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Background Standardisation of outcome measures is integral to value-based healthcare (VBHC), which may conflict with patient-centred care, focusing on personalisation.Objectives We aimed to provide an overview of measures used to assess the effect of VBHC implementation and to examine to what extent the evidence indicates that VBHC supports patient-centred care.Design A scoping review guided by the Joanna Briggs Institute methodology.Sources of evidence We searched the following databases on 18 February 2021: Cochrane Library, EMBASE, MEDLINE and Web of Science.Eligibility criteria We included empirical papers assessing the effect of the implementation of VBHC, published after introduction of VBHC in 2006.Data extraction and synthesis Two independent reviewers double-screened papers and data were extracted by one reviewer and checked by the other. We classified the study measures used in included papers into six categories: process indicator, cost measure, clinical outcome, patient-reported outcome, patient-reported experience or clinician-reported experience. We then assessed the patient-centredness of the study measures used.Results We included 39 studies using 94 unique study measures. The most frequently used study measures (n=72) were process indicators, cost measures and clinical outcomes, which rarely were patient-centred. The less frequently used (n=20) patient-reported outcome and experience measures often measured a dimension of patient-centred care.Conclusion Our study shows that the evidence on VBHC supporting patient-centred care is limited, exposing a knowledge gap in VBHC research. The most frequently used study measures in VBHC research are not patient-centred. The major focus seems to be on measures of quality of care defined from a provider, institution or payer perspective.

Objectives To identify what patient-related characteristics have been reported to be associated with the occurrence of shared decision-making (SDM) about treatment.Design Scoping review.Eligibility criteria Peer-reviewed articles in English or Dutch reporting on associations between patient-related characteristics and the occurrence of SDM for actual treatment decisions.Information sources COCHRANE Library, Embase, MEDLINE, PsycInfo, PubMed and Web of Science were systematically searched for articles published until 25 March 2019.Results The search yielded 5289 hits of which 53 were retained. Multiple categories of patient characteristics were identified: (1) sociodemographic characteristics (eg, gender), (2) general health and clinical characteristics (eg, symptom severity), (3) psychological characteristics and coping with illness (eg, self-efficacy) and (4) SDM style or preference. Many characteristics showed no association or unclear relationships with SDM occurrence. For example, for female gender positive, negative and, most frequently, non-significant associations were seen.Conclusions A large variety of patient-related characteristics have been studied, but for many the association with SDM occurrence remains unclear. The results will caution often-made assumptions about associations and provide an important step to target effective interventions to foster SDM with all patients.

Objective Many treatment decisions are preference-sensitive and call for shared decision-making, notably when benefits are limited or uncertain, and harms impact quality of life. We explored if clinical practice guidelines (CPGs) acknowledge preference-sensitive decisions in how they motivate and phrase their recommendations.Design We performed a qualitative analysis of the content of CPGs and verified the results in semistructured interviews with CPG panel members.Setting Dutch oncology CPGs issued in 2010 or later, concerning primary treatment with curative intent.Participants 14 CPG panel members.Main outcomes For treatment recommendations from six CPG modules, two researchers extracted the following: strength of recommendation in terms of the Grading of Recommendations Assessment, Development and Evaluation and its consistency with the CPG text; completeness of presentation of benefits and harms; incorporation of patient preferences; statements on the panel’s benefits–harm trade-off underlying recommendation; and advice on patient involvement in decision-making.Results We identified 32 recommendations, 18 were acknowledged preference-sensitive decisions. Three of 14 strong recommendations should have been weak based on the module text. The reporting of benefits and harms, and their probabilities, was sufficiently complete and clear to inform the strength of the recommendation in one of the six modules only. Numerical probabilities were seldom presented. None of the modules presented information on patient preferences. CPG panel’s preferences were not made explicit, but appeared to have impacted 15 of 32 recommendations. Advice to involve patients and their preferences in decision-making was given for 20 recommendations (14 weak). Interviewees confirmed these findings. Explanations for lack of information were, for example, that clinicians know the information and that CPGs must be short. Explanations for trade-offs made were cultural-historical preferences, compliance with daily care, presumed role of CPGs and lack of time.Conclusions The motivation and phrasing of CPG recommendations do not stimulate choice awareness and a neutral presentation of options, thus hindering shared decision-making.

Objectives To (1) provide an up-to-date overview of shared decision making (SDM)-models, (2) give insight in the prominence of components present in SDM-models, (3) describe who is identified as responsible within the components (patient, healthcare professional, both, none), (4) show the occurrence of SDM-components over time, and (5) present an SDM-map to identify SDM-components seen as key, per healthcare setting.Design Systematic review.Eligibility criteria Peer-reviewed articles in English presenting a new or adapted model of SDM.Information sources Academic Search Premier, Cochrane, Embase, Emcare, PsycINFO, PubMed, and Web of Science were systematically searched for articles published up to and including September 2, 2019.Results Forty articles were included, each describing a unique SDM-model. Twelve models were generic, the others were specific to a healthcare setting. Fourteen were based on empirical data, 26 primarily on analytical thinking. Fifty-three different elements were identified and clustered into 24 components. Overall, Describe treatment options was the most prominent component across models. Components present in >50% of models were: Make the decision (75%), Patient preferences (65%), Tailor information (65%), Deliberate (58%), Create choice awareness (55%), and Learn about the patient (53%). In the majority of the models (27/40), both healthcare professional and patient were identified as actors. Over time, Describe treatment options and Make the decision are the two components which are present in most models in any time period. Create choice awareness stood out for being present in a markedly larger proportion of models over time.Conclusions This review provides an up-to-date overview of SDM-models, showing that SDM-models quite consistently share some components but that a unified view on what SDM is, is still lacking. Clarity about what SDM constitutes is essential though for implementation, assessment, and research purposes. A map is offered to identify SDM-components seen as key.Trial registration PROSPERO registration CRD42015019740