Doubeni, Chyke

AbstractPurposeRural populations are disproportionately affected by the COVID‐19 pandemic. We characterized urban‐rural disparities in patient portal messaging utilization for COVID‐19, and, of those who used the portal during its early stage in the Midwest.MethodsWe collected over 1 million portal messages generated by midwestern Mayo Clinic patients from February to August 2020. We analyzed patient‐generated messages (PGMs) on COVID‐19 by urban‐rural locality and incorporated patients’ sociodemographic factors into the analysis.FindingsThe urban‐rural ratio of portal users, message senders, and COVID‐19 message senders was 1.18, 1.31, and 1.79, indicating greater use among urban patients. The urban‐rural ratio (1.69) of PGMs on COVID‐19 was higher than that (1.43) of general PGMs. The urban‐rural ratios of messaging were 1.72‐1.85 for COVID‐19‐related care and 1.43‐1.66 for other health care issues on COVID‐19. Compared with urban patients, rural patients sent fewer messages for COVID‐19 diagnosis and treatment but more messages for other reasons related to COVID‐19‐related health care (eg, isolation and anxiety). The frequent senders of COVID‐19‐related messages among rural patients were 40+ years old, women, married, and White.ConclusionsIn this Midwest health system, rural patients were less likely to use patient online services during a pandemic and their reasons for its use differ from urban patients. Results suggest opportunities for increasing equity in rural patient engagement in patient portals (in particular, minority populations) for COVID‐19. Public health intervention strategies could target reasons why rural patients might seek health care in a pandemic, such as social isolation and anxiety.

AbstractIntroductionMany evidence‐based programs (EBPs) have been determined in randomized controlled trials to be effective, but few studies explore the real‐world effectiveness of EBPs implemented in the natural community setting. Our study evaluated whether a novel linked infrastructure would enable such insights and continuous improvement as part of a learning healthcare‐community bridged “wellcare” ecosystem.MethodsWe created a secure, web‐based data entry and storage platform with a network of Minnesota community‐based organizations to record EBP participants' demographics and attendance, and program details. We then linked participant's information to their Rochester Epidemiology Project (REP) medical records. With this infrastructure, we conducted a proof of concept, retrospective cohort study by matching EBP participants to REP controls and comparing medical record‐documented outcomes over 1 year follow‐up.ResultsWe successfully linked EBP participant records with medical records in 77.6% of cases, and the infrastructure proved feasible and scalable. Still, key challenges remain in obtaining participant consent for data sharing. Upfront resource investments and the availability of REP‐like warehouses limit generalizability. Optimal learning will be improved by enhancements that better track program fidelity. Our pilot study established a proof‐of‐concept, but sample sizes (n = 99 for falls prevention and n = 97 chronic disease/pain management EBP completers) were too small to detect significant differences in hospital admittance as compared to matched controls for either EBP group, (OR = 0.66[0.36, 1.19]) and (OR = 0.81[0.43, 1.54]), respectively. Events were too rare to gather meaningful information about effects on fall rates.ConclusionsOur pilot demonstrates the feasibility of developing an online infrastructure that connects information from community leaders with medical record documented health outcomes, bridging the knowledge gap between community programs and the health care system. Insights gleaned from our infrastructure can be used to continuously shape community program delivery to reduce the need for formal health care services.