Faculty Bibliography

PURPOSE: Usability testing can be used to evaluate human-computer interaction (HCI) and communication in shared decision making (SDM) for patient-provider behavioral change and behavioral contracting. Traditional evaluations of usability using scripted or mock patient scenarios with think-aloud protocol analysis provide a way to identify HCI issues. In this paper we describe the application of these methods in the evaluation of the Avoiding Diabetes Thru Action Plan Targeting (ADAPT) tool, and test the usability of the tool to support the ADAPT framework for integrated care counseling of pre-diabetes. The think-aloud protocol analysis typically does not provide an assessment of how patient-provider interactions are effected in "live" clinical workflow or whether a tool is successful. Therefore, "Near-live" clinical simulations involving applied simulation methods were used to compliment the think-aloud results. This complementary usability technique was used to test the end-user HCI and tool performance by more closely mimicking the clinical workflow and capturing interaction sequences along with assessing the functionality of computer module prototypes on clinician workflow. We expected this method to further complement and provide different usability findings as compared to think-aloud analysis. Together, this mixed method evaluation provided comprehensive and realistic feedback for iterative refinement of the ADAPT system prior to implementation. METHODS: The study employed two phases of testing of a new interactive ADAPT tool that embedded an evidence-based shared goal setting component into primary care workflow for dealing with pre-diabetes counseling within a commercial physician office electronic health record (EHR). Phase I applied usability testing that involved "think-aloud" protocol analysis of eight primary care providers interacting with several scripted clinical scenarios. Phase II used "near-live" clinical simulations of five providers interacting with standardized trained patient actors enacting the clinical scenario of counseling for pre-diabetes, each of whom had a pedometer that recorded the number of steps taken over a week. In both phases, all sessions were audio-taped and motion screen-capture software was activated for onscreen recordings. Transcripts were coded using iterative qualitative content analysis methods. RESULTS: In Phase I, the impact of the components and layout of ADAPT on user's Navigation, Understandability, and Workflow were associated with the largest volume of negative comments (i.e. approximately 80% of end-user commentary), while Usability and Content of ADAPT were representative of more positive than negative user commentary. The heuristic category of Usability had a positive-to-negative comment ratio of 2.1, reflecting positive perception of the usability of the tool, its functionality, and overall co-productive utilization of ADAPT. However, there were mixed perceptions about content (i.e., how the information was displayed, organized and described in the tool). In Phase II, the duration of patient encounters was approximately 10 min with all of the Patient Instructions (prescriptions) and behavioral contracting being activated at the end of each visit. Upon activation, providers accepted the pathway prescribed by the tool 100% of the time and completed all the fields in the tool in the simulation cases. Only 14% of encounter time was spent using the functionality of the ADAPT tool in terms of keystrokes and entering relevant data. The rest of the time was spent on communication and dialog to populate the patient instructions. In all cases, the interaction sequence of reviewing and discussing exercise and diet of the patient was linked to the functionality of the ADAPT tool in terms of monitoring, response-efficacy, self-efficacy, and negotiation in the patient-provider dialog. There was a change from one-way dialog to two-way dialog and negotiation that ended in a behavioral contract. This change demonstrated the tool's sequence, which supported recording current exercise and diet followed by a diet and exercise goal setting procedure to reduce the risk of diabetes onset. CONCLUSIONS: This study demonstrated that "think-aloud" protocol analysis with "near-live" clinical simulations provided a successful usability evaluation of a new primary care pre-diabetes shared goal setting tool. Each phase of the study provided complementary observations on problems with the new onscreen tool and was used to show the influence of the ADAPT framework on the usability, workflow integration, and communication between the patient and provider. The think-aloud tests with the provider showed the tool can be used according to the ADAPT framework (exercise-to-diet behavior change and tool utilization), while the clinical simulations revealed the ADAPT framework to realistically support patient-provider communication to obtain behavioral change contract. SDM interactions and mechanisms affecting protocol-based care can be more completely captured by combining "near-live" clinical simulations with traditional "think-aloud analysis" which augments clinician utilization. More analysis is required to verify if the rich communication actions found in Phase II compliment clinical workflows.

BACKGROUND: Effective communication of risks and benefits to patients is critical for shared decision making. PURPOSE: To review the comparative effectiveness of methods of communicating probabilistic information to patients that maximize their cognitive and behavioral outcomes. DATA SOURCES: PubMed (1966 to March 2014) and CINAHL, EMBASE, and the Cochrane Central Register of Controlled Trials (1966 to December 2011) using several keywords and structured terms. STUDY SELECTION: Prospective or cross-sectional studies that recruited patients or healthy volunteers and compared any method of communicating probabilistic information with another method. DATA EXTRACTION: Two independent reviewers extracted study characteristics and assessed risk of bias. DATA SYNTHESIS: Eighty-four articles, representing 91 unique studies, evaluated various methods of numerical and visual risk display across several risk scenarios and with diverse outcome measures. Studies showed that visual aids (icon arrays and bar graphs) improved patients' understanding and satisfaction. Presentations including absolute risk reductions were better than those including relative risk reductions for maximizing accuracy and seemed less likely than presentations with relative risk reductions to influence decisions to accept therapy. The presentation of numbers needed to treat reduced understanding. Comparative effects of presentations of frequencies (such as 1 in 5) versus event rates (percentages, such as 20%) were inconclusive. LIMITATION: Most studies were small and highly variable in terms of setting, context, and methods of administering interventions. CONCLUSION: Visual aids and absolute risk formats can improve patients' understanding of probabilistic information, whereas numbers needed to treat can lessen their understanding. Due to study heterogeneity, the superiority of any single method for conveying probabilistic information is not established, but there are several good options to help clinicians communicate with patients. PRIMARY FUNDING SOURCE: None.

BACKGROUND: Statins reduce the risk of coronary heart disease (CHD) in individuals with a history of CHD or risk equivalents. A 10-year CHD risk >20% is considered a risk equivalent but is frequently not detected. Statin use and low-density lipoprotein cholesterol (LDL-C) control were examined among participants with CHD or risk equivalents in the nationwide Reasons for Geographic and Racial Differences in Stroke study (n = 8812). METHODS: Participants were categorized into 4 mutually exclusive groups: (1) history of CHD (n = 4025); (2) no history of CHD but with a history of stroke and/or abdominal aortic aneurysm (AAA) (n = 946); (3) no history of CHD or stroke/AAA but with diabetes mellitus (n = 3134); or (4) no history of the conditions in (1) through (3) but with 10-year Framingham CHD risk score (FRS) >20% calculated using the third Adult Treatment Panel point scoring system (n = 707). RESULTS: Statins were used by 58.4% of those in the CHD group and 41.7%, 40.4% and 20.1% of those in the stroke/AAA, diabetes mellitus and FRS >20% groups, respectively. Among those taking statins, 65.1% had LDL-C <100 mg/dL, with no difference between the CHD, stroke/AAA, or diabetes mellitus groups. However, compared with those in the CHD group, LDL-C <100 mg/dL was less common among participants in the FRS >20% group (multivariable adjusted prevalence ratio: 0.72; 95% confidence interval: 0.62-0.85). Results were similar using the 2013 American College of Cardiology/American Heart Association cholesterol treatment guideline. CONCLUSIONS: These data suggest that many people with high CHD risk, especially those with an FRS >20%, do not receive guideline-concordant lipid-lowering therapy and do not achieve an LDL-C <100 mg/dL.

OBJECTIVE: This study assessed the baseline knowledge, perceptions, attitudes and behaviors of prediabetes patients in order to tailor a new technology-enhanced primary care-based lifestyle modification intervention. METHODS: Patients with a diagnosis of prediabetes were enrolled in a randomized, controlled pilot study, Avoiding Diabetes Thru Action Plan Targeting (ADAPT), a technology-based intervention to promote action plan discussions around patient-selected behavior change goals. RESULTS: A total of 54 adults (82% female) were enrolled in the pilot study. Most (89%) had comorbid conditions and mean BMI was 36. Participants exhibited high risk of diabetes knowledge (knowledge score 20 on a 32 point scale) and high levels of willingness to make changes to decrease diabetes risk. Number of daily steps was inversely correlated with perceived physical activity (r=-0.35082, p<0.001). Poorer scores on diet quality were inversely correlated with BMI. CONCLUSION: Participants in this sample demonstrated requisite levels of knowledge, self-efficacy, motivation and risk perception for effective behavior change. These data suggest that primary care-based prediabetes interventions can move beyond educational goals and focus on enhancing patients' ability to select, plan and enact action plans.

BACKGROUND: Physicians have limited time for weight-loss counseling, and there is a lack of resources to which they can refer patients for assistance with weight loss. Weight-loss mobile applications (apps) have the potential to be a helpful tool, but the extent to which they include the behavioral strategies included in evidence-based interventions is unknown. PURPOSE: The primary aims of the study were to determine the degree to which commercial weight-loss mobile apps include the behavioral strategies included in evidence-based weight-loss interventions, and to identify features that enhance behavioral strategies via technology. METHODS: Thirty weight-loss mobile apps, available on iPhone and/or Android platforms, were coded for whether they included any of 20 behavioral strategies derived from an evidence-based weight-loss program (i.e., Diabetes Prevention Program). Data on available apps were collected in January 2012; data were analyzed in June 2012. RESULTS: The apps included on average 18.83% (SD=13.24; range=0%-65%) of the 20 strategies. Seven of the strategies were not found in any app. The most common technology-enhanced features were barcode scanners (56.7%) and a social network (46.7%). CONCLUSIONS: Weight-loss mobile apps typically included only a minority of the behavioral strategies found in evidence-based weight-loss interventions. Behavioral strategies that help improve motivation, reduce stress, and assist with problem solving were missing across apps. Inclusion of additional strategies could make apps more helpful to users who have motivational challenges.

IMPORTANCE: There is consensus that incorporating clinical decision support into electronic health records will improve quality of care, contain costs, and reduce overtreatment, but this potential has yet to be demonstrated in clinical trials. OBJECTIVE: To assess the influence of a customized evidence-based clinical decision support tool on the management of respiratory tract infections and on the effectiveness of integrating evidence at the point of care. DESIGN, SETTING, AND PARTICIPANTS: In a randomized clinical trial, we implemented 2 well-validated integrated clinical prediction rules, namely, the Walsh rule for streptococcal pharyngitis and the Heckerling rule for pneumonia. INTERVENTIONS AND MAIN OUTCOMES AND MEASURES: The intervention group had access to the integrated clinical prediction rule tool and chose whether to complete risk score calculators, order medications, and generate progress notes to assist with complex decision making at the point of care. RESULTS: The intervention group completed the integrated clinical prediction rule tool in 57.5% of visits. Providers in the intervention group were significantly less likely to order antibiotics than the control group (age-adjusted relative risk, 0.74; 95% CI, 0.60-0.92). The absolute risk of the intervention was 9.2%, and the number needed to treat was 10.8. The intervention group was significantly less likely to order rapid streptococcal tests compared with the control group (relative risk, 0.75; 95% CI, 0.58-0.97; P= .03). CONCLUSIONS AND RELEVANCE: The integrated clinical prediction rule process for integrating complex evidence-based clinical decision report tools is of relevant importance for national initiatives, such as Meaningful Use. TRIAL REGISTRATION clinicaltrials.gov Identifier: NCT01386047.

BACKGROUND: Although higher visit-to-visit variability (VVV) of blood pressure (BP) is associated with increased cardiovascular disease risk, the physiological basis for VVV of BP is incompletely understood. METHODS: We examined the associations of aortic distensibility (assessed by magnetic resonance imaging) and artery elasticity indices (determined by radial artery pulse contour analysis) with VVV of BP in 2,640 and 4,560 participants, respectively, from the Multi-Ethnic Study of Atherosclerosis. Arterial measures were obtained at exam 1. BP readings were taken at exam 1 and at 3 follow-up visits at 18-month intervals (exams 2, 3, and 4). VVV was defined as the SD about each participant's mean systolic BP (SBP) across visits. RESULTS: The mean SDs of SBP were inversely associated with aortic distensibility: 7.7, 9.9, 10.9, and 13.2mm Hg for quartiles 4, 3, 2, and 1 of aortic distensibility, respectively (P trend < 0.001). This association remained significant after adjustment for demographics, cardiovascular risk factors, mean SBP, and antihypertensive medication use (P trend < 0.01). In a fully adjusted model, lower quartiles of large artery and small artery elasticity (LAE and SAE) indices were also associated with higher mean SD of SBP (P trend = 0.02 for LAE; P trend < 0.001 for SAE). CONCLUSIONS: In this multiethnic cohort, functional alterations of central and peripheral arteries were associated with greater long-term VVV of SBP.

OBJECTIVE: Many studies of diabetes have examined risk factors at the time of diabetes diagnosis instead of considering the lifetime burden of adverse risk factor levels. We examined the 30-year cardiovascular disease (CVD) risk factor burden that participants have up to the time of diabetes diagnosis. RESEARCH DESIGN AND METHODS: Among participants free of CVD, incident diabetes cases (fasting plasma glucose >/= 126 mg/dL or treatment) occurring at examinations 2 through 8 (1979-2008) of the Framingham Heart Study Offspring cohort were age- and sex-matched 1:2 to controls. CVD risk factors (hypertension, high LDL cholesterol, low HDL cholesterol, high triglycerides, obesity) were measured at the time of diabetes diagnosis and at time points 10, 20, and 30 years prior. Conditional logistic regression was used to compare risk factor levels at each time point between diabetes cases and controls. RESULTS: We identified 525 participants with new-onset diabetes who were matched to 1,049 controls (mean age, 60 years; 40% women). Compared with those without diabetes, individuals who eventually developed diabetes had higher levels of hypertension (odds ratio [OR], 2.2; P = 0.003), high LDL (OR, 1.5; P = 0.04), low HDL (OR, 2.1; P = 0.0001), high triglycerides (OR, 1.7; P = 0.04), and obesity (OR, 3.3; P < 0.0001) at time points 30 years before diabetes diagnosis. After further adjustment for BMI, the ORs for hypertension (OR, 1.9; P = 0.02) and low HDL (OR, 1.7; P = 0.01) remained statistically significant. CONCLUSIONS: CVD risk factors are increased up to 30 years before diagnosis of diabetes. These findings highlight the importance of a life course approach to CVD risk factor identification among individuals at risk for diabetes.

Nonadherence to cardiovascular medications such as statins is a common, important problem. Clinicians currently rely on intuition to identify medication nonadherence. The visit-to-visit variability (VVV) of low-density lipoprotein (LDL) cholesterol might represent an opportunity to identify statin nonadherence with greater accuracy. We examined the clinical and pharmacy data from 782 members of the Boston Medical Center Health Plan, seen at either the Boston Medical Center or its affiliated community health centers, who were taking statins and had >/=3 LDL cholesterol measurements from 2008 to 2011. The LDL cholesterol VVV (defined by the within-patient SD) was categorized into quintiles. Multivariate logistic regression models were generated with statin nonadherence (defined by the standard 80% pharmacy refill-based medication possession ratio threshold) as the dependent variable. The proportion of statin nonadherence increased across the quintiles of LDL cholesterol VVV (64.3%, 71.2%, 89.2%, 92.3%, 91.7%). Higher quintiles of LDL cholesterol VVV had a strong positive association with statin nonadherence, with an adjusted odds ratio of 3.4 (95% confidence interval 1.7 to 7.1) in the highest versus lowest quintile of LDL cholesterol VVV. The age- and gender-adjusted model had poor discrimination (C-statistic 0.62, 95% confidence interval 0.57 to 0.67), but the final adjusted model (age, gender, race, mean LDL cholesterol) demonstrated good discrimination (C-statistic 0.75, 95% confidence interval 0.71 to 0.79) between the adherent and nonadherent patients. In conclusion, the VVV of LDL cholesterol demonstrated a strong association with statin nonadherence in a clinic setting. Furthermore, a VVV of LDL cholesterol-based model had good discrimination characteristics for statin nonadherence. Research is needed to validate and generalize these findings to other populations and biomarkers.