Development of a patient decision aid for treatment resistant depression.

BACKGROUND: Shared decision-making (SDM) involves patients and clinicians choosing treatment jointly. SDM in mental health is hampered by lack of well-developed supporting tools. We describe an evidence-based patient decision aid (PDA) to facilitate SDM for treatment-resistant depression (TRD) following US National Quality Forum standards which are based upon the International Patient Decision Aid Standards (IPDAS). METHODS: A web-based PDA was developed by a multidisciplinary steering committee of clinicians, patient advocates, patients and a decision scientist. Development included creating content consistent with decision-making domains that are impacted by patient preference in TRD. Development was guided by literature review, group conference calls/discussions, patient and clinician interviews (N = 8), high and lower literacy focus groups (N = 11) and pilot study (N = 5). The PDA presents risk-benefit information on domains (e.g., effectiveness, mode of administration, side effects, cost) and includes values clarification exercises. Pilot study patients were administered the Decisional Conflict Scale (DCS) and Decision Self-Efficacy Scale (DSES) prior to and following PDA interaction and clinician SDM. RESULTS: During the pilot, prior to PDA interaction, mean (standard deviation) DCS score was 42.2 (14.4) and DSES score was 86.0 (14.6) out of 100. Following PDA interaction and SDM, DCS decreased (improved) to 28.1 (SD 4.1) and DSES increased to 95.5 (6.7). All patients endorsed that the PDA helped them to: recognize pros and cons of options; understand how treatments were administered, possible side-effects, and likelihood of benefit; recognize what was important relative to the decision; organize thoughts and prepare for a discussion with their clinician. CONCLUSIONS: This PDA may support SDM in TRD. A future trial to determine impact of the present SMD on decision-making quality is warranted. It also highlights gaps in comparative effectiveness trials that could guide equitable shared decision-making.

From patient education to patient engagement: implications for the field of patient education.

OBJECTIVE: Advances in health care require that individuals participate knowledgeably and actively in their health care to realize its full benefit. Implications of these changes for the behavior of individuals and for the practice of patient education are described. METHODS: An "engagement behavior framework" (EBF) was compiled from literature reviews and key informant interviews. To assess the focus of research and interventions on the identified engagement behaviors, the EBF was used to code scientific sessions in professional conferences relevant to patient education in the US in 2006-2007. RESULTS: Many specific behaviors constitute engagement. Professional conferences on patient education show only modest attention to the full range of relevant behaviors. CONCLUSION: People must make informed choices about insurance and clinicians, coordinate communications among providers and manage complex treatments on their own. Not doing so risks preventable illness, suboptimal outcomes and wasted resources. PRACTICE IMPLICATIONS: Increased responsibilities of individuals, sick and well, to find and actively participate in high quality health care provides an opportunity for patient education researchers and clinicians to improve health outcomes by developing innovative strategies to support all individuals to effectively participate in their care to the extent possible.

Assessing the quality of decision support technologies using the International Patient Decision Aid Standards instrument (IPDASi).

OBJECTIVES: To describe the development, validation and inter-rater reliability of an instrument to measure the quality of patient decision support technologies (decision aids). DESIGN: Scale development study, involving construct, item and scale development, validation and reliability testing. SETTING: 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. METHODS: Scale development study, involving construct, item and scale development, validation and reliability testing. PARTICIPANTS: 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. RESULTS: 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). CONCLUSIONS: 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.