Primary care provider adherence to an alert for intensification of diabetes blood pressure medications before and after the addition of a "chart closure" hard stop

Implementing a Clinical Decision Support Tool to Improve Physical Activity

BACKGROUND

Currently, only about half of U.S. adults achieve current physical activity guidelines. Routine physical activity is not regularly assessed, nor are patients routinely counseled by their healthcare provider on achieving recommended levels. The three-question physical activity vital sign (PAVS) was developed to assess physical activity duration and intensity and identify adults not meeting physical activity guidelines. Clinical decision support provided via a best practice advisory in an electronic health record (EHR) system can be triggered as a prompt, reminding healthcare providers to implement the best practice intervention when appropriate. Remote patient monitoring of physical activity can provide objective data in the EHR.

OBJECTIVES

This study aimed to evaluate the feasibility and clinical utility of embedding the PAVS and a triggered best practice advisor into the EHR in an ambulatory preventive cardiology practice setting to alert providers to patients reporting low physical activity and prompt healthcare providers to counsel these patients as needed.

METHODS

Three components based in the EHR were integrated for the purpose of this study: Patients completed the PAVS through their electronic patient portal prior to an office visit, a best practice advisory was created to prompt providers to counsel patients who reported low levels of physical activity, and remote patient monitoring via Fitbit synced to the EHR provided objective physical activity data. The intervention was pilot-tested in the Epic EHR for 1 year (July 1, 2021 to June 30, 2022). Qualitative feedback on the intervention from both providers and patients was obtained at the completion of the study.

RESULTS

Monthly assessments of the use of the PAVS and best practice advisory and remote patient monitoring were completed. Patients' completion of the PAVS varied from 35% to 48% per month. The best practice advisory was signed by providers between 2% and 65% and was acknowledged by 2%-22% per month. The majority (58%) of patients were able to sync a Fitbit device to their EHR for remote monitoring.

DISCUSSION

Although uptake of each component needs improvement, this pilot demonstrated the feasibility of incorporating a physical activity promotion intervention into the EHR. Qualitative feedback provided guidance for future implementation.

Characterization of pentosan polysulfate patients for development of an alert and screening system for ophthalmic monitoring

OBJECTIVE

Pentosan polysulfate (PPS; ELMIRON, Janssen Pharmaceuticals, Titusville, NJ) is a U.S. Food and Drug Administration-approved oral medication for interstitial cystitis. Numerous reports have been published detailing retinal toxicity with the use of PPS. Studies characterizing this condition are primarily retrospective, and consequently, alert and screening systems need to be developed to actively screen for this disease. The goal of this study was to characterize ophthalmic monitoring trends of a PPS-using patient sample to construct an alert and screening system for monitoring this condition.

METHODS

A single-institution retrospective chart review was conducted between January 2005 and November 2020 to characterize PPS use. An electronic medical record (EMR) alert was constructed to trigger based on new PPS prescriptions and renewals offering ophthalmology referral.

RESULTS

A total of 1407 PPS users over 15 years was available for characterization, with 1220 (86.7%) being female, the average duration of exposure being 71.2 ± 62.6 months, and the average medication cumulative exposure being 669.7 ± 569.2 g. A total of 151 patients (10.7%) had a recorded visit with an ophthalmologist, with 71 patients (5.0%) having optical coherence tomography imaging. The EMR alert fired for 88 patients over 1 year, with 34 patients (38.6%) either already being screened by an ophthalmologist or having been referred for screening.

CONCLUSIONS

An EMR support tool can improve referral rates of PPS maculopathy screening with an ophthalmologist and may serve as an efficient method for longitudinal screening of this condition with the added benefit of informing pentosan polysulfate prescribers about this condition. Effective screening and detection may help determine which patients are at high risk for this condition.

Quality improvement project to reduce medicare 1-day write-offs due to inappropriate admission orders

BACKGROUND

We identified that Stanford Health Care had a significant number of patients who after discharge are found by the utilization review committee not to meet Center for Mediare and Medicaid Services (CMS) 2-midnight benchmark for inpatient status. Some of the charges incurred during the care of these patients are written-off and known as Medicare 1-day write-offs. This study which aims to evaluate the use of a Best Practice Alert (BPA) feature on the electronic medical record, EPIC, to ensure appropriate designation of a patient's hospitalization status as either inpatient or outpatient in accordance with Center for Medicare and Medicaid services (CMS) 2 midnight length of stay benchmark thereby reducing the number of associated write-offs.

METHOD

We incorporated a best practice alert (BPA) into the Epic Electronic Medical Record (EMR) that would prompt the discharging provider and the case manager to review the patients' inpatient designation prior to discharge and change the patient's designation to observation when deemed appropriate. Patients who met the inclusion criteria (Patients must have Medicare fee-for-service insurance, inpatient length of stay (LOS) less than 2 midnights, inpatient designation as hospitalization status at time of discharge, was hospitalized to an acute level of care and belonged to one of 37 listed hospital services at the time of signing of the discharge order) were randomized to have the BPA either silent or active over a three-month period from July 18, 2019, to October 18, 2019.

RESULT

A total of 88 patients were included in this study: 40 in the control arm and 48 in the intervention arm. In the intervention arm, 8 (8/48, 16.7%) had an inpatient status designation despite potentially meeting Medicare guidelines for an observation stay, comparing to 23 patients (23/40, 57.5%) patients in the control group (p = 0.001). The estimated number of write-offs in the control arm was 17 (73.9%, out of 23 inpatient patients) while in the intervention arm was 1 (12.5%, out of 8 inpatient patient) after accounting for patients who may have met inpatient criteria for other reasons based on case manager note review.

CONCLUSION

This is the first time to our knowledge that a BPA has been used in this manner to reduce the number of Medicare 1-day write-offs.

A quality improvement initiative to improve folic acid supplementation counseling for adolescent females with epilepsy

OBJECTIVE

We designed a quality improvement (QI) project to improve rates of documented folic acid supplementation counseling for adolescent females with epilepsy, consistent with a quality measure from the American Academy of Neurology and American Epilepsy Society. Our SMART aim was to increase the percentage of visits at which folic acid counseling was addressed from our baseline rate of 23% to 50% by July 1, 2020.

METHODS

This initiative was conducted in female patients ≥12 years old with epilepsy who were prescribed daily antiseizure medication and were seen by the 13 providers in our Neurology QI Program. Using provider interviews, we undertook a root cause analysis of low counseling rates and identified the following main factors: insufficient time during clinic visit to counsel, lack of provider knowledge, and forgetting to counsel. Countermeasures were designed to address these main root causes and were implemented through iterative plan-do-study-act (PDSA) cycles. Interventions included provider education and features within the electronic health record, which were introduced sequentially, culminating in the creation of a best practice advisory (BPA). We performed biweekly chart reviews of visits for applicable patients to establish baseline performance rate and track progress over time. We used a statistical process control p-chart to analyze the outcome measure of documented counseling. As a balancing measure, clinicians were surveyed using the Technology Adoption Model survey to assess acceptance of the BPA.

RESULTS

From September 2019 to August 2022, the QI team improved rates of documented folic acid counseling from 23% to 73% through several PDSA cycles. This level of performance has been sustained over time. The most successful and sustainable intervention was the BPA. Provider acceptance of the BPA was overall positive.

SIGNIFICANCE

We successfully used QI methodology to improve and sustain our rates of documented folic acid supplementation counseling for adolescent females with epilepsy.

A population-based, electronic health record-guided approach to improve the quality of dementia care

BACKGROUND

The quality of care of the 6.5 million Americans living with dementia has been suboptimal, leading to worse outcomes and higher costs. Few health systems have formal systems in place to guide the care of these patients. To help improve the care of persons living with dementia, we developed and preliminarily evaluated the effectiveness of electronic health record (EHR)-generated recommendations for patients with dementia.

METHODS

This quality improvement study was conducted from October 2020 through June 2022 at a single academic healthcare system and included patients identified as having dementia on their problem list and their physicians. Ten (seven outpatient and three inpatient) algorithms based on clinical logic and evidence were embedded in an EHR system to generate specific recommendations based on combinations of utilization, diagnosis, and medications. The number of each type of recommendation generated, and orders for each type of recommendation were recorded, as well as physician's perceptions of this approach.

RESULTS

Three thousand six hundred and nine recommendations on 763 patients were triggered by the algorithms in the outpatient setting, and 185 referrals were placed. The most common recommendations were for ongoing care through the UCLA Alzheimer's and Dementia Care program, Palliative Care, the Extensivist Clinic, Urogynecology, and Clinical Pharmacy. The most commonly acted upon by providers were recommendations for referral to Pharmacists and the UCLA Alzheimer's and Dementia Care program. The most common reason for not responding to specific recommendations was that these were not perceived as relevant to the patient. Compared to general medicine physicians, geriatricians felt more comfortable managing dementia care without a referral to a service (23% (95% CI 15%-34%) versus 3% (95% CI 0%-17%), p = 0.012) and less commonly felt the recommendation was appropriate (1% (95% CI 0%-7%) versus 13% (95% CI 4%-30%), p = 0.02).

CONCLUSIONS

EHR-generated algorithms can help guide patients with dementia to appropriate clinical services.

Remote monitoring of cognition in cirrhosis and encephalopathy: future opportunity and challenge

Hepatic Encephalopathy (HE) is a critically important complication of chronic liver disease and portal hypertension, but especially in early covert stages remains underdiagnosed and a common cause of hospitalization and morbidity. Defined by often subtle neuropsychiatric changes, significant cognitive deficits have been extensively described. While traditional methods of assessment remain underutilized in practice and subject to significant confounding with other diseases, mobile technology has emerged as a potential future tool to provide simple and dynamic cognitive assessments. This review discusses the proliferation of cognitive assessment tools, describing possible applications in encephalopathy and the challenges such an implementation may face. There are significant potential advantages to assessing cognition in real time in order to aid early detection and intervention and provide a more realistic measurement of real-world function. Despite this, there are issues with reliability, privacy, applicability and more which must be addressed prior to wide proliferation and acceptance for clinical use. Regardless, the rapid uptake of mobile technology in healthcare is likely to have significant implications for the future management of encephalopathy and liver disease at large.

Addressing Therapeutic Inertia: Development and Implementation of an Electronic Health Record-Based Diabetes Intensification Tool

Objective

To assess whether an electronic health record (EHR)-based diabetes intensification tool can improve the rate of A1C goal attainment among patients with type 2 diabetes and an A1C ≥8%.

Methods

An EHR-based tool was developed and sequentially implemented in a large, integrated health system using a four-phase, stepped-wedge design (single pilot site [phase 1] and then three practice site clusters [phases 2-4]; 3 months/phase), with full implementation during phase 4. A1C outcomes, tool usage, and treatment intensification metrics were compared retrospectively at implementation (IMP) sites versus nonimplementation (non-IMP) sites with sites matched on patient population characteristics using overlap propensity score weighting.

Results

Overall, tool utilization was low among patient encounters at IMP sites (1,122 of 11,549 [9.7%]). During phases 1-3, the proportions of patients achieving the A1C goal (<8%) were not significantly improved between IMP and non-IMP sites at 6 months (range 42.9-46.5%) or 12 months (range 46.5-53.1%). In phase 3, fewer patients at IMP sites versus non-IMP sites achieved the goal at 12 months (46.7 vs. 52.3%, P = 0.02). In phases 1-3, mean changes in A1C from baseline to 6 and 12 months (range -0.88 to -1.08%) were not significantly different between IMP and non-IMP sites. Times to intensification were similar between IMP and non-IMP sites.

Conclusion

Utilization of a diabetes intensification tool was low and did not influence rates of A1C goal attainment or time to treatment intensification. The low level of tool adoption is itself an important finding highlighting the problem of therapeutic inertia in clinical practice. Testing additional strategies to better incorporate, increase acceptance of, and improve proficiency with EHR-based intensification tools is warranted.

Human-centered design of clinical decision support for management of hypertension with chronic kidney disease

BACKGROUND

Primary care providers face challenges in recognizing and controlling hypertension in patients with chronic kidney disease (CKD). Clinical decision support (CDS) has the potential to aid clinicians in identifying patients who could benefit from medication changes. This study designed an alert to control hypertension in CKD patients using an iterative human-centered design process.

METHODS

In this study, we present a human-centered design process employing multiple methods for gathering user requirements and feedback on design and usability. Initially, we conducted contextual inquiry sessions to gather user requirements for the CDS. This was followed by group design sessions and one-on-one formative think-aloud sessions to validate requirements, obtain feedback on the design and layout, uncover usability issues, and validate changes.

RESULTS

This study included 20 participants. The contextual inquiry produced 10 user requirements which influenced the initial alert design. The group design sessions revealed issues related to several themes, including recommendations and clinical content that did not match providers' expectations and extraneous information on the alerts that did not provide value. Findings from the individual think-aloud sessions revealed that participants disagreed with some recommended clinical actions, requested additional information, and had concerns about the placement in their workflow. Following each step, iterative changes were made to the alert content and design.

DISCUSSION

This study showed that participation from users throughout the design process can lead to a better understanding of user requirements and optimal design, even within the constraints of an EHR alerting system. While raising awareness of design needs, it also revealed concerns related to workflow, understandability, and relevance.

CONCLUSION

The human-centered design framework using multiple methods for CDS development informed the creation of an alert to assist in the treatment and recognition of hypertension in patients with CKD.

Modulators Influencing Medication Alert Acceptance: An Explorative Review

OBJECTIVES

Clinical decision support systems (CDSSs) use alerts to enhance medication safety and reduce medication error rates. A major challenge of medication alerts is their low acceptance rate, limiting their potential benefit. A structured overview about modulators influencing alert acceptance is lacking. Therefore, we aimed to review and compile qualitative and quantitative modulators of alert acceptance and organize them in a comprehensive model.

METHODS

In accordance with the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guideline, a literature search in PubMed was started in February 2018 and continued until October 2021. From all included articles, qualitative and quantitative parameters and their impact on alert acceptance were extracted. Related parameters were then grouped into factors, allocated to superordinate determinants, and subsequently further allocated into five categories that were already known to influence alert acceptance.

RESULTS

Out of 539 articles, 60 were included. A total of 391 single parameters were extracted (e.g., patients' comorbidity) and grouped into 75 factors (e.g., comorbidity), and 25 determinants (e.g., complexity) were consequently assigned to the predefined five categories, i.e., CDSS, care provider, patient, setting, and involved drug. More than half of all factors were qualitatively assessed (n = 21) or quantitatively inconclusive (n = 19). Furthermore, 33 quantitative factors clearly influenced alert acceptance (positive correlation: e.g., alert type, patients' comorbidity; negative correlation: e.g., number of alerts per care provider, moment of alert display in the workflow). Two factors (alert frequency, laboratory value) showed contradictory effects, meaning that acceptance was significantly influenced both positively and negatively by these factors, depending on the study. Interventional studies have been performed for only 12 factors while all other factors were evaluated descriptively.

CONCLUSION

This review compiles modulators of alert acceptance distinguished by being studied quantitatively or qualitatively and indicates their effect magnitude whenever possible. Additionally, it describes how further research should be designed to comprehensively quantify the effect of alert modulators.

The Acceptance of Interruptive Medication Alerts in an Electronic Decision Support System Differs between Different Alert Types

BACKGROUND

 Through targeted medication alerts, clinical decision support systems (CDSS) help users to identify medication errors such as disregarded drug-drug interactions (DDIs). Override rates of such alerts are high; however, they can be mitigated by alert tailoring or workflow-interrupting display of severe alerts that need active user acceptance or overriding. Yet, the extent to which the displayed alert interferes with the prescribers' workflow showed inconclusive impact on alert acceptance.

OBJECTIVES

 We aimed to assess whether and how often prescriptions were changed as a potential result of interruptive alerts on different (contraindicated) prescription constellations with particularly high risks for adverse drug events (ADEs).

METHODS

 We retrospectively collected data of all interruptive alerts issued between March 2016 and August 2020 in the local CDSS (AiDKlinik) at Heidelberg University Hospital. The alert battery consisted of 31 distinct alerts for contraindicated DDI with simvastatin, potentially inappropriate medication for patients > 65 years (PIM, N = 14 drugs and 36 drug combinations), and contraindicated drugs in hyperkalemia (N = 5) that could be accepted or overridden giving a reason in free-text form.

RESULTS

 In 935 prescribing sessions of 500 274 total sessions, at least one interruptive alert was fired. Of all interruptive alerts, about half of the sessions were evaluable whereof in total 57.5% (269 of 468 sessions) were accepted while 42.5% were overridden. The acceptance rate of interruptive alerts differed significantly depending on the alert type (p <0.0001), reaching 85.7% for DDI alerts (N = 185), 65.3% for contraindicated drugs in hyperkalemia (N = 98), and 25.1% for PIM alerts (N = 185).

CONCLUSION

 A total of 57.5% of the interruptive medication alerts with particularly high risks for ADE in our setting were accepted while the acceptance rate differed according to the alert type with contraindicated simvastatin DDI alerts being accepted most frequently.

Wearable Bioimpedance Monitoring: Viewpoint for Application in Chronic Conditions

Currently, nearly 6 in 10 US adults are suffering from at least one chronic condition. Wearable technology could help in controlling the health care costs by remote monitoring and early detection of disease worsening. However, in recent years, there have been disappointments in wearable technology with respect to reliability, lack of feedback, or lack of user comfort. One of the promising sensor techniques for wearable monitoring of chronic disease is bioimpedance, which is a noninvasive, versatile sensing method that can be applied in different ways to extract a wide range of health care parameters. Due to the changes in impedance caused by either breathing or blood flow, time-varying signals such as respiration and cardiac output can be obtained with bioimpedance. A second application area is related to body composition and fluid status (eg, pulmonary congestion monitoring in patients with heart failure). Finally, bioimpedance can be used for continuous and real-time imaging (eg, during mechanical ventilation). In this viewpoint, we evaluate the use of wearable bioimpedance monitoring for application in chronic conditions, focusing on the current status, recent improvements, and challenges that still need to be tackled.

The impact of electronic health record-integrated patient-generated health data on clinician burnout

Patient-generated health data (PGHD), such as patient-reported outcomes and mobile health data, have been increasingly used to improve health care delivery and outcomes. Integrating PGHD into electronic health records (EHRs) further expands the capacities to monitor patients' health status without requiring office visits or hospitalizations. By reviewing and discussing PGHD with patients remotely, clinicians could address the clinical issues efficiently outside of clinical settings. However, EHR-integrated PGHD may create a burden for clinicians, leading to burnout. This study aims to investigate how interactions with EHR-integrated PGHD may result in clinician burnout. We identify the potential contributing factors to clinician burnout using a modified FITT (Fit between Individuals, Task and Technology) framework. We found that technostress, time pressure, and workflow-related issues need to be addressed to accelerate the integration of PGHD into clinical care. The roles of artificial intelligence, algorithm-based clinical decision support, visualization format, human-computer interaction mechanism, workflow optimization, and financial reimbursement in reducing burnout are highlighted.

On the potential of wearable bioimpedance for longitudinal fluid monitoring in end-stage kidney disease

Bioimpedance spectroscopy (BIS) has proven to be a promising non-invasive technique for fluid monitoring in HD patients. While current BIS-based monitoring of pre- and post-dialysis fluid status utilizes benchtop devices, designed for intramural use, advancements in micro-electronics have enabled the development of wearable bioimpedance systems. Wearable systems meanwhile can offer a similar frequency range for current injection as commercially available benchtop devices. This opens opportunities for unobtrusive longitudinal fluid status monitoring, including transcellular fluid shifts, with the ultimate goal of improving fluid management, thereby lowering mortality and improving quality of life for HD patients. Ultra-miniaturized wearable devices can also offer simultaneous acquisition of multiple other parameters, including hemodynamic parameters. Combination of wearable BIS and additional longitudinal multiparametric data may aid in the prevention of both hemodynamic instability as well as fluid overload. The opportunity to also acquire data during interdialytic periods using wearable devices likely will give novel pathophysiological insights and the development of smart (predicting) algorithms could contribute to personalizing dialysis schemes and ultimately to autonomous (nocturnal) home dialysis. This review provides an overview of current research regarding wearable bioimpedance, with special attention to applications in ESKD patients. Furthermore, we present an outlook on the future use of wearable bioimpedance within dialysis practice.

Clinical Decision Support and Implications for the Clinician Burnout Crisis

OBJECTIVES

This survey aimed to review aspects of clinical decision support (CDS) that contribute to burnout and identify key themes for improving the acceptability of CDS to clinicians, with the goal of decreasing said burnout.

METHODS

We performed a survey of relevant articles from 2018-2019 addressing CDS and aspects of clinician burnout from PubMed and Web of Science™. Themes were manually extracted from publications that met inclusion criteria.

RESULTS

Eighty-nine articles met inclusion criteria, including 12 review articles. Review articles were either prescriptive, describing how CDS should work, or analytic, describing how current CDS tools are deployed. The non-review articles largely demonstrated poor relevance and acceptability of current tools, and few studies showed benefits in terms of efficiency or patient outcomes from implemented CDS. Encouragingly, multiple studies highlighted steps that succeeded in improving both acceptability and relevance of CDS.

CONCLUSIONS

CDS can contribute to clinician frustration and burnout. Using the techniques of improving relevance, soliciting feedback, customization, measurement of outcomes and metrics, and iteration, the effects of CDS on burnout can be ameliorated.

Medical Decision Support to Reduce Unwarranted Methylene Tetrahydrofolate Reductase (MTHFR) Genetic Testing

Most major national medical associations have advised against routine MTHFR testing since at least 2013. However, many providers continue to order this unwarranted genetic test. This study assessed the efficacy of an electronic best practice alert to aid ordering providers. We tracked the rate of MTHFR tests ordered per 1 million patients in the twelve months before and after the implementation of an alert that suggested an alternative test. Associated factors including the ordering department, diagnosis, patient sex, and patient age were also analyzed. Chi square analysis was used to compare the difference between pre- and post-alert test ordering rates. A total of 997 MTHFR analysis were ordered in Southern California Kaiser Permanente from January 2017 through December 2018. Overall, the average MTHFR monthly test ordering rates dropped significantly from 12.93 per million patients in 2017 to 7.08 per million patients in 2018 (p = 0.0056). However, testing rates in children were unchanged and, in some associated diagnoses, such as psychiatric illnesses and neurodevelopmental conditions, the testing rates increased. Recommending an alternate test in lieu of the unwarranted one significantly reduced the overall rate of MTHFR testing. The alert was most effective for specialties and diagnoses where MTHFR was historically medically indicated. This suggests such alerts are an effective intervention that health care systems can implement to serve as an educational update and to reduce unwarranted genetic testing.

Impact of a "Chart Closure" Hard Stop Alert on Prescribing for Elevated Blood Pressures Among Patients With Diabetes: Quasi-Experimental Study

BACKGROUND

University of California at Los Angeles Health implemented a Best Practice Advisory (BPA) alert for the initiation of an angiotensin-converting enzyme inhibitor (ACEI) or angiotensin-receptor blocker (ARB) for individuals with diabetes. The BPA alert was configured with a "chart closure" hard stop, which demanded a response before closing the chart.

OBJECTIVE

The aim of the study was to evaluate whether the implementation of the BPA was associated with changes in ACEI and ARB prescribing during primary care encounters for patients with diabetes.

METHODS

We defined ACEI and ARB prescribing opportunities as primary care encounters in which the patient had a diabetes diagnosis, elevated blood pressure in recent encounters, no active ACEI or ARB prescription, and no contraindications. We used a multivariate logistic regression model to compare the change in the probability of an ACEI or ARB prescription during opportunity encounters before and after BPA implementation in primary care sites that did (n=30) and did not (n=31) implement the BPA. In an additional subgroup analysis, we compared ACEI and ARB prescribing in BPA implementation sites that had also implemented a pharmacist-led medication management program.

RESULTS

We identified a total of 2438 opportunity encounters across 61 primary care sites. The predicted probability of an ACEI or ARB prescription increased significantly from 11.46% to 22.17% during opportunity encounters in BPA implementation sites after BPA implementation. However, in the subgroup analysis, we only observed a significant improvement in ACEI and ARB prescribing in BPA implementation sites that had also implemented the pharmacist-led program. Overall, the change in the predicted probability of an ACEI or ARB prescription from before to after BPA implementation was significantly greater in BPA implementation sites compared with nonimplementation sites (difference-in-differences of 11.82; P<.001).

CONCLUSIONS

A BPA with a "chart closure" hard stop is a promising tool for the treatment of patients with comorbid diabetes and hypertension with an ACEI or ARB, especially when implemented within the context of team-based care, wherein clinical pharmacists support the work of primary care providers.

Wearable Health Technology and Electronic Health Record Integration: Scoping Review and Future Directions

BACKGROUND

Due to the adoption of electronic health records (EHRs) and legislation on meaningful use in recent decades, health systems are increasingly interdependent on EHR capabilities, offerings, and innovations to better capture patient data. A novel capability offered by health systems encompasses the integration between EHRs and wearable health technology. Although wearables have the potential to transform patient care, issues such as concerns with patient privacy, system interoperability, and patient data overload pose a challenge to the adoption of wearables by providers.

OBJECTIVE

This study aimed to review the landscape of wearable health technology and data integration to provider EHRs, specifically Epic, because of its prevalence among health systems. The objectives of the study were to (1) identify the current innovations and new directions in the field across start-ups, health systems, and insurance companies and (2) understand the associated challenges to inform future wearable health technology projects at other health organizations.

METHODS

We used a scoping process to survey existing efforts through Epic's Web-based hub and discussion forum, UserWeb, and on the general Web, PubMed, and Google Scholar. We contacted Epic, because of their position as the largest commercial EHR system, for information on published client work in the integration of patient-collected data. Results from our searches had to meet criteria such as publication date and matching relevant search terms.

RESULTS

Numerous health institutions have started to integrate device data into patient portals. We identified the following 10 start-up organizations that have developed, or are in the process of developing, technology to enhance wearable health technology and enable EHR integration for health systems: Overlap, Royal Philips, Vivify Health, Validic, Doximity Dialer, Xealth, Redox, Conversa, Human API, and Glooko. We reported sample start-up partnerships with a total of 16 health systems in addressing challenges of the meaningful use of device data and streamlining provider workflows. We also found 4 insurance companies that encourage the growth and uptake of wearables through health tracking and incentive programs: Oscar Health, United Healthcare, Humana, and John Hancock.

CONCLUSIONS

The future design and development of digital technology in this space will rely on continued analysis of best practices, pain points, and potential solutions to mitigate existing challenges. Although this study does not provide a full comprehensive catalog of all wearable health technology initiatives, it is representative of trends and implications for the integration of patient data into the EHR. Our work serves as an initial foundation to provide resources on implementation and workflows around wearable health technology for organizations across the health care industry.