Bring on the Machines: Could Machine Learning Improve the Quality of Patient Education Materials? A Systematic Search and Rapid Review

PURPOSE

Clear and trustworthy information is essential for people who are ill. People with cancer, in particular, are targeted with vast quantities of patient education material, but of variable quality. Machine learning technologies are popular across industries for automated tasks, like analyzing language and spotting readability issues. With the experience of patients with cancer in mind, we reviewed whether anyone has proposed, modeled, or applied machine learning technologies for the assessment of patient education materials and explored the utility of this application.

METHODS

We systematically searched the literature to identify English-language articles published in peer-reviewed journals or as conference abstracts that proposed, used, or modeled the use of machine learning technology to assess patient education materials. Specifically, we searched MEDLINE, Web of Science, CINAHL, and Compendex. Two reviewers assessed study eligibility and performed study screening.

RESULTS

We identified 1,570 publications in our search after duplicate removal. After screening, we included five projects (detailed in nine articles) that proposed, modeled, or used machine learning technology to assess the quality of patient education materials. We evaluated the utility of each application across four domains: multidimensionality (2 of 5 applications), patient centeredness (1 of 5 applications), customizability (0 of 5 applications), and development stage (theoretical, 1 of 5 applications; in development, 3 of 5 applications; complete and available, 1 of 5 applications). Combining points across each domain, the mean utlity score across included projects was 1.8 of 5 possible points.

CONCLUSION

Given its potential, machine learning has not yet been leveraged substantially in the assessment of patient education materials. We propose machine learning systems that can dynamically identify problematic language and content by assessing the quality of patient education materials across a range of flexible, customizable criteria. Assessment may help patients and families decide which materials to use and encourage developers to improve materials overall.

Assessing Preference Shift and Effects on Patient Knowledge and Decisional Conflict: Cross-Sectional Study of an Interactive Prostate-Specific Antigen Test Patient Decision Aid

Background

Randomized trials of Web-based decision aids for prostate-specific antigen (PSA) testing indicate that these interventions improve knowledge and reduce decisional conflict. However, we do not know about these tools’ impact on people who spontaneously use a PSA testing patient decision aid on the internet.

Objective

The objectives of this study were to (1) determine the impact of the Web-based PSA Option Grid patient decision aid on preference shift, knowledge, and decisional conflict; (2) identify which frequently asked questions (FAQs) are associated with preference shift; and (3) explore the possible relationships between these outcomes.

Methods

Data were collected between January 1, 2016, and December 30, 2017. Users who accessed the Web-based, interactive PSA Option Grid were provided with 3 options: have a PSA test, no PSA test, or unsure. Users first declared their initial preference and then completed 5 knowledge questions and a 4-item (yes or no) validated decisional conflict scale (Sure of myself, Understand information, Risk-benefit ratio, Encouragement; SURE). Next, users were presented with 10 FAQs and asked to identify their preference for each question based on the information provided. At the end, users declared their final preference and completed the same knowledge and decisional conflict questions. Paired sample t tests were employed to compare before and after knowledge and decisional conflict scores. A multinomial regression analysis was performed to determine which FAQs were associated with a shift in screening preference.

Results

Of all the people who accessed the PSA Option Grid, 39.8% (186/467) completed the interactive journey and associated surveys. After excluding 22 female users, we analyzed 164 responses. At completion, users shifted their preference to “not having the PSA test” (43/164, 26.2%, vs 117/164, 71.3%; P<.001), had higher levels of knowledge (112/164, 68.3%, vs 146/164, 89.0%; P<.001), and lower decisional conflict (94/164, 57.3%, vs 18/164, 11.0%; P<.001). There were 3 FAQs associated with preference shift: “What does the test involve?” “If my PSA level is high, what are the chances that I have prostate cancer?” and “What are the risks?” We did not find any relationship between knowledge, decisional conflict, and preference shift.

Conclusions

Unprompted use of the interactive PSA Option Grid leads to preference shift, increased knowledge, and reduced decisional conflict, which confirms the ability of these tools to influence decision making, even when used outside clinical encounters.

How do healthcare professionals working in accountable care organisations understand patient activation and engagement? Qualitative interviews across two time points

OBJECTIVE

If patient engagement is the new 'blockbuster drug' why are we not seeing spectacular effects? Studies have shown that activated patients have improved health outcomes, and patient engagement has become an integral component of value-based payment and delivery models, including accountable care organisations (ACO). Yet the extent to which clinicians and managers at ACOs understand and reliably execute patient engagement in clinical encounters remains unknown. We assessed the use and understanding of patient engagement approaches among frontline clinicians and managers at ACO-affiliated practices.

DESIGN

Qualitative study; 103 in-depth, semi-structured interviews.

PARTICIPANTS

Sixty clinicians and eight managers were interviewed at two established ACOs.

APPROACH

We interviewed healthcare professionals about their awareness, attitudes, understanding and experiences of implementing three key approaches to patient engagement and activation: 1) goal-setting, 2) motivational interviewing and 3) shared decision making. Of the 60 clinicians, 33 were interviewed twice leading to 93 clinician interviews. Of the 8 managers, 2 were interviewed twice leading to 10 manager interviews. We used a thematic analysis approach to the data.

KEY RESULTS

Interviewees recognised the term 'patient activation and engagement' and had favourable attitudes about the utility of the associated skills. However, in-depth probing revealed that although interviewees reported that they used these patient activation and engagement approaches, they have limited understanding of these approaches.

CONCLUSIONS

Without understanding the concept of patient activation and the associated approaches of shared decision making and motivational interviewing, effective implementation in routine care seems like a distant goal. Clinical teams in the ACO model would benefit from specificity defining key terms pertaining to the principles of patient activation and engagement. Measuring the degree of understanding with reward that are better-aligned for behaviour change will minimise the notion that these techniques are already being used and help fulfil the potential of patient-centred care.

US-based cross-sectional survey of clinicians' knowledge and attitudes about shared decision-making across healthcare professions and specialties

OBJECTIVE

In this study, we aim to compare shared decision-making (SDM) knowledge and attitudes between US-based physician assistants (PAs), nurse practitioners (NPs) and physicians across surgical and family medicine specialties.

SETTING

We administered a cross-sectional, web-based survey between 20 September 2017 and 1 November 2017.

PARTICIPANTS

272 US-based NPs, PA and physicians completed the survey. 250 physicians were sent a generic email invitation to participate, of whom 100 completed the survey. 3300 NPs and PAs were invited, among whom 172 completed the survey. Individuals who met the following exclusion criteria were excluded from participation: (1) lack of English proficiency; (2) area of practice other than family medicine or surgery; (3) licensure other than physician, PA or NP; (4) practicing in a country other than the US.

RESULTS

We found few substantial differences in SDM knowledge and attitudes across clinician types, revealing positive attitudes across the sample paired with low to moderate knowledge. Family medicine professionals (PAs) were most knowledgeable on several items. Very few respondents (3%; 95% CI 1.5% to 6.2%) favoured a paternalistic approach to decision-making.

CONCLUSIONS

Recent policy-level promotion of SDM may have influenced positive clinician attitudes towards SDM. Positive attitudes despite limited knowledge warrant SDM training across occupations and specialties, while encouraging all clinicians to promote SDM. Given positive attitudes and similar knowledge across clinician types, we recommend that SDM is not confined to the patient-physician dyad but instead advocated among other health professionals.

The Promise of Electronic Health Records to Promote Shared Decision Making: A Narrative Review and a Look Ahead

BACKGROUND

Shared decision making (SDM) involves the sharing of best available evidence between patients and providers in the face of difficult decisions. We examine outcomes that occur when electronic health records (EHRs) are purposefully used with the goal of improving SDM and detail which EHR functions can benefit SDM.

METHODS

A systematic search of PubMed yielded 1369 articles. Studies were included only if they used EHR interventions to support SDM and included results that showed impact on SDM. Articles were excluded if they did not measure the impact of the intervention on SDM or did not discuss how SDM had been supported by the EHR.

RESULTS

Five studies demonstrated improved clinical outcomes, positive lifestyle behavior changes, more deliberation from patients regarding use of imaging, and less decisional conflict about medication use among patients with use of EHRs aiding SDM.

DISCUSSION

Few EHRs have integrated SDM, and even fewer evaluations of these exist. EHRs have potential in supporting providers during all steps of SDM. The promise of EHRs to support SDM has yet to be fully exploited.

Interventions for increasing the use of shared decision making by healthcare professionals

BACKGROUND

Shared decision making (SDM) is a process by which a healthcare choice is made by the patient, significant others, or both with one or more healthcare professionals. However, it has not yet been widely adopted in practice. This is the second update of this Cochrane review.

OBJECTIVES

To determine the effectiveness of interventions for increasing the use of SDM by healthcare professionals. We considered interventions targeting patients, interventions targeting healthcare professionals, and interventions targeting both.

SEARCH METHODS

We searched CENTRAL, MEDLINE, Embase and five other databases on 15 June 2017. We also searched two clinical trials registries and proceedings of relevant conferences. We checked reference lists and contacted study authors to identify additional studies.

SELECTION CRITERIA

Randomized and non-randomized trials, controlled before-after studies and interrupted time series studies evaluating interventions for increasing the use of SDM in which the primary outcomes were evaluated using observer-based or patient-reported measures.

DATA COLLECTION AND ANALYSIS

We used standard methodological procedures expected by Cochrane.We used GRADE to assess the certainty of the evidence.

MAIN RESULTS

We included 87 studies (45,641 patients and 3113 healthcare professionals) conducted mainly in the USA, Germany, Canada and the Netherlands. Risk of bias was high or unclear for protection against contamination, low for differences in the baseline characteristics of patients, and unclear for other domains.Forty-four studies evaluated interventions targeting patients. They included decision aids, patient activation, question prompt lists and training for patients among others and were administered alone (single intervention) or in combination (multifaceted intervention). The certainty of the evidence was very low. It is uncertain if interventions targeting patients when compared with usual care increase SDM whether measured by observation (standardized mean difference (SMD) 0.54, 95% confidence interval (CI) -0.13 to 1.22; 4 studies; N = 424) or reported by patients (SMD 0.32, 95% CI 0.16 to 0.48; 9 studies; N = 1386; risk difference (RD) -0.09, 95% CI -0.19 to 0.01; 6 studies; N = 754), reduce decision regret (SMD -0.10, 95% CI -0.39 to 0.19; 1 study; N = 212), improve physical (SMD 0.00, 95% CI -0.36 to 0.36; 1 study; N = 116) or mental health-related quality of life (QOL) (SMD 0.10, 95% CI -0.26 to 0.46; 1 study; N = 116), affect consultation length (SMD 0.10, 95% CI -0.39 to 0.58; 2 studies; N = 224) or cost (SMD 0.82, 95% CI 0.42 to 1.22; 1 study; N = 105).It is uncertain if interventions targeting patients when compared with interventions of the same type increase SDM whether measured by observation (SMD 0.88, 95% CI 0.39 to 1.37; 3 studies; N = 271) or reported by patients (SMD 0.03, 95% CI -0.18 to 0.24; 11 studies; N = 1906); (RD 0.03, 95% CI -0.02 to 0.08; 10 studies; N = 2272); affect consultation length (SMD -0.65, 95% CI -1.29 to -0.00; 1 study; N = 39) or costs. No data were reported for decision regret, physical or mental health-related QOL.Fifteen studies evaluated interventions targeting healthcare professionals. They included educational meetings, educational material, educational outreach visits and reminders among others. The certainty of evidence is very low. It is uncertain if these interventions when compared with usual care increase SDM whether measured by observation (SMD 0.70, 95% CI 0.21 to 1.19; 6 studies; N = 479) or reported by patients (SMD 0.03, 95% CI -0.15 to 0.20; 5 studies; N = 5772); (RD 0.01, 95%C: -0.03 to 0.06; 2 studies; N = 6303); reduce decision regret (SMD 0.29, 95% CI 0.07 to 0.51; 1 study; N = 326), affect consultation length (SMD 0.51, 95% CI 0.21 to 0.81; 1 study, N = 175), cost (no data available) or physical health-related QOL (SMD 0.16, 95% CI -0.05 to 0.36; 1 study; N = 359). Mental health-related QOL may slightly improve (SMD 0.28, 95% CI 0.07 to 0.49; 1 study, N = 359; low-certainty evidence).It is uncertain if interventions targeting healthcare professionals compared to interventions of the same type increase SDM whether measured by observation (SMD -0.30, 95% CI -1.19 to 0.59; 1 study; N = 20) or reported by patients (SMD 0.24, 95% CI -0.10 to 0.58; 2 studies; N = 1459) as the certainty of the evidence is very low. There was insufficient information to determine the effect on decision regret, physical or mental health-related QOL, consultation length or costs.Twenty-eight studies targeted both patients and healthcare professionals. The interventions used a combination of patient-mediated and healthcare professional directed interventions. Based on low certainty evidence, it is uncertain whether these interventions, when compared with usual care, increase SDM whether measured by observation (SMD 1.10, 95% CI 0.42 to 1.79; 6 studies; N = 1270) or reported by patients (SMD 0.13, 95% CI -0.02 to 0.28; 7 studies; N = 1479); (RD -0.01, 95% CI -0.20 to 0.19; 2 studies; N = 266); improve physical (SMD 0.08, -0.37 to 0.54; 1 study; N = 75) or mental health-related QOL (SMD 0.01, -0.44 to 0.46; 1 study; N = 75), affect consultation length (SMD 3.72, 95% CI 3.44 to 4.01; 1 study; N = 36) or costs (no data available) and may make little or no difference to decision regret (SMD 0.13, 95% CI -0.08 to 0.33; 1 study; low-certainty evidence).It is uncertain whether interventions targeting both patients and healthcare professionals compared to interventions of the same type increase SDM whether measured by observation (SMD -0.29, 95% CI -1.17 to 0.60; 1 study; N = 20); (RD -0.04, 95% CI -0.13 to 0.04; 1 study; N = 134) or reported by patients (SMD 0.00, 95% CI -0.32 to 0.32; 1 study; N = 150 ) as the certainty of the evidence was very low. There was insuffient information to determine the effects on decision regret, physical or mental health-related quality of life, or consultation length or costs.

AUTHORS' CONCLUSIONS

It is uncertain whether any interventions for increasing the use of SDM by healthcare professionals are effective because the certainty of the evidence is low or very low.

Improving shared decision-making in advanced Parkinson's disease: protocol of a mixed methods feasibility study

BACKGROUND

In advanced stages of Parkinson's disease (PD), patients and neurologists regularly face complex treatment decisions. Shared decision-making (SDM) can support the process where evidence, the clinician's expertise and the patient's preferences jointly contribute to reach an optimal decision. Here, we describe the rationale of our feasibility study protocol.The aim of the study is to test the feasibility of the SDM intervention by (1) analysing the acceptability of the intervention by users (i.e. professionals and patients), (2) assessing the level of implementation, (3) testing efficacy on a small scale and (4) evaluating the study procedures.

METHODS

Using an uncontrolled before-after mixed methods design, patients in the pre-intervention group will receive information and decisional support as usual. Patients in the post-intervention group will receive the SDM intervention, consisting of an Option Grid™ patient decision aid and a website with supplementary information plus a value clarification tool for both patients and professionals. An Option Grid is a one-page, evidence-based summary of available options, listing the frequently asked questions that patients consider when making treatment decisions. A value clarification tool helps patients identify which option he/she prefers based on attributes in the treatment decision context. Neurologists and PD nurse specialists will receive a 1-h instruction on SDM and how to use the SDM intervention.Through purposive sampling, neurologists and PD nurse specialists will be recruited from both specialised neurology clinics and community-based hospitals. Included professionals will invite consecutive patients who are eligible for the advanced therapies.Data will be collected using questionnaires, interviews and audio observations of the consultations and by tracking users' logging behaviour of the website. Data will be analysed using a mixed methods design.

DISCUSSION

The mixed methods design will create a deeper understanding of how the SDM intervention affects the interactions between professionals (a neurologist and/or a PD nurse specialist) and the patient, when an advanced treatment is chosen. The results of the study will inform the design of an RCT to test the effectiveness of the SDM intervention.

TRIAL REGISTRATION

NTR6649, retrospectively registered 28 August 2017.

Adapting the Breast Cancer Surgery Decision Quality Instrument for Lower Socioeconomic Status: Improving Readability, Acceptability, and Relevance

Introduction. Breast cancer is the second most common malignancy in women. The Decision Quality Instrument (DQI) measures the extent to which patients are informed and involved in breast surgery decisions and receive treatment that aligns with their preferences. There are limited data on the performance of the DQI in women of lower socioeconomic status (SES). Our aims were to 1) examine (and if necessary adapt) the readability, usability, and acceptability of the DQI and 2) explore whether it captures factors important to breast cancer surgery decisions among women of lower SES (relevance). Methods. We conducted semistructured cognitive interviews with women of lower SES (based on insurance status, income, and education) who had completed early-stage breast cancer treatments at three cancer centers. We used a two-step thematic analysis with dual independent coding. The study team (including Patient Partners and a Community Advisory Board) reviewed and refined suggested changes. The revised DQI was presented in two focus groups of breast cancer survivors. Results. We conducted 39 interviews. Participants found most parts of the DQI to be helpful and easy to understand. We made the following suggested changes: 1) added a glossary of key terms, 2) added two answer choices and an open text question in the goals and concerns subscale, 3) reworded the treatment intention question, and 4) revised the knowledge subscale instructions since several women disliked the wording and were unsure of what was expected. Discussion. The readability, usability, acceptability, and relevance of a measure that was primarily developed and validated in women of higher SES required adaptation for optimal use by women of lower SES. Further research will test these adaptations in lower SES populations.

Existing evidence summarization methods cannot guarantee trustworthy patient decision aids

OBJECTIVES

Our aim was to evaluate how organizations that develop patient decision aids conduct their evidence summarization process and assess whether their current processes provide sufficient information to instill confidence that patient decision aids are trustworthy and up to date.

STUDY DESIGN AND SETTING

We identified 23 organizations from a public inventory of patient decision aid developers and included only organizations that have produced five or more tools. These organizations were asked to complete a 17-item survey and to share relevant documents.

RESULTS

Of the 23 organizations, 18 completed the survey, and 15 were eligible for analysis. Most organizations reported using existing systematic reviews and clinical practice guidelines. Seven of 15 had a documented approach for summarizing evidence, but the documents offered varying levels of detail. Common steps identified are tool-relevant question formation, search strategies, evidence appraisals, and updating policies.

CONCLUSIONS

Organizations do not use a standardized process to summarize evidence for the patient decision aids that they develop. This is problematic, given that the information they contain is known to influence patients' decisions. Further attention to how organizations summarize evidence for these tools is required.

Continue, adjust, or stop antipsychotic medication: developing and user testing an encounter decision aid for people with first-episode and long-term psychosis

BACKGROUND

People with psychosis struggle with decisions about their use of antipsychotics. They often want to reduce the dose or stop, while facing uncertainty regarding the effects these decisions will have on their treatment and recovery. They may also fear raising this issue with clinicians. The purpose of this study was to develop and test a shared decision making (SDM) tool to support patients and clinicians in making decisions about antipsychotics.

METHODS

A diverse editorial research team developed an Encounter Decision Aid (EDA) for patients and clinicians to use as part of the psychiatric consultation. The EDA was tested using 24 semistructured interviews with participants representing six stakeholder groups: patients with first-episode psychosis, patients with long-term psychosis, family members, psychiatrists, mental health counselors, and administrators. We used inductive and deductive coding of interview transcripts to identify points to revise within three domains: general impression and purpose of the EDA; suggested changes to the content, wording, and appearance; and usability and potential contribution to the psychiatric consultation.

RESULTS

An EDA was developed in an iterative process that yielded evidence-based answers to five frequently asked questions about antipsychotic medications. Patients with long-term psychosis and mental health counselors suggested more changes and revisions than patients with first-episode psychosis and psychiatrists. Family members suggested more revisions to the answers about potential risks of stopping or adjusting antipsychotics than other respondents.

CONCLUSIONS

The EDA was perceived as potentially useful and feasible in psychiatric routine care, especially if presented during the consultation.

Abstract 162: Does a Telehealth “Virtual Consult” Including Referring Physicians, Specialist Physicians and Patients Increase Shared Decision Making for Patients With Heart Disease?

Background: Shared decision making (SDM) is highly recommended but difficult to implement for patients with severe heart disease referred for cardiac intervention. This study utilized telehealth (TH) to bring referring physicians and their patients together with a specialist physician to exchange treatment options and patient preferences via a triadic “virtual consult”. This study explores the impact of this innovative approach on SDM and patient decisional conflict.

Methods: Two cohorts were included: usual care (UC) and TH. UC patients were seen in a clinic with one of 4 participating physicians, and visits were recorded. Telehealth patients met with their local referring physician in the office, and connected remotely with the specialist physician. One of two decision aids (DA) was used: HealthDecision, an electronic health record-integrated DA for atrial fibrillation, or AS Choice, a paper-based DA for severe aortic stenosis. Patient characteristics were collected via surveys. SDM was measured via Observer OPTION-5, a tool used to rate audio or video-taped clinical encounters, with raters’ agreement being assessed by the Bland-Altman analysis (2-rater pairs). Decisional conflict was measured by a 4-item survey, SURE. Data from two cohorts were compared using the Fisher exact test and the Student’s t test.

Results: Twenty UC visits (5 per physician) were compared with 7 telehealth visits from 4 clinical sites. Patient mean age was 84.3 years and 52% were women. UC patients were older than telehealth patients (87.6 vs. 74.9, p=0.002). Patient decisional conflict was significantly different between the two groups (p=0.02). Telehealth visits had higher OPTION-5 scores than UC visits (99.3 vs. 19.0, p<0.001). (Figure) Rater pairs were used for each observation with evidence of lack of strong agreement in 2 pairs (95% limits of agreement in 3 pairs: [-6.0, 8.8], n=7; [-24.3, 20.7], n=11; [-34.2, 18.7], n=9).

Conclusions: A combined clinical visit with both the referring and specialist physicians, along with their patient in a “virtual consult,” led to decreased patient decisional conflict. Higher OPTION-5 scores were suggested, indicating improvement in the presence of SDM; lack of strong agreement between raters limits this finding and larger studies are needed.

Organizational- and system-level characteristics that influence implementation of shared decision-making and strategies to address them - a scoping review

Background

Shared decision-making (SDM) is poorly implemented in routine care, despite being promoted by health policies. No reviews have solely focused on an in-depth synthesis of the literature around organizational- and system-level characteristics (i.e., characteristics of healthcare organizations and of healthcare systems) that may affect SDM implementation. A synthesis would allow exploration of interventions to address these characteristics. The study aim was to compile a comprehensive overview of organizational- and system-level characteristics that are likely to influence the implementation of SDM, and to describe strategies to address those characteristics described in the literature.

Methods

We conducted a scoping review using the Arksey and O’Malley framework. The search strategy included an electronic search and a secondary search including gray literature. We included publications reporting on projects that promoted implementation of SDM or other decision support interventions in routine healthcare. We screened titles and abstracts, and assessed full texts for eligibility. We used qualitative thematic analysis to identify organizational- and system-level characteristics.

Results

After screening 7745 records and assessing 354 full texts for eligibility, 48 publications on 32 distinct implementation projects were included. Most projects (N = 22) were conducted in the USA. Several organizational-level characteristics were described as influencing the implementation of SDM, including organizational leadership, culture, resources, and priorities, as well as teams and workflows. Described system-level characteristics included policies, clinical guidelines, incentives, culture, education, and licensing. We identified potential strategies to influence the described characteristics, e.g., examples how to facilitate distribution of decision aids in a healthcare institution.

Conclusions

Although infrequently studied, organizational- and system-level characteristics appear to play a role in the failure to implement SDM in routine care. A wide range of characteristics described as supporting and inhibiting implementation were identified. Future studies should assess the impact of these characteristics on SDM implementation more thoroughly, quantify likely interactions, and assess how characteristics might operate across types of systems and areas of healthcare. Organizations that wish to support the adoption of SDM should carefully consider the role of organizational- and system-level characteristics. Implementation and organizational theory could provide useful guidance for how to address facilitators and barriers to change.

Electronic supplementary material

The online version of this article (10.1186/s13012-018-0731-z) contains supplementary material, which is available to authorized users.

Interventions to Engage Affective Forecasting in Health-Related Decision Making: A Meta-Analysis

Background

People often use affective forecasts, or predictions about how a decision will make them feel, to guide medical and health decision making. However, these forecasts are susceptible to biases and inaccuracies that can have consequential effects on decision making and health.

Purpose

A meta-analysis was performed to determine the effectiveness of intervening to address affective forecasting as a means of helping patients make better health-related choices.

Methods

We included between-subjects experimental and intervention studies that targeted variables related to affective forecasting (e.g., anticipated regret, anticipated affect) as a means of changing health behaviors or decisions. We determined the overall effect of these interventions on targeted affective constructs and behavioral outcomes, and whether conceptual and methodological factors moderated these effects.

Results

A total of 133 independent effect sizes were identified from 37 publications (N = 72,020). Overall, affective forecasting interventions changed anticipated regret, d = 0.24, 95% confidence interval (CI) (0.15, 0.32), p < .001, behavior, d = 0.29, 95% CI (0.13, 0.45), p < .001, and behavioral intentions, d = 0.19, 95% CI (0.11, 0.28), p < .001, all measured immediately postintervention. Interventions did not change anticipated positive and negative affect, and effects on intentions and regret did not extend to follow-up time points, ps > .05. Generally, effects were not moderated by conceptual model, intervention intensity, or behavioral context.

Conclusions

Affective forecasting interventions had a small consistent effect on behavioral outcomes regardless of intervention intensity and conceptual framework, suggesting such constructs are promising intervention targets across several health domains.

On a learning curve for shared decision making: Interviews with clinicians using the knee osteoarthritis Option Grid

RATIONAL

Tools used in clinical encounters to illustrate to patients the risks and benefits of treatment options have been shown to increase shared decision making. However, we do not have good information about how these tools are viewed by clinicians and how clinicians think patients would react to their use.

OBJECTIVE

Our aim was to examine clinicians' views about the possible and actual use of tools designed to support patients and clinicians to collaborate and deliberate about treatment options, namely, Option Grid decision aids.

METHOD

We conducted a thematic analysis of qualitative interviews embedded in the intervention phase of a trial of an Option Grid decision aid for osteoarthritis of the knee. Interviews were conducted with 6 participating clinicians before they used the tool and again after clinicians had used the tool with 6 patients.

RESULTS

In the first interview, clinicians voiced concerns that the tool would lead to an increase in encounter duration, patient resistance regarding involvement in decision making, and potential information overload. At the second interview, after minimal training, the clinicians reported that the tool had changed their usual way of communicating, and it was generally acceptable and helpful to integrate it into practice.

DISCUSSION AND CONCLUSIONS

After experiencing the use of Option Grids, clinicians became more willing to use the tools in their clinical encounters with patients. How best to introduce Option Grids to clinicians and adopt their use into practice will need careful consideration of context, workflow, and clinical pathways.

Psychometric properties of the German version of Observer OPTION5

BACKGROUND

In order to conduct studies on shared decision-making (SDM) and to implement SDM in routine practice, psychometrically tested measures are needed. The development of the short 5-item version of the OPTION scale (Observer OPTION⁵) allows to assess SDM from an observer perspective. Observer OPTION⁵ is so far only available in English and Dutch. The aim of this study was to translate the Observer OPTION⁵ rating scale into German and to test its psychometric properties.

METHODS

The German Observer OPTION⁵ was tested in a secondary data analysis of audio-recordings of patient-physician-consultations (N = 79) in German primary care practices. Demographic data were analysed using descriptive statistics. To assess inter- and intra-rater reliability, intraclass correlation coefficients (ICCs) were calculated. For assessing concurrent validity, a correlation (Spearman's Rho) of the sum score of Observer OPTION⁵ and Observer OPTION¹² was calculated.

RESULTS

The consultations dealt with decisions regarding type 2 diabetes (N = 31), chronic back pain (N = 23), depression (N = 20), and other diseases (N = 5). Analysis of inter-rater reliability yielded an ICC of 0.82 for the sum score; across the five single items ICCs ranged between 0.45 and 0.77. For the intra-rater reliability an ICC of 0.83 was observed for the total score; across the five single items ICCs ranged between 0.45 and 0.86. The Observer OPTION⁵ had a mean total score of 11.84 (SD = 11.92) and the Observer OPTION¹² had a mean total score of 10.3 (SD = 7.9), both on a potential range of 0 to 100. The correlation between the total scores of Observer OPTION⁵ and Observer OPTION¹² was r = 0.47 (p = 0.01).

CONCLUSIONS

The results regarding inter- and intra-rater reliability were excellent on the total score level. Observer OPTION⁵ showed moderate concurrent validity using Observer OPTON¹². The results are generally comparable to the results of the original English version of Observer OPTION⁵. The German version of Observer OPTION⁵ can be used in research and evaluation of clinical practice. Nevertheless, further testing is adviced.

Supporting Shared Decision-making for Children's Complex Behavioral Problems: Development and User Testing of an Option Grid™ Decision Aid

There is a lack of research to guide collaborative treatment decision-making for children who have complex behavioral problems, despite the extensive use of mental health services in this population. We developed and pilot-tested a one-page Option Grid™ patient decision aid to facilitate shared decision-making for these situations. An editorial team of parents, child psychiatrists, researchers, and other stakeholders developed the scope and structure of the decision aid. Researchers included information about a carefully chosen number of psychosocial and pharmacological treatment options, using descriptions based on the best available evidence. Using semi-structured qualitative interviews (n = 18), we conducted user testing with four parents and four clinical prescribers and field testing with four parents, four clinical prescribers, and two clinic administrators. The researchers coded and synthesized the interview responses using mixed inductive and deductive methods. Parents, clinicians, and administrators felt the Option Grid had significant value, although they reported that additional training and other support would be required in order to successfully implement the Option Grid and achieve shared decision-making in clinical practice.

A three-goal model for patients with multimorbidity: A qualitative approach

Background

To meet the challenge of multimorbidity in decision making, a switch from a disease‐oriented to a goal‐oriented approach could be beneficial for patients and clinicians. More insight about the concept and the implementation of this approach in clinical practice is needed.

Objective

This study aimed to develop conceptual descriptions of goal‐oriented care by examining the perspectives of general practitioners (GPs) and clinical geriatricians (CGs), and how the concept relates to collaborative communication and shared decision making with elderly patients with multimorbidity.

Method

Qualitative interviews with GPs and CGs were conducted and analyzed using thematic analysis.

Results

Clinicians distinguished disease‐ or symptom‐specific goals, functional goals and a new type of goals, which we labelled as fundamental goals. “Fundamental goals” are goals specifying patient's priorities in life, related to their values and core relationships. These fundamental goals can be considered implicitly or explicitly in decision making or can be ignored. Reasons to explicate goals are the potential mismatch between medical standards and patient preferences and the need to know individual patient values in case of multimorbidity, including the management in acute situations.

Conclusion

Based on the perspectives of clinicians, we expanded the concept of goal‐oriented care by identifying a three‐level goal hierarchy. This model could facilitate collaborative goal‐setting for patients with multiple long‐term conditions in clinical practice. Future research is needed to refine and validate this model and to provide specific guidance for medical training and practice.

A three-talk model for shared decision making: multistage consultation process

Objectives To revise an existing three-talk model for learning how to achieve shared decision making, and to consult with relevant stakeholders to update and obtain wider engagement.Design Multistage consultation process.Setting Key informant group, communities of interest, and survey of clinical specialties.Participants 19 key informants, 153 member responses from multiple communities of interest, and 316 responses to an online survey from medically qualified clinicians from six specialties.Results After extended consultation over three iterations, we revised the three-talk model by making changes to one talk category, adding the need to elicit patient goals, providing a clear set of tasks for each talk category, and adding suggested scripts to illustrate each step. A new three-talk model of shared decision making is proposed, based on "team talk," "option talk," and "decision talk," to depict a process of collaboration and deliberation. Team talk places emphasis on the need to provide support to patients when they are made aware of choices, and to elicit their goals as a means of guiding decision making processes. Option talk refers to the task of comparing alternatives, using risk communication principles. Decision talk refers to the task of arriving at decisions that reflect the informed preferences of patients, guided by the experience and expertise of health professionals.Conclusions The revised three-talk model of shared decision making depicts conversational steps, initiated by providing support when introducing options, followed by strategies to compare and discuss trade-offs, before deliberation based on informed preferences.

Online, Interactive Option Grid Patient Decision Aids and their Effect on User Preferences

Background. Randomized trials have shown that patient decision aids can modify users’ preferred healthcare options, but research has yet to identify the attributes embedded in these tools that cause preferences to shift. Objectives. The aim of this study was to investigate people’s preferences as they used decision aids for 5 health decisions and, for each of the following: 1) determine if using the interactive Option Grid led to a pre–post shift in preferences; 2) determine which frequently asked questions (FAQs) led to preference shifts; 3) determine the FAQs that were rated as the most important as users compared options. Methods. Interactive Option Grid decision aids enable users to view attributes of available treatment or screening options, rate their importance, and specify their preferred options before and after decision aid use. The McNemar–Bowker paired test was used to compare stated pre–post preferences. Multinomial logistic regressions were conducted to investigate possible associations between covariates and preference shifts. Results. Overall, 626 users completed the 5 most-used tools: 1) Amniocentesis test: yes or no? ( n = 73); 2) Angina: treatment options ( n = 88); 3) Breast cancer: surgical options ( n = 265); 4) Prostate Specific Antigen (PSA) test: yes or no? ( n = 82); 5) Statins for heart disease risk: yes or no? ( n = 118). The breast cancer, PSA, and statins Option Grid decision aids generated significant preference shifts. Generally, users shifted their preference when presented with the description of the available treatment options, and the risk associated with each option. Conclusion. The use of decision aids for some, but not all health decisions, was accompanied by a shift in user preferences. Users typically valued information associated with risks, and chose more risk averse options after completing the interactive tool.

Right For Me: protocol for a cluster randomised trial of two interventions for facilitating shared decision-making about contraceptive methods

INTRODUCTION

Despite the observed and theoretical advantages of shared decision-making in a range of clinical contexts, including contraceptive care, there remains a paucity of evidence on how to facilitate its adoption. This paper describes the protocol for a study to assess the comparative effectiveness of patient-targeted and provider-targeted interventions for facilitating shared decision-making about contraceptive methods.

METHODS AND ANALYSIS

We will conduct a 2×2 factorial cluster randomised controlled trial with four arms: (1) video+prompt card, (2) decision aids+training, (3) video+prompt card and decision aids+training and (4) usual care. The clusters will be clinics in USA that deliver contraceptive care. The participants will be people who have completed a healthcare visit at a participating clinic, were assigned female sex at birth, are aged 15-49 years, are able to read and write English or Spanish and have not previously participated in the study. The primary outcome will be shared decision-making about contraceptive methods. Secondary outcomes will be the occurrence of a conversation about contraception in the healthcare visit, satisfaction with the conversation about contraception, intended contraceptive method(s), intention to use a highly effective method, values concordance of the intended method(s), decision regret, contraceptive method(s) used, use of a highly effective method, use of the intended method(s), adherence, satisfaction with the method(s) used, unintended pregnancy and unwelcome pregnancy. We will collect study data via longitudinal patient surveys administered immediately after the healthcare visit, four weeks later and six months later.

ETHICS AND DISSEMINATION

We will disseminate results via presentations at scientific and professional conferences, papers published in peer-reviewed, open-access journals and scientific and lay reports. We will also make an anonymised copy of the final participant-level dataset available to others for research purposes.

TRIAL REGISTRATION NUMBER

ClinicalTrials.gov Identifier: NCT02759939.