ABSTRACT
In today's world, digital technologies are advancing at a rapid pace. Almost every industry has benefited from this ongoing change. In the health sector, the digitization of medical records was proposed decades ago. Whereas some developed countries have successfully adopted and implemented Electronic Health Record (EHR) systems. Developing countries like India still heavily rely on paper-based medical records. Although there are a number of systems for electronic medical record management, they have issues related to interoperability, timely access, and storage. Due to poor infrastructure and design, the current systems are not robust for communicating and tracking medical records. The need for a better EHR system was highly emphasized during the COVID-19 pandemic. The two major shortcomings of the existing system are a lack of interoperability, which causes delays in sharing the information, and a lack of standardization, due to which the data quality of the data that is shared suffers. To mitigate these issues, we need a nationwide EHR system. Another issue is the lack of a ubiquitous UPI (Unique Patient Identifier). In a country like India, the second most populated country in the world, Aadhar is the best option for UPI, which can be used for creating a national EHR system. In this paper, we have presented a framework for a standardized, interoperable, and unified EHR system based on blockchain technology with Aadhar as the UPI. Using blockchain as the base of this model provides numerous advantages over a cloud-based system, like decentralization, better security, immutability, and traceability. © 2023 IEEE.
ABSTRACT
Objective: To test the hypothesis that the Monoclonal Antibody Screening Score performs consistently better in identifying the need for monoclonal antibody infusion throughout each "wave" of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) variant predominance during the coronavirus disease 2019 (COVID-19) pandemic and that the infusion of contemporary monoclonal antibody treatments is associated with a lower risk of hospitalization. Patients and Methods: In this retrospective cohort study, we evaluated the efficacy of monoclonal antibody treatment compared with that of no monoclonal antibody treatment in symptomatic adults who tested positive for SARS-CoV-2 regardless of their risk factors for disease progression or vaccination status during different periods of SARS-CoV-2 variant predominance. The primary outcome was hospitalization within 28 days after COVID-19 diagnosis. The study was conducted on patients with a diagnosis of COVID-19 from November 19, 2020, through May 12, 2022. Results: Of the included 118,936 eligible patients, hospitalization within 28 days of COVID-19 diagnosis occurred in 2.52% (456/18,090) of patients who received monoclonal antibody treatment and 6.98% (7,037/100,846) of patients who did not. Treatment with monoclonal antibody therapies was associated with a lower risk of hospitalization when using stratified data analytics, propensity scoring, and regression and machine learning models with and without adjustments for putative confounding variables, such as advanced age and coexisting medical conditions (eg, relative risk, 0.15; 95% CI, 0.14-0.17). Conclusion: Among patients with mild to moderate COVID-19, including those who have been vaccinated, monoclonal antibody treatment was associated with a lower risk of hospital admission during each wave of the COVID-19 pandemic.
ABSTRACT
In safety-net healthcare systems, colonoscopy completion within 1-year of an abnormal fecal immunochemical test (FIT) result rarely exceeds 50%. Understanding how electronic health records (EHR) documented reasons for missed colonoscopy match or differ from patient-reported reasons, is critical to optimize effective interventions to address this challenge. We conducted a convergent mixed-methods study which included a retrospective analysis of EHR data and semi-structured interviews of adults 50-75 years old, with abnormal FIT results between 2014 and 2020 in a large safety-net healthcare system. Of the 299 patients identified, 59.2% (n = 177) did not complete a colonoscopy within one year of their abnormal result. EHR abstraction revealed a documented reason for lack of follow-up colonoscopy in 49.2% (n = 87/177); patient-level (e.g., declined colonoscopy; 51.5%) and multi-factorial reasons (e.g., lost to follow-up; 37.9%) were most common. In 18 patient interviews, patient (e.g., fear of colonoscopy), provider (e.g., lack of result awareness), and system-level reasons (e.g., scheduling challenges) were most common. Only three reasons for lack of colonoscopy overlapped between EHR data and patient interviews (competing health issues, lack of transportation, and abnormal FIT result attributed to another cause). In a cohort of safety-net patients with abnormal FIT results, the most common reasons for lack of follow-up were patient-related. Our analysis revealed a discordance between EHR documented and patient-reported reasons for lack of colonoscopy after an abnormal FIT result. Mixed-methods analyses, as in the present study, may give us the greatest insight into modifiable determinants to develop effective interventions beyond quantitative and qualitative data analysis alone.
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Objective: To examine the clinical characteristics, risk of hospitalization, and mortality of patients diagnosed with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) reinfection. Patients and Methods: We retrospectively reviewed all patients with SARS-CoV-2 reinfection at all Mayo Clinic sites between May 23, 2020, and June 30, 2021 (the period before the emergence of the Delta variant in the United States). The reinfection was defined as a positive SARS-CoV-2 test more than or equal to 90 days after initial infection or 45-89 days after with symptomatic second episode. Vaccination status was classified as fully vaccinated, first dose, and unvaccinated. Comparative analysis of baseline characteristics and comorbidities was performed by hospitalization and vaccination status. The survival analysis of the hospitalized patients was performed using Cox proportional hazard regression. Results: Among the 554 patients reinfected with SARS-CoV-2, 59 (10.6%) were pediatric, and 495 (89.4%) were adults. The median age was 13.9 years (interquartile range, 8.5-16.5 years) for the pediatric and 50.2 years (interquartile range, 28.4-65.6 years) for the adult population. Among the adult patients, the majority were unvaccinated (83.4%, n=413), and the duration to reinfection from initial infection was the longest in the fully vaccinated group (P<.001). Forty-two (75%) out of 56 patients were seropositive within 7 days of reinfection. In hospitalized adult patients, Charlson Comorbidity Index was an independent risk factor for mortality (adjusted hazard ratio, 0.35; 95% CI, 0.19-0.51). Conclusion: In this study, most adult patients with SARS-CoV-2 reinfection were unvaccinated. Furthermore, the duration to reinfection was longest in fully vaccinated individuals. Seropositivity was common among adult patients.
ABSTRACT
Traditional medical systems are vulnerable to attacks, leaks, and loss of data. The centralized structure of medical systems makes them more susceptible to attacks. Blockchain can be used as a solution to this issue. In particular, using blockchain to track patient medical history and vaccination records can guarantee privacy and security, which are critical requirements for healthcare systems. In this paper, we propose a blockchain-based application to maintain and share medical data and vaccination records using Hyperledger Fabric and Ethereum platforms to ensure data integrity and immutability. Our vaccination tracking system based on the Ethereum platform allows easy verification for people who want to travel abroad. For this system, we employ Ganache to test these vaccination records in a safe and deterministic environment. We have evaluated the performance of our implementation using Hyperledger Caliper and Explorer. The results show that our blockchain-based systems can increase the efficiency and transparency of tracking medical and vaccination records. We believe our proposal is especially valuable in the context of the ongoing COVID-19 pandemic because it providesa secure way to update, share and verify vaccination records. © 2021 IEEE.
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OBJECTIVE: To describe medical factors that are associated with caregiver intention to vaccinate their children against COVID-19. METHODS: We conducted a cross-sectional study of families receiving primary care in a mid-Atlantic pediatric healthcare system, linking caregiver-reported data from a survey completed March 19 to April 16, 2021 to comprehensive data from the child's EHR. RESULTS: 513 families were included (28% Black, 16% Hispanic, 44% public insurance, 21% rural, child age range 0-21 years). 44% of caregivers intended to vaccinate their children against COVID-19, while 41% were not sure and 15% would not. After adjusting for socio-demographics, the only medical factors that were associated with caregiver COVID-19 vaccine hesitancy were caregiver COVID-19 vaccination status at the time of the survey (aOR 3.0 if the caregiver did not receive the vaccine compared to those who did, 95% CI 1.7-5.3) and child seasonal influenza immunization history (aOR 3.3 if the child had not received the influenza vaccine in the 2020-2021 season compared to those who did, 95% CI 2.0-5.4). Other medical factors, including family medical experiences with COVID-19, other child immunization history, child health conditions like obesity and asthma, and family engagement with the healthcare system were not associated with caregiver intention to vaccinate their children against COVID-19. CONCLUSIONS: This study highlights important factors, such as general attitudes towards vaccines and understanding of COVID-19 morbidity risk factors, that healthcare providers should address when having conversations with families about the COVID-19 vaccine.
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BACKGROUND: There is an incomplete understanding of the risk of COVID-19 infection in atopic dermatitis (AD) patients. OBJECTIVE: To evaluate the risk of COVID-19 infection in AD patients in a large, diverse cohort. METHODS: A case-control study of the All of Us cohort to analyze the association between AD and COVID-19. Comorbidities and risk factors were compared between cases and controls using multivariable analyses. RESULTS: In a cohort of 11,752 AD cases with 47,008 matched controls, AD patients were more likely to have a COVID-19 diagnosis (4.2% vs 2.8%, P < .001). AD remained significantly associated with COVID-19 in multivariable analysis (odds ratio, 1.29; P < .001) after adjusting for demographic factors and comorbidities. LIMITATIONS: Ascertainment of AD and COVID-19 cases using electronic health records and lack of clinical data on AD severity or therapy and COVID-19 outcomes. CONCLUSION: AD is associated with increased odds of COVID-19 infection even after controlling for common comorbidities.
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BACKGROUND: The prescription pickup and renewal process in ambulatory care settings requires numerous steps, such as making an appointment with a physician to renew prescriptions and direct pharmacy visits to pick up medications. This process can be difficult or cumbersome for some patients; however, digital health-associated patient portals can reduce the burden on both patients and healthcare professionals. METHODS: A retrospective study was conducted in an ambulatory care setting of Johns Hopkins Aramco Healthcare. We analyzed the utilization pattern of MyChart for medication renewal and refill pickup services for ambulatory care patients of all specialties from October 1, 2018, to September 30, 2020. The data were extracted electronically from the Epic-Hyperspace EHR system, and the effects of factors such as year of access and COVID-19 on MyChart utilization were analyzed. RESULTS: A total of 125,538 patients were registered using MyChart. In the first and second year of this study, MyChart was utilized by 44,063 (8.7%) and 59,622 (13.6%) patients, respectively, for medication pickup. Additionally, in these two years, 92,997 (21.6%) and 156,020 (38.9%) medication refills were requested through MyChart (with no direct pharmacy visit) and collected from different pickup locations, respectively. In two years, there were 363,159 medications sent to physicians for renewal through Epic-MyChart, of which 347,244 (95.6%) were approved and 15,915 (4.4%) were denied. A significant increasing (p less than 0.05) trend in utilization, medication requests, and renewal requests using the MyChart were observed over a period of 24 months and during quarantine due to COVID-19. Although there was a decrease in physicians denying renewal request, these were not significantly affected by time or COVID-19. CONCLUSION: The high and consistent utilization of the patient portal MyChart indicates its broad acceptance, significantly minimizing the barriers to medication pickup and renewal processes in ambulatory care settings. The year of access and COVID-19 were significantly associated with an increasing trend in MyChart utilization. With increased utilization and higher acceptability, the internet-based patient portal MyChart continues to hold great potential for providing quality healthcare services by increasing access and making patients decision-makers in their healthcare.
ABSTRACT
Fidelity monitoring is the degree to which a clinical trial intervention is implemented as intended by a research protocol. Consistent implementation of research protocols supported with extant fidelity monitoring plans contribute rigor and validity of study results. Fidelity monitoring plans should be comprehensive yet practical to accommodate the realities of conducting research, particularly a pragmatic clinical trial, in dynamic settings with heterogeneous patient populations. The purposes of this paper are to describe the (1) iterative development and implementation of protocols for intervention fidelity monitoring, (2) pilot testing of the fidelity monitoring plan, (3) the identification of interventionist training deficiencies, and (4) opportunities to enhance protocol rigor for a cancer symptom management intervention delivered through the electronic health record patient portal and telephone as part of a complex, multi-component pragmatic clinical trial to uncover training deficits and bolster protocol integrity. The intervention focuses on prominent symptoms reported among medical oncology patients including sleep disturbance, pain, anxiety, depression, low energy (fatigue) and physical function. In this pragmatic trial, the role of interventionist is a registered nurse symptom care manager (RN SCM). A three-part fidelity monitoring plan with checklists audit: Part-1 RN SCM role training activities in research components, clinical training components, and protocol simulation training; Part-2 RN SCM adherence to the intervention core components delivered over the telephone; and Part-3 maintenance of adherence to core intervention components. The goal is ≥ 80% adherence to components of each of the three checklists. An initial pilot test of the fidelity monitoring plan was conducted to evaluate the checklists and the RN SCM adherence to core protocol components. RN SCM skills and training deficits were identified during the pilot phase, as were opportunities to improve protocol integrity. Overall, approximately 50% of the audited RN SCM telephone calls had ≥80% fidelity to the core components. There remains on-going need for RN SCM training and skill building in action planning. The content presented in this paper is intended to begin to fill the gap of fidelity monitoring plans for complex interventions tested in pragmatic clinical trials and delivered remotely in an effort to strengthen protocol integrity.
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OBJECTIVE: There has been a substantial decline in patients presenting for emergent and routine cardiovascular care in the United States after the onset of the coronavirus disease 2019 (COVID-19) pandemic. We sought to assess the risk of adverse clinical outcomes among patients undergoing coronary artery bypass graft (CABG) surgery during the 2020 COVID-19 pandemic period and compare the risks with those undergoing CABG before the pandemic in the year 2019. METHODS: A retrospective cross-sectional analysis of the TriNetX Research Network database was performed. Patients undergoing CABG between January 20, 2019, and September 15, 2019, contributed to the 2019 cohort, and those undergoing CABG between January 20, 2020, and September 15, 2020, contributed to the 2020 cohort. Propensity-score matching was performed, and the odds of mortality, acute kidney injury, stroke, acute respiratory distress syndrome, and mechanical ventilation occurring by 30 days were evaluated. RESULTS: The number of patients undergoing CABG in 2020 declined by 35.5% from 5534 patients in 2019 to 3569 patients in 2020. After propensity-score matching, 3569 patient pairs were identified in the 2019 and the 2020 cohorts. Compared with those undergoing CABG in 2019, the odds of mortality by 30 days were 0.96 (95% confidence interval [CI], 0.69-1.33; P = .80) in those undergoing CABG in 2020. The odds for stroke (odds ratio [OR], 1.201; 95% CI, 0.96-1.39), acute kidney injury (OR, 0.76; 95% CI, 0.59-1.08), acute respiratory distress syndrome (OR, 1.01; 95% CI, 0.60-2.42), and mechanical ventilation (OR, 1.11; 95% CI, 0.94-1.30) were similar between the 2 cohorts. CONCLUSIONS: The number of patients undergoing CABG in 2020 has substantially declined compared with 2019. Similar odds of adverse clinical outcomes were seen among patients undergoing CABG in the setting of COVID-19 compared with those in 2019.
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OBJECTIVE: To study the impact of a 60-day pilot of an innovative virtual-care model using general internal medicine physicians and nurses to respond rapidly to more than 1200 coronavirus disease-2019 (COVID-19)-positive nasopharyngeal polymerase chain reaction tests. PATIENTS AND METHODS: The current study was approved by the Mayo Clinic COVID-19 Research Committee and the Mayo Clinic Institutional Review Board. The data for all SARS-CoV-2-positive patients treated by our team were entered into a prospectively maintained internal research electronic data capture database. We searched this database retrospectively for the first 60 days of our program (March 23, 2020 to May 22, 2020). The data included basic deidentified demographics; symptoms at intake into the program; date of symptom onset; risk factors; location; and outcomes including hospitalization, admission to intensive care unit, and death. RESULTS: Patients were contacted, on average, 6.3 hours after their results became available. There was a total of 138 ED visits. Of these, 40% were admitted to the hospital, with 36% of those admitted requiring intensive care unit level of care. Of the 849 patients in this sample, there were only 2 deaths (0.23%) at 60 days. CONCLUSION: Our innovative multidisciplinary COVID team provided excellent clinical care for patients with COVID, with a very low mortality rate compared with the national average. Although data are not available on a national scale for time to contact patient, our team was able to contact patients within the established recommendation for contact within 48 hours of testing, which is optimal.
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OBJECTIVE: To describe the design, implementation, and utilization of electronic health record (EHR)-based digital health surveillance strategies used to manage the coronavirus disease 2019 (COVID-19) pandemic and to ensure delivery of high-quality clinical care, such as case identification, remote monitoring, telemedicine services, and recruitment to clinical trials at Mayo Clinic. METHODS: The design and implementation work described in this report was performed at Mayo Clinic, a large multistate integrated health care system with more than 1.5 million annual patient visits that uses the Epic EHR system. Rule-based live registries were designed in the EHR system to classify patients who currently test positive for COVID-19, patients who test positive but have recovered from COVID-19, patients who are thought to have COVID-19 but do not yet meet clinical diagnostic criteria, patients who test negative for COVID-19, and patients who exceed a risk score for serious complications from COVID-19. RESULTS: By use of registries, custom dashboards and operational reports were developed to provide a daily high-level summary for clinical practice use and up-to-date information to manage individual patients affected by COVID-19, including support of case identification, contact isolation, and other care management tasks. CONCLUSION: We developed and implemented a systematic approach to the use of EHR patient registries to manage the COVID-19 pandemic that proved feasible and useful in a large multistate group clinical practice. The key to harnessing the potential of digital surveillance tools to promote patient-centered care during the COVID-19 pandemic was to use the registry data, reports, and dashboards as informatics tools to inform decision-making.