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ABSTRACT: OBJECTIVE: To describe the exploratory use of short decision support tools for patients, called Option Grids. Option Grids are summary tables, using one side of paper to enable rapid comparisons of options, using questions that patients frequently ask (FAQs) and designed for face-to-face clinical encounters. To date, most evidence about 'patient decision aids' has been based on tools with high content levels, designed for patients to use independently, either before or after visits. METHODS: We studied the use of Option Grids in a quality improvement project, collecting field notes and conducting interviews with clinical teams. RESULTS: In the 'Making Good Decisions in Collaboration' (MAGIC) program, clinicians found that using Option Grids made it easier to explain the existence of options and reported a 'handover' effect, where patient involvement in decision making was enhanced. CONCLUSION: Option Grids made options more visible and clinicians found it easier to undertake shared decision making when these tools were available. Used in a collaborative way, they enhance patients' confidence and voice, increasing their involvement in collaborative dialogs. PRACTICE IMPLICATIONS: Further work to confirm these preliminary findings is required, to measure processes and to assess whether these tools have similar impact in other clinical settings.
Patient Education and Counseling 07/2012; · 2.31 Impact Factor
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Glyn Elwyn,
Dominick Frosch, Richard Thomson,
Natalie Joseph-Williams,
Amy Lloyd,
Paul Kinnersley,
Emma Cording,
Dave Tomson,
Carole Dodd,
Stephen Rollnick,
Adrian Edwards,
Michael Barry
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ABSTRACT: The principles of shared decision making are well documented but there is a lack of guidance about how to accomplish the approach in routine clinical practice. Our aim here is to translate existing conceptual descriptions into a three-step model that is practical, easy to remember, and can act as a guide to skill development. Achieving shared decision making depends on building a good relationship in the clinical encounter so that information is shared and patients are supported to deliberate and express their preferences and views during the decision making process. To accomplish these tasks, we propose a model of how to do shared decision making that is based on choice, option and decision talk. The model has three steps: a) introducing choice, b) describing options, often by integrating the use of patient decision support, and c) helping patients explore preferences and make decisions. This model rests on supporting a process of deliberation, and on understanding that decisions should be influenced by exploring and respecting "what matters most" to patients as individuals, and that this exploration in turn depends on them developing informed preferences.
Journal of General Internal Medicine 05/2012; 27(10):1361-7. · 2.83 Impact Factor
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ABSTRACT: WHAT ABOUT POLICY REGARDING SDM? SDM is on the national policy agenda and has been prioritised as part of the health reform bill currently going through the Houses of Parliament. The NHS Constitution emphasises patients' right to be involved in decisions and this is reinforced in standards set by professional regulators. WHAT ABOUT TOOLS - DECISION SUPPORT FOR PATIENTS? The UK governments have invested in patient information and a few decision aids are freely available on public websites. WHAT ABOUT PROFESSIONAL INTEREST AND IMPLEMENTATION? There is interest in SDM and in collaborative care planning, but this is not yet the norm in clinical practice and few clinicians have received training in the topic. Several programmes are under way to encourage implementation of SDM. WHAT DOES THE FUTURE LOOK LIKE? Future developments will depend on the extent of clinical commitment and on whether there are sufficient funds available to invest in the promotion of SDM at a time when health care resources are tightly constrained.
Zeitschrift für Evidenz Fortbildung und Qualität im Gesundheitswesen 01/2011; 105(4):300-4.
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ABSTRACT: Decision aids prepare people to participate in decisions that involve weighing benefits, harms, and scientific uncertainty.
To evaluate the effectiveness of decision aids for people facing treatment or screening decisions.
For this update, we searched from January 2006 to December 2009 in MEDLINE (Ovid); Cochrane Central Register of Controlled Trials (CENTRAL, The Cochrane Library, issue 4 2009); CINAHL (Ovid) (to September 2008 only); EMBASE (Ovid); PsycINFO (Ovid); and grey literature. Cumulatively, we have searched each database since its start date.
We included published randomised controlled trials (RCTs) of decision aids, which are interventions designed to support patients' decision making by providing information about treatment or screening options and their associated outcomes, compared to usual care and/or alternative interventions. We excluded studies in which participants were not making an active treatment or screening decision.
Two review authors independently screened abstracts for inclusion, extracted data, and assessed potential risk of bias. The primary outcomes, based on the International Patient Decision Aid Standards, were:A) decision attributes;B) decision making process attributes.Secondary outcomes were behavioral, health, and health system effects. We pooled results of RCTs using mean differences (MD) and relative risks (RR), applying a random effects model.
Of 34,316 unique citations, 86 studies involving 20,209 participants met the eligibility criteria and were included. Thirty-one of these studies are new in this update. Twenty-nine trials are ongoing. There was variability in potential risk of bias across studies. The two criteria that were most problematic were lack of blinding and the potential for selective outcome reporting, given that most of the earlier trials were not registered.Of 86 included studies, 63 (73%) used at least one measure that mapped onto an IPDAS effectiveness criterion: A) criteria involving decision attributes: knowledge scores (51 studies); accurate risk perceptions (16 studies); and informed value-based choice (12 studies); and B) criteria involving decision process attributes: feeling informed (30 studies) and feeling clear about values (18 studies).A) Criteria involving decision attributes:Decision aids performed better than usual care interventions by increasing knowledge (MD 13.77 out of 100; 95% confidence interval (CI) 11.40 to 16.15; n = 26). When more detailed decision aids were compared to simpler decision aids, the relative improvement in knowledge was significant (MD 4.97 out of 100; 95% CI 3.22 to 6.72; n = 15). Exposure to a decision aid with expressed probabilities resulted in a higher proportion of people with accurate risk perceptions (RR 1.74; 95% CI 1.46 to 2.08; n = 14). The effect was stronger when probabilities were expressed in numbers (RR 1.93; 95% CI 1.58 to 2.37; n = 11) rather than words (RR 1.27; 95% CI 1.09 to 1.48; n = 3). Exposure to a decision aid with explicit values clarification compared to those without explicit values clarification resulted in a higher proportion of patients achieving decisions that were informed and consistent with their values (RR 1.25; 95% CI 1.03 to 1.52; n = 8).B) Criteria involving decision process attributes:Decision aids compared to usual care interventions resulted in: a) lower decisional conflict related to feeling uninformed (MD -6.43 of 100; 95% CI -9.16 to -3.70; n = 17); b) lower decisional conflict related to feeling unclear about personal values (MD -4.81; 95% CI -7.23 to -2.40; n = 14); c) reduced the proportions of people who were passive in decision making (RR 0.61; 95% CI 0.49 to 0.77; n = 11); and d) reduced proportions of people who remained undecided post-intervention (RR 0.57; 95% CI 0.44 to 0.74; n = 9). Decision aids appear to have a positive effect on patient-practitioner communication in the four studies that measured this outcome. For satisfaction with the decision (n = 12) and/or the decision making process (n = 12), those exposed to a decision aid were either more satisfied or there was no difference between the decision aid versus comparison interventions. There were no studies evaluating the decision process attributes relating to helping patients to recognize that a decision needs to be made or understand that values affect the choice.C) Secondary outcomesExposure to decision aids compared to usual care continued to demonstrate reduced choice of: major elective invasive surgery in favour of conservative options (RR 0.80; 95% CI 0.64 to 1.00; n = 11). Exposure to decision aids compared to usual care also resulted in reduced choice of PSA screening (RR 0.85; 95% CI 0.74 to 0.98; n = 7). When detailed compared to simple decision aids were used, there was reduced choice of menopausal hormones (RR 0.73; 95% CI 0.55 to 0.98; n = 3). For other decisions, the effect on choices was variable. The effect of decision aids on length of consultation varied from -8 minutes to +23 minutes (median 2.5 minutes). Decision aids do not appear to be different from comparisons in terms of anxiety (n = 20), and general health outcomes (n = 7), and condition specific health outcomes (n = 9). The effects of decision aids on other outcomes (adherence to the decision, costs/resource use) were inconclusive.
New for this updated review is evidence that: decision aids with explicit values clarification exercises improve informed values-based choices; decision aids appear to have a positive effect on patient-practitioner communication; and decision aids have a variable effect on length of consultation.Consistent with findings from the previous review, which had included studies up to 2006: decision aids increase people's involvement, and improve knowledge and realistic perception of outcomes; however, the size of the effect varies across studies. Decision aids have a variable effect on choices. They reduce the choice of discretionary surgery and have no apparent adverse effects on health outcomes or satisfaction. The effects on adherence with the chosen option, patient-practitioner communication, cost-effectiveness, and use with developing and/or lower literacy populations need further evaluation. Little is known about the degree of detail that decision aids need in order to have positive effects on attributes of the decision or decision-making process.
Cochrane database of systematic reviews (Online) 01/2011; · 5.72 Impact Factor
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BMJ (Clinical research ed.). 01/2010; 341:c5146.
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Glyn Elwyn,
Annette M O'Connor,
Carol Bennett,
Robert G Newcombe,
Mary Politi,
Marie-Anne Durand,
Elizabeth Drake,
Natalie Joseph-Williams,
Sara Khangura,
Anton Saarimaki, [......],
Angela Coulter,
Karen Eden,
Martin Härter,
Margaret Holmes Rovner,
Nora Moumjid,
Dawn Stacey, Richard Thomson,
Tim Whelan,
Trudy van der Weijden,
Adrian Edwards
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ABSTRACT: To describe the development, validation and inter-rater reliability of an instrument to measure the quality of patient decision support technologies (decision aids).
Scale development study, involving construct, item and scale development, validation and reliability testing.
There has been increasing use of decision support technologies--adjuncts to the discussions clinicians have with patients about difficult decisions. A global interest in developing these interventions exists among both for-profit and not-for-profit organisations. It is therefore essential to have internationally accepted standards to assess the quality of their development, process, content, potential bias and method of field testing and evaluation.
Scale development study, involving construct, item and scale development, validation and reliability testing.
Twenty-five researcher-members of the International Patient Decision Aid Standards Collaboration worked together to develop the instrument (IPDASi). In the fourth Stage (reliability study), eight raters assessed thirty randomly selected decision support technologies.
IPDASi measures quality in 10 dimensions, using 47 items, and provides an overall quality score (scaled from 0 to 100) for each intervention. Overall IPDASi scores ranged from 33 to 82 across the decision support technologies sampled (n = 30), enabling discrimination. The inter-rater intraclass correlation for the overall quality score was 0.80. Correlations of dimension scores with the overall score were all positive (0.31 to 0.68). Cronbach's alpha values for the 8 raters ranged from 0.72 to 0.93. Cronbach's alphas based on the dimension means ranged from 0.50 to 0.81, indicating that the dimensions, although well correlated, measure different aspects of decision support technology quality. A short version (19 items) was also developed that had very similar mean scores to IPDASi and high correlation between short score and overall score 0.87 (CI 0.79 to 0.92).
This work demonstrates that IPDASi has the ability to assess the quality of decision support technologies. The existing IPDASi provides an assessment of the quality of a DST's components and will be used as a tool to provide formative advice to DSTs developers and summative assessments for those who want to compare their tools against an existing benchmark.
PLoS ONE 02/2009; 4(3):e4705. · 4.09 Impact Factor
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Glyn Elwyn,
Annette O'Connor,
Dawn Stacey,
Robert Volk,
Adrian Edwards,
Angela Coulter, Richard Thomson,
Alexandra Barratt,
Michael Barry,
Steven Bernstein, [......],
Vikki Entwistle,
Deb Feldman-Stewart,
Margaret Holmes-Rovner,
Hilary Llewellyn-Thomas,
Nora Moumjid,
Al Mulley,
Cornelia Ruland,
Karen Sepucha,
Alan Sykes,
Tim Whelan
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ABSTRACT: To develop a set of quality criteria for patient decision support technologies (decision aids).
Two stage web based Delphi process using online rating process to enable international collaboration.
Individuals from four stakeholder groups (researchers, practitioners, patients, policy makers) representing 14 countries reviewed evidence summaries and rated the importance of 80 criteria in 12 quality domains on a 1 to 9 scale. Second round participants received feedback from the first round and repeated their assessment of the 80 criteria plus three new ones.
Aggregate ratings for each criterion calculated using medians weighted to compensate for different numbers in stakeholder groups; criteria rated between 7 and 9 were retained.
212 nominated people were invited to participate. Of those invited, 122 participated in the first round (77 researchers, 21 patients, 10 practitioners, 14 policy makers); 104/122 (85%) participated in the second round. 74 of 83 criteria were retained in the following domains: systematic development process (9/9 criteria); providing information about options (13/13); presenting probabilities (11/13); clarifying and expressing values (3/3); using patient stories (2/5); guiding/coaching (3/5); disclosing conflicts of interest (5/5); providing internet access (6/6); balanced presentation of options (3/3); using plain language (4/6); basing information on up to date evidence (7/7); and establishing effectiveness (8/8).
Criteria were given the highest ratings where evidence existed, and these were retained. Gaps in research were highlighted. Developers, users, and purchasers of patient decision aids now have a checklist for appraising quality. An instrument for measuring quality of decision aids is being developed.
BMJ (Clinical research ed.). 09/2006; 333(7565):417.
