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Forecasting, uncertainty and risk; perspectives on clinical decision-making in preventive and curative medicine

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  • Makridakis, Spyros
  • Kirkham, Richard
  • Wakefield, Ann
  • Papadaki, Maria
  • Kirkham, Joanne
  • Long, Lisa

Abstract

Should we screen the population routinely for the presence of breast or prostatic cancer? This simple proposition masks a landscape of complexities, including the economics of screening, the prevalence and probability of the disease, desired frequencies of intervention and a willingness to adopt preventive screening. These ‘risk factors’ form part of a broader landscape of uncertainty that characterises the intricacies of clinical decision-making. Deepening our understanding of the way in which clinicians evaluate risk and uncertainty requires a framing of insights into language, communication, psychology and epistemology. This paper explores perspectives in forecasting and uncertainty as a basis for understanding individuals’ perceptions of risk when assessing their options in both preventative and curative medicine. At the heart of the issue is the prevalence of diagnostic error; this paper argues for the use of systematised approaches to medical error management and inclusive approaches to research in the field. The advantages of augmenting the management of unforeseen consequences through an improved understanding of the issues that are of concern to patients, carers, and medical practitioners alike forms a key construct in this paper. We conclude with an exploration of potential opportunities for improvements in medical practice: changes that may reduce the disbenefits of uncertainty and enhance the management of the general risks associated with clinical decision-making.

Suggested Citation

  • Makridakis, Spyros & Kirkham, Richard & Wakefield, Ann & Papadaki, Maria & Kirkham, Joanne & Long, Lisa, 2019. "Forecasting, uncertainty and risk; perspectives on clinical decision-making in preventive and curative medicine," International Journal of Forecasting, Elsevier, vol. 35(2), pages 659-666.
    • Handle: RePEc:eee:intfor:v:35:y:2019:i:2:p:659-666
    DOI: 10.1016/j.ijforecast.2017.11.003
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    References listed on IDEAS

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    1. Waring, Justin J., 2005. "Beyond blame: cultural barriers to medical incident reporting," Social Science & Medicine, Elsevier, vol. 60(9), pages 1927-1935, May.
    2. John P A Ioannidis, 2005. "Why Most Published Research Findings Are False," PLOS Medicine, Public Library of Science, vol. 2(8), pages 1-1, August.
    3. Sujan, Mark A. & Habli, Ibrahim & Kelly, Tim P. & Gühnemann, Astrid & Pozzi, Simone & Johnson, Christopher W., 2017. "How can health care organisations make and justify decisions about risk reduction? Lessons from a cross-industry review and a health care stakeholder consensus development process," Reliability Engineering and System Safety, Elsevier, vol. 161(C), pages 1-11.
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    Cited by:

    1. Petropoulos, Fotios & Apiletti, Daniele & Assimakopoulos, Vassilios & Babai, Mohamed Zied & Barrow, Devon K. & Ben Taieb, Souhaib & Bergmeir, Christoph & Bessa, Ricardo J. & Bijak, Jakub & Boylan, Joh, 2022. "Forecasting: theory and practice," International Journal of Forecasting, Elsevier, vol. 38(3), pages 705-871.
      • Fotios Petropoulos & Daniele Apiletti & Vassilios Assimakopoulos & Mohamed Zied Babai & Devon K. Barrow & Souhaib Ben Taieb & Christoph Bergmeir & Ricardo J. Bessa & Jakub Bijak & John E. Boylan & Jet, 2020. "Forecasting: theory and practice," Papers 2012.03854, arXiv.org, revised Jan 2022.
    2. Feng Xiao & Kin Keung Lai & Chun Kit Lau & Bhagwat Ram, 2024. "Robust Overbooking for No-Shows and Cancellations in Healthcare," Mathematics, MDPI, vol. 12(16), pages 1-18, August.

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