Background

Patient-centered care is one of the fundamental aspects of high-quality health care. Central to patient-centered care is shared decision making (SDM), which is a collaborative process in which clinicians and patients jointly participate when making decisions about health care.1 In a SDM approach, healthcare practitioners and patients require access to information to make a decision, while understanding and respecting both the practitioners' expertise and the patients' preferences and values. It involves a process in which a patient and a practitioner collaborate to discuss possible options, ensure that the patient is well informed, and make a choice of care that is consistent with the patient's values and preferences and the best available scientific evidence.1,2 The benefits of SDM are widely reported in literature and include improved knowledge of risks and benefits by the patient, improved patient participation in the decision making process, improved accuracy of "risk" perception, decreased decisional conflict, less patient indecision and increased patient comfort with the final decision.1-4 Shared decision making does not only benefit patients and improve their experience with health services but it may also increase the uptake of scientific evidence by healthcare professionals, which is a basic tenet of evidence-based practice.3 As a result, SDM can reduce the unnecessary variations in care that occur when clinicians' opinions dominate the decision making process.1

While SDM is applicable in most situations, it is particularly relevant under conditions of uncertainty.1,3 Uncertainty can occur when the scientific evidence is absent, equivocal or when conflicting evidence offers no definitive conclusions. It can also arise when a decision is elective or "preference-sensitive". A preference-sensitive decision is "one in which there is no clear scientific evidence to demonstrate the superiority of one treatment, and the treatment choices may vary in ways that matter to patients".4^(p.2) Whether or not to undergo surgery, for example, is a preference-sensitive decision that requires consideration of the patients' attitudes toward the risks and benefits of surgical and non-surgical treatment alternatives. Elective surgical procedures such as joint replacement for osteoarthritis or treatment for early-stage breast cancer or localized prostate cancer offer the patient choices, including conservative options. The SDM process ensures that the patient understands not only the risks and benefits associated with the surgery but also alternative options, in the context of their own life.2 A systematic review evaluated the use and outcomes of SDM in elective surgery and found that it can reduce decision conflict and improve the decision quality for patients making choices about elective surgery.4 The results suggest that greater patient involvement in the decision making can lead to a more positive experience with health care regardless of their ultimate surgical decision.

Although SDM has clear benefits in enhancing patient-centered care, it has not been widely adopted in clinical practice.5,6 The literature suggests there are patient-, practitioner- and systems-related barriers associated with the adoption of SDM.6,7 For patients, for example, lack of familiarity and experience in evaluating and expressing their values and preferences is a major obstacle in engaging with physicians.6,7 Practitioners, on the other hand, have indicated they have neither the knowledge nor the time to engage in the kind of dialog that SDM demands.6,7 Systems-related factors also conspire against full implementation of SDM, with economic incentives encouraging short patient-practitioner engagement rather than the lengthy interactions required in SDM.7

Decision aids have been proposed as a strategy to address some of these commonly reported barriers and as a medium to promote SDM.2,5,7,8 They are evidence-based tools designed to inform patients about their choices and allow them to articulate their values and preferences.2,5 Decision aids provide information about the health condition, options, costs, associated harms and benefits, and uncertainties. The aim is to engage the patients and help them make an informed decision. A Cochrane systematic review found evidence to support the use of decision aids in improving patients' knowledge regarding options and outcomes, and providing more accurate risk perception, resulting in greater comfort with the decision and fewer people remaining undecided.8 Patients generally feel more informed about options and clearer regarding their personal values. Decision aids can also encourage patients to take a more active role in decision making and improve their perception and understanding of risk.8 There is also some evidence to suggest that they can improve the congruence between the chosen option and the patient's values and preferences.8

Despite the benefits associated with SDM, and the use of decision aids in particular, its uptake in clinical practice remains a challenge for many healthcare practitioners. Strategies are required to promote a sustainable approach for implementing SDM and decision aids in everyday practice. However, to understand the effects of these strategies, it is important to have a means by which SDM can be measured. Currently, there is wide variation in the measures used for evaluating SDM, and there is no consensus in the literature on how best to measure SDM. This lack of agreement poses methodological challenges not only to healthcare practitioners but also researchers.9-12 A measurement framework has been proposed by researchers in the field, which includes three major domains or constructs: decision antecedents, decision making process and decision outcomes.9,10 Decision antecedents refer to the characteristics of the patient, healthcare practitioner or organization that can influence the decision making process, for example, patient preference for participation in decision making, patient knowledge, competencies of the healthcare practitioner relevant to SDM or the availability of tools (e.g. decision aids) within the organization.9,10 Decision making process refers to the behavior of the patient and healthcare practitioner during the consultation or the deliberation that occurs (or does not occur) between the patient and the health practitioner when making a decision about care or treatment.9,10 Decision outcomes refer to the decision quality (i.e. extent to which the patients receive a treatment that match their preferences/goals), decision regret and experiences of patients with care.9,10 A standardized set of core constructs to be measured would be ideal; however until they are identified, the International Patient Decision Aids Standards group emphasizes the measurement of decision process and decision quality for evaluating the effectiveness of SDM and decision aids.10

A search of the JBI Database of Systematic Reviews and Implementation Reports, Cochrane Database of Systematic Reviews, MEDLINE and CINAHL found no systematic review that has explicitly examined strategies for facilitating or improving healthcare practitioners' adoption of SDM, particularly for elective surgery patients.

Inclusion criteria

Types of participants

The current review will consider two types of participants: patients for elective surgery or any healthcare practitioner involved in the care of patients for elective surgery. Elective surgery is an operative procedure for conditions that do not involve a medical emergency.13

Types of interventions

The current review will include any strategy aimed at facilitating or improving healthcare practitioners' adoption and implementation of SDM. Studies that investigate the effect of strategies targeted at patients, healthcare practitioners or health system/organization will be considered. These interventions can include, but are not limited to, structured tools (e.g. option grids and decision cards), coaching, education and training, distribution of informative materials, audit and feedback, multifaceted interventions based on barriers assessment and financial incentives.

Types of comparators

The current review will consider studies with any (including an alternative SDM intervention, no intervention or usual practice) or no comparator interventions.

Outcomes

The current review will focus on the measurement of decision process and decision outcome (e.g. decision quality), measures highlighted by the International Patient Decision Aids Standards group. Studies that examine both decision process and decision outcomes will be included, as well as those that measure decision process only. However, studies that measure decision outcomes only will be excluded as without the decision process measure, the fundamental piece of the presumed linkage between patient's involvement in the deliberation process and improved decision outcome is missing.14 Decision process could be assessed using a patient-, practitioner- or observer-rated questionnaires such as OPTION scale, Decision Support Analysis Tool, Perceived Involvement in Care Scale, Facilitation of Patient Involvement Scale or other validated scales.9,11 Other measures such as health practitioners' self-reported SDM behavior, patients' perceived involvement or level of control in decision making or observer's perspectives on practitioner or patient behavior relevant to SDM process will also be included. Decision outcomes, on the other hand, could be assessed using a patient-, practitioner- or observer-rated questionnaires such as COMRADE scale, Decisional Conflict Scale, Satisfaction with Decision Scale, Decision Regret Scale, SURE scale or other validated questionnaires. Other measures such as patients' satisfaction with the treatment decision or patients' experience with their care will also be considered.

Types of studies

The current review will consider quantitative studies including randomized controlled trials, pseudo-randomized controlled trials, quasi-experimental studies (e.g. one group pre-test-post-test study and post-test only) and prospective cohort studies.

Search strategy

The search will seek published quantitative studies written in the English language. A three-step search strategy will be utilized in this review. An initial limited search of MEDLINE and CINAHL will be undertaken followed by analysis of the text words contained in the title and abstract, and of the index terms used to describe the article. A second search using all identified keywords and index terms will then be undertaken across all included databases. Third, the reference list of all identified articles will be searched for additional studies.

The electronic databases of MEDLINE, CINAHL, Embase and PsycINFO will be searched, with no date limit. Registries including Cochrane Central Trials Register, Current Controlled Trials, ClincalTrials.gov and the Australian New Zealand Trial registry will also be searched. In addition, published systematic reviews of intervention studies on SDM will be hand-searched to further identify relevant primary studies.

A proposed MEDLINE (on Ovid platform) search strategy is included in Appendix I.

Selection of studies

Two reviewers will independently screen all titles and abstracts against the inclusion criteria. Full-text copies of potentially relevant papers will be retrieved for further examination. Any disagreements will be resolved through discussion or with a third reviewer if required.

Assessment of methodological quality

Papers selected for retrieval will be assessed by two independent reviewers using the standardized critical appraisal instruments from the JBI System for the Unified Management, Assessment and Review of Information package (SUMARI, Appendix II). Any disagreements between reviewers will be resolved through discussion or with a third reviewer if required.

Data extraction

A data extraction tool will be developed for this review. The following data will be extracted from relevant studies:

* Study design

* Geographic setting

* Healthcare setting/practice setting

* Patient characteristics (e.g. clinical condition)

* Healthcare practitioner characteristics (e.g. discipline, age, gender and professional experience)

* Intervention characteristics (e.g. type, components, intensity, duration, delivery, format and key personnel involved)

* Potential barriers and enablers to implementation of intervention

* Outcomes and results.

Data extraction will be carried out by one reviewer with verification by another reviewer to minimize bias and potential errors in data extraction. Authors of primary studies will be contacted for missing information or to clarify unclear data.

Data synthesis

Results from individual studies, where possible, will be pooled in statistical meta-analysis using RevMan 5.3 (The Nordic Cochrane Centre, Cochrane; Copenhagen, Denmark). All results will be subject to double data entry. Effect sizes expressed as odds ratio (for categorical data) and standardized mean differences (for continuous data) and their 95% confidence intervals will be calculated for analysis. Heterogeneity will be assessed statistically using the standard chi-square and I-square. Subgroup analyses, if appropriate, will also be considered. Where statistical pooling is not possible, the findings will be presented in narrative form to address the review questions. Tables and figures will be used as appropriate to aid in data presentation.

Acknowledgements

The current systematic review is funded by the Health Services Charitable Gifts Board, Adelaide, Australia.

Appendix I: MEDLINE (on Ovid platform) search strategy

Appendix II: Critical appraisal tools

JBI critical appraisal checklist for randomized controlled trials

JBI critical appraisal checklist for quasi-experimental studies

JBI critical appraisal checklist for cohort studies

References