Objectives: The purpose of this study was threefold. First, we gathered and synthesized the historic literature regarding electronic health record (E

Asymptomatic SARS-CoV-2 infection and delayed implementation of diagnostics have led to poorly defined viral prevalence rates in the United States and elsewhere. To address this, we analyzed seropositivity in 9089 adults in the United States who had not been diagnosed previously with COVID-19. Individuals with characteristics that reflected the U.S. population (n = 27,716) were selected by quota sampling from 462,949 volunteers. Enrolled participants (n = 11,382) provided medical, geographic, demographic, and socioeconomic information and dried blood samples. Survey questions coincident with the Behavioral Risk Factor Surveillance System survey, a large probability-based national survey, were used to adjust for selection bias. Most blood samples (88.7%) were collected between 10 May and 31 July 2020 and were processed using ELISA to measure seropositivity (IgG and IgM antibodies against SARS-CoV-2 spike protein and the spike protein receptor binding domain). The overall weighted undiagnosed seropositivity estimate was 4.6% (95% CI, 2.6 to 6.5%), with race, age, sex, ethnicity, and urban/rural subgroup estimates ranging from 1.1% to 14.2%. The highest seropositivity estimates were in African American participants; younger, female, and Hispanic participants; and residents of urban centers. These data indicate that there were 4.8 undiagnosed SARS-CoV-2 infections for every diagnosed case of COVID-19, and an estimated 16.8 million infections were undiagnosed by mid-July 2020 in the United States.

Objective: The purpose of this study is to reassess the projected rate of Electronic Health Record (EHR) diffusion and examine how the federal govern

Journal of Medical Internet Research - International Scientific Journal for Medical Research, Information and Communication on the Internet

Journal of Medical Internet Research - International Scientific Journal for Medical Research, Information and Communication on the Internet #Preprint #PeerReviewMe: Warning: This is a unreviewed preprint. Readers are warned that the document has not been peer-reviewed by expert/patient reviewers or an academic editor, may contain misleading claims, and is likely to undergo changes before final publication, if accepted, or may have been rejected/withdrawn. Readers with interest and expertise are encouraged to sign up as peer-reviewer, if the paper is within an open peer-review period. Please cite this preprint only for review purposes or for grant applications and CVs (if you are the author). Background: The Meaningful Use (MU) program has promoted the EHR adoption among U.S. hospitals. Studies have shown that EHR adoption has been slower than desired in certain types of hospitals; but generally, the overall adoption rate has increased among hospitals. However, these studies have neither evaluated the adoption of advanced functionalities of EHRs (beyond MU) nor forecasted EHR maturation over an extended period in holistic fashion. Additional research is needed to assess U.S. hospitals’ EHR technology adoption and advancement patterns prospectively. Objective: This study forecasts the maturation of EHR functionality adoption among U.S. hospitals through 2035. Methods: The HIMSS Analytics’ Electronic Medical Record Adoption Model (EMRAM) dataset was used to track historic uptakes of various EHR functionalities considered critical to improving healthcare quality and efficiency in hospitals. The Bass model was used to predict the technological diffusion rates for repeated EHR adoptions where upgrades undergo rapid technological improvements. The forecast used EMRAM data from 2006 to 2014 to estimate adoption levels to the year 2035. Results: In 2014, over 5,400 hospitals completed HIMSS’ annual EMRAM survey (86%+ of total U.S. hospitals). In 2006, the majority of the U.S. hospitals were in EMRAM stages zero, one and two. By 2014, most hospitals had achieved stages three, four and five of EMRAM. The overall technology diffusion model (i.e., the Bass Model) reached an adjusted R-squared of .91. The final forecast depicted differing trends for each of the EMRAM stages. In 2006, the first year of observation, peaks of stages zero and one were shown as EHR adoption predates HIMSS’ EMRAM. By 2007, Stage-2 reached its peak. Stage-3 reached its full height by 2011, while Stage-4 maxed out by 2014. The first three stages created a graph that exhibits the expected ‘S-curve’ for technology diffusion with inflection point being the peak diffusion rate. The forecast indicates that Stage-5 will reach its peak by 2019 and Stage-6 will top out in 2026. Though this forecast extends to the year 2035, no peak was readily observed for Stage-7. Overall, most hospitals will achieve stages five, six or seven of EMRAM by 2020; however, a considerable number of hospitals will not achieve Stage-7 by 2035. Conclusions: We forecasted the adoption of EHR capabilities from a paper-based environment (Stage-0) to an environment where only electronic information is used to document and direct care delivery (Stage-7). According to our forecasts, the majority of hospitals will not reach Stage-7 until 2035, absent major policy changes or leaps in the technologies’ capabilities. These results indicate that U.S. hospitals are decades away from fully implementing sophisticated decision support applications and interoperability functionalities into their EHR as defined by EMRAM’s Stage-7.