A patient-centered nurse-supported primary care-based collaborative care program to treat opioid use disorder and depression: Design and protocol for the MI-CARE randomized controlled trial.

BACKGROUND: Opioid use disorder (OUD) contributes to rising morbidity and mortality. Life-saving OUD treatments can be provided in primary care but most patients with OUD don't receive treatment. Comorbid depression and other conditions complicate OUD management, especially in primary care. The MI-CARE trial is a pragmatic randomized encouragement (Zelen) trial testing whether offering collaborative care (CC) to patients with OUD and clinically-significant depressive symptoms increases OUD medication treatment with buprenorphine and improves depression outcomes compared to usual care. METHODS: Adult primary care patients with OUD and depressive symptoms (n ≥ 800) from two statewide health systems: Kaiser Permanente Washington and Indiana University Health are identified with computer algorithms from electronic Health record (EHR) data and automatically enrolled. A random sub-sample (50%) of eligible patients is offered the MI-CARE intervention: a 12-month nurse-driven CC intervention that includes motivational interviewing and behavioral activation. The remaining 50% of the study cohort comprise the usual care comparison group and is never contacted. The primary outcome is days of buprenorphine treatment provided during the intervention period. The powered secondary outcome is change in Patient Health Questionnaire (PHQ)-9 depression scores. Both outcomes are obtained from secondary electronic healthcare sources and compared in "intent-to-treat" analyses. CONCLUSION: MI-CARE addresses the need for rigorous encouragement trials to evaluate benefits of offering CC to generalizable samples of patients with OUD and mental health conditions identified from EHRs, as they would be in practice, and comparing outcomes to usual primary care. We describe the design and implementation of the trial, currently underway. TRIAL REGISTRATION: ClinicalTrials.gov Identifier: NCT05122676. Clinical trial registration date: November 17, 2021.

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.

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.

Risk Factors for Bleeding and Clinical Ineffectiveness Associated With Clopidogrel Therapy: A Comprehensive Meta-Analysis.

Although clopidogrel is a frequently used antiplatelet medication to treat and prevent atherothrombotic disease, clinicians must balance its clinical effectiveness with the potential side effect of bleeding. However, many previous studies have evaluated beneficial and adverse factors separately. The objective of our study was to perform a comprehensive meta-analysis of studies of clopidogrel's clinical effectiveness and/or risk of bleeding in order to identify and assess all reported risk factors, thus helping clinicians to balance patient safety with drug efficacy. We analyzed randomized controlled trials (RCTs) of maintenance use in four stages: search for relevant primary articles; abstract and full article screening; quality assessment and data extraction; and synthesis and data analysis. Screening of 7,109 articles yielded 52 RCTs that met the inclusion criteria. Twenty-seven risk factors were identified. "Definite risk factors" were defined as those with aggregated odds ratios (ORs) > 1 and confidence intervals (CIs) > 1 if analyzed in more than one study. Definite risk factors for major bleeding were concomitant aspirin use (OR 2.83, 95% CI 2.04-3.94) and long duration of clopidogrel therapy (> 6 months) (OR 1.74, 95% CI 1.21-2.50). Dual antiplatelet therapy, extended clopidogrel therapy, and high maintenance dose (150 mg/day) of clopidogrel were definite risk factors for any bleeding. Reduced renal function, both mild and severe, was the only definite risk factor for clinical ineffectiveness. These findings can help clinicians predict the risks and effectiveness of clopidogrel use for their patients and be used in clinical decision support tools.

Preliminary evaluation of the Chest Pain Dashboard, a FHIR-based approach for integrating health information exchange information directly into the clinical workflow.

Despite efforts aimed at improving the integration of clinical data from health information exchanges (HIE) and electronic health records (EHR), interoperability remains limited. Barriers due to inefficiencies and workflow interruptions make using HIE data during care delivery difficult. Capitalizing on the development of the Fast Healthcare Interoperability Resource (FHIR) specification, we designed and developed a Chest Pain Dashboard that integrates HIE data into EHRs. This Dashboard was implemented in one emergency department (ED) of Indiana University Health in Indiana. In this paper, we present the preliminary findings from a mixed-methods evaluation of the Dashboard. A difference-in-difference analysis suggests that the ED with the Dashboard implementation resulted in a significant increase in HIE use compared to EDs without. This finding was supported by qualitative interviews. While these results are encouraging, we also identified areas for improvement. FHIR-based solutions may offer promising approaches to encourage greater accessibility and use of HIE data.

Three-Component Mixture Model-Based Adverse Drug Event Signal Detection for the Adverse Event Reporting System.

The US Food and Drug Administration (FDA) Adverse Event Reporting System (FAERS) is an important source for detecting adverse drug event (ADE) signals. In this article, we propose a three-component mixture model (3CMM) for FAERS signal detection. In 3CMM, a drug-ADE pair is assumed to have either a zero relative risk (RR), or a background RR (mean RR = 1), or an increased RR (mean RR >1). By clearly defining the second component (mean RR = 1) as the null distribution, 3CMM estimates local false discovery rates (FDRs) for ADE signals under the empirical Bayes framework. Compared with existing approaches, the local FDR's top signals have noninferior or better sensitivities to detect true signals in both FAERS analysis and simulation studies. Additionally, we identify that the top signals of different approaches have different patterns, and they are complementary to each other.

A comprehensive review and meta-analysis of risk factors for statin-induced myopathy.

PURPOSE: To aid prescribers in assessing a patient's risk for statin-induced myopathy (SIM), we performed a comprehensive review of currently known risk factors and calculated aggregated odds ratios for each risk factor through a meta-analysis. METHODS: This meta-analysis was done through four phases: (1) Identification of the relevant primary literature; (2) abstract screening using inclusion and exclusion criteria; (3) detailed review and data extraction; and (4) synthesis and statistical analysis. RESULTS: Out of 44 papers analyzed from 836 papers searched from MEDLINE, 18 different potential risk factors were collected, divided into three categories: three demographics (11 papers), ten clinical factors (31 papers), and five pharmacogenetics/biomarkers (12 papers). Risk factors significant for myopathy and/or rhabdomyolysis included age, gender, diabetes, renal impairment, cardiovascular disease, certain interacting drugs, and mutations of the SLCO1B1 gene, which encodes a transporter protein in the liver. Several factors, such as gender, race, cardiovascular disease, and the GATM gene, which encodes a protein for creatine synthesis, appeared to be protective in terms of the outcomes of interest. CONCLUSIONS: This comprehensive assessment of risk factors can help support clinicians in reducing the incidence of SIM in their patient population on statins.

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).

A prototype mobile application for triaging dental emergencies.

BACKGROUND: Evidence suggests that dental emergencies are likely to occur when preferred care is less accessible. Communication barriers often exist that cause patients to receive suboptimal treatment or experience discomfort for extended lengths of time. Furthermore, limitations in the conventional approach for managing dental emergencies prevent dentists from receiving critical information before patient visits. METHODS: The authors developed a mobile application to mediate the uncertainty of dental emergencies. The development and study consisted of a needs analysis and quality assessment of intraoral images captured by smartphones, prototype development, refining the prototype through usability inspection methods, and formative evaluation through usability testing with prospective users. RESULTS: The developed application successfully guided all users through a series of questions designed to capture clinically meaningful data by using familiar smartphone functions. All participants were able to complete a report within 4 minutes, and all clinical information was comprehended by the users. CONCLUSIONS: Patient-provided information accompanied by high-resolution images may help dentists substantially in predicting urgency or preparing necessary treatment resources. The results illustrate the feasibility of patients using smartphone applications to report dental emergencies. This technology allows dentists to assess care remotely when direct patient contact is less practical. PRACTICAL IMPLICATIONS: This study's results demonstrate that patients can use mobile applications to transmit clinical data to their dentists and suggest the possibility of expanding the use of mobile applications to enhance access to routine and emergency dental care. The authors addressed how to enable patients to communicate emergency needs directly to a dentist while obviating patient emergency department visits.

Finding collaborators: toward interactive discovery tools for research network systems.

BACKGROUND: Research networking systems hold great promise for helping biomedical scientists identify collaborators with the expertise needed to build interdisciplinary teams. Although efforts to date have focused primarily on collecting and aggregating information, less attention has been paid to the design of end-user tools for using these collections to identify collaborators. To be effective, collaborator search tools must provide researchers with easy access to information relevant to their collaboration needs. OBJECTIVE: The aim was to study user requirements and preferences for research networking system collaborator search tools and to design and evaluate a functional prototype. METHODS: Paper prototypes exploring possible interface designs were presented to 18 participants in semistructured interviews aimed at eliciting collaborator search needs. Interview data were coded and analyzed to identify recurrent themes and related software requirements. Analysis results and elements from paper prototypes were used to design a Web-based prototype using the D3 JavaScript library and VIVO data. Preliminary usability studies asked 20 participants to use the tool and to provide feedback through semistructured interviews and completion of the System Usability Scale (SUS). RESULTS: Initial interviews identified consensus regarding several novel requirements for collaborator search tools, including chronological display of publication and research funding information, the need for conjunctive keyword searches, and tools for tracking candidate collaborators. Participant responses were positive (SUS score: mean 76.4%, SD 13.9). Opportunities for improving the interface design were identified. CONCLUSIONS: Interactive, timeline-based displays that support comparison of researcher productivity in funding and publication have the potential to effectively support searching for collaborators. Further refinement and longitudinal studies may be needed to better understand the implications of collaborator search tools for researcher workflows.

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.

Integrating tobacco dependence counseling into electronic dental records: a multi-method approach.

Dentistry has historically seen tobacco dependence as a medical problem. As a consequence, dentistry has not adopted or developed effective interventions to deal with tobacco dependence. With the expanded use of electronic dental records, the authors identified an opportunity to incorporate standardized expert support for tobacco dependence counseling during the dental visit. Using qualitative results from observations and focus groups, a decision support system was designed that suggested discussion topics based on the patient's desire to quit and his or her level of nicotine addiction. Because dental providers are always pressed for time, the goal was a three-minute average intervention interval. To fulfill the provider's need for an easy way to track ongoing interventions, script usage was recorded. This process helped the provider track what he or she had said to the patient about tobacco dependence during previous encounters and to vary the messages. While the individual elements of the design process were not new, the combination of them proved to be very effective in designing a usable and accepted intervention. The heavy involvement of stakeholders in all components of the design gave providers and administrators ownership of the final product, which was ultimately adopted for use in all the clinics of a large dental group practice in Minnesota.

Computer-assisted guidance for dental office tobacco-cessation counseling: a randomized controlled trial.

BACKGROUND: Decreases in smoking prevalence from recent decades have slowed, and national goals to reduce tobacco use remain unmet. Healthcare providers, including those in physician and dental teams, have access to evidence-based guidelines to help patients quit smoking. Translation of those guidelines into practice, however, remains low. Approaches that involve screening for drug use, brief intervention, and referral to treatment (SBIRT) are a promising, practical solution. PURPOSE: This study examined whether dentists and dental hygienists would assess interest in quitting, deliver a brief tobacco intervention, and refer to a tobacco quitline more frequently as reported by patients if given computer-assisted guidance in an electronic patient record versus a control group providing usual care. DESIGN: A blocked, group-randomized trial was conducted from November 2010 to April 2011. Randomization was conducted at the clinic level. Patients nested within clinics represented the lowest-level unit of observation. SETTING/PARTICIPANTS: Participants were patients in HealthPartners dental clinics. INTERVENTION: Intervention clinics were given a computer-assisted tool that suggested scripts for patient discussions. Usual care clinics provided care without the tool. MAIN OUTCOME MEASURES: Primary outcomes were post-appointment patient reports of the provider assessing interest in quitting, delivering a brief intervention, and referring them to a quitline. RESULTS: Patient telephone surveys (72% response rate) indicated that providers assessed interest in quitting (control 70% vs intervention 87%, p=0.0006); discussed specific strategies for quitting (control 26% vs intervention 47%, p=0.003); and referred the patient to a tobacco quitline (control 17% vs intervention 37%, p=0.007) more frequently with the support of a computer-assisted tool integrated into the electronic health record. CONCLUSIONS: Clinical decision support embedded in electronic health records can effectively help providers deliver tobacco interventions. These results build on evidence in medical settings supporting this approach to improve provider-delivered tobacco cessation. TRIAL REGISTRATION: This study is registered at ClinicalTrials.govNCT01584882.

From information technology to informatics: the information revolution in dental education.

The capabilities of information technology (IT) have advanced precipitously in the last fifty years. Many of these advances have enabled new and beneficial applications of IT in dental education. However, conceptually, IT use in dental schools is only in its infancy. Challenges and opportunities abound for improving how we support clinical care, education, and research with IT. In clinical care, we need to move electronic dental records beyond replicating paper, connect information on oral health to that on systemic health, facilitate collaborative care through teledentistry, and help clinicians apply evidence-based dentistry and preventive management strategies. With respect to education, we should adopt an evidence-based approach to IT use for teaching and learning, share effective educational content and methods, leverage technology-mediated changes in the balance of power between faculty and students, improve technology support for clinical teaching, and build an information infrastructure centered on learners and organizations. In research, opportunities include reusing clinical care data for research studies, helping advance computational methods for research, applying generalizable research tools in dentistry, and reusing research data and scientific workflows. In the process, we transition from a focus on IT-the mere technical aspects of applying computer technology-to one on informatics: the what, how, and why of managing information.

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.

The feasibility of a three-dimensional charting interface for general dentistry.

BACKGROUND: Most current paper- and computer-based formats for patient documentation use a two-dimensional dental chart, a design that originated almost 150 years ago in the United States. No studies have investigated the inclusion of a three-dimensional (3-D) charting interface in a general dental record. METHODS: A multidisciplinary research team with expertise in human-computer interaction, dental informatics and computer science conducted a 14-week project to develop and evaluate a proof of concept for a 3-D dental record. Through several iterations of paper- and computer-based prototypes, the project produced a high-fidelity (hi-fi) prototype that was evaluated by two dentists and two dental students. RESULTS: The project implemented a prototypical patient record built around a 3-D model of a patient's maxillofacial structures. Novel features include automatic retrieval of images and radiographs; a flexible view of teeth, soft tissue and bone; access to historical patient data through a timeline; and the ability to focus on a single tooth. CONCLUSIONS: Users tests demonstrated acceptance for the basic design of the prototype, but also identified several challenges in developing intuitive, easy-to-use navigation methods and hi-fi representations in a 3-D record. CLINICAL IMPLICATIONS: Test participants in this project accepted the preliminary design of a 3-D dental record. Significant further research must be conducted before the concept can be applied and evaluated in clinical practice.

Heuristic evaluation of clinical functions in four practice management systems: a pilot study.

BACKGROUND: Dentists report that the complexity and poor usability of practice management systems (PMSs) are factors in the slow adoption of computers at chairside. METHODS: Three dental informatics researchers performed heuristic evaluations of four PMSs to identify potential usability problems that may be encountered during the clinical care process. Each researcher performed three common clinical documentation tasks on each PMS and examined the clinical user interface of each system using a published list of 10 software heuristics. An observer recorded all findings, summarized the results and totaled the heuristic violations across all programs. RESULTS: The authors found 229 heuristic violations. Consistency and Standards, Match Between System and the Real World, and Error Prevention were the heuristics that were violated most commonly. The patterns of heuristic violations across software packages were relatively similar. CONCLUSIONS: The findings provide an initial assessment of potential usability problems in four PMSs. The identified violations highlight aspects of dental software that may present the most significant problems to users. CLINICAL IMPLICATIONS: Heuristic violations in PMSs may result in usability problems for dentists and other office personnel, reducing efficiency and effectiveness of a software implementation. Vendors should consider applying user-centered design methodologies to reduce the number of potential usability problems.