Usability testing of Avoiding Diabetes Thru Action Plan Targeting (ADAPT) decision support for integrating care-based counseling of pre-diabetes in an electronic health record

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.

[1]  Emilie M. Roth,et al.  Research Paper: Impact of Clinical Reminder Redesign on Learnability, Efficiency, Usability, and Workload for Ambulatory Clinic Nurses , 2007, J. Am. Medical Informatics Assoc..

[2]  Sean Sullivan,et al.  Case finding of lifestyle and mental health disorders in primary care: validation of the 'CHAT' tool. , 2008, The British journal of general practice : the journal of the Royal College of General Practitioners.

[3]  Shari Barkin,et al.  Primary Health Care: Potential Home for Family-Focused Preventive Interventions. , 2016, American journal of preventive medicine.

[4]  David W. Bates,et al.  Research Paper: Electronic Health Records in Specialty Care: A Time-Motion Study , 2007, J. Am. Medical Informatics Assoc..

[5]  Devin M Mann,et al.  Application of persuasion and health behavior theories for behavior change counseling: design of the ADAPT (Avoiding Diabetes Thru Action Plan Targeting) program. , 2012, Patient education and counseling.

[6]  Qi Li,et al.  Using qualitative studies to improve the usability of an EMR , 2005, J. Biomed. Informatics.

[7]  V. Strecher Internet methods for delivering behavioral and health-related interventions (eHealth). , 2007, Annual review of clinical psychology.

[8]  Charlene R. Weir,et al.  Research Paper: A Cognitive Task Analysis of Information Management Strategies in a Computerized Provider Order Entry Environment , 2007, J. Am. Medical Informatics Assoc..

[9]  Alissa L. Russ,et al.  A Human Factors Investigation of Medication Alerts: Barriers to Prescriber Decision-Making and Clinical Workflow , 2009, AMIA.

[10]  V. Patel,et al.  Assessment of a computerized patient record system: a cognitive approach to evaluating medical technology. , 1996, M.D. computing : computers in medical practice.

[11]  Johanna Kaipio,et al.  Usability in healthcare : overcoming the mismatch between information systems and clinical work , 2011 .

[12]  Robert Harmon,et al.  Research Paper: Electronic Health Records in Four Community Physician Practices: Impact on Quality and Cost of Care , 2007, J. Am. Medical Informatics Assoc..

[13]  Trisha Greenhalgh,et al.  Why do we always end up here? Evidence-based medicine's conceptual cul-de-sacs and some off-road alternative routes. , 2012, Journal of primary health care.

[14]  D. Sackett,et al.  Evidence based medicine: what it is and what it isn't , 1996, BMJ.

[15]  Troy D. Abel,et al.  The use of partner-seeking computer-mediated communication applications by young men that have sex with men (YMSM): uncovering human-computer interaction (HCI) design opportunities in HIV prevention , 2012 .

[16]  Jo Rycroft-Malone,et al.  A realistic evaluation: the case of protocol-based care , 2010, Implementation science : IS.

[17]  Kenneth R Ong Medical informatics : an executive primer , 2011 .

[18]  Joseph L. Kannry,et al.  Integrating usability testing and think-aloud protocol analysis with "near-live" clinical simulations in evaluating clinical decision support , 2012, Int. J. Medical Informatics.

[19]  R Brian Haynes,et al.  Evidence based medicine: what it is and what it isn't. 1996. , 2007, Clinical orthopaedics and related research.

[20]  Devin M Mann,et al.  Increasing efficacy of primary care-based counseling for diabetes prevention: Rationale and design of the ADAPT (Avoiding Diabetes Thru Action Plan Targeting) trial , 2012, Implementation Science.

[21]  Vimla L. Patel,et al.  A framework for analyzing the cognitive complexity of computer-assisted clinical ordering , 2003, J. Biomed. Informatics.

[22]  Vimla L. Patel,et al.  Impact of a computer-based patient record system on data collection, knowledge organization, and reasoning. , 2000, Journal of the American Medical Informatics Association : JAMIA.

[23]  Anne Holbrook,et al.  Features predicting the success of computerized decision support for prescribing: a systematic review of randomized controlled trials , 2009, BMC Medical Informatics Decis. Mak..

[24]  Vimla L. Patel,et al.  Cognitive and usability engineering methods for the evaluation of clinical information systems , 2004, J. Biomed. Informatics.

[25]  Emily S. Patterson,et al.  Identifying barriers to the effective use of clinical reminders: Bootstrapping multiple methods , 2005, J. Biomed. Informatics.

[26]  C. Raina Elley,et al.  The eCHAT Program to Facilitate Healthy Changes in New Zealand Primary Care , 2013, The Journal of the American Board of Family Medicine.

[27]  Blackford Middleton,et al.  Complementary methods of system usability evaluation: Surveys and observations during software design and development cycles , 2010, J. Biomed. Informatics.

[28]  Sidney Fels,et al.  A framework for evaluating usability of clinical monitoring technology , 2007, Journal of Clinical Monitoring and Computing.

[29]  Emily S. Patterson,et al.  Exploring barriers and facilitators to the use of computerized clinical reminders. , 2005, Journal of the American Medical Informatics Association : JAMIA.

[30]  L. Hayden,et al.  Ten Commandments for Effective Clinical Decision Support: Making the Practice of Evidence-based Medicine a Reality , 2011 .

[31]  Joseph L. Kannry,et al.  Emerging Approaches to Usability Evaluation of Health Information Systems: Towards In-Situ Analysis of Complex Healthcare Systems and Environments , 2011, MIE.

[32]  Electronic Health Record Usability Interface Design Considerations , 2009 .