Design and implementation of a digital health home spirometry intervention for remote monitoring of lung transplant function.

BACKGROUND: We developed an automated, chat-based, digital health intervention using Bluetooth-enabled home spirometers to monitor for complications of lung transplantation in a real-world application. METHODS: A chat-based application prompted patients to perform home spirometry, enter their forced expiratory volume in 1 second (FEV1), answer symptom queries, and provided patient education. The program alerted patients and providers to substantial FEV1 decreases and concerning symptoms. Data was integrated into the electronic health record (EHR) system and dashboards were developed for program monitoring. RESULT: Between May 2020 and December 2021, 544 patients were invited to enroll, of whom 427 were invited remotely and 117 were enrolled in-person. 371 (68%) participated by submitting ≥1 FEV1 values. Overall engagement was high, with an average of 197 unique patients submitting FEV1 data per month. In-person enrollees submitted an average of 4.6 FEV1 values per month and responded to 55% of scheduled chats. Home and laboratory FEV1 values correlated closely (rho = 0.93). There was an average of 133 ± 59 FEV1 decline alerts and 59 ± 23 symptom alerts per month. 72% of patients accessed education modules, and the program had a high net promoter score (53) amongst users. CONCLUSIONS: We demonstrate that a novel, automated, chat-based, and EHR-integrated home spirometry intervention is well accepted, generates reliable assessments of graft function, and can deliver automated feedback and education resulting in moderately-high adherence rates. We found that in-person onboarding yields better engagement and adherence. Future work will aim to demonstrate the impact of remote care monitoring on early detection of lung transplant complications.

Utilization patterns and efficiency gains from use of a fully EHR-integrated COVID-19 self-triage and self-scheduling tool: a retrospective analysis.

OBJECTIVE: Symptom checkers can help address high demand for SARS-CoV2 (COVID-19) testing and care by providing patients with self-service access to triage recommendations. However, health systems may be hesitant to invest in these tools, as their associated efficiency gains have not been studied. We aimed to quantify the operational efficiency gains associated with use of an online COVID-19 symptom checker as an alternative to a telephone hotline. METHODS: In our health system, ambulatory patients can either use an online symptom checker or a telephone hotline to be triaged and connected to COVID-19 care. We performed a retrospective analysis of adults who used either method between October 20, 2021 and January 10, 2022, using call logs, electronic health record data, and local wages to calculate labor costs. RESULTS: Of the 15 549 total COVID-19 triage encounters, 1820 (11.7%) used only the telephone hotline and 13 729 (88.3%) used the symptom checker. Only 271 (2%) of the patients who used the symptom checker also called the hotline. Hotline encounters required more clinician time compared to those involving the symptom checker (17.8 vs 0.4 min/encounter), resulting in higher average labor costs ($24.21 vs $0.55 per encounter). The symptom checker resulted in over 4200 clinician labor hours saved. CONCLUSION: When given the option, most patients completed COVID-19 triage and visit scheduling online, resulting in substantial efficiency gains. These benefits may encourage health system investment in such tools.

Patient Experience and Feedback After Using an Electronic Health Record-Integrated COVID-19 Symptom Checker: Survey Study.

BACKGROUND: Symptom checkers have been widely used during the COVID-19 pandemic to alleviate strain on health systems and offer patients a 24-7 self-service triage option. Although studies suggest that users may positively perceive web-based symptom checkers, no studies have quantified user feedback after use of an electronic health record-integrated COVID-19 symptom checker with self-scheduling functionality. OBJECTIVE: In this paper, we aimed to understand user experience, user satisfaction, and user-reported alternatives to the use of a COVID-19 symptom checker with self-triage and self-scheduling functionality. METHODS: We launched a patient-portal-based self-triage and self-scheduling tool in March 2020 for patients with COVID-19 symptoms, exposures, or questions. We made an optional, anonymous Qualtrics survey available to patients immediately after they completed the symptom checker. RESULTS: Between December 16, 2021, and March 28, 2022, there were 395 unique responses to the survey. Overall, the respondents reported high satisfaction across all demographics, with a median rating of 8 out of 10 and 288/395 (47.6%) of the respondents giving a rating of 9 or 10 out of 10. User satisfaction scores were not associated with any demographic factors. The most common user-reported alternatives had the web-based tool not been available were calling the COVID-19 telephone hotline and sending a patient-portal message to their physician for advice. The ability to schedule a test online was the most important symptom checker feature for the respondents. The most common categories of user feedback were regarding other COVID-19 services (eg, telephone hotline), policies, or procedures, and requesting additional features or functionality. CONCLUSIONS: This analysis suggests that COVID-19 symptom checkers with self-triage and self-scheduling functionality may have high overall user satisfaction, regardless of user demographics. By allowing users to self-triage and self-schedule tests and visits, tools such as this may prevent unnecessary calls and messages to clinicians. Individual feedback suggested that the user experience for this type of tool is highly dependent on the organization's operational workflows for COVID-19 testing and care. This study provides insight for the implementation and improvement of COVID-19 symptom checkers to ensure high user satisfaction.

Smart Insulin Pens: Advancing Digital Transformation and a Connected Diabetes Care Ecosystem.

With the first commercially available smart insulin pens, the predominant insulin delivery device for millions of people living with diabetes is now coming into the digital age. Smart insulin pens (SIPs) have the potential to reshape a connected diabetes care ecosystem for patients, providers, and health systems. Existing SIPs are enhanced with real-time wireless connectivity, digital dose capture, and integration with personalized dosing decision support. Automatic dose capture can promote effective retrospective review of insulin dose data, particularly when paired with glucose data. Patients, providers, and diabetes care teams will be able to make increasingly data-driven decisions and recommendations, in real time, during scheduled visits, and in a more continuous, asynchronous care model. As SIPs continue to progress along the path of digital transformation, we can expect additional benefits: iteratively improving software, machine learning, and advanced decision support. Both these technological advances, and future care delivery models with asynchronous interactions, will depend on easy, open, and continuous data exchange between the growing number of diabetes devices. SIPs have a key role in modernizing diabetes care for a large population of people living with diabetes.

Analysis of "Accuracy of a 14-Day Factory Calibrated Continuous Glucose Monitoring System With Advanced Algorithm in Pediatric and Adult Population With Diabetes".

In this study by Alva et al, accuracy of a second-generation factory calibrated continuous glucose monitoring system is evaluated. Compared to the first-generation FreeStyle Libre 14-day system (FSL), accuracy was improved throughout the 14-day wear period, including improved accuracy in hypoglycemia for adults and youth. The addition of optional real-time alerts for hypoglycemia and hyperglycemia as well as an integrated continuous glucose monitor (iCGM) designation by the FDA may further enable users to benefit from using CGM in real time, including in future automated insulin delivery systems. As CGM accuracy, affordability, and accessibility improve, we anticipate increased uptake of CGM by people on intensive insulin therapy, and also potential benefits and expansion into a broader patient population. There are growing opportunities to leverage cloud-connected CGM devices in the increasingly virtual, continuous telehealth-driven diabetes care model, which will require more focus on development and use of data interoperability standards.

Telehealth in type 1 diabetes.

PURPOSE OF REVIEW: The role of telehealth in the care of people with type 1 diabetes (T1D) has expanded dramatically during the coronavirus pandemic, and is expected to remain a major care delivery modality going forward. This review explores the landscape of recent evidence for telehealth in T1D care. RECENT FINDINGS: Telemedicine for routine T1D care has shown equivalence to standard in-person care, with respect to glycemic control, while also increasing access, convenience, and satisfaction. Telehealth use promotes increased engagement of adolescents with T1D. Telehealth platforms have successfully been used in the care of microvascular complications and to support mental health related to diabetes. Machine learning and advanced decision support will increasingly be used to augment T1D care, as recent evidence suggests increasing capabilities to improve glycemic control. A spectrum of digital connected care services are emerging to support people with diabetes with daily management of diabetes. Finally, policy and systems are required that promote data interoperability, telemedicine provision, and reimbursement to support the ongoing growth of telehealth in T1D. SUMMARY: A developing field of evidence supports use of telehealth in T1D. As this care modality scales, it has the potential to increase access to high-quality diabetes care for many people with T1D.

Design and development of referrals automation, a SMART on FHIR solution to improve patient access to specialty care.

BACKGROUND: Referring patients to specialty care is an inefficient and error-prone process. Gaps in the referral process lead to delays in patients' access to care, negative patient experience, worse health outcomes, and increased operational costs. While implementation of standards-based electronic referral options can alleviate some of these inefficiencies, many referrals to tertiary and quaternary care centers continue to be sent via fax. OBJECTIVE: We describe the design process and architecture for a software application that has been developed and deployed to optimize the referrals intake process by automating the processing and digitization of incoming specialty referral faxes, extracting key data elements and integrating them into the electronic health record (EHR), and organizing referrals. METHODS: A human-centered design approach was used to identify and describe the inefficiencies in the external referral process at our large, urban tertiary care center. Referrals Automation, an application to convert referral faxes to digital referrals in the EHR, was conceptualized based on key stakeholder interviews and time and motion studies. This application was designed using Substitutable Medical Applications and Reusable Technologies (SMART) and Fast Healthcare Interoperability Resource (FHIR) platforms to allow for adaptability into other healthcare organizations. RESULTS: Referrals Automation software was developed as a healthcare information technology solution to streamline the fax to referral process. The application was implemented into several specialty clinics. Metrics were built-in to the applications to evaluate and guide the further iteration of these features. CONCLUSIONS: Referrals Automation will enhance the referrals process by further streamlining and organizing the patient referral process.

Implementation of a digital chatbot to screen health system employees during the COVID-19 pandemic.

The screening of healthcare workers for COVID-19 (coronavirus disease 2019) symptoms and exposures prior to every clinical shift is important for preventing nosocomial spread of infection but creates a major logistical challenge. To make the screening process simple and efficient, University of California, San Francisco Health designed and implemented a digital chatbot-based workflow. Within 1 week of forming a team, we conducted a product development sprint and deployed the digital screening process. In the first 2 months of use, over 270 000 digital screens have been conducted. This process has reduced wait times for employees entering our hospitals during shift changes, allowed for physical distancing at hospital entrances, prevented higher-risk individuals from coming to work, and provided our healthcare leaders with robust, real-time data for make staffing decisions.

Rapid design and implementation of an integrated patient self-triage and self-scheduling tool for COVID-19.

OBJECTIVE: To rapidly deploy a digital patient-facing self-triage and self-scheduling tool in a large academic health system to address the COVID-19 pandemic. MATERIALS AND METHODS: We created a patient portal-based COVID-19 self-triage and self-scheduling tool and made it available to all primary care patients at the University of California, San Francisco Health, a large academic health system. Asymptomatic patients were asked about exposure history and were then provided relevant information. Symptomatic patients were triaged into 1 of 4 categories-emergent, urgent, nonurgent, or self-care-and then connected with the appropriate level of care via direct scheduling or telephone hotline. RESULTS: This self-triage and self-scheduling tool was designed and implemented in under 2 weeks. During the first 16 days of use, it was completed 1129 times by 950 unique patients. Of completed sessions, 315 (28%) were by asymptomatic patients, and 814 (72%) were by symptomatic patients. Symptomatic patient triage dispositions were as follows: 193 emergent (24%), 193 urgent (24%), 99 nonurgent (12%), 329 self-care (40%). Sensitivity for detecting emergency-level care was 87.5% (95% CI 61.7-98.5%). DISCUSSION: This self-triage and self-scheduling tool has been widely used by patients and is being rapidly expanded to other populations and health systems. The tool has recommended emergency-level care with high sensitivity, and decreased triage time for patients with less severe illness. The data suggests it also prevents unnecessary triage messages, phone calls, and in-person visits. CONCLUSION: Patient self-triage tools integrated into electronic health record systems have the potential to greatly improve triage efficiency and prevent unnecessary visits during the COVID-19 pandemic.

A Pilot Study of Use of a Software Platform for the Collection, Integration, and Visualization of Diabetes Device Data by Health Care Providers in a Multidisciplinary Pediatric Setting.

BACKGROUND: Diabetes devices provide data for health care providers (HCPs) and people with type 1 diabetes to make management decisions. Extracting and viewing the data require separate, proprietary software applications for each device. In this pilot study, we examined the feasibility of using a single software platform (Tidepool) that integrates data from multiple devices. MATERIALS AND METHODS: Participating HCPs (n = 15) used the software with compatible devices in all patient visits for 6 months. Samples of registration desk activity and office visits were observed before and after introducing the software, and HCPs provided feedback by survey and focus groups. RESULTS: The time required to upload data and the length of the office visit did not change. However, the number of times the HCP referred to the device data with patients increased from a mean of 2.8 (±1.2) to 6.1 (±3.1) times per visit (P = 0.0002). A significantly larger proportion of children looked at the device data with the new application (baseline: 61% vs. study end: 94%, P = 0.015). HCPs liked the web-based user interface, integration of the data from multiple devices, the ability to remotely access data, and use of the application to initiate patient education. Challenges included the need for automated data upload and integration with electronic medical records. CONCLUSIONS: The software did not add to the time needed to upload data or the length of clinic visits and promoted discussions with patients about data. Future studies of HCP use of the application will evaluate clinical outcomes and effects on patient engagement and self-management.

Pilot Study of a Novel Application for Data Visualization in Type 1 Diabetes.

BACKGROUND: A novel software application, Blip, was created to combine and display diabetes data from multiple devices in a uniform, user-friendly manner. The objective of this study was to test the usability of this application by adults and caregivers of children with type 1 diabetes (T1D). METHODS: Patients (n = 35) and caregivers of children with T1D (n = 30) using an insulin pump for >1 year ± CGM were given access to the software for 3 months. Diabetes management practices and the use of diabetes data were assessed at baseline and at study end, and feedback was gathered in a concluding questionnaire. RESULTS: At baseline, 97% of participants agreed it was important for patients to know how to interpret glucose data. Most felt that clinicians and patients should share the tasks of reviewing data, finding patterns, and making changes to their insulin plans. However, despite valuing shared responsibility, at baseline, 43% of participants never downloaded pump data, and only 9% did so at least once per month. At study end, 72% downloaded data at least once during the 3-month study, and 38% downloaded at least once per month. Regarding the software application, participants liked the central repository of data and the user interface. Suggestions included providing tools for understanding and interpreting glucose patterns, an easier uploading process, and access with mobile devices. CONCLUSIONS: Collaboration between developers and researchers prompted iterative, rapid development of data visualization software and improvements in the uploading process and user interface, which facilitates clinical integration and future clinical studies.

A Minority of Patients with Type 1 Diabetes Routinely Downloads and Retrospectively Reviews Device Data.

BACKGROUND: In type 1 diabetes (T1D), periodic review of blood glucose and insulin dosing should be performed, but it is not known how often patients review these data on their own. We describe the proportion of patients with T1D who routinely downloaded and reviewed their data at home. MATERIALS AND METHODS: A cross-sectional survey of 155 adults and 185 caregivers of children with T1D at a single academic institution was performed. "Routine Downloaders" (downloaded four or more times in the past year) were also considered "Routine Reviewers" if they reviewed their data most of the time they downloaded from devices. Logistic regression was used to identify factors associated with being a Routine Reviewer. RESULTS: Only 31% of adults and 56% of caregivers reported ever downloading data from one or more devices, whereas 20% and 40%, respectively, were considered Routine Downloaders. Only 12% of adults and 27% of caregivers were Routine Reviewers. Mean hemoglobin A1c was lower in Routine Reviewers compared with non-Routine Reviewers (7.2±1.0% vs. 8.1±1.6% [P=0.03] in adults and 7.8±1.4% vs. 8.6±1.7% [P=0.001] in children). In adjusted analysis of adults, the odds ratio of being a Routine Reviewer of one or more devices for every 10-year increase in age was 1.5 (95% confidence interval, 1.1, 2.1 [P=0.02]). For every 10 years since diabetes diagnosis, the odds ratio of being a Routine Reviewer was 1.7 (95% confidence interval, 1.2, 2.4 [P=0.01]). For caregivers, there were no statistically significant factors associated with being a Routine Reviewer. CONCLUSIONS: A minority of T1D patients routinely downloads and reviews data from their devices on their own. Further research is needed to understand obstacles, provide better education and tools for self-review, and determine if patient self-review is associated with improved glycemic control.