Integration of patient and clinician narratives into systematic reviews: An applied proof of concept.

Health systems currently underutilize systematic reviews. Here, we describe a proof of concept project designed to augment the standard systematic review process by presenting qualitative information as a companion to a review on deprescribing interventions. We conducted a thematic analysis of semi-structured interviews with Veterans Health Administration clinicians and Veterans to describe first-hand experiences of engaging in the deprescribing process. Qualitative findings were incorporated into an interactive, web-based product designed to supplement the systematic review report. Preliminary evaluation suggests that integration of narratives as a companion to systematic reviews is of interest to frontline clinicians, researchers, and health system administrators.

Applying the Effective Technology Use Model to Implementation of Electronic Consult Management Software.

Theoretical models of technology acceptance are critical to scope projects, select interventions, and measure adoption. We describe use of the Effective Technology Use (ETU) model in the design and deployment of software supporting electronic consult management. We applied the model to four project phases: (1) needs assessment; (2) software design; (3) deployment; and (4) uptake assessment. In this paper, we describe how we used the ETU to plan stakeholder meetings, conduct usability simulations, and organize findings from a qualitative analysis to identify implementation facilitators and barriers.

Evaluation of Multimedia Medication Reconciliation Software: A Randomized Controlled, Single-Blind Trial to Measure Diagnostic Accuracy for Discrepancy Detection.

BACKGROUND: The Veterans Affairs Portland Healthcare System developed a medication history collection software that displays prescription names and medication images. OBJECTIVE: This article measures the frequency of medication discrepancy reporting using the medication history collection software and compares with the frequency of reporting using a paper-based process. This article also determines the accuracy of each method by comparing both strategies to a best possible medication history. STUDY DESIGN: Randomized, controlled, single-blind trial. SETTING: Three community-based primary care clinics associated with the Veterans Affairs Portland Healthcare System: a 300-bed teaching facility and ambulatory care network serving Veteran soldiers in the Pacific Northwest United States. PARTICIPANTS: Of 212 patients with primary care appointments, 209 patients fulfilled the study requirements. INTERVENTION: Patients randomized to a software-directed medication history or a paper-based medication history. Randomization and allocation to treatment groups were performed using a computer-based random number generator. Assignments were placed in a sealed envelope and opened after participant consent. The research coordinator did not know or have access to the treatment assignment until the time of presentation. MAIN OUTCOME MEASURES: The primary analysis compared the discrepancy detection rates between groups with respect to the health record and a best possible medication history. RESULTS: Of 3,500 medications reviewed, we detected 1,435 discrepancies. Forty-six percent of those discrepancies were potentially high risk for causing an adverse drug event. There was no difference in detection rates between treatment arms. Software sensitivity was 83% and specificity was 91%; paper sensitivity was 81% and specificity was 94%. No participants were lost to follow-up. CONCLUSION: The medication history collection software is an efficient and scalable method for gathering a medication history and detecting high-risk discrepancies. Although it included medication images, the technology did not improve accuracy over a paper list when compared with a best possible medication history. TRIAL REGISTRATION: ClinicalTrials.gov Identifier: NCT02135731.

Naturalistic Usability Testing of Inpatient Medication Reconciliation Software.

Medication history errors are common at admission, but can be mitigated through the implementation of medication reconciliation (MR). We designed multi-media software to assist clinicians with collection of an admission history. This manuscript describes a naturalistic usability study conducted on the hospital wards. Our goals were to 1) estimate the impact of our workflow upon departmental productivity and 2) determine the ability of our software to detect discrepancies. We furnished clinical pharmacists with our application on a tablet PC and asked them to collect a bedside history. We used 1) time-motion analysis to estimate cycle-time and 2) chart reviews to estimate error detection rates. Our intervention detected an average of 7.7 discrepancies per admission (11.7 per pharmacy-shift). A panel rated 67% of these discrepancies as 'high' or 'very high' risk. The cycle-time per admission was slightly longer than usual care processes (20.5 min vs. 17.9 min), but included a bedside interview. In general, pharmacists agreed that the technology improved the completeness and accuracy of a medication history. However, workflow leveling strategies are important to implementing a durable process. In conclusion, a pharmacist-mediated, patient-centered technology holds promise for improving the quality of MR and overall clinical performance.

Implementation of a Medication Reconciliation Assistive Technology: A Qualitative Analysis.

Objective: To aid the implementation of a medication reconciliation process within a hybrid primary-specialty care setting by using qualitative techniques to describe the climate of implementation and provide guidance for future projects. Methods: Guided by McMullen et al's Rapid Assessment Process1, we performed semi-structured interviews prior to and iteratively throughout the implementation. Interviews were coded and analyzed using grounded theory2 and cross-examined for validity. Results: We identified five barriers and five facilitators that impacted the implementation. Facilitators identified were process alignment with user values, and motivation and clinical champions fostered by the implementation team rather than the administration. Barriers included a perceived limited capacity for change, diverging priorities, and inconsistencies in process standards and role definitions. Discussion: A more complete, qualitative understanding of existing barriers and facilitators helps to guide critical decisions on the design and implementation of a successful medication reconciliation process.

Usability Evaluation of a Medication Reconciliation and Allergy Review (MRAR) Kiosk: A Methodological Approach for Analyzing User Interactions.

Internationally, major efforts are underway to improve medication safety and reduce medication errors during transitions of care. One strategy that has emerged to improve data accuracy and close information gaps is the introduction of software applications and workflow models that allow patients to review, enter, and modify their own patient data (e.g. information about medications they are taking). Evaluating the quality and effectiveness of such patient-facing healthcare applications is critical, especially when this approach is applied to high-stakes clinical tasks such as medication reconciliation. In this paper we describe an approach that has been used to assess the usability of a patient-facing medication reconciliation and allergy review (MRAR) kiosk. The phases involved are described along with implications and challenges of carrying out this work.

Design of admission medication reconciliation technology: a human factors approach to requirements and prototyping.

OBJECTIVE: Our objectives were to (1) develop an in-depth understanding of the workflow and information flow in medication reconciliation, and (2) design medication reconciliation support technology using a combination of rapid-cycle prototyping and human-centered design. BACKGROUND: Although medication reconciliation is a national patient safety goal, limitations both of physical environment and in workflow can make it challenging to implement durable systems. We used several human factors techniques to gather requirements and develop a new process to collect a medication history at hospital admission. METHODS: We completed an ethnography and time and motion analysis of pharmacists in order to illustrate the processes used to reconcile medications. We then used the requirements to design prototype multimedia software for collecting a bedside medication history. We observed how pharmacists incorporated the technology into their physical environment and documented usability issues. RESULTS: Admissions occurred in three phases: (1) list compilation, (2) order processing, and (3) team coordination. Current medication reconciliation processes at the hospital average 19 minutes to complete and do not include a bedside interview. Use of our technology during a bedside interview required an average of 29 minutes. The software represents a viable proof-of-concept to automate parts of history collection and enhance patient communication. However, we discovered several usability issues that require attention. CONCLUSIONS: We designed a patient-centered technology to enhance how clinicians collect a patient's medication history. By using multiple human factors methods, our research team identified system themes and design constraints that influence the quality of the medication reconciliation process and implementation effectiveness of new technology. KEYWORDS: Evidence-based design, human factors, patient-centered care, safety, technology.