Dynamics of SARS-CoV-2 Seroprevalence in a Large US population Over a Period of 12 Months.

Due to a combination of asymptomatic or undiagnosed infections, the proportion of the United States population infected with SARS-CoV-2 was unclear from the beginning of the pandemic. We previously established a platform to screen for SARS-CoV-2 positivity across a representative proportion of the US population, from which we reported that almost 17 million Americans were estimated to have had undocumented infections in the Spring of 2020. Since then, vaccine rollout and prevalence of different SARS-CoV-2 variants have further altered seropositivity trends within the United States population. To explore the longitudinal impacts of the pandemic and vaccine responses on seropositivity, we re-enrolled participants from our baseline study in a 6- and 12- month follow-up study to develop a longitudinal antibody profile capable of representing seropositivity within the United States during a critical period just prior to and during the initiation of vaccine rollout. Initial measurements showed that, since July 2020, seropositivity elevated within this population from 4.8% at baseline to 36.2% and 89.3% at 6 and 12 months, respectively. We also evaluated nucleocapsid seropositivity and compared to spike seropositivity to identify trends in infection versus vaccination relative to baseline. These data serve as a window into a critical timeframe within the COVID-19 pandemic response and serve as a resource that could be used in subsequent respiratory illness outbreaks.

Leveraging CTSA hubs for rapid, large-scale, high-impact research: A case study during a global public health emergency.

As the COVID-19 pandemic took hold in the USA in early 2020, it became clear that knowledge of the prevalence of antibodies to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) among asymptomatic individuals could inform public health policy decisions and provide insight into the impact of the infection on vulnerable populations. Two Clinical and Translational Science Award (CTSA) Hubs and the National Institutes of Health (NIH) set forth to conduct a national seroprevalence survey to assess the infection's rate of spread. This partnership was able to quickly design and launch the project by leveraging established research capacities, prior experiences in large-scale, multisite studies and a highly skilled workforce of CTSA hubs and unique experimental capabilities at the NIH to conduct a diverse prospective, longitudinal observational cohort of 11,382 participants who provided biospecimens and participant-reported health and behavior data. The study was completed in 16 months and benefitted from transdisciplinary teamwork, information technology innovations, multimodal communication strategies, and scientific partnership for rigor in design and analytic methods. The lessons learned by the rapid implementation and dissemination of this national study is valuable in guiding future multisite projects as well as preparation for other public health emergencies and pandemics.

Perspectives on Challenges and Opportunities for Interoperability: Findings From Key Informant Interviews With Stakeholders in Ohio.

BACKGROUND: Interoperability-the exchange and integration of data across the health care system-remains a challenge despite ongoing policy efforts aimed at promoting interoperability. OBJECTIVE: This study aimed to identify current challenges and opportunities to advancing interoperability across stakeholders. METHODS: Primary data were collected through qualitative, semistructured interviews with stakeholders (n=24) in Ohio from July to October 2021. Interviewees were sampled using a stratified purposive sample of key informants from 4 representative groups as follows: acute care and children's hospital leaders, primary care providers, behavioral health providers, and regional health information exchange networks. Interviews focused on key informant perspectives on electronic health record implementation, the alignment of public policy with organizational strategy, interoperability implementation challenges, and opportunities for health information technology. The interviews were transcribed verbatim followed by rigorous qualitative analysis using directed content analysis. RESULTS: The findings illuminate themes related to challenges and opportunities for interoperability that align with technological (ie, implementation challenges, mismatches in interoperability capabilities across stakeholders, and opportunities to leverage new technology and integrate social determinants of health data), organizational (ie, facilitators of interoperability and strategic alignment of participation in value-based payment programs with interoperability), and environmental (ie, policy) domains. CONCLUSIONS: Interoperability, although technically feasible for most providers, remains challenging for technological, organizational, and environmental reasons. Our findings suggest that the incorporation of end user considerations into health information technology development, implementation, policy, and standard deployment may support interoperability advancement.

Achieving Consensus Among Stakeholders Using the Nominal Group Technique: A Perinatal Quality Collaborative Approach.

BACKGROUND AND OBJECTIVES: Public health systems exhibiting strong connections across the workforce experience substantial population health improvements. This is especially important for improving quality and achieving value among vulnerable populations such as mothers and infants. The purpose of this research was to demonstrate how Alabama's newly formed perinatal quality collaborative (Alabama Perinatal Quality Collaborative [ALPQC]) used evidenced-based processes to achieve consensus in identifying population quality improvement (QI) initiatives. METHODS: This multiphase quantitative and qualitative study engaged stakeholders (n = 44) at the ALPQC annual meeting. Maternal and neonatal focused QI project topics were identified and catalogued from active perinatal quality collaborative websites. The Delphi method and the nominal group technique (NGT) were used to prioritize topics using selected criteria ( impact , enthusiasm , alignment , and feasibility ) and stakeholder input. RESULTS: Using the Delphi method, 11 of 27 identified project topics met inclusion criteria for stakeholder consideration. Employing the NGT, maternal projects received more total votes (n = 535) than neonatal projects (n = 313). Standard deviations were higher for neonatal projects (SD: feasibility = 10.9, alignment = 17.9, enthusiasm = 19.2, and impact = 22.1) than for maternal projects (SD: alignment = 5.9, enthusiasm = 7.3, impact = 7.9, and feasibility = 11.1). Hypertension in pregnancy (n = 117) and neonatal abstinence syndrome (n = 177) achieved the most votes total and for impact (n = 35 and n = 54, respectively) but variable support for feasibility . CONCLUSIONS: Together, these techniques achieved valid consensus across multidisciplinary stakeholders in alignment with state public health priorities. This model can be used in other settings to integrate stakeholder input and enhance the value of a common population QI agenda.

Satisfaction with modes of telemedicine delivery during COVID-19: A randomized, single-blind, parallel group, noninferiority trial.

BACKGROUND: Little is known about satisfaction with different modes of telemedicine delivery. The objective of this study was to determine whether patient satisfaction with phone-only was noninferior to video visits. METHODS: We conducted a parallel group, randomized (1:1), single-blind, noninferiority trial in multispecialty clinics at a tertiary academic medical center. Adults age ≥ 60 years or with Medicare/Medicaid insurance were eligible. Primary outcome was visit satisfaction rate (9 or 10 on a 0-10 satisfaction scale). Noninferiority was determined if satisfaction with phone-only (intervention) versus video visits (comparator) was no worse by a -15% prespecified noninferiority margin. We performed modified intent-to-treat (mITT) and per protocol analyses, after adjusting for age and insurance. RESULTS: 200 participants, 43% Black, 68% women completed surveys. Visit satisfaction rates were high. In the mITT analysis, phone-only visits were noninferior by an adjusted difference of 3.2% (95% CI, -7.6% to 14%). In the per protocol analysis, phone-only were noninferior by an adjusted difference of -4.1% (95% CI, -14.8% to 6.6%). The proportion of participants who indicated they preferred the same type of telemedicine visit as their next clinic visit were similar (30.2% vs 27.9% video vs phone-only, p = 0.78) and a majority said their medical concerns were addressed and would recommend a telemedicine visit. CONCLUSIONS: Among a group of diverse, established older or underserved patients, the satisfaction rate for phone-only was noninferior to video visits. These findings could impact practice and policies governing telemedicine.

Information system use antecedents of nursing employee turnover in a hospital setting.

BACKGROUND: Voluntary turnover (VTO) of nursing employees is expensive for hospital systems and is often associated with lower levels of patient satisfaction, as well as adverse patient outcomes such as falls and medication errors. PURPOSE: The aim of this study was to establish nurses' electronic medical record (EMR) use patterns and test if they can be used to predict VTO. METHODOLOGY/APPROACH: The study followed 1,836 hospital nurses via the collection of EMR metadata through two 1-month time periods that were 1 year apart. Machine learning algorithms were then used to derive patterns of EMR utilization using VTO as a key variable for classification. Post hoc analysis of the most predictive variables was conducted. RESULTS: The predictive model was effective in identifying which nurses would turnover 73.4% of the time and which nurses would not turnover 84.1% of the time. PRACTICE APPLICATIONS: The ability to accurately predict nurses' intentions to leave is critical to reducing turnover. Early identification can lead to specific interventions to mitigate factors that are adversely impacting the nursing experience. Post hoc analysis and the key informant interviews indicated that many nurses do not appear to have good EMR navigation skills and spend significant effort in search of patient information.