Applied Clinical Informatics最新文献

Background: Adolescents are at high risk for sexually transmitted infections (STIs) and frequently present to emergency departments (EDs) for care. Screening for STIs using confidential patient-reported outcomes represents an ideal use of electronic screening methodology.

Objectives: The objectives of this study were to implement a patient-facing, confidential electronic survey to assess adolescent risk for STIs and consent for testing with integrated provider facing electronic clinical decision support (CDS) across six geographically dispersed pediatric EDs and evaluate implementation based on survey and CDS usage metrics.

Methods: A pilot site provided code for the electronic survey, data query, and CDS templates to six EDs. Institutions identified necessary information technology (IT) personnel, completed local build, and made modifications to suit individual site workflow variations with all sites successfully deploying the electronic survey with electronic health record (EHR) -embedded CDS.

Results: 6,165 adolescents completed the confidential health survey between April 12, 2021 - September 25, 2022 out of 79,780 eligible adolescents. The CDS was triggered indicating the patient was at-risk or consented to STI testing across all six sites 2,058 times. The average percentage of time the CDS was acknowledged by a provider was 81.6% (range 45.7% - 97.6%). The median number of providers who acknowledged each instance of the CDS was 2.0. STI testing was ordered from the CDS on average 47.3% of the time. CDS acknowledge selections of "other" and "[testing] already ordered" were the most frequent indications STI testing was not ordered from the CDS.

Conclusions: Successful deployment of patient-facing screeners with integrated electronic CDS across multiple healthcare institutions is feasible. A combination of different types of IT and informatics expertise combined with local knowledge of clinical workflows is essential to success.

Background The Centers for Medicare & Medicaid Services (CMS) introduced changes in outpatient and inpatient evaluation and management (E/M) current procedural terminology (CPT) codes in 2021 and 2023, which were intended to streamline providers' clinical documentation. Objectives To study the effects of aligning inpatient and outpatient note templates with updated CMS guidelines on character length and documentation time per note at an internal medicine residency program in the southeastern United States. Methods In April 2023, the Atrium Health Wake Forest Baptist Internal Medicine Residency Program's inpatient and outpatient note templates were updated according to the most recent CMS guidelines. A pre-post analysis of resident documentation time and length was conducted comparing notes written with the residency note templates from May 1, 2022 to August 31, 2022 (6439 notes) to notes written with the residency note templates from May 1, 2023 to August 31, 2023 (8828 notes). Interns were surveyed regarding their perceptions of the updated note templates. Results After the note template updates, when adjusted for differing percentages of note types in the pre- and post-periods and accounting for multiple notes written by each resident, notes written with the residency note templates decreased by a mean character length of -882 characters (95% CI: -953, -811, p<.0001), while time spent writing notes did not significantly decrease. 17/17 respondents had favorable perceptions of the note templates. Conclusions The internal medicine residency inpatient and outpatient note templates were updated to align with the most recent CMS E/M documentation requirement changes. These note template changes were associated with a meaningful decrease in documentation length but no overall significant reduction in mean documentation time when adjusted for differing percentages of note types in the pre- and post-periods and multiple notes written by the same author. The interns perceived the note template changes positively.

Objective: To assist residents in selecting the correct Current Procedural Terminology (CPT) code for evaluation and management (E/M) services thru the addition of disappearing help text into a standardized note template.

Methods: We created a disappearing text block that summarizes E/M requirements and embedded it into the note template used by residents at a pediatric urgent care clinic. An intervention cohort composed of post graduate year 1 (PGY 1) residents was instructed to use this note template, while senior residents (PGY 2-3) were instructed to use an identical template that lacked the help text. We evaluated the incidence of CPT change by the attending physician for each visit as a proxy for improvement in resident billing practices. Logistic regression with a primary outcome of whether the encounter CPT code was changed was completed.

Results: There were 2,869 encounters during the 255-day study period; the help text was used in 1,112 (38.8%) encounters. There was some crossover in note use; i.e., PGY 1s using the note without help text and PGY 2s using the note with help text. Nevertheless, all residents who used the help text had a lower unadjusted rate of CPT change (22.1% vs 30.6%, OR= 0.64, p < 0.0001). This pattern persisted when stratified by trainee level - PGY 1 (22.6% vs 45.3%, OR=0.35,p < 0.0001) and PGY 2-3 (12.2% vs 27.8%, p = 0.018). Adjusting for multiple factors, the use of help text was associated with a lower incidence of CPT change (odds ratio [OR] = 0.28, 95% confidence interval [CI]: 0.19-0.44).

Conclusions: Residents' use of the disappearing help text was associated with a large decrease in CPT code adjustment by attending physicians, which demonstrates its promise for improved E/M coding and for other applications.

The NIH Pragmatic Trials Collaboratory supports the design and conduct of 31 embedded pragmatic clinical trials, and many of these trials use patient-reported outcome measures (PROMs) to provide valuable information about their patients' health and wellness. Often these trials enroll medically underserved patients, including people with incomes below the federal poverty threshold, racial or ethnically minoritized groups, or rural or frontier communities. In this series of trial case reports, we provide lessons learned about collecting PROMs in these populations. The unbiased collection of PROM data is critical to increase the generalizability of trial outcomes and to address health inequities. Use of electronic health records (EHRs) and other digital modes of PROM administration have gained traction. However, engagement with these modes is often low among disparities prone populations due to lessened digital proficiency, device access, and uptake of EHR portals and web interfaces. To maximize the completeness and representativeness of their trial outcome data, study teams tested a range of strategies to improve PROM response rates with emphasis on disparities prone and underserved patient groups. This manuscript describes the approaches, their implementation, and the targeted populations. Optimized PROM collection required hybrid approaches with multiple outreach modes, high-touch methods, creativity in promoting digital uptake, multi-modal participant engagement, and text messaging.

Background: Healthcare provider burnout is a critical issue with significant implications for individual well-being, patient care, and healthcare system efficiency. Addressing burnout is essential for improving both provider well-being and the quality of patient care. Ambient artificial intelligence (AI) offers a novel approach to mitigating burnout by reducing the documentation burden through advanced speech recognition and natural language processing technologies that summarize the patient encounter into a clinical note to be reviewed by clinicians.

Objective: To assess provider burnout and professional fulfilment associated with Ambient AI technology during a pilot study, assessed using the Stanford Professional Fulfillment Index (PFI).

Methods: A pre-post observational study was conducted at University of Iowa Health Care with 38 volunteer physicians and advanced practice providers. Participants used a commercial ambient AI tool, over a 5-week trial in ambulatory environments. The AI tool transcribed patient-clinician conversations and generated preliminary clinical notes for review and entry into the electronic medical record. Burnout and professional fulfillment were assessed using the Stanford PFI at baseline and post-intervention.

Results: Pre-test and post-test surveys were completed by 35/38 participants (92% survey completion rate). Results showed a significant reduction in burnout scores, with the median burnout score improving from 4.16 to 3.16 (p=0.005), with validated Stanford PFI cutoff for overall burnout 3.33. Burnout rates decreased from 69% to 43%. There was a notable improvement in interpersonal disengagement scores (3.6 vs. 2.5, p<0.001), although work exhaustion scores did not significantly change. Professional fulfillment showed a modest, non-significant upward trend (6.1 vs. 6.5, p=0.10).

Conclusions: Ambient AI significantly reduces healthcare provider burnout and may enhance professional fulfillment. By alleviating documentation burdens, ambient AI can improve operational efficiency and provider well-being. These findings suggest that broader implementation of ambient AI could be a strategic intervention to combat burnout in healthcare settings.

Introduction: During and after the COVID-19 pandemic, communities must cope with several conditions that cause similar upper-respiratory symptoms but are managed differently. We describe community reactions to a self-management toolkit for patients with upper respiratory symptoms to inform mobile e-health app development. The toolkit is based on the '4R' (Right Information, Right Care, Right Patient, Right Time) care planning and management model.

Methods: The 4R Cold, Flu and COVID-19 Information Tool (4R-Toolkit) along with a brief evaluation survey were distributed in three ways: through a Bronx NY Allergy/Asthma clinic, through the Bronx Borough President's Office listserv, and through peer recruitment. The survey assessed respondents' perceptions of the 4R-Toolkit's accessibility, preferences for sharing symptoms with clinicians, social media use, and e-health literacy.

Results: We obtained a diverse sample of 106 Bronx residents, with 83% reporting personal or a social contact with symptoms suggestive of COVID-19. Respondents varied in the information sources they preferred: computer (39%); smart phone (28%); paper (11%) and no preference (22%). Most (67%) reported that social media had at least some impact on their healthcare decisions. Regardless of media preferences, respondents were positive about the 4R-Toolkit. Out of 106 respondents, 91% believed the 4R-Toolkit would help people self-manage upper respiratory symptoms and 85% found it easy to understand. Respondents strongly endorsed retention of all 4R-Toolkit content domains with 81% indicating that they would be willing to share symptoms with providers using a 4R-Toolkit smartphone app.

Conclusion: The 4R-Toolkit can offer patients and community members accurate and up-to-date information on COVID-19, the common cold, and the flu. The user-friendly tool is accessible to diverse individuals, including those with limited e-health literacy. It has potential to support self-management of upper respiratory symptoms and promote patient engagement with providers.

Objectives: To evaluate critical care provider perspectives about diagnostic practices for rare and atypical infections and the potential for using artificial intelligence (AI) as a decision-support system (DSS).

Methods: We conducted an anonymous web-based survey among critical care providers at Mayo Clinic Rochester between 11/25/2023 and 1/15/2024, to evaluate their experience with rare and atypical infection diagnostic processes and AI-based DSSs. We also assessed the perceived usefulness of AI-based DSSs, their potential impact on improving diagnostic practices for rare and atypical infections, and the perceived risks and benefits of their use.

Results: A total of 47/143 providers completed the survey. 38/47 agreed that there was a delay in diagnosing rare and atypical infections. Among those who agreed, limited assessment of specific patient factors and failure to consider them were the most frequently cited important contributing factors (33/38). 38/47 reported familiarity with the AI-based DSS applications available to critical care providers. Less than half (18/38) thought AI-based DSSs often provided valuable insights for patient care, but almost three quarters (34/47) thought AI-based DDSs often provided valuable insight when specifically asked about their ability to improve the diagnosis of rare and atypical infections. All respondents rated reliability as important in enhancing the perceived utility of AI-based DSSs (47/47) and almost all rated interpretability and integration into the workflow as important (45/47). The primary concern about implementing an AI-based DSS in this context was alert fatigue (44/47).

Conclusion: Most critical care providers perceived that there are delays in diagnosing rare infections, indicating inadequate assessment and consideration of the diagnosis as the major contributors. Reliability, interpretability, workflow integration, and alert fatigue emerged as key factors impacting usability of AI-based DSS. These findings will inform the development and implementation of an AI-based diagnostic algorithm to aid in identifying rare and atypical infections.

Background Opioid overdoses have contributed significantly to mortality in the United States. Despite long-standing recommendations from the Centers for Disease Control and Prevention to co-prescribe naloxone for patients receiving opioids who are at high risk of overdose, compliance with these guidelines has remained low. Objectives The objective of this study was to develop and evaluate a hospital-wide electronic health record (EHR)-based clinical decision support (CDS) tool designed to promote naloxone co-prescription for high-risk opioids. Methods We employed an iterative approach to develop a point-of-order, interruptive EHR alert as the primary intervention and assessed naloxone prescription rates, EHR efficiency metrics, and barriers to adoption. Data was obtained from our EHR's clinical data warehouse and analyzed using statistical process control and Chi-square analyses to assess statistically significant differences in prescribing rates during the intervention periods. Results The initial implementation phase of the intervention, spanning from April 2019 to May 2022, yielded a nearly 3-fold increase in the proportion of high-risk patients receiving naloxone, rising from 13.4% [95% CI, 12.9% - 13.8%] to 36.4% [95% CI, 35.2% - 37.5%; p = 1 x 10-38]. Enhancements to the CDS design and logic during the subsequent iteration's study period, June 2022 and December 2023, reduced the number of CDS triggers by more than 30-fold while simultaneously driving an additional increase in naloxone receipt to 42.7% [95% CI, 40.6% - 44.8%; p = 2 x 10-5]. The efficiency of the CDS demonstrated marked improvement, with prescribers accepting the naloxone co-prescription recommendation provided by the CDS in 41.1% of the encounters in version two, compared to 6.2% in version one (p = 6 x 10-9). Conclusion This study offers a sustainable and scalable model to address low rates of naloxone co-prescription and may also be used to target other opportunities for improving guideline-concordant prescribing practices.

Background: Dental informatics is an emerging discipline. Although the accreditation agency governing dental education programs asserts the importance of informatics as foundational knowledge, no well-defined dental informatics courses currently exist within the standard predoctoral dental curriculum. There is a nationwide lack of dental informatics academic programs. This training gap is due to a lack of qualified dental informaticians to impart knowledge on dental informatics.

Objectives: This paper aims to introduce a novel conceptual framework for an interdisciplinary dental informatics program in preparing students to become dental informaticians.

Methods: In 2023, we developed a standalone graduate certificate program in dental informatics at Indiana University (IU) School of Dentistry in collaboration with IU Luddy School of Informatics, Computing, and Engineering and IU Fairbanks School of Public Health. Feedback was collected through online surveys to assess course quality from students who took Introduction to Health Information in Dentistry. Feedback was analyzed qualitatively, utilizing a thematic analysis approach. Common responses relevant to dental informatics education were grouped into themes.

Results: Five major themes emerged during our analysis of the students' feedback: foundational knowledge and skills; experiential learning: learning by doing; access to resources and working on clinical information systems; health promotion through team-based learning; and retention of knowledge assessment and application. A conceptual framework was formulated through these themes as a guideline for future program improvement. This interdisciplinary educational program framework showed how students and faculty from various disciplines could collaborate, learn from each other, and bring in expertise from different domains. The collaboration happens in clinical, laboratory, and virtual settings to acquire hands on learning through practice and research projects.

Conclusions: The developed conceptual framework aligned with the interdisciplinary nature of dental informatics. It can potentially be adopted by other interdisciplinary informatics programs in health and non-health care disciplines.

Background While necessary and educationally beneficial, administrative tasks such as case and patient tracking may carry additional burden for surgical trainees. Automated systems targeting these tasks are scarce, leading to manual and inefficient workflows. Methods We created an electronic health record (EHR)-based, user-specific dashboard for surgical residents to compile resident-specific data: bedside procedures performed, operative cases performed or participated in, and notes written by the resident as a surrogate for patients cared for. Usability testing was performed with resident volunteers, and residents were also surveyed post-implementation to assess for efficacy and satisfaction. Access log data from the EHR was used to assess dashboard usage over time. Descriptive statistics were calculated. Results The dashboard was implemented on a population of approximately 175 surgical residents in 5 different departments (General Surgery, Obstetrics and Gynecology, Neurosurgery, Orthopedics, and Otolaryngology) at a single academic medical center. 6 resident volunteers participating in usability testing completed an average of 96% of preset tasks independently. Average responses to five questions extracted from the System Usability Scale (SUS) questions ranged from 4.0 to 4.67 out of 5. Post-implementation surveys indicated high resident satisfaction (4.39 out of 5) and moderate rates of use, with 46.4% of residents using the dashboard at least monthly. Daily use of the dashboard has increased over time, especially after making the dashboard a default for surgical residents. Conclusion An EHR-based dashboard compiling resident-specific data can improve the efficiency of administrative tasks and supplement longitudinal education.