Applying incentives to adopting shared decision-making with patient decision tools

Shared decision-making (SDM) is a well-known approach where clinicians and patients share evidence-based information about medical interventions and their risks and benefits, while taking into account the patient’s concerns and preferences. Tools such as patients’ decision aids (PDAs) have been developed to support SDM. Patients using PDAs improve their understanding of the treatment options, are more likely to participate in the decision-making process, and can as a result avoid unwanted treatment [1]. Despite the reported positive effects, decision-making tools are not often implemented in routine clinical care [2]. There is a clear need for sustainable incentives for both individuals [3] and organisations to engage in the adoption and use of a PDAs.

In the last several years, there has been growing interest by academics and policy-makers in advancing SDM in routine healthcare. Many countries are attempting to commit to an SDM approach and its inclusion in a number of clinical practice procedures by developing specific health policies [4]. Despite these efforts, the uptake in the real-world application stays poor[1].

There has been less focus on the characteristics of the healthcare system in which SDM with its decision aids are embedded

There are various factors influencing the implementation of SDM which have been conceptualized into the several models and frameworks. For instance, such factors could be categorized by the level of impact into four main groups: individual-level (patient, clinicians), interactional-level (patient-clinician), organizational-level and system-level factors [1]. Many efforts have already been made to study the interaction between clinicians and patients, but there has been less focus on the characteristics of the healthcare system in which the SDM and PDAs are embedded and which guide the work of the healthcare organizations [5]. To shed more light on this topic we focus on one of the system-level factors – incentives. Incentives are defined as external stimuli that serve as a motive for implementation [6]. We can differentiate between financial and non-financial incentives [7].

Providing financial and non-financial incentives

Financial incentives used for implementation of SDM and PDAs can be, for instance, payment models (i.e. bonuses, saving contracts, payment for activities etc.). These could be especially attractive to healthcare organizations. In practice, we can see that the payment models can influence the “amount of time a HCP has for a patient’s visit” and in turn the use of the PDAs tool itself [1]. In case of individuals like clinic staff working within the healthcare system, the research shows that monetary factors can discourage or ‘‘cheapen’’ desired behaviors that may be linked to more intrinsic motivations such as altruism or self-determination [3]. Furthermore, it has been shown that the financial incentives to promote an adoption of new approaches have a short-term positive effect, but they do not lead to sustained use when rewards are withdrawn [8].

Non-financial incentives, on the other hand, can be, for instance, the issuing of accreditation/certification criteria when applying SDM. The policy-makers could include the degree to which SDM with PDAs are included in the HCP´s workflow as a criterion for the accreditation [1]. This would make it possible for the organizations to differ from each other and be more motivated to adopt the SDM approach and its PDAs. In case of individuals, non-financial incentives are based as emphasized above on the intrinsic motivation of the individuals and other factors like “social/professional role and identity” or “belief about consequences” [6]. Possible examples of such incentives are: the clinic staff seeing the real-life and immediate positive effects on patient’s care [3] or continuing in educational activities by receiving education credits [7].

All in all, the implementation of SDM is frequently included in the healthcare policies of individual countries and seems to generally be encouraged. However, the level of utilization of the SDM approach and its tools in the routine practice stays poor. As the literature indicates, incentives are an important strategy at the system-level to facilitate the implementation of SDM with its PDAs. Nevertheless, it should be recognized that even successful behavioral changes can diminish once incentives are removed. There is therefore a need for such incentives for individuals and organizations to be sustainable.

My Post (6)

Paula Zietzsch

Paula has a background in Health Economics and works at OptiMedis in different national and EU projects with a particular interest in shared decision-making. As a Research & Innovation Manager, she focuses on implementing evidence-based interventions in routine clinical care.

  1. Scholl, Isabelle, Allison LaRussa, Pola Hahlweg, Sarah Kobrin, und Glyn Elwyn. „Organizational- and System-Level Characteristics That Influence Implementation of Shared Decision-Making and Strategies to Address Them — a Scoping Review“. Implementation Science 13, Nr. 1 (Dezember 2018): 40.
  2. Gayer, Christopher C, Matthew J Crowley, William F Lawrence, Jennifer M Gierisch, Bridget Gaglio, John W Williams, Evan R Myers, Amy Kendrick, Jean Slutsky, und Gillian D Sanders. „An Overview and Discussion of the Patient-Centered Outcomes Research Institute’s Decision Aid Portfolio“. Journal of Comparative Effectiveness Research 5, Nr. 4 (Juli 2016): 407–15.
  3. Kostick, Kristin M., Meredith Trejo, Robert J. Volk, Jerry D. Estep, und J.S. Blumenthal-Barby. „Using Nudges to Enhance Clinicians’ Implementation of Shared Decision Making With Patient Decision Aids“. MDM Policy & Practice 5, Nr. 1 (Januar 2020): 238146832091590.
  4. Härter, Martin, Nora Moumjid, Jacques Cornuz, Glyn Elwyn, und Trudy van der Weijden. „International accomplishments in policy, research and implementation.“ ZEFQ Z Evidenz Fortbild Qual G., Nr. 123–124 (o. J.): 1–5.
  5. Elwyn, Glyn, Dominick L. Frosch, und Sarah Kobrin. „Implementing Shared Decision-Making: Consider All the Consequences“. Implementation Science 11, Nr. 1 (Dezember 2015): 114.
  6. Munro, Sarah, Ruth Manski, Kyla Z. Donnelly, Daniela Agusti, Gabrielle Stevens, Michelle Banach, Maureen B. Boardman, u. a. „Investigation of Factors Influencing the Implementation of Two Shared Decision-Making Interventions in Contraceptive Care: A Qualitative Interview Study among Clinical and Administrative Staff“. Implementation Science 14, Nr. 1 (Dezember 2019): 95.
  7. Flottorp, Signe A, Andrew D Oxman, Jane Krause, Nyokabi R Musila, Michel Wensing, Maciek Godycki-Cwirko, Richard Baker, und Martin P Eccles. „A Checklist for Identifying Determinants of Practice: A Systematic Review and Synthesis of Frameworks and Taxonomies of Factors That Prevent or Enable Improvements in Healthcare Professional Practice“. Implementation Science 8, Nr. 1 (Dezember 2013): 35.
  8. Uy, Visith, Suepattra G. May, Caroline Tietbohl, und Dominick L. Frosch. „Barriers and Facilitators to Routine Distribution of Patient Decision Support Interventions: A Preliminary Study in Community-Based Primary Care Settings: Distribution of Patient Decision Support“. Health Expectations 17, Nr. 3 (Juni 2014): 353–64.

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