Increased Utilization of Virtual Visits and Electronic Approaches in Clinical Research During the COVID-19 Pandemic and Thereafter.

OBJECTIVES: To assess the impact of the COVID-19 pandemic on clinical research and the use of electronic approaches to mitigate this impact. METHODS: We compared the utilization of electronic consenting, remote visits, and remote monitoring by study monitors in all research studies conducted at Mayo Clinic sites (Arizona, Florida, and Minnesota) before and during the COVID-19 pandemic (ie, between May 1, 2019 and December 31, 2020). Participants are consented through a participant-tracking system linked to the electronic health record. RESULTS: Between May 2019, and December 2020, there were 130,800 new consents across every modality (electronic and paper) to participate in a non-trial (107,176 [82%]) or a clinical trial (23,624 [18%]). New consents declined from 5741 in February 2020 to 913 in April 2020 but increased to 11,864 in November 2020. The mean (standard deviation [SD]) proportion of electronic consent increased from 22 (2%) before to 45 (20%) during the pandemic (P=.001). Mean (SD) remote electronic consenting increased from 0.3 (0.5%) to 29 (21%) (P<.001). The mean (SD) number of patients with virtual visits increased from 3.5 (2.4%) to 172 (135%) (P=.003) per month between pre-COVID (July 2019 to February 2020) and post-COVID (March to December 2020) periods. Virtual visits used telemedicine (68%) or video (32%). Requests for remote monitor access to complete visits increased from 44 (17%) per month between May 2019 and February 2020 to 111 (74%) per month between March and December 2020 (P=.10). CONCLUSION: After a sharp early decline, the enrollment of new participants and ongoing study visits recovered during the COVID-19 pandemic. This recovery was accompanied by the increased use of electronic tools.

Comparing Methods for Record Linkage for Public Health Action: Matching Algorithm Validation Study.

BACKGROUND: Many public health departments use record linkage between surveillance data and external data sources to inform public health interventions. However, little guidance is available to inform these activities, and many health departments rely on deterministic algorithms that may miss many true matches. In the context of public health action, these missed matches lead to missed opportunities to deliver interventions and may exacerbate existing health inequities. OBJECTIVE: This study aimed to compare the performance of record linkage algorithms commonly used in public health practice. METHODS: We compared five deterministic (exact, Stenger, Ocampo 1, Ocampo 2, and Bosh) and two probabilistic record linkage algorithms (fastLink and beta record linkage [BRL]) using simulations and a real-world scenario. We simulated pairs of datasets with varying numbers of errors per record and the number of matching records between the two datasets (ie, overlap). We matched the datasets using each algorithm and calculated their recall (ie, sensitivity, the proportion of true matches identified by the algorithm) and precision (ie, positive predictive value, the proportion of matches identified by the algorithm that were true matches). We estimated the average computation time by performing a match with each algorithm 20 times while varying the size of the datasets being matched. In a real-world scenario, HIV and sexually transmitted disease surveillance data from King County, Washington, were matched to identify people living with HIV who had a syphilis diagnosis in 2017. We calculated the recall and precision of each algorithm compared with a composite standard based on the agreement in matching decisions across all the algorithms and manual review. RESULTS: In simulations, BRL and fastLink maintained a high recall at nearly all data quality levels, while being comparable with deterministic algorithms in terms of precision. Deterministic algorithms typically failed to identify matches in scenarios with low data quality. All the deterministic algorithms had a shorter average computation time than the probabilistic algorithms. BRL had the slowest overall computation time (14 min when both datasets contained 2000 records). In the real-world scenario, BRL had the lowest trade-off between recall (309/309, 100.0%) and precision (309/312, 99.0%). CONCLUSIONS: Probabilistic record linkage algorithms maximize the number of true matches identified, reducing gaps in the coverage of interventions and maximizing the reach of public health action.

Ambulatory care for epilepsy via telemedicine during the COVID-19 pandemic.

OBJECTIVE: To assess feasibility, patient satisfaction, and financial advantages of telemedicine for epilepsy ambulatory care during the current COVID-19 pandemic. METHODS: The demographic and clinical characteristics of all consecutive patients evaluated via telemedicine at a level 4 epilepsy center between March 20 and April 20, 2020 were obtained retrospectively from electronic medical records. A telephone survey to assess patient satisfaction and preferences was conducted within one month following the initial visit. RESULTS: Among 223 telehealth patients, 85.7% used both synchronous audio and video technology. During the visits, 39% of patients had their anticonvulsants adjusted while 18.8% and 11.2% were referred to laboratory/diagnostic testing and specialty consults, respectively. In a post-visit survey, the highest degree of satisfaction with care was expressed by 76.9% of patients. The degree of satisfaction tended to increase the further a patient lived from the clinic (p = 0.05). Beyond the pandemic, 89% of patients reported a preference for continuing telemedicine if their epilepsy symptoms remained stable, while only 44.4% chose telemedicine should their symptoms worsen. Inclement weather and lack of transportation were factors favoring continued use of telemedicine. An estimated cost saving to patient attributed to telemedicine was $30.20 ±â€¯3.8 per visit. SIGNIFICANCE: Our findings suggest that epilepsy care via telemedicine provided high satisfaction and economic benefit, without compromising patients' quality of care, thereby supporting the use of virtual care during current and future epidemiological fallouts. Beyond the current pandemic, patients with stable seizure symptoms may prefer to use telemedicine for their epilepsy care.

Angiotensin-converting enzyme inhibitors or angiotensin II receptor blockers and prognosis of hypertensive patients hospitalised with COVID-19.

BACKGROUND: Among hypertensive patients, the association between treatment with angiotensin-converting enzyme inhibitors (ACEI) or angiotensin II receptor blockers (ARB) and the clinical severity of COVID-19, remains uncertain. AIMS: To determine whether hypertensive patients hospitalised with COVID-19 are at risk of worse outcomes if on treatment with ACEI or ARB compared to other anti-hypertensive medications. METHODS: This is a retrospective study conducted at a single academic medical centre (Fondazione Policlinico A. Gemelli IRCCS, Rome, Italy) from 1 to 31 March 2020. We compared patients on treatment with an ACEI/ARB (ACEI/ARB group) to patients receiving other anti-hypertensive medications (No-ACEI/ARB group). The end-points of the study were the all-cause in-hospital death and the combination of in-hospital death or need for intensive care unit (ICU) admission. RESULTS: The sample included 166 COVID-19 patients; median age was 74 years and 109 (66%) were men. Overall, 111 (67%) patients were taking an ACEI or ARB. Twenty-nine (17%) patients died during the hospital stay, and 51 (31%) met the combined end-point. After adjustment for comorbidities, age and degree of severity at the presentation, ACEI or ARB treatment was an independent predictor neither of in-hospital death nor of the combination of in-hospital death/need for ICU. No differences were documented between treatment with ACEI compared to ARB. CONCLUSIONS: Among hypertensive patients hospitalised for COVID-19, treatment with ACEI or ARB is not associated with an increased risk of in-hospital death.

Differences Between Neurosurgical Subspecialties in Telehealth Adoption.

OBJECTIVE: The health care field has been faced with unprecedented challenges during the COVID 19 pandemic. One such challenge was the implementation of enhanced telehealth capabilities to ensure continuity of care. In this study, we aim to understand differences between subspecialties with regard to patient consent and satisfaction following telehealth implementation. METHODS: A retrospective review of the electronic medical record was performed from March 2 to May 8, 2020 to evaluate surgical consents before and after telehealth implementation. Press Ganey survey results were also obtained both pre- and posttelehealth implementation and compared. RESULTS: There was no significant difference in the percentage of new patients consented for surgery (after being seen via telehealth only) between the cranial and spine services. For procedures in which >10 patients were consented for surgery, the highest proportion of patients seen only via telehealth was for ventriculoperitoneal shunt placement/endoscopic third ventriculostomy for the cranial service, and lumbar laminectomy and microdiscectomy for the spine service. Additionally, the spine service experienced marked improvement in Press Ganey scores posttelehealth implementation with overall doctor ranking improving from the 29th to the 93rd percentile, and likelihood to recommend increasing from the 24th to the 94th percentile. CONCLUSIONS: There were clear trends with regard to which pathologies and procedures were most amenable to telehealth visits, which suggests a potential roadmap for future clinic planning. Additionally, the notable improvement in spine patient satisfaction following the implementation of a telehealth program suggests the need for long-term process changes.