Purpose:    Patient decision aids (pDAs) are complex interventions designed to help patients make informed decisions by a) reducing bias and b) encourage active thinking. This research examined the added value of decision aid components, over and above the provision of evidence-based information, on people’s decision making about dialysis options for established renal failure whilst developing the Yorkshire Dialysis Decision Aid (YoDDA).

Method:    Staff and students from 30 UK Universities participated in five linked, web-based studies using experimental designs to test the added value of decision guidance, information structure and categorisation, value clarification, and patient narrative components, over and above evidence-based, accessible information. Electronic tracking and questionnaires assessed: information utilisation, treatment choice, decisional conflict, knowledge, values, perception of risk, others’ opinion, and resource acceptability.

Result:    Study 1 (n = 138) adding decision guidance (decision tree diagram + choice talk statements) to an information aid increased knowledge and reduced mixed feelings about the decision.    Study 2 (n = 348) structuring treatment option information in parallel, and by attribute, with an even categorisation (2 haemodialysis options; 2 peritoneal dialysis options) supported people’s dialysis decision making in a better way than treatment option information presented sequentially and with an uneven categorisation (1 hospital option; 3 home options).    Study 3 (n = 351) using value-clarification tasks about the importance of lifestyle activities (work, holidays, family, etc) rather than treatment attributes (location, blood, overnight, etc) enhanced the value-choice consistency more than treatment attribute tasks or no tasks.    Study 4 (n = 406) providing a decision-outcome narrative, or a decision-guidance plus a decision-outcome narrative, encouraged participants to choose the treatment mentioned in the narrative than groups without a narrative. Two different decision-outcome narratives counterbalanced this effect. A decision-guidance narrative alone did not affect choices.    Study 5 (n = 171) using a lifestyle activity value-clarification task may counterbalance the affect of narratives on choices more than other treatment attribute value-clarification tasks.

Conclusion:    Explicit decision representation and guidance, and information structure and categorisation, enable people to evaluate more treatment option details before making a decision than providing evidence-based and accessible information alone. Patient narratives are more likely to bias participants’ choices than facilitate informed decision making. Value-clarification tasks’ contribution to pDAs may depend on the type of task and the timing of pDA evaluation.

Purpose: To develop and test the efficacy of a web-based Intelligent Tutoring System (ITS) based on fuzzy-trace theory (FTT) that engages women in a tutorial dialogue to help them understand and make decisions about genetic testing for breast cancer risk.

Methods: This interactive tutorial of about one hour appears to be the first use of an ITS in medical decision-making. Tutorial dialogues address questions such as, "what should someone do if she finds out that she has inherited an altered BRCA gene?" Using a set of "expectations texts" and Latent Semantic Analysis, a conversational agent (avatar) tries to "understand" what participants are saying and respond appropriately. Information pertaining to breast cancer and genetic risk was taken from the National Cancer Institute (NCI) web site, and vetted by medical experts. Three female avatars appearing to be of varying ethnicities present the information orally, visually, in brief video clips and in writing. The figure is a screen shot from the tutorial.    The efficacy of the ITS was tested in a randomized, controlled experiment equating time on task. Participants were randomly assigned to one of three conditions: the ITS; studying pages from the NCI web site covering comparable materials; or studying irrelevant information (control). Participants were then given two tests of declarative knowledge about breast cancer and genetic risk, and twelve scenarios applying their knowledge assessing breast cancer risk. These tasks were first pilot tested and vetted by medical experts.

Results: In two tests of declarative knowledge about breast cancer, one from the research literature, and one on the NCI web site content, participants in the ITS group scored significantly higher than both comparison groups. The NCI group also scored significantly higher than the control group. Effect sizes are considered large following Cohen's conventions.    Participants assessed breast cancer risk on twelve scenarios providing gist-based ordinal rankings (low, medium, high) of breast cancer including conditional probabilities. A multiple signal detection theory analysis provided independent measures of sensitivity to risk, (d') and criteria for distinguishing among risk levels. The ITS group was significantly more sensitive in distinguishing among all levels of risk than the control group.

Conclusions: This ITS may be fruitfully applied in educating laypeople and assisting their medical decision-making by enhancing gist-based comprehension and reducing class-inclusion interference.

Purpose: Patient decision aids (DAs) have been shown to help patients make informed healthcare decisions.  Dashboards were developed as a business intelligence tool to monitor key performance indicators and provide insight into day-to-day operations.  Our goal was to develop a dashboard that incorporates shared decision making (SDM) measures to monitor the effect of DAs on patient decision making in routine clinical care.

Method: Eligible patients are systematically referred to the Center for Shared Decision Making at Dartmouth Hitchcock Medical Center for decision support programs.  Participants: 1) complete pre-DA questionnaire, 2) watch a condition specific video DA, 3) complete post-DA questionnaire. Measures: DA loan tracking (checkout/return dates, referring department/provider, distribution method), pre/post-video intention, and multiple choice knowledge quiz.  DA topics: PSA screening, knee osteoarthritis, hip osteoarthritis, breast cancer surgery, breast reconstruction, herniated disc, and spinal stenosis.  Clinical and SDM questionnaire data are summarized by topic into a single page html dashboard report and provided to clinicians on a monthly basis.  The html dashboard can be e-mailed, posted on a website, or printed on paper.

Result: From November 2009 – April 2012, 7009 DAs were distributed.  Across conditions, similar patterns emerged (Table 1). After watching the video decision aid: fewer patients were unsure about their decision (X², p ≤ .05*) and most patients (65%) had acceptable knowledge scores.  Historic and current DA referral counts are reported by department and provider to provide feedback to clinicians.

Conclusion: Regular reporting of DA prescribing patterns and decision process measures can be used to monitor the impact of decision aids on informed patient choice in routine care.  Dashboards also have the potential to identify ‘missed opportunity’ patients that could benefit from decision aids as well act as an instrument to assess continuous quality improvement in health care.

Table 1.   DA title	DA loans - n Returned SDM Questionnaire (%)	Unsure Patients		Knowledge Score (> 68%)
		Before DA	After DA	After DA
PSA screening	2019 (28%)	28%	18%*	89%
Knee osteoarthritis	1343 (53%)	31%	24%*	64%
Hip osteoarthritis	758 (53%)	26%	23%*	64%
Breast cancer surgery	437 (53%)	38%	28%*	69%
Breast reconstruction	335 (45%)	15%	15%	72%
Spinal stenosis	1164 (34%)	35%	26%*	45%
Herniated disc	953 (46%)	27%	20%*	49%

Purpose: Decision aids (DAs) have been shown to facilitate shared decision making (SDM) about cancer screening. Pre-visit delivery to appropriate patients is challenging, but allows the patient to arrive at the visit better prepared to make their decision. Our goal was to use a web-based survey system to identify and provide prostate cancer screening (PSA) and colorectal cancer screening (CRC) DAs to appropriate patients prior to a preventive medicine visit.

Methods: Patients complete a web-based health history questionnaire before their preventive medicine appointment. Age and gender appropriate patients are asked further questions to determine eligibility for PSA or CRC screening. Screening-eligible patients are presented with a brief description of the screening decision to be made, asked their screening preference, and offered the choice of a video or print DA. Patients are then asked to complete questions assessing their knowledge and values regarding the screening question. Feedback on incorrect answers to knowledge questions and another offer of further information are displayed on a written report given to the patient. Patients´ screening choice and responses to knowledge and values questions are fed forward to a clinician report available at the visit.

Results: From January 2008 – March 2011, 4384 PSA and 11493 CRC questionnaires were completed. The questionnaire properly identified patients eligible for screening: 2962 (68%) for PSA and 2187 (19%)for CRC. 15% of eligible patients requested a DA, with the majority of those preferring the written format over video. 16% of patients declined a DA because they preferred the doctor make the decision. Many patients declined a DA because they “already know enough to make their decision” (50% for PSA, 31% for CRC).  PSA knowledge scores for patients who “already knew enough” were significantly higher than those requesting additional information (mean(SD): 79(21) vs. 63(32), T-test, p < 0.0001).  This prior knowledge was due in large part to 41% of patients having received the PSA DA during a previous intervention.

Conclusions: A web based health history questionnaire provides an efficient means to identify patients eligible for cancer screening and offer them DAs before an appointment. Although many patients appropriately chose not to view a DA based on prior knowledge and experience, DA viewing rates among the remaining patients were lower than hoped.

Purpose: To evaluate the performance of a standard decision aid (DA) in an underserved population with and without a scripted, low-literacy educational supplement.

Method:  We assessed understanding of a standard DA on early stage prostate cancer treatment (Informed Medical Decisions Foundation) using scripted face to face interviews of African American men recruited from three low-income clinics. To avoid interfering in decision making with an untested intervention, men age ≥ 40 without a history of prostate cancer were included. Patients viewed the DA and then participated in a low-literacy educational supplement that did not rely on the patients’ reading or math skills. The low-literacy supplement allowed patients to choose between colloquial and medical terms for genitourinary (GU) function to augment explanation of DA content. Symbols were used to explain treatment side effects using the patient’s chosen language; chance wheels, poker chips, or cards served as tangible representations of the probabilities of treatment side effects. We measured decisional conflict, understanding of treatment side effects and prevalence of side effects, after patients viewed the DA, and after they received the low-literacy supplement.

Result:  A total of 62 men were interviewed; 94% were African American. Average age was 50; median annual income $9,438. Most patients (53%) had a high school degree, 24% had less than a high school education, and 6% had a college degree. Median health literacy was 7^th-8^thgrade measured by the Rapid Estimate of Adult Literacy in Medicine. Only 34% could calculate a simple fraction and percents. Participants generally did not understand the DA: 54% could name the cancer treatments discussed without prompting and 44% understood the icon arrays used to illustrate probabilities of treatment side effects.  Comprehension of medical terms used in the DA was poor (e.g. only 15% knew the word “incontinence” and 60% understood “impotent”).  Most patients preferred colloquial terms for GU function and anatomy. After participating in the low-literacy educational supplement, comprehension of treatment side effects and prevalence were improved to ≈90% or more (p<0.05); and decisional conflict decreased statistically significantly (from mean total 21.2 to 11.7).

Conclusion: DA content, including icon arrays, was poorly understood by most study patients. Comprehension of prostate cancer treatment side effects and decisional conflict was significantly improved by explicitly addressing health literacy.