Cumulus: a federated electronic health record-based learning system powered by Fast Healthcare Interoperability Resources and artificial intelligence.

OBJECTIVE: To address challenges in large-scale electronic health record (EHR) data exchange, we sought to develop, deploy, and test an open source, cloud-hosted app "listener" that accesses standardized data across the SMART/HL7 Bulk FHIR Access application programming interface (API). METHODS: We advance a model for scalable, federated, data sharing and learning. Cumulus software is designed to address key technology and policy desiderata including local utility, control, and administrative simplicity as well as privacy preservation during robust data sharing, and artificial intelligence (AI) for processing unstructured text. RESULTS: Cumulus relies on containerized, cloud-hosted software, installed within a healthcare organization's security envelope. Cumulus accesses EHR data via the Bulk FHIR interface and streamlines automated processing and sharing. The modular design enables use of the latest AI and natural language processing tools and supports provider autonomy and administrative simplicity. In an initial test, Cumulus was deployed across 5 healthcare systems each partnered with public health. Cumulus output is patient counts which were aggregated into a table stratifying variables of interest to enable population health studies. All code is available open source. A policy stipulating that only aggregate data leave the institution greatly facilitated data sharing agreements. DISCUSSION AND CONCLUSION: Cumulus addresses barriers to data sharing based on (1) federally required support for standard APIs, (2) increasing use of cloud computing, and (3) advances in AI. There is potential for scalability to support learning across myriad network configurations and use cases.

Real world performance of the 21st Century Cures Act population-level application programming interface.

OBJECTIVE: To evaluate the real-world performance of the SMART/HL7 Bulk Fast Health Interoperability Resources (FHIR) Access Application Programming Interface (API), developed to enable push button access to electronic health record data on large populations, and required under the 21st Century Cures Act Rule. MATERIALS AND METHODS: We used an open-source Bulk FHIR Testing Suite at 5 healthcare sites from April to September 2023, including 4 hospitals using electronic health records (EHRs) certified for interoperability, and 1 Health Information Exchange (HIE) using a custom, standards-compliant API build. We measured export speeds, data sizes, and completeness across 6 types of FHIR. RESULTS: Among the certified platforms, Oracle Cerner led in speed, managing 5-16 million resources at over 8000 resources/min. Three Epic sites exported a FHIR data subset, achieving 1-12 million resources at 1555-2500 resources/min. Notably, the HIE's custom API outperformed, generating over 141 million resources at 12 000 resources/min. DISCUSSION: The HIE's custom API showcased superior performance, endorsing the effectiveness of SMART/HL7 Bulk FHIR in enabling large-scale data exchange while underlining the need for optimization in existing EHR platforms. Agility and scalability are essential for diverse health, research, and public health use cases. CONCLUSION: To fully realize the interoperability goals of the 21st Century Cures Act, addressing the performance limitations of Bulk FHIR API is critical. It would be beneficial to include performance metrics in both certification and reporting processes.

Cumulus: A federated EHR-based learning system powered by FHIR and AI.

Objective: To address challenges in large-scale electronic health record (EHR) data exchange, we sought to develop, deploy, and test an open source, cloud-hosted app 'listener' that accesses standardized data across the SMART/HL7 Bulk FHIR Access application programming interface (API). Methods: We advance a model for scalable, federated, data sharing and learning. Cumulus software is designed to address key technology and policy desiderata including local utility, control, and administrative simplicity as well as privacy preservation during robust data sharing, and AI for processing unstructured text. Results: Cumulus relies on containerized, cloud-hosted software, installed within a healthcare organization's security envelope. Cumulus accesses EHR data via the Bulk FHIR interface and streamlines automated processing and sharing. The modular design enables use of the latest AI and natural language processing tools and supports provider autonomy and administrative simplicity. In an initial test, Cumulus was deployed across five healthcare systems each partnered with public health. Cumulus output is patient counts which were aggregated into a table stratifying variables of interest to enable population health studies. All code is available open source. A policy stipulating that only aggregate data leave the institution greatly facilitated data sharing agreements. Discussion and Conclusion: Cumulus addresses barriers to data sharing based on (1) federally required support for standard APIs (2), increasing use of cloud computing, and (3) advances in AI. There is potential for scalability to support learning across myriad network configurations and use cases.

Real World Performance of the 21st Century Cures Act Population Level Application Programming Interface.

Objective: To evaluate the real-world performance in delivering patient data on populations, of the SMART/HL7 Bulk FHIR Access API, required in Electronic Health Records (EHRs) under the 21st Century Cures Act Rule. Materials and Methods: We used an open-source Bulk FHIR Testing Suite at five healthcare sites from April to September 2023, including four hospitals using EHRs certified for interoperability, and one Health Information Exchange (HIE) using a custom, standards-compliant API build. We measured export speeds, data sizes, and completeness across six types of FHIR resources. Results: Among the certified platforms, Oracle Cerner led in speed, managing 5-16 million resources at over 8,000 resources/min. Three Epic sites exported a FHIR data subset, achieving 1-12 million resources at 1,555-2,500 resources/min. Notably, the HIE's custom API outperformed, generating over 141 million resources at 12,000 resources/min. Discussion: The HIE's custom API showcased superior performance, endorsing the effectiveness of SMART/HL7 Bulk FHIR in enabling large-scale data exchange while underlining the need for optimization in existing EHR platforms. Agility and scalability are essential for diverse health, research, and public health use cases. Conclusion: To fully realize the interoperability goals of the 21st Century Cures Act, addressing the performance limitations of Bulk FHIR API is critical. It would be beneficial to include performance metrics in both certification and reporting processes.

Exploratory Descriptive Analysis of Smart Speaker Utilization in the Emergency Department During the COVID-19 Pandemic.

BACKGROUND: In March 2020, the U.S. Department of Health and Human Services Office for Civil Rights stated that they would use discretion when enforcing the Health Insurance Portability and Accountability Act regarding remote communication technologies that promoted telehealth delivery during the COVID-19 pandemic. This was in an effort to protect patients, clinicians, and staff. More recently, smart speakers-voice-activated, hands-free devices-are being proposed as productivity tools within hospitals. OBJECTIVE: We aimed to characterize the novel use of smart speakers in the emergency department (ED). METHODS: A retrospective observational study of Amazon Echo Show® utilization from May 2020 to October 2020 in a large academic Northeast health system ED. Voice commands and queries were classified as either patient care-related or non-patient care-related, and then further subcategorized to explore the content of given commands. RESULTS: Of 1232 commands analyzed, 200 (16.23%) were determined to be patient care-related. Of these commands, 155 (77.5%) were clinical in nature (i.e., "drop in on triage") and 23 (11.5%) were environment-enhancing commands (i.e., "play calming sounds"). Among non-patient care-related commands, 644 (62.4%) were for entertainment. Among all commands, 804 (65.3%) were during night-shift hours, which was statistically significant (p < 0.001). CONCLUSIONS: Smart speakers showed notable engagement, primarily being used for patient communication and entertainment. Future studies should examine content of patient care conversations using these devices, effects on frontline staff wellbeing, productivity, patient satisfaction, and even explore opportunities for "smart" hospital rooms.

Real-World Observational Evaluation of Common Interventions to Reduce Emergency Department Prescribing of Opioid Medications.

BACKGROUND: Prior work on opioid prescribing has examined dosing defaults, interruptive alerts, or "harder" stops such as electronic prescribing of controlled substances (EPCS), which has become increasingly required by state policy. Given that real-world opioid stewardship policies are concurrent and overlapping, the authors examined the effect of such policies on emergency department (ED) opioid prescriptions. METHODS: The researchers performed observational analysis of all ED visits discharged between December 17, 2016, and December 31, 2019, across seven EDs of a hospital system. Four interventions were examined in chronological order, with each successive intervention added on top of all previous interventions: 12-pill prescription default, EPCS, electronic health record (EHR) pop-up alert, and 8-pill prescription default. The primary outcome was opioid prescribing, which was described as number of opioid prescriptions per 100 discharged ED visits and modeled as a binary outcome for each visit. Secondary outcomes included prescription morphine milligram equivalents (MME) and non-opioid analgesia prescriptions. RESULTS: A total of 775,692 ED visits were included in the study. Compared to the preintervention period, cumulative reductions in opioid prescribing were seen with incremental interventions, including after adding a 12-pill default (odds ratio [OR] 0.88, 95% confidence interval [CI] 0.82-0.94), after adding EPCS (OR 0.7, 95% CI 0.63-0.77), after adding pop-up alerts (OR 0.67, 95% CI 0.63-0.71), and after adding an 8-pill default (OR 0.61, 95% CI 0.58-0.65). CONCLUSION: EHR-implemented solutions such as EPCS, pop-up alerts, and pill defaults had varying but significant effects on reducing ED opioid prescribing. Policy makers and quality improvement leaders might achieve sustainable improvements in opioid stewardship while balancing clinician alert fatigue through policy efforts promoting implementation of EPCS and default dispense quantities.

Progress Report on EMBED: A Pragmatic Trial of User-Centered Clinical Decision Support to Implement EMergency Department-Initiated BuprenorphinE for Opioid Use Disorder.

Buprenorphine (BUP) can safely and effectively reduce craving, overdose, and mortality rates in people with opioid use disorder (OUD). However, adoption of ED-initiation of BUP has been slow partly due to physician perception this practice is too complex and disruptive. We report progress of the ongoing EMBED (EMergency department-initiated BuprenorphinE for opioid use Disorder) project. This project is a five-year collaboration across five healthcare systems with the goal to develop, integrate, study, and disseminate user-centered Clinical Decision Support (CDS) to promote the adoption of Emergency Department (ED)-initiation of buprenorphine/naloxone (BUP) into routine emergency care. Soon to enter its third year, the project has already completed multiple milestones to achieve its goals including (1) user-centered design of the CDS prototype, (2) integration of the CDS into an automated electronic health record (EHR) workflow, (3) data coordination including derivation and validation of an EHR-based computable phenotype, (4) meeting all ethical and regulatory requirements to achieve a waiver of informed consent, (5) pilot testing of the intervention at a single site, and (6) launching a parallel group-randomized 18-month pragmatic trial in 20 EDs across 5 healthcare systems. Pilot testing of the intervention in a single ED was associated with increased rates of ED-initiated BUP and naloxone prescribing and a doubling of the number of unique physicians adopting the practice. The ongoing multi-center pragmatic trial will assess the intervention's effectiveness, scalability, and generalizability with a goal to shift the emergency care paradigm for OUD towards early identification and treatment. TRIAL REGISTRATION: Clinicaltrials.gov # NCT03658642.

User-centred clinical decision support to implement emergency department-initiated buprenorphine for opioid use disorder: protocol for the pragmatic group randomised EMBED trial.

INTRODUCTION: The goal of this trial is to determine whether implementation of a user-centred clinical decision support (CDS) system can increase adoption of initiation of buprenorphine (BUP) into the routine emergency care of individuals with opioid use disorder (OUD). METHODS: A pragmatic cluster randomised trial is planned to be carried out in 20 emergency departments (EDs) across five healthcare systems over 18 months. The intervention consists of a user-centred CDS integrated into ED clinician electronic workflow and available for guidance to: (1) determine whether patients presenting to the ED meet criteria for OUD, (2) assess withdrawal symptoms and (3) ascertain and motivate patient willingness to initiate treatment. The CDS guides the ED clinician to initiate BUP and facilitate follow-up. The primary outcome is the rate of BUP initiated in the ED. Secondary outcomes are: (1) rates of receiving a referral, (2) fidelity with the CDS and (3) rates of clinicians providing any ED-initiated BUP, referral for ongoing treatment and receiving Drug Addiction Act of 2000 training. Primary and secondary outcomes will be analysed using generalised linear mixed models, with fixed effects for intervention status (CDS vs usual care), prespecified site and patient characteristics, and random effects for study site. ETHICS AND DISSEMINATION: The protocol has been approved by the Western Institutional Review Board. No identifiable private information will be collected from patients. A waiver of informed consent was obtained for the collection of data for clinician prescribing and other activities. As a minimal risk implementation study of established best practices, an Independent Study Monitor will be utilised in place of a Data Safety Monitoring Board. Results will be reported in ClinicalTrials.gov and published in open-access, peer-reviewed journals, presented at national meetings and shared with the clinicians at participating sites via a broadcast email notification of publications. TRIAL REGISTRATION NUMBER: NCT03658642; Pre-results.

Computerized Clinical Decision Support System for Emergency Department-Initiated Buprenorphine for Opioid Use Disorder: User-Centered Design.

BACKGROUND: Emergency departments (EDs) frequently care for individuals with opioid use disorder (OUD). Buprenorphine (BUP) is an effective treatment option for patients with OUD that can safely be initiated in the ED. At present, BUP is rarely initiated as a part of routine ED care. Clinical decision support (CDS) could accelerate adoption of ED-initiated BUP into routine emergency care. OBJECTIVE: This study aimed to design and formatively evaluate a user-centered decision support tool for ED initiation of BUP for patients with OUD. METHODS: User-centered design with iterative prototype development was used. Initial observations and interviews identified workflows and information needs. The design team and key stakeholders reviewed prototype designs to ensure accuracy. A total of 5 prototypes were evaluated and iteratively refined based on input from 26 attending and resident physicians. RESULTS: Early feedback identified concerns with the initial CDS design: an alert with several screens. The timing of the alert led to quick dismissal without using the tool. User feedback on subsequent iterations informed the development of a flexible tool to support clinicians with varied levels of experience with the intervention by providing both one-click options for direct activation of care pathways and user-activated support for critical decision points. The final design resolved challenging navigation issues through targeted placement, color, and design of the decision support modules and care pathways. In final testing, users expressed that the tool could be easily learned without training and was reasonable for use during routine emergency care. CONCLUSIONS: A user-centered design process helped designers to better understand users' needs for a Web-based clinical decision tool to support ED initiation of BUP for OUD. The process identified varying needs across user experience and familiarity with the protocol, leading to a flexible design supporting both direct care pathways and user-initiated decision support.

An integrated web application for decision support and automation of EHR workflow: a case study of current challenges to standards-based messaging and scalability from the EMBED trial.

Computerized clinical decision support (CDS) faces challenges to interoperability and scalability. Centralized, web-based solutions offer a mechanism to share the cost of CDS development, maintenance, and implementation across practices. Data standards have emerged to facilitate interoperability and rapid integration of such third-party CDS. This case report describes the challenges to implementation and scalability of an integrated, web-based CDS intervention for EMergency department-initiated BuprenorphinE for opioid use Disorder which will soon be evaluated in a trial across 20 sites in five healthcare systems. Due to limitations of current standards, security concerns, and the need for resource-intensive local customization, barriers persist related to centralized CDS at this scale. These challenges demonstrate the need and importance for future standards to support two-way messaging (read and write) between electronic health records and web applications, thus allowing for more robust sharing across health systems and decreasing redundant, resource-intensive CDS development at individual sites.

Navigating the Digital Health Ecosystem to Bridge the Gap from Innovation to Transformation: A NODE. Health Perspective on Digital Evidence.

This article examines the challenges of broad adoption of digital solutions within the healthcare industry and why evidence is so critical for advancement of digital health technologies. It then illustrates how emerging nonprofits are positioned to help the ecosystem overcome these challenges and to catalyze the process of matching the right evidence-based solution to the right clinical challenge.

An Algorithm for Digital Medicine Testing: A NODE.Health Perspective Intended to Help Emerging Technology Companies and Healthcare Systems Navigate the Trial and Testing Period prior to Full-Scale Adoption.

Over the last several years, there has been rapid growth of digital technologies attempting to transform healthcare. Unique features of digital medicine technology lead to both challenges and opportunities for testing and validation. Yet little guidance exists to help a health system decide whether to undertake a pilot test of new technology, move right to full-scale adoption or start somewhere in between. To navigate this complexity, this paper proposes an algorithm to help choose the best path toward validation and adoption. Special attention is paid to considering whether the needs of patients with limited digital skills, equipment (e.g., smart-phones) and connectivity (e.g., data plans) have been considered in technology development and deployment. The algorithm reflects the collective experience of 20+ health systems and academic institutions that have established the Network of Digital Evidence for Health, NODE. Health, plus insights from existing clinical research taxonomies, syntheses or frameworks for assessing technology or for reporting clinical trials.

Do you see what I see? Insights from using google glass for disaster telemedicine triage.

INTRODUCTION: Disasters are high-stakes, low-frequency events. Telemedicine may offer a useful adjunct for paramedics performing disaster triage. The objective of this study was to determine the feasibility of telemedicine in disaster triage, and to determine whether telemedicine has an effect on the accuracy of triage or the time needed to perform triage. METHODS: This is a feasibility study in which an intervention team of two paramedics used the mobile device Google Glass (Google Inc; Mountain View, California USA) to communicate with an off-site physician disaster expert. The paramedic team triaged simulated disaster victims at the triennial drill of a commercial airport. The simulated victims had preassigned expected triage levels. The physician had an audio-video interface with the paramedic team and was able to observe the victims remotely. A control team of two paramedics performed disaster triage in the usual fashion. Both teams used the SMART Triage System (TSG Associates LLP; Halifax, England), which assigns patients into Red, Yellow, Green, and Black triage categories. The paramedics were video recorded, and their time required to triage was logged. It was determined whether the intervention team and the control team varied regarding accuracy of triage. Finally, the amount of time the intervention team needed to triage patients when telemedicine was used was compared to when that team did not use telemedicine. RESULTS: The two teams triaged the same 20 patients. There was no significant difference between the two groups in overall triage accuracy (85.7% for the intervention group vs 75.9% for the control group; P = .39). Two patients were triaged with telemedicine. For the intervention group, there was a significant difference in time to triage patients with telemedicine versus those without telemedicine (35.5 seconds; 95% CI, 72.5-143.5 vs 18.5 seconds; 95% CI, 13.4-23.6; P = .041). CONCLUSION: There was no increase in triage accuracy when paramedics evaluating disaster victims used telemedicine, and telemedicine required more time than conventional triage. There are a number of obstacles to available technology that, if overcome, might improve the utility of telemedicine in disaster response.

Influence of colonoscopy quality measures on patients' colonoscopist selection.

OBJECTIVES: The Affordable Care Act emphasizes the use of quality metrics and greater patient understanding of health-care options and access to physician performance data. The objectives of this study were to determine patients' familiarity with colonoscopy quality measures (CQMs) and their influence on patient selection of a colonoscopist. METHODS: A prospective survey of patients before screening or surveillance colonoscopy at university hospital, community hospital, and ambulatory procedure center endoscopy units was performed from 2011 to 2012. RESULTS: Among the 417 participants, 20% (85/417) researched their physician's rating. The rates of familiarity with CQM were 88 % (353/402) for adequate bowel preparation, 30% (118/398) for adenoma detection rate (ADR), 26% (102/397) for cecal intubation rate, and 21% (82/394) for greater-than-6-min withdrawal time. Ninety-six percent (366/386) believed that colonoscopists' reporting of ADR to other physicians was important or very important. In selecting a colonoscopist, primary care provider referral was ranked as the first or second-most important of four factors in 87% (339/391). Even among patients who responded "it is very important" to report CQM to other doctors and patients, none ranked CQM as the most important factor in selecting a colonoscopist. CONCLUSIONS: Patient awareness of CQM, other than adequate bowel preparation, was low. Quality measure reporting is important to patients, but primary care provider referral was the most important factor in colonoscopist selection. This suggests that primary care providers, as well as patients, are important to include in educational strategies regarding quality metrics.