Carrie Burk

Importance: Clinician adoption and adaptation of new tools evolve over time. Prior studies of ambient Artificial intelligence (AI) scribes have primarily relied on single time-point measurements (e.g., pre-post), potentially obfuscating their true impact on outcomes. Objective: To investigate longitudinal effects of an AI scribe tool on patient encounter-level outcomes. Design: Case series across 48 weeks (24 pre, 24 post) per clinician. Setting: Primary care clinical encounters occurring between 01/05/24 and 10/31/25. Participants: Primary care clinicians (attending physicians and advanced practice providers). Exposure: Ambient AI scribe introduction to clinical workflow, indexed to study day zero, per clinician. Main outcomes and measures: Encounter-level measurements of documentation time (note writing time, time outside of scheduled hours (TOSH), pajama time), note writing patterns (note length, note closure <24h) and clinician’s billed work Relative Value Units (wRVU) with a focus on changes from pre-period outcomes at Day 0 and 150. Results: 220 primary care clinicians (Mean age=43.7, 70.9% females; 56.4% physicians) from 36 clinics, conducting 314,845 patient encounters were included. All outcomes evolved from day zero to day 150 and are compared back to pre-period levels. There was evidence of an immediate 7% decrease on average in note writing time at day zero (Incidence Rate Ratio, IRR 0.93, 95%CI [0.89, 0.96]), intensifying to a 15% decrease by day 150 (IRR 0.85, 95%CI [0.83, 0.87]). There was no evidence of a change in pajama time or TOSH at day zero; however, at day 150, there was evidence of a 18% decrease in pajama time (0.82, 95%CI [0.73, 0.91]) and a 13% decrease in TOSH (0.87, 95%CI [0.77, 0.99]). At day zero, there was evidence of a 5% increase (1.05, 95%CI [1.00, 1.10]) in note length and 31% increase in note closures (1.31, 95%CI [1.13, 1.53]), with both slowly attenuating to pre-period levels by day 150. Although there was no evidence of changes in wRVU at day zero, there was a 2% increase total wRVU at day 150 (1.02, 95%CI [1.01, 1.03]). Conclusions and relevance: Longitudinal changes were gradual, but persistent, underscoring the gradual adaptation of AI scribes, as clinicians situated these tools within their workflows. Key Points: Question: How do the patterns of use of an ambient Artificial Intelligence (AI) scribe evolve over time? Findings: In this longitudinal, quasi-experimental study on clinician use of an ambient AI scribe, documentation time, note writing patterns and financial productivity evolved over a 150-day period. Compared to the pre-period, note writing time savings increased from 7% (day zero) to 15% (day 150); changes in all other considered outcomes including time outside of scheduled hours, pajama time, note length, note closure <24h, billed work Relative Value Units evolved over the 150-day period. Meaning: Clinician use of ambient AI scribes showed persistent changes in patterns of use over a 150-day period, highlighting a gradual adaptation process and the need for longitudinal assessment.

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection can cause neurological sequelae after the resolution of symptomatic COVID-19 illness, but the occurrence of peripheral neuropathy symptoms and cranial nerve dysfunction is unknown. This study aimed to characterize the occurrence and severity of pain and peripheral neuropathy symptoms in patients with SARS-CoV-2 infection. An observational cohort study included adults tested for a SARS-CoV-2 infection at an academic medical center (assigned as CV+ or control, based on test results). Thirty to 90 days after the index SARS-CoV-2 test, patients completed a web-based questionnaire assessing pain, peripheral neuropathy-related sensory symptoms, and symptoms in the distribution of cranial nerves (current symptoms, symptoms at testing and 2 weeks thereafter). Univariate analyses compared the outcomes between the groups. Multivariable analysis was used to determine the odds for neuropathy symptoms after adjusting for key baseline variables. A total of 1556 participants were included: 542 CV+ patients and 1014 control subjects. CV+ patients reported a higher occurrence of peripheral neuropathy symptoms in the extremities anytime within 90 days postinfection (28.8% vs 12.9%, odds ratio [OR] [95% confidence interval] = 2.72 [2.10-3.54]), as well as such symptoms persisting up to 90 days after infection (6.1% vs 1.9%, OR = 3.39 [1.91-6.03]). The occurrence of pain in the extremities was higher in the CV+ group (24.2% vs 9.8%, OR = 2.95 [2.21-3.91]). SARS-CoV-2 infection was also associated with higher occurrence of peripheral neuropathy symptoms, after adjusting for the history of chronic pain and neuropathy (OR = 3.19 [2.37-4.29]). The results suggest that SARS-CoV-2 infection was independently associated with an increased risk of pain and peripheral neuropathy symptoms.

Introduction and Objectives: The coronavirus disease 2019 (COVID-19) pandemic has resulted in patients experiencing symptoms that include neurological dysfunction. As many viral infections are associated with neuropathy, the aim of the study is to characterize the incidence and severity of neuropathic pain in patients with COVID-19. Methods: A cohort study will be conducted in adult (≥18 years) patients who were tested for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) at Washington University/Barnes-Jewish Hospital. Participants who are deceased, with incomplete test results, or who cannot be contacted will be excluded. Approximately 1320 participants will be recruited in a 1:2 ratio of those with a positive-to-negative SARS-CoV-2 test result. Each participant will be invited to complete a survey to assess their symptoms related to neuropathy, 30 to 90 days after their initial SARS-CoV-2 test. Survey responses, demographics, and clinical data from the electronic health record will be used for analysis. The primary outcome is the incidence of new symptoms of neuropathic pain. The self-reported DN4 and Neuropathic Pain Symptom Inventory questionnaires (Appendix 1, http://links.lww.com/PR9/A103) will be used for neuropathic pain screening and severity assessment, respectively. Exploratory analyses will be performed to investigate other potential clinical endpoints and trends. Results/Conclusion: Similar to previous coronavirus infections, an increased incidence of new-onset neuropathic pain after COVID-19 disease is expected, along with an increase in the severity experienced by patients with COVID-19 with pre-existing chronic pain. Comprehensive understanding of how COVID-19 affects the nervous system can provide a better framework for managing pain in this disease.