• Negin Hajizadeh, Rafael E Perez Figueroa, Lauren M Uhler, Erin Chiou, Jennifer E Perchonok, and Enid Montague.
• Department of Population Health, New York University School of Medicine, New York, NY.
• J Particip Med. 2013 Mar 6; 5.

Background And ObjectiveComputerized decision aids could facilitate shared decision-making at the point of outpatient clinical care. The objective of this study was to investigate whether a computerized shared decision aid would be feasible to implement in an inner-city clinic by evaluating the current practices in shared decision-making, clinicians' use of computers, patient and clinicians' attitudes and beliefs toward computerized decision aids, and the influence of time on shared decision-making.MethodsQualitative data analysis of observations and semi-structured interviews with patients and clinicians at an inner-city outpatient clinic.FindingsThe findings provided an exploratory look at the prevalence of shared decision-making and attitudes about health information technology and decision aids. A prominent barrier to clinicians engaging in shared decision-making was a lack of perceived patient understanding of medical information. Some patients preferred their clinicians make recommendations for them rather than engage in formal shared decision-making. Health information technology was an integral part of the clinic visit and welcomed by most clinicians and patients. Some patients expressed the desire to engage with health information technology such as viewing their medical information on the computer screen with their clinicians. All participants were receptive to the idea of a decision aid integrated within the clinic visit although some clinicians were concerned about the accuracy of prognostic estimates for complex medical problems.ImplicationsWe identified several important considerations for the design and implementation of a computerized decision aid including opportunities to: bridge clinician-patient communication about medical information while taking into account individual patients' decision-making preferences, complement expert clinician judgment with prognostic estimates, take advantage of patient waiting times, and make tasks involved during the clinic visit more efficient. These findings should be incorporated into the design and implementation of a computerized shared decision aid at an inner-city hospital.

3 keywords...

hide…