Use, Impact, Weaknesses, and Advanced Features of Search Functions for Clinical Use in Electronic Health Records: A Scoping Review

Objective: Although vast amounts of patient information are captured in electronic health records (EHRs), effective clinical use of this information is challenging due to inadequate and inefficient access to it at the point of care. The purpose of this study was to conduct a scoping review of the literature on the use of EHR search functions within a single patient's record in clinical settings to characterize the current state of research on the topic and identify areas for future study. Methods: We conducted a literature search of four databases to identify articles on within-EHR search functions or the use of EHR search function in the context of clinical tasks. After reviewing titles and abstracts and performing a full-text review of selected articles, we included 17 articles in the analysis. We qualitatively identified themes in those articles and synthesized the literature for each theme. Results: Based on the 17 articles analyzed, we delineated four themes: (1) how clinicians use search functions, (2) impact of search functions on clinical workflow, (3) weaknesses of current search functions, and (4) advanced search features. Our review found that search functions generally facilitate patient information retrieval by clinicians and are positively received by users. However, existing search functions have weaknesses, such as yielding false negatives and false positives, which can decrease trust in the results, and requiring a high cognitive load to perform an inclusive search of a patient's record. Conclusion: Despite the widespread adoption of EHRs, only a limited number of articles describe the use of EHR search functions in a clinical setting, despite evidence that they benefit clinician workflow and productivity. Some of the weaknesses of current search functions may be addressed by enhancing EHR search functions with collaborative filtering

Advancing cognitive engineering methods to support user interface design for electronic health records

Background Despite many decades of research on the effective development of clinical systems in medicine, the adoption of health information technology to improve patient care continues to be slow, especially in ambulatory settings. This applies to dentistry as well, a primary care discipline with approximately 137,000 practitioners in the United States. A critical reason for slow adoption is the poor usability of clinical systems, which makes it difficult for providers to navigate through the information and obtain an integrated view of patient data. Objective In this study, we documented the cognitive processes and information management strategies used by dentists during a typical patient examination. The results will inform the design of a novel electronic dental record interface. Methods We conducted a cognitive task analysis (CTA) study to observe ten general dentists (five general dentists and five general dental faculty members, each with more than two years of clinical experience) examining three simulated patient cases using a think-aloud protocol. Results Dentists first reviewed the patient’s demographics, chief complaint, medical history and dental history to determine the general status of the patient. Subsequently, they proceeded to examine the patient’s intraoral status using radiographs, intraoral images, hard tissue and periodontal tissue information. The results also identified dentists’ patterns of navigation through patient’s information and additional information needs during a typical clinician-patient encounter. Conclusion This study reinforced the significance of applying cognitive engineering methods to inform the design of a clinical system. Second, applying CTA to a scenario closely simulating an actual patient encounter helped with capturing participants’ knowledge states and decision-making when diagnosing and treating a patient. The resultant knowledge of dentists’ patterns of information retrieval and review will significantly contribute to designing flexible and task-appropriate information presentation in electronic dental records

Categorizing Health Outcomes and Efficacy of mHealth Apps for Persons With Cognitive Impairment: A Systematic Review

Background Use of mobile health (mHealth) apps is growing at an exponential rate in the United States and around the world. Mild cognitive impairment (MCI), Alzheimer disease, and related dementias are a global health problem. Numerous mHealth interventions exist for this population, yet the effect of these interventions on health has not been systematically described. Objective The aim of this study is to catalog the types of health outcomes used to measure effectiveness of mHealth interventions and assess which mHealth interventions have been shown to improve the health of persons with MCI, Alzheimer disease, and dementia. Methods We searched 13 databases, including Ovid MEDLINE, PubMed, EMBASE, the full Cochrane Library, CINAHL, PsycINFO, Ei Compendex, IEEE Xplore, Applied Science & Technology Source, Scopus, Web of Science, ClinicalTrials.gov, and Google Scholar from inception through May 2017 for mHealth studies involving persons with cognitive impairment that were evaluated using at least one quantitative health outcome. Proceedings of the Annual ACM Conferences on Human Factors in Computing Systems, the ACM User Interface Software and Technology Symposium, and the IEEE International Symposium on Wearable Computers were searched in the ACM Digital Library from 2012 to 2016. A hand search of JMIR Publications journals was also completed in July 2017. Results After removal of duplicates, our initial search returned 3955 records. Of these articles, 24 met final inclusion criteria as studies involving mHealth interventions that measured at least one quantitative health outcome for persons with MCI, Alzheimer disease, and dementia. Common quantitative health outcomes included cognition, function, mood, and quality of life. We found that 21.2% (101/476) of the fully reviewed articles were excluded because of a lack of health outcomes. The health outcomes selected were observed to be inconsistent between studies. For those studies with quantitative health outcomes, more than half (58%) reported postintervention improvements in outcomes. Conclusions Results showed that many mHealth app interventions targeting those with cognitive impairment lack quantitative health outcomes as a part of their evaluation process and that there is a lack of consensus as to which outcomes to use. The majority of mHealth app interventions that incorporated health outcomes into their evaluation noted improvements in the health of persons with MCI, Alzheimer disease, and dementia. However, these studies were of low quality, leading to a grade C level of evidence. Clarification of the benefits of mHealth interventions for people with cognitive impairment requires more randomized controlled trials, larger numbers of participants, and trial designs that minimize bias. Trial Registration PROSPERO Registration: PROSPERO 2016:CRD42016033846; http://www.crd.york.ac.uk/PROSPERO/ display_record.asp?ID=CRD42016033846 (Archived by WebCite at http://www.webcitation.org/6sjjwnv1M

Hybrid Collaborative Filtering Methods for Recommending Search Terms to Clinicians

With increasing and extensive use of electronic health records (EHR), clinicians are often challenged in retrieving relevant patient information efficiently and effectively to arrive at a diagnosis. While using the search function built into an EHR can be more useful than browsing in a voluminous patient record, it is cumbersome and repetitive to search for the same or similar information on similar patients. To address this challenge, there is a critical need to build effective recommender systems that can recommend search terms to clinicians accurately. In this study, we developed a hybrid collaborative filtering model to recommend search terms for a specific patient to a clinician. The model draws on information from patients' clinical encounters and the searches that were performed during them. To generate recommendations, the model uses search terms which are (1) frequently co-occurring with the ICD codes recorded for the patient and (2) highly relevant to the most recent search terms. In one variation of the model (Hybrid Collaborative Filtering Method for Healthcare, or HCFMH), we use only the most recent ICD codes assigned to the patient, and in the other (Co-occurrence Pattern based HCFMH, or cpHCFMH), all ICD codes. We have conducted comprehensive experiments to evaluate the proposed model. These experiments demonstrate that our model outperforms state-of-the-art baseline methods for top-N search term recommendation on different data sets

Supporting Emerging Disciplines with e-Communities: Needs and Benefits

Background: Science has developed from a solitary pursuit into a team-based collaborative activity and, more recently, into a multidisciplinary research enterprise. The increasingly collaborative character of science, mandated by complex research questions and problems that require many competencies, requires that researchers lower the barriers to the creation of collaborative networks of experts, such as communities of practice (CoPs). Objectives: The aim was to assess the information needs of prospective members of a CoP in an emerging field, dental informatics, and to evaluate their expectations of an e-community in order to design a suitable electronic infrastructure. Methods: A Web-based survey instrument was designed and administered to 2768 members of the target audience. Benefit expectations were analyzed for their relationship to (1) the respondents’ willingness to participate in the CoP and (2) their involvement in funded research. Two raters coded the respondents’ answers regarding expected benefits using a 14-category coding scheme (Kappa = 0.834). Results: The 256 respondents (11.1% response rate) preferred electronic resources over traditional print material to satisfy their information needs. The most frequently expected benefits from participation in the CoP were general information (85% of respondents), peer networking (31.1%), and identification of potential collaborators and/or research opportunities (23.2%). Conclusions: The competitive social-information environment in which CoPs are embedded presents both threats to sustainability and opportunities for greater integration and impact. CoP planners seeking to support the development of emerging biomedical science disciplines should blend information resources, social search and filtering, and visibility mechanisms to provide a portfolio of social and information benefits. Assessing benefit expectations and alternatives provides useful information for CoP planners seeking to prioritize community infrastructure development and encourage participation

Frequency and Correlates of Pediatric High-Flow Nasal Cannula Use for Bronchiolitis, Asthma, and Pneumonia

Background: Heated humidified high-flow nasal cannula (HFNC) is a respiratory support device historically used in pediatrics for infants with bronchiolitis. No large-scale analysis has determined the current frequency or demographic distribution of HFNC use in children. The objective of this study was to determine the frequency and correlates of HFNC use in children presenting to the hospital for asthma, bronchiolitis, or pneumonia. Methods: This longitudinal observational study was based on electronic health record data from a large regional health information exchange, the Indiana Network for Patient Care (INPC). Subjects were age 0-18 y with recorded hospital encounters at an INPC hospital between 2010-2019 with International Classification of Diseases codes for bronchiolitis, asthma, or pneumonia. Annual proportions of HFNC use among all hospital encounters were assessed using generalized additive models. Log-binomial regression models were used to identify correlates of incident HFNC use and determine risk ratios of specific subjects receiving HFNC. Results: The study sample included 242,381 unique subjects with 412,712 hospital encounters between 2010-2019. The 10-y period prevalence of HFNC use was 2.54% (6,155/242,381) involving 7,974 encounters. Hospital encounters utilizing HFNC increased by 400%, from 326 in 2010 to 1,310 in 2019. This increase was evenly distributed across all 3 diagnostic categories (bronchiolitis, asthma, and pneumonia). Sex, race, age, and ethnicity all significantly influenced the risk of HFNC use. Over the 10-y period, the percentage of all hospital encounters using HFNC increased from 1.11% in 2010 to 3.15% in 2018. Subjects with multiple diagnoses had significantly higher risk of receiving HFNC. Conclusions: The use of HFNC in children presenting to the hospital with common respiratory diseases has increased substantially over the past decade and is no longer confined to treating infants with bronchiolitis. Demographic and diagnostic factors significantly influenced the frequency of HFNC use

Comparative Case Study of Two Biomedical Research Collaboratories

BACKGROUND: Working together efficiently and effectively presents a significant challenge in large-scale, complex, interdisciplinary research projects. Collaboratories are a nascent method to help meet this challenge. However, formal collaboratories in biomedical research centers are the exception rather than the rule. OBJECTIVE: The main purpose of this paper is to compare and describe two collaboratories that used off-the-shelf tools and relatively modest resources to support the scientific activity of two biomedical research centers. The two centers were the Great Lakes Regional Center for AIDS Research (HIV/AIDS Center) and the New York University Oral Cancer Research for Adolescent and Adult Health Promotion Center (Oral Cancer Center). METHODS: In each collaboratory, we used semistructured interviews, surveys, and contextual inquiry to assess user needs and define the technology requirements. We evaluated and selected commercial software applications by comparing their feature sets with requirements and then pilot-testing the applications. Local and remote support staff cooperated in the implementation and end user training for the collaborative tools. Collaboratory staff evaluated each implementation by analyzing utilization data, administering user surveys, and functioning as participant observers. RESULTS: The HIV/AIDS Center primarily required real-time interaction for developing projects and attracting new participants to the center; the Oral Cancer Center, on the other hand, mainly needed tools to support distributed and asynchronous work in small research groups. The HIV/AIDS Center’s collaboratory included a center-wide website that also served as the launch point for collaboratory applications, such as NetMeeting, Timbuktu Conference, PlaceWare Auditorium, and iVisit. The collaboratory of the Oral Cancer Center used Groove and Genesys Web conferencing. The HIV/AIDS Center was successful in attracting new scientists to HIV/AIDS research, and members used the collaboratory for developing and implementing new research studies. The Oral Cancer Center successfully supported highly distributed and asynchronous research, and the collaboratory facilitated real-time interaction for analyzing data and preparing publications. CONCLUSIONS: The two collaboratory implementations demonstrated the feasibility of supporting biomedical research centers using off-the-shelf commercial tools, but they also identified several barriers to successful collaboration. These barriers included computing platform incompatibilities, network infrastructure complexity, variable availability of local versus remote IT support, low computer and collaborative software literacy, and insufficient maturity of available collaborative software. Factors enabling collaboratory use included collaboration incentives through funding mechanism, a collaborative versus competitive relationship of researchers, leadership by example, and tools well matched to tasks and technical progress. Integrating electronic collaborative tools into routine scientific practice can be successful but requires further research on the technical, social, and behavioral factors influencing the adoption and use of collaboratories