Applied Clinical Informatics最新文献

Background:  There is a need to integrate informatics education into medical training programs given the rise in demand for health informaticians and the call on the Accreditation Council for Graduate Medical Education and the body of undergraduate medical education for implementation of informatics curricula.

Objectives:  This report outlines a 2-year longitudinal informatics curriculum now currently in its seventh year of implementation. This report is intended to inform U.S. Graduate Medical Education (GME) program leaders of the necessary requirements for implementation of a similar program at their institution.

Methods:  The curriculum aligns with the core content for the subspecialty of clinical informatics (CI) and is led by a multidisciplinary team with both informatics and clinical expertise. This educational pathway has a low direct cost and is a practical example of the academic learning health system (aLHS) in action. The pathway is housed within an internal medicine department at a large tertiary academic medical center.

Results:  The curriculum has yielded 13 graduates from both internal medicine (11, 85%) and pediatrics (2, 15%) whose projects have spanned acute and ambulatory care and multiple specialties. Projects have included clinical decision support tools, of which some will be leveraged as substrate in applications seeking extramural funding. Graduates have gone on to CI board certification and fellowship, as well as several other specialties, creating a distributed network of clinicians with specialized experience in applied CI.

Conclusion:  An informatics curriculum at the GME level may increase matriculation to CI fellowship and more broadly increase development of the CI workforce through building a cadre of physicians with health information technology expertise across specialties without formal CI board certification. We offer an example of a longitudinal pathway, which is rooted in aLHS principles. The pathway requires a dedicated multidisciplinary team and departmental and information technology leadership support.

Objectives:  Duplicate patient records can increase costs and medical errors. We assessed the association between demographic factors, comorbidities, health care usage, and duplicate electronic health records.

Methods:  We analyzed the association between duplicate patient records and multiple demographic variables (race, Hispanic ethnicity, sex, and age) as well as the Charlson Comorbidity Index (CCI), number of diagnoses, and number of health care encounters. The study population included 3,018,413 patients seen at a large urban academic medical center with at least one recorded diagnosis. Duplication of patient medical records was determined by using a previously validated enterprise Master Person Index.

Results:  Unknown or missing demographic data, Black race when compared with White race (odds ratio [OR]: 1.35, p < 0.001), Hispanic compared with non-Hispanic ethnicity (OR: 1.48, p < 0.001), older age (OR: 1.01, p < 0.001), and "Other" sex compared with female sex (OR: 4.71, p < 0.001) were associated with higher odds of having a duplicate record. Comorbidities (CCI, OR: 1.10, p < 0.001) and more encounters with the health care system (OR: 1.01, p < 0.001) were also associated with higher odds of having a duplicate record. In contrast, male sex compared with female sex was associated with lower odds of having a duplicate record (OR: 0.88, p < 0.001).

Conclusion:  The odds of duplications in medical records were higher in Black, Hispanic, older, nonmale patients with more health care encounters, more comorbidities, and unknown demographic data. Understanding the epidemiology of duplicate records can help guide prevention and mitigation efforts for high-risk populations. Duplicate records can contribute to disparities in health care outcomes for minority populations.

Background:  Ensuring the security of nursing information holds substantial importance to nursing outcomes and healthcare system management. The awareness of information security among nurses in China is generally inadequate, and there is a lack of standardized evaluation tools for nurse information security in nursing practice. The nursing sector necessitates the establishment of a robust culture surrounding information security.

Objective:  The aim of this study was to construct a self-reporting instrument for evaluating nursing information security.

Methods:  The research team utilized literature analysis and group discussions to draft the item pool. After two rounds of Delphi consultation by 15 experts and pilot testing, the initial questionnaire was formed. Item analysis was carried out on the questionnaire, and the validity and reliability of the instrument were statistically tested by computing the Keiser-Meier-Olkin and Bartlett's tests, an exploratory factor analysis (EFA), a confirmatory factor analysis (CFA), convergent and discriminative validity, descriptive statistics, Cronbach's α, and test-retest reliability.

Results:  A total of 501 nurses participated in the study, supplemented by the inclusion of five experts who were invited to contribute to the assessment of content validity. Four factors were formed using EFA (n = 250), and the cumulative variance contribution rate was found to be 60.10%. The CFA (n = 251) showed that the model fit was good. The overall Cronbach's α coefficient of the questionnaire was 0.948, and the test-retest reliability was 0.837.

Conclusion:  Finally, the nursing information security questionnaire (NIS-Q) with 38 items and three dimensions of knowledge, attitude, and practice were formed. A promising assessment instrument for gauging the degree of nursing information security was introduced. Further, a foundational platform was established for implementing specific enhancement strategies aimed at advancing nursing information security.

Background:  As teleconsultations continue to rise in popularity due to their convenience and accessibility, it is crucial to identify and address the challenges they present in order to improve the patient experience, enhance outcomes, and ensure the quality of care. To identify communication challenges that clinicians and patients experience during teleconsultation, a scoping review was conducted.

Objective:  This study aimed to identify communication challenges that clinicians and patients experience during teleconsultation.

Methods:  Studies were obtained from four databases (Ovid [MEDLINE], Ovid [Embase], CINAHL, and Scopus). Gray literatures were not included. Studies focused on communication challenges between clinicians and their patients during teleconsultation in the context of coronavirus disease 2019 (COVID-19) and published from January 2000 to December 2022, were collected. The screening process was conducted by two independent reviewers. Data extraction was performed using a standardized form to capture study characteristics and communication challenges. Extracted data were analyzed to identify the communication challenges during teleconsultation, adherent to Preferred Reporting Items for Systematic Reviews and Meta-Analyses for Scoping Review (PRISMA-ScR).

Results:  A total of 893 studies were collected from four databases and 26 studies were selected based on inclusion/exclusion criteria. Of these 26 eligible studies, 12 (46%) were from the United States, 3 studies (12%) were from Australia, and 2 (8%) were from the United Kingdom and Canada. These studies included 12 (46%) qualitative studies, 6 (23%) quantitative studies, 6 (23%) review articles, and 2 (8%) case reports. Eight factors contributing to communication challenges between clinicians and patients during teleconsultations were identified: technical issues, difficulties in developing rapport, lack of non-verbal communication, lack of physical examination, language barrier, spatial issues, clinician preparation, and difficulties in assessing patients' health literacy.

Conclusion:  Eight factors were identified as contributing to communication challenges during teleconsultation in the context of COVID-19. These findings highlight the need to address communication challenges to ensure effective teleconsultations. With the rise of teleconsultation in routine health care delivery, further research is warranted to confirm these findings and to explore ways to overcome communication challenges during teleconsultation.

Background:  Health professions trainees (trainees) are unique as they learn a chosen field while working within electronic health records (EHRs). Efforts to mitigate EHR burden have been described for the experienced health professional (HP), but less is understood for trainees. EHR or documentation burden (EHR burden) affects trainees, although not all trainees use EHRs, and use may differ for experienced HPs.

Objectives:  This study aimed to develop a model of how interventions to mitigate EHR burden fit within the trainee EHR workflow: the Trainee EHR Burden Model. (We: 1) Examined trainee experiences of interventions aimed at mitigating EHR burden (scoping review) and (2) Adapted an existing workflow model by mapping included studies (concept clarification).

Methods:  We conducted a four-database scoping review applying Preferred Reporting Items for Systematic Reviews and Meta-Analysis Extensions for Scoping Review (PRISMA-ScR) guidance, examining scholarly, peer-reviewed studies that measured trainee experience of interventions to mitigate EHR burden. We conducted a concept clarification categorizing, then mapping studies to workflow model elements. We adapted the model to intervenable points for trainee EHR burden.

Results:  We identified 11 studies examining interventions to mitigate EHR burden that measured trainee experience. Interventions included curriculum, training, and coaching on the existing EHR for both simulated or live tasks; evaluating scribes' impact; adding devices or technology tailored to rounds; and team communication or data presentation at end-of-shift handoffs. Interventions had varying effects on EHR burden, most commonly measured through surveys, and less commonly, direct observation. Most studies had limited sample sizes and focused on inpatient settings and physician trainees.

Conclusion:  Few studies measured trainee perspectives of interventions aiming to mitigate EHR burden. Many studies applied quasi-experimental designs and focused on inpatient settings. The Trainee EHR Burden Model, adapted from an existing workflow model, offers a starting place to situate points of intervention in trainee workflow. Further research is needed to design new interventions targeting stages of HP trainee workflow, in a range of clinical settings.

Objective:  This study aimed to bridge the educational gap in clinical informatics (CI) at the residency level and stimulate interest in CI as a rewarding career path.

Methods:  We developed an innovative CI and quality improvement (QI) resident rotation. This rotation replaced traditional QI blocks for Internal Medicine and several other residency programs, offering comprehensive exposure to core informatics and QI principles. The curriculum featured prerecorded didactics, hands-on projects, department meetings, and an optional EPIC SmartUser program. Resident participation and feedback were evaluated through postrotation surveys.

Results:  Since its inception on July 1, 2022, 57 residents have completed the rotation, with a majority rating their experience favorably. Residents also valued the educational course content and expressed an increased likelihood of integrating informatics into their future careers.

Conclusion:  The rotation has successfully integrated into existing multiple residency programs, demonstrating an effective model for delivering informatics education. Initial outcomes show enhanced resident engagement and competency in CI, promising a progressive impact on the future physician workforce. Continued expansion and evaluation of this rotation are expected to further encourage formal CI training and career interest.

Objective:  Commercially available large language models such as Chat Generative Pre-Trained Transformer (ChatGPT) cannot be applied to real patient data for data protection reasons. At the same time, de-identification of clinical unstructured data is a tedious and time-consuming task when done manually. Since transformer models can efficiently process and analyze large amounts of text data, our study aims to explore the impact of a large training dataset on the performance of this task.

Methods:  We utilized a substantial dataset of 10,240 German hospital documents from 1,130 patients, created as part of the investigating hospital's routine documentation, as training data. Our approach involved fine-tuning and training an ensemble of two transformer-based language models simultaneously to identify sensitive data within our documents. Annotation Guidelines with specific annotation categories and types were created for annotator training.

Results:  Performance evaluation on a test dataset of 100 manually annotated documents revealed that our fine-tuned German ELECTRA (gELECTRA) model achieved an F1 macro average score of 0.95, surpassing human annotators who scored 0.93.

Conclusion:  We trained and evaluated transformer models to detect sensitive information in German real-world pathology reports and progress notes. By defining an annotation scheme tailored to the documents of the investigating hospital and creating annotation guidelines for staff training, a further experimental study was conducted to compare the models with humans. These results showed that the best-performing model achieved better overall results than two experienced annotators who manually labeled 100 clinical documents.

Objectives:  This research study aims to advance the staging of Parkinson's disease (PD) by incorporating machine learning to assess and include a broader multifunctional spectrum of neurocognitive symptoms in the staging schemes beyond motor-centric assessments. Specifically, we provide a novel framework to modernize and personalize PD staging more objectively by proposing a hybrid feature scoring approach.

Methods:  We recruited 37 individuals diagnosed with PD, each of whom completed a series of tablet-based neurocognitive tests assessing motor, memory, speech, executive functions, and tasks ranging in complexity from single to multifunctional. Then, the collected data were used to develop a hybrid feature scoring system to calculate a weighted vector for each function. We evaluated the current PD staging schemes and developed a new approach based on the features selected and extracted using random forest and principal component analysis.

Results:  Our findings indicate a substantial bias in current PD staging systems toward fine motor skills, that is, other neurological functions (memory, speech, executive function, etc.) do not map into current PD stages as well as fine motor skills do. The results demonstrate that a more accurate and personalized assessment of PD severity could be achieved by including a more exhaustive range of neurocognitive functions in the staging systems either by involving multiple functions in a unified staging score or by designing a function-specific staging system.

Conclusion:  The proposed hybrid feature score approach provides a comprehensive understanding of PD by highlighting the need for a staging system that covers various neurocognitive functions. This approach could potentially lead to more effective, objective, and personalized treatment strategies. Further, this proposed methodology could be adapted to other neurodegenerative conditions such as Alzheimer's disease or amyotrophic lateral sclerosis.

Background:  Nephrotoxin exposure may worsen kidney injury and impair kidney recovery if continued in patients with acute kidney injury (AKI).

Objectives:  This study aimed to determine if tiered implementation of a clinical decision support system (CDSS) would reduce nephrotoxin use in cardiac surgery patients with AKI.

Methods:  We assessed patients admitted to the cardiac surgery intensive care unit at a tertiary care center from January 2020 to December 2021, and August 2022 to September 2023. A passive electronic AKI alert was activated in July 2020, followed by an electronic nephrotoxin alert in March 2023. In this alert, active nephrotoxic medication orders resulted in a passive alert, whereas new orders were met with an interruptive alert. Primary outcome was discontinuation of nephrotoxic medications within 30 hours after AKI. Secondary outcomes included AKI-specific clinical actions, determined through modified Delphi process and patient-centered outcomes. We compared all outcomes across five separate eras, divided based on the tiered implementation of these alerts.

Results:  A total of 503 patients met inclusion criteria. Of 114 patients who received nephrotoxins before AKI, nephrotoxins were discontinued after AKI in 6 (25%) patients in pre AKI-alert era, 8 (33%) patients in post AKI-alert era, 7 (35%) patients in AKI-alert long-term follow up era, 7 (35%) patients in pre nephrotoxin-alert era, and 14 (54%) patients in post nephrotoxin-alert era (p = 0.047 for trend). Among AKI-specific consensus actions, we noted a decreased use of intravenous fluids, increased documentation of goal mean arterial pressure of 65 mm Hg or higher, and increased use of bedside point of care echocardiogram over time. Among exploratory clinical outcomes we found a decrease in proportion of stage III AKI, need for dialysis, and length of hospital stay over time.

Conclusion:  Tiered implementation of CDSS for recognition of AKI and nephrotoxin exposure resulted in a progressive improvement in the discontinuation of nephrotoxins.

Background:  Interoperability between electronic health records (EHR) and immunization information systems (IIS) may positively influence data quality, affecting timeliness, completeness, and accuracy of these data. However, the extent to which EHR/IIS interoperability may influence the day-to-day vaccination workflow and related recordkeeping tasks performed at medical practices is unclear.

Objective:  This study aimed to assess how EHR/IIS interoperability may influence the vaccination workflow at medical practices and to identify related impacts on clinical and administrative activities.

Methods:  We identified practices (family medicine, pediatrics, internal medicine, local health departments) from the Michigan Care Improvement Registry (MCIR), the statewide IIS in Michigan, representing each of the three HL7 interoperability levels (non-HL7, unidirectional, bidirectional). We conducted semi-structured interviews to assess how practices interact with the MCIR throughout the vaccination workflow. Transcripts were reviewed and coded to characterize practices' use of EHRs, MCIR, and other related technologies across the vaccination workflow.

Results:  Practices completed Phase 1 (n = 45) and Phase 2 (n = 42) interviews, representing a range of medical specialties, geographic locations, and sizes. HL7 connectivity expanded among the participating practices; by the conclusion of the study, all practices had initiated at least unidirectional HL7 capability. Providers and staff relied heavily upon both their EHRs and MCIR throughout a wide range of vaccination-related activities. Most practices relied on MCIR as their primary source of vaccination history information, and nearly all practices also reported use of paper forms, documentation, and other summaries throughout the vaccination workflow.

Conclusion:  Practices employed both their EHRs and IIS throughout the entire vaccination workflow, although the use of each relied heavily on paper-based processes. While benefits of adopting EHR/IIS interoperability were reported by practices, this may require staff to learn and implement new workflow processes that can be time consuming and may introduce new challenges.