The Promise and Peril of Healthcare Forecasting

被引:0
作者
Wharam, J. Frank [1 ]
Weiner, Jonathan P. [2 ]
机构
[1] Harvard Univ, Sch Med, Dept Populat Med, Boston, MA 02114 USA
[2] Johns Hopkins Bloomberg Sch Publ Hlth, Baltimore, MD USA
关键词
HIGH-RISK PATIENTS; PREDICTION; MANAGEMENT; MODELS;
D O I
暂无
中图分类号
R19 [保健组织与事业(卫生事业管理)];
学科分类号
摘要
Health plans and physician groups increasingly use sophisticated tools to predict individual patient outcomes. Such analytics will accelerate as US medicine enters the digital age. Promising applications of forecasting include better targeting of disease management as well as innovative patient care approaches such as personalized health insurance and clinical decision support systems. In addition, stakeholders will use predictions to advance their organizational agendas, and unintended consequences could arise. Forecasting-based interventions might have uncertain effectiveness, focus on cost savings rather than long-term health, or specifically exclude disadvantaged populations. Policy makers, health plans, and method developers should adopt strategies that address these concerns in order to maximize the benefit of healthcare forecasting on the long-term health of patients.
引用
收藏
页码:E82 / E85
页数:4
相关论文
共 50 条
  • [11] A dual hybrid forecasting model for support of decision making in healthcare management
    Purwanto
    Eswaran, Chikkannan
    Logeswaran, Rajasvaran
    ADVANCES IN ENGINEERING SOFTWARE, 2012, 53 : 23 - 32
  • [12] BIODIVERSITY Penguins in peril
    Oli, Madan K.
    NATURE CLIMATE CHANGE, 2014, 4 (08) : 667 - 668
  • [13] Towards reliable forecasting of healthcare capacity needs: A scoping review and evidence mapping
    Grontved, Simon
    Kirkeby, Mette Jorgine
    Johnsen, Soren Paaske
    Mainz, Jan
    Valentin, Jan Brink
    Jensen, Christina Mohr
    INTERNATIONAL JOURNAL OF MEDICAL INFORMATICS, 2024, 189
  • [14] Forecasting future crop suitability with microclimate data
    Gardner, A. S.
    Maclean, I. M. D.
    Gaston, K. J.
    Butikofer, L.
    AGRICULTURAL SYSTEMS, 2021, 190
  • [15] Evolutionary Hybrid System for Energy Consumption Forecasting for Smart Meters
    Izidio, Diogo M. F.
    de Mattos Neto, Paulo S. G.
    Barbosa, Luciano
    de Oliveira, Joao F. L.
    Marinho, Manoel Henrique da Nobrega
    Rissi, Guilherme Ferretti
    ENERGIES, 2021, 14 (07)
  • [16] Editorial: ‘Make a promise — Keep a promise’
    I Ryder
    Journal of Brand Management, 2002, 9 (6) : 408 - 409
  • [17] Harvesting the promise of AOPs: An assessment and recommendations
    Carusi, Annamaria
    Davies, Mark R.
    De Grandis, Giovanni
    Escher, Beate I.
    Hodges, Geoff
    Leung, Kenneth M. Y.
    Whelan, Maurice
    Willett, Catherine
    Ankley, Gerald T.
    SCIENCE OF THE TOTAL ENVIRONMENT, 2018, 628-629 : 1542 - 1556
  • [18] Elevating security and disease forecasting in smart healthcare through artificial neural synchronized federated learning
    Hai, Tao
    Sarkar, Arindam
    Aksoy, Muammer
    Karmakar, Rahul
    Manna, Sarbajit
    Prasad, Amrita
    CLUSTER COMPUTING-THE JOURNAL OF NETWORKS SOFTWARE TOOLS AND APPLICATIONS, 2024, 27 (06): : 7889 - 7914
  • [19] Analysing and forecasting the energy consumption of healthcare facilities in the short and medium term. A case study
    Koc, Ali
    Seckiner, Serap Ulusam
    OPERATIONS RESEARCH AND DECISIONS, 2024, 34 (03) : 165 - 192
  • [20] Forecasting sustainability of healthcare supply chains using deep learning and network data envelopment analysis
    Azadi, Majid
    Yousefi, Saeed
    Saen, Reza Farzipoor
    Shabanpour, Hadi
    Jabeen, Fauzia
    JOURNAL OF BUSINESS RESEARCH, 2023, 154