Use of implementation mapping in the planning of a hybrid type 1 pragmatic clinical trial: the BeatPain Utah study.

Background: Considerable disparities in chronic pain management have been identified. Persons in rural, lower income and minoritized communities are less likely to receive evidence-based, nonpharmacologic care. Telehealth delivery of nonpharmacologic, evidence-based interventions for persons with chronic pain is a promising strategy to lessen disparities, but implementation comes with many challenges. The BeatPain Utah study is a hybrid type I effectiveness-implementation pragmatic clinical trial investigating telehealth strategies to provide nonpharmacologic care from physical therapists to persons with chronic back pain receiving care in Community Health Centers (CHCs). CHCs provide primary care to all persons regardless of ability to pay. This paper outlines the use of implementation mapping to develop a multifaceted implementation plan for the BeatPain study. Methods: During a planning year for the BeatPain trial we developed a comprehensive logic model including the 5-step implementation mapping process informed by additional frameworks and theories. The five iterative implementation mapping steps were addressed in the planning year; 1) conduct needs assessments for involved groups; 2) identify implementation outcomes, performance objectives and determinants; 3) select implementation strategies; 4) produce implementation protocols and materials; and 5) evaluate implementation outcomes. Results: CHC leadership/providers, patients and physical therapists were identified as involved groups. Barriers and assets were identified across groups which informed identification of performance objectives necessary to implement two key processes; 1) electronic referral of patients with back pain in CHC clinics to the BeatPain team; and 2) connecting patients with physical therapists providing telehealth. Determinants of the performance objectives for each group informed our choice of implementation strategies which focused on training, education, clinician support and tailoring physical therapy interventions for telehealth delivery and cultural competency. We selected implementation outcomes for the BeatPain trial to evaluate the success of our implementation strategies. Conclusions: Implementation mapping provided a comprehensive and systematic approach to develop an implementation plan during the planning phase for our ongoing hybrid effectiveness-implementation trial. We will be able to evaluate the implementation strategies used in the BeatPain Utah study to inform future efforts to implement telehealth delivery of evidence-based pain care in CHCs and other settings. Trial registration: Clinicaltrials.gov Identifier: NCT04923334. Registered June 11, 2021 (https://clinicaltrials.gov/study/NCT04923334.

Correction: Identifying Patients Who Meet Criteria for Genetic Testing of Hereditary Cancers Based on Structured and Unstructured Family Health History Data in the Electronic Health Record: Natural Language Processing Approach.

[This corrects the article DOI: 10.2196/37842.].

Identifying Patients Who Meet Criteria for Genetic Testing of Hereditary Cancers Based on Structured and Unstructured Family Health History Data in the Electronic Health Record: Natural Language Processing Approach.

BACKGROUND: Family health history has been recognized as an essential factor for cancer risk assessment and is an integral part of many cancer screening guidelines, including genetic testing for personalized clinical management strategies. However, manually identifying eligible candidates for genetic testing is labor intensive. OBJECTIVE: The aim of this study was to develop a natural language processing (NLP) pipeline and assess its contribution to identifying patients who meet genetic testing criteria for hereditary cancers based on family health history data in the electronic health record (EHR). We compared an algorithm that uses structured data alone with structured data augmented using NLP. METHODS: Algorithms were developed based on the National Comprehensive Cancer Network (NCCN) guidelines for genetic testing for hereditary breast, ovarian, pancreatic, and colorectal cancers. The NLP-augmented algorithm uses both structured family health history data and the associated unstructured free-text comments. The algorithms were compared with a reference standard of 100 patients with a family health history in the EHR. RESULTS: Regarding identifying the reference standard patients meeting the NCCN criteria, the NLP-augmented algorithm compared with the structured data algorithm yielded a significantly higher recall of 0.95 (95% CI 0.9-0.99) versus 0.29 (95% CI 0.19-0.40) and a precision of 0.99 (95% CI 0.96-1.00) versus 0.81 (95% CI 0.65-0.95). On the whole data set, the NLP-augmented algorithm extracted 33.6% more entities, resulting in 53.8% more patients meeting the NCCN criteria. CONCLUSIONS: Compared with the structured data algorithm, the NLP-augmented algorithm based on both structured and unstructured family health history data in the EHR increased the number of patients identified as meeting the NCCN criteria for genetic testing for hereditary breast or ovarian and colorectal cancers.

Enhancing the use of EHR systems for pragmatic embedded research: lessons from the NIH Health Care Systems Research Collaboratory.

OBJECTIVE: We identified challenges and solutions to using electronic health record (EHR) systems for the design and conduct of pragmatic research. MATERIALS AND METHODS: Since 2012, the Health Care Systems Research Collaboratory has served as the resource coordinating center for 21 pragmatic clinical trial demonstration projects. The EHR Core working group invited these demonstration projects to complete a written semistructured survey and used an inductive approach to review responses and identify EHR-related challenges and suggested EHR enhancements. RESULTS: We received survey responses from 20 projects and identified 21 challenges that fell into 6 broad themes: (1) inadequate collection of patient-reported outcome data, (2) lack of structured data collection, (3) data standardization, (4) resources to support customization of EHRs, (5) difficulties aggregating data across sites, and (6) accessing EHR data. DISCUSSION: Based on these findings, we formulated 6 prerequisites for PCTs that would enable the conduct of pragmatic research: (1) integrate the collection of patient-centered data into EHR systems, (2) facilitate structured research data collection by leveraging standard EHR functions, usable interfaces, and standard workflows, (3) support the creation of high-quality research data by using standards, (4) ensure adequate IT staff to support embedded research, (5) create aggregate, multidata type resources for multisite trials, and (6) create re-usable and automated queries. CONCLUSION: We are hopeful our collection of specific EHR challenges and research needs will drive health system leaders, policymakers, and EHR designers to support these suggestions to improve our national capacity for generating real-world evidence.

Barriers and facilitators to clinical information seeking: a systematic review.

OBJECTIVE: The study sought to identify barriers to and facilitators of point-of-care information seeking and use of knowledge resources. MATERIALS AND METHODS: We searched MEDLINE, Embase, PsycINFO, and Cochrane Library from 1991 to February 2017. We included qualitative studies in any language exploring barriers to and facilitators of point-of-care information seeking or use of electronic knowledge resources. Two authors independently extracted data on users, study design, and study quality. We inductively identified specific barriers or facilitators and from these synthesized a model of key determinants of information-seeking behaviors. RESULTS: Forty-five qualitative studies were included, reporting data derived from interviews (n = 26), focus groups (n = 21), ethnographies (n = 6), logs (n = 4), and usability studies (n = 2). Most studies were performed within the context of general medicine (n = 28) or medical specialties (n = 13). We inductively identified 58 specific barriers and facilitators and then created a model reflecting 5 key determinants of information-seeking behaviors: time includes subthemes of time availability, efficiency of information seeking, and urgency of information need; accessibility includes subthemes of hardware access, hardware speed, hardware portability, information restriction, and cost of resources; personal skills and attitudes includes subthemes of computer literacy, information-seeking skills, and contextual attitudes about information seeking; institutional attitudes, cultures, and policies includes subthemes describing external individual and institutional information-seeking influences; and knowledge resource features includes subthemes describing information-seeking efficiency, information content, information organization, resource familiarity, information credibility, information currency, workflow integration, compatibility of recommendations with local processes, and patient educational support. CONCLUSIONS: Addressing these determinants of information-seeking behaviors may facilitate clinicians' question answering to improve patient care.

Understanding Primary Care Providers' Information Gathering Strategies in the Care of Children and Youth with Special Health Care Needs.

Background: Effective care coordination of children and youth with special health care needs (CYSHCN) is critical but challenging. Objective: To investigate clinicians' information-gathering strategies while preparing for visits with CYSHCN. Methods: Critical incident interviews with primary care physicians and care coordinators. Results: Six themes emerged indicating 1) substantial reliance on the electronic health record; 2) a central role of the problem list in organizing and summarizing information; 3) Medical Home's central role in organizing clinical documentation; 4) universal need to integrate information from external records; 5) lack of well-organized and labeled encounter documentation; and 6) lack of tools reconcile medication lists. Conclusion: Our findings have important implications to the design of informatics tools to support information-gathering in the care of CYSHCN.

When an Alert is Not an Alert: A Pilot Study to Characterize Behavior and Cognition Associated with Medication Alerts.

Introduction. Preventable adverse drug events are a significant patient-safety concern, yet most medication alerts are disregarded. Pharmacists encounter the highest number of medication alerts and likely have developed behaviors to cope with alerting inefficiencies. The study objective was to better understand alert override behavior relating to a motivational construct framework. Methods. Mixed-methods study of 10 pharmacists (567 verifications) with eye-tracking observations and retrospective think aloud interviews. Results. Pharmacists spent on average 14 seconds longer verifying orders with alerts than orders without alerts (p<0.001). Verification occurred before alerts were triggered, and no order changes occurred after alerts. Pharmacists reported 62% of alerts as unhelpful and 21% as frustrating. Alert interactions took on average 3.9 seconds. Discussion. Pharmacists anticipate alerts by making appropriate checks and changes before alert prompts. Medication alerts seem to be useful. However, the observed pharmacists' behavior suggests changes in the alert context are needed to match cognition.

Randomized Trial of Population-Based Clinical Decision Support to Facilitate Care Transitions.

Medicaid beneficiaries in 6 North Carolina counties were randomly assigned to 1 of 3 clinical decision support (CDS) care transition strategies: (1) usual care (Control), (2) CDS messaging to patients and their medical homes (Reports), or (3) CDS messaging to patients, their medical homes, and their care managers (Reports+). We included 7146 Medicaid patients and evaluated transitions from specialist visit, ER and hospital encounters back to the patient's medical home. Patients enrolled in Medicare and Medicaid were not eligible. The number of care manager contacts was greater for patients in the Reports+ Group than in the Control Group. However, there were no treatment-related differences in emergency department (ED) encounter rates, or in the secondary outcomes of outpatient and hospital encounter rates and medical costs. Study monitors found study intervention documentation in approximately 60% of patient charts. These results highlight the importance of effectively integrating information interventions into healthcare delivery workflow systems.

Evaluation of a systematic methodology to detect in near real-time performance changes during electronic health record system implementations: a longitudinal study.

Introduction. Although Electronic Health Record (EHR) adoption has increased in the U.S., our understanding of how it affects health care organizations is still limited. Current literature has produced mixed-results due to the use of simple, non-standardized measurements and poor research designs. Methods. We propose the use of a systematic methodology that combines measures of quality, productivity and safety processes, tracked over time using an interrupted time-series design with multiple control sites. Results. Our methodology successfully detected performance changes during an EHR implementation on 17 (77%) outcomes, including a significant increase in Emergency Department length of stay immediately after go live by 0.19 hours [95%CI (0.12, 0.27), p<0.001], and an improvement in time to complete radiology tests, which significantly decreased per month by 0.19 minutes [95%CI (-0.26, -0.12), p<0.001]. Conclusion. The proposed methodology was able to detect several changes immediately after an EHR implementation and over time. The method is a promising and robust approach to assessing the impact of EHR implementations on a wide range of health care quality, productivity, and safety care processes.

User-centered design of multi-gene sequencing panel reports for clinicians.

The objective of this study was to develop a high-fidelity prototype for delivering multi-gene sequencing panel (GS) reports to clinicians that simulates the user experience of a final application. The delivery and use of GS reports can occur within complex and high-paced healthcare environments. We employ a user-centered software design approach in a focus group setting in order to facilitate gathering rich contextual information from a diverse group of stakeholders potentially impacted by the delivery of GS reports relevant to two precision medicine programs at the University of Maryland Medical Center. Responses from focus group sessions were transcribed, coded and analyzed by two team members. Notification mechanisms and information resources preferred by participants from our first phase of focus groups were incorporated into scenarios and the design of a software prototype for delivering GS reports. The goal of our second phase of focus group, to gain input on the prototype software design, was accomplished through conducting task walkthroughs with GS reporting scenarios. Preferences for notification, content and consultation from genetics specialists appeared to depend upon familiarity with scenarios for ordering and delivering GS reports. Despite familiarity with some aspects of the scenarios we proposed, many of our participants agreed that they would likely seek consultation from a genetics specialist after viewing the test reports. In addition, participants offered design and content recommendations. Findings illustrated a need to support customized notification approaches, user-specific information, and access to genetics specialists with GS reports. These design principles can be incorporated into software applications that deliver GS reports. Our user-centered approach to conduct this assessment and the specific input we received from clinicians may also be relevant to others working on similar projects.