.3389/fpubh.2022.986933 – ident: e_1_2_9_25_1 doi: 10.3390/ijerph192013293 – ident: e_1_2_9_17_1 doi: 10.1080/10864415.2016.1171977 – ident: e_1_2_9_11_1 doi: 10.1016/j.indmarman.2018.01.004 – ident: e_1_2_9_9_1 doi: 10.2196/16765 – ident: e_1_2_9_7_1 doi: 10.1016/j.ijmedinf.2022.104781 – ident: e_1_2_9_20_1 doi: 10.1038/s41598-022-11607-9 – ident: e_1_2_9_26_1 doi: 10.1080/16549716.2023.2179163 – ident: e_1_2_9_10_1 doi: 10.21037/qims-22-268 – ident: e_1_2_9_13_1 doi: 10.1002/for.2953 – ident: e_1_2_9_19_1 doi: 10.3390/healthcare9101401 – ident: e_1_2_9_27_1 doi: 10.1038/s42256-022-00538-9 – ident: e_1_2_9_16_1 doi: 10.1007/978-3-319-08416-9_11 – volume-title: An empirical investigation of their impact on offline appointments year: 2022 ident: e_1_2_9_5_1 – ident: e_1_2_9_31_1 doi: 10.1016/j.dss.2015.05.006 – ident: e_1_2_9_14_1 doi: 10.1287/isre.2017.0749 – ident: e_1_2_9_29_1 doi: 10.1111/j.1365-2753.2009.01297.x – ident: e_1_2_9_12_1 doi: 10.1287/isre.2019.0836 – ident: e_1_2_9_21_1 doi: 10.3389/fpubh.2014.00095 – volume: 11 start-page: 1 issue: 1 year: 2022 ident: e_1_2_9_28_1 article-title: What affects patients' choice of consultant: An empirical study of online doctor consultation service publication-title: Electronic Commerce Research – ident: e_1_2_9_18_1 doi: 10.1186/s12911-016-0386-0 – ident: e_1_2_9_30_1 doi: 10.1016/j.dss.2012.10.047 – ident: e_1_2_9_23_1 doi: 10.2196/21892 – ident: e_1_2_9_32_1 doi: 10.1108/INTR-07-2020-0379 – ident: e_1_2_9_24_1 doi: 10.1007/s12652-019-01434-8 – ident: e_1_2_9_15_1 doi: 10.1016/j.omega.2022.102784 – ident: e_1_2_9_2_1 doi: 10.1016/j.dss.2013.01.003 – ident: e_1_2_9_8_1 doi: 10.2196/jmir.6423 |
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| SubjectTerms | Accuracy Algorithms Clinical information feature selection forecast Forecasting GDP Gross Domestic Product Health services Imbalance Internet Machine learning online medical platform Patient satisfaction Patients Physicians Practitioner patient relationship Projections Registration Satisfaction |
| Title | Forecasting healthcare service volumes with machine learning algorithms |
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