PST11 THE USE OF MULTI-CRITERIA DECISION METHODS IN HEALTH CARE. DOES METHOD USED INFLUENCE OUTCOME?

OBJECTIVES: To investigate how the choice of multicriteria decision method influences outcome (ranking criteria and criteria weights). Population. A convenience sample of 28 subjects, 12 healthy and 16 cognitively impaired. METHODS: Based on a literature review, 5 multicriteria methods were chosen for comparison including: Kepner-tregoe analysis (KTA), simple multi attribute rating technique (SMART), SMART using swing weights (SWING), Analytic Hierarchy Process (AHP) and Conjoint Analysis (CA). Four attributes of treatment were identified (impact, duration, and end-result of treatment and associated risks). Subjects were asked to both rank and rate the importance of these attributes with each method. The order of methods was randomized and the total length of the interview was restricted to one hour. Some subjects therefore did not use all methods. Subjects were interviewed either once (n = 14) or twice (n = 14) (Only the results of the first measurement are presented) RESULTS: The highest percentages of rank reversals were found between CA and other methods (55–62%). The lowest percentage of rank reversals was between KTA and SMART (18%). The percentage of rank reversals was significantly higher in impaired population (An average of 54% compared to 36% in unimpaired population). When comparing actual weights, AHP and SMART correlate highly with all other methods except CA. CONCLUSIONS: The high percentages in rank reversal and divergent correlation between individual weights (especially CA compared to other methods) show that the method chosen influences outcome. This has to be taken into account when the ranks or weights are used in multi-criteria decision analysis to make actual treatment decisions. The dissimilar methodology of CA might explain the high percentages of rank-reversals and low correlation between this method and other. Also, the design of the survey might have influenced CA weights and ranking

Opportunities for personalised follow-up care among patients with breast cancer: A scoping review to identify preference-sensitive decisions

Abstract Introduction Current follow‐up arrangements for breast cancer do not optimally meet the needs of individual patients. We therefore reviewed the evidence on preferences and patient involvement in decisions about breast cancer follow‐up to explore the potential for personalised care. Methods Studies published between 2008 and 2017 were extracted from MEDLINE, PsycINFO and EMBASE. We then identified decision categories related to content and form of follow‐up. Criteria for preference sensitiveness and patient involvement were compiled and applied to determine the extent to which decisions were sensitive to patient preferences and patients were involved. Results Forty‐one studies were included in the full‐text analysis. Four decision categories were identified: “surveillance for recurrent/secondary breast cancer; consultations for physical and psychosocial effects; recurrence‐risk reduction by anti‐hormonal treatment; and improving quality of life after breast cancer.” There was little evidence that physicians treated decisions about anti‐hormonal treatment, menopausal symptoms, and follow‐up consultations as sensitive to patient preferences. Decisions about breast reconstruction were considered as very sensitive to patient preferences, and patients were usually involved. Conclusion Patients are currently not involved in all decisions that affect them during follow‐up, indicating a need for improvements. Personalised follow‐up care could improve resource allocation and the value of care for patients

User needs elicitation via analytic hierarchy process (AHP). A case study on a Computed Tomography (CT) scanner

Background: The rigorous elicitation of user needs is a crucial step for both medical device design and purchasing. However, user needs elicitation is often based on qualitative methods whose findings can be difficult to integrate into medical decision-making. This paper describes the application of AHP to elicit user needs for a new CT scanner for use in a public hospital. Methods: AHP was used to design a hierarchy of 12 needs for a new CT scanner, grouped into 4 homogenous categories, and to prepare a paper questionnaire to investigate the relative priorities of these. The questionnaire was completed by 5 senior clinicians working in a variety of clinical specialisations and departments in the same Italian public hospital. Results: Although safety and performance were considered the most important issues, user needs changed according to clinical scenario. For elective surgery, the five most important needs were: spatial resolution, processing software, radiation dose, patient monitoring, and contrast medium. For emergency, the top five most important needs were: patient monitoring, radiation dose, contrast medium control, speed run, spatial resolution. Conclusions: AHP effectively supported user need elicitation, helping to develop an analytic and intelligible framework of decision-making. User needs varied according to working scenario (elective versus emergency medicine) more than clinical specialization. This method should be considered by practitioners involved in decisions about new medical technology, whether that be during device design or before deciding whether to allocate budgets for new medical devices according to clinical functions or according to hospital department

Emerging Use of Early Health Technology Assessment in Medical Product Development: A Scoping Review of the Literature

Early health technology assessment is increasingly being used to support health economic evidence development during early stages of clinical research. Such early models can be used to inform research and development about the design and management of new medical technologies to mitigate the risks, perceived by industry and the public sector, associated with market access and reimbursement. Over the past 25 years it has been suggested that health economic evaluation in the early stages may benefit the development and diffusion of medical products. Early health technology assessment has been suggested in the context of iterative economic evaluation alongside phase I and II clinical research to inform clinical trial design, market access, and pricing. In addition, performing early health technology assessment was also proposed at an even earlier stage for managing technology portfolios. This scoping review suggests a generally accepted definition of early health technology assessment to be “all methods used to inform industry and other stakeholders about the potential value of new medical products in development, including methods to quantify and manage uncertainty”. The present review also aimed to identify recent published empirical studies employing an early-stage assessment of a medical product. With most included studies carried out to support a market launch, the dominant methodology was early health economic modeling. Further methodological development is required, in particular, by combining systems engineering and health economics to manage uncertainty in medical product portfolios