Characterizing participants who respond to text, email, phone calls, or postcards in a SARS-CoV-2 prevalence study.

INTRODUCTION: Multiple modalities and frequencies of contact are needed to maximize recruitment in many public health surveys. The purpose of this analysis is to characterize respondents to a statewide SARS-CoV-2 testing study whose participation followed either postcard, phone outreach or electronic means of invitation. In addition, we examine how participant characteristics differ based upon the number of contacts needed to elicit participation. METHODS: This is a cross-sectional analysis of survey data collected from participants who were randomly selected to represent Indiana residents and were invited to be tested for Covid-19 in April 2020. Participants received invitations via postcard, text/emails, and/or robocalls/texts based upon available contact information. The modality, and frequency of contacts, that prompted participation was determined by when the notification was sent and when the participant responded and subsequently registered to participate in the study. Chi square analyses were used to determine differences between groups and significant findings were analyzed using multinomial logistic regression. RESULTS: Respondents included 3,658 individuals and were stratified by postcards (7.9%), text/emails (26.5%), and robocalls/text (65.7%) with 19.7% registering after 1 contact, 47.9% after 2 contacts, and 32.4% after 3 contacts encouraging participation. Females made up 54.6% of the sample and responded at a higher rate for postcards (8.2% vs. 7.5%) and text/emails (28.1 vs. 24.6%) as compared to males (χ2 = 7.43, p = 0.025). Compared to males, females responded at a higher percentage after 1 contact (21.4 vs. 17.9%, χ2 = 7.6, p = 0.023). Those over 60 years responded most often after 2 contacts (χ2 = 27.5, p < 0.001) when compared to others at younger age groups. In regression analysis, participant sex (p = 0.036) age (p = 0.005), educational attainment (p = < 0.0001), and being motivated by "free testing" (p = 0.036) were correlated with participation in the prevalence study. DISCUSSION: Researchers should be aware that the modality of contact as well as the number of prompts used could influence differential participation in public health studies. Our findings can inform researchers developing studies that rely on selective participation by study subjects. We explore how to increase participation within targeted demographic groups using specific modalities and examining frequency of contact.

The effects of Pediococcus acidilactici MA18/5M on growth performance, gut integrity, and immune response using in vitro and in vivo Pacific salmonid models.

Microbial management is central to aquaculture's efficiency. Pediococcus acidilactici MA18/5M has shown promising results promoting growth, modulation of the immune response, and disease resistance in many fishes. However, the mechanisms through which this strain confers health benefits in fish are poorly understood, particularly in Pacific salmonid models. Briefly, the aims of this study were to i) assess the protective effects of P. acidilactici MA18/5M by examining gut barrier function and the expression of tight junction (TJ) and immune genes in vitro and in vivo, and ii) to determine the protective effects of this strain against a common saltwater pathogen, Vibrio anguillarum J382. An in vitro model of the salmonid gut was employed utilizing the cell line RTgutGC. Barrier formation and integrity assessed by TEER measurements in RTgutGC, showed a significant decrease in resistance in cells exposed only to V. anguillarum J382 for 24 h, but pre-treatment with P. acidilactici MA18/5M for 48 h mitigated these effects. While P. acidilactici MA18/5M did not significantly upregulate tight junction and immune molecules, pre-treatment with this strain protected against pathogen-induced insults to the gut barrier. In particular, the expression of ocldn was significantly induced by V. anguillarum J382, suggesting that this molecule might play a role in the host response against this pathogen. To corroborate these observations in live fish, the effects of P. acidilactici MA18/5M was evaluated in Chinook salmon reared in real aquaculture conditions. Supplementation with P. acidilactici MA18/5M had no effect on Chinook salmon growth parameters after 10 weeks. Interestingly, histopathological results did not show alterations associated with P. acidilactici MA18/5M supplementation, indicating that this strain is safe to be used in the industry. Finally, the expression pattern of transcripts encoding TJ and immune genes in all the treatments suggest that variation in expression is more likely to be due to developmental processes rather than P. acidilactici MA18/5M supplementation. Overall, our results showed that P. acidilactici MA18/5M is a safe strain for use in fish production, however, to assess the effects on growth and immune response previously observed in other salmonid species, an assessment in adult fish is needed.

PACAP sequence modifications modulate the peptide antimicrobial activity against bacterial pathogens affecting aquaculture.

The global aquaculture industry has significant losses each year due to disease outbreaks. Antibiotics are one of the common methods to treat fish infections, but prolonged use can lead to the emergence of resistant strains. Aeromonas spp. Infections are a common and problematic disease in fish, and members of this genera can produce antibiotic resistant strains. Antimicrobial peptides (AMPs) have emerged as an alternative method to treat and prevent infections and pituitary adenylate cyclase activating polypeptide (PACAP) is a prominent member of this family. The objective of this research was to study PACAP's direct antimicrobial activity and its toxicity in fish cells. Four synthetic variants of the natural PACAP from Clarias gariepinus were tested in addition to the natural variant. The experimental results show a different antimicrobial activity against A. salmonicida and A. hydrophila of each PACAP variant, and for the first time show dependence on the culture broth used. Furthermore, the results suggest that the underlying mechanism of PACAP antimicrobial activity includes a bacterial membrane permeabilizing effect, classifying PACAP as a membrane disruptive AMP. This study also demonstrated that the five PACAP variants evaluated showed low toxicity in vitro, at concentrations relevant for in vivo applications. Therefore, PACAP could be a promising alternative to antibiotics in the aquaculture sector.

Interim Effectiveness of Updated 2023-2024 (Monovalent XBB.1.5) COVID-19 Vaccines Against COVID-19-Associated Hospitalization Among Adults Aged ≥18 Years with Immunocompromising Conditions - VISION Network, September 2023-February 2024.

In September 2023, CDC's Advisory Committee on Immunization Practices recommended updated 2023-2024 (monovalent XBB.1.5) COVID-19 vaccination for all persons aged ≥6 months to prevent COVID-19, including severe disease. As with past COVID-19 vaccines, additional doses may be considered for persons with immunocompromising conditions, who are at higher risk for severe COVID-19 and might have decreased response to vaccination. In this analysis, vaccine effectiveness (VE) of an updated COVID-19 vaccine dose against COVID-19-associated hospitalization was evaluated during September 2023-February 2024 using data from the VISION VE network. Among adults aged ≥18 years with immunocompromising conditions, VE against COVID-19-associated hospitalization was 38% in the 7-59 days after receipt of an updated vaccine dose and 34% in the 60-119 days after receipt of an updated dose. Few persons (18%) in this high-risk study population had received updated COVID-19 vaccine. All persons aged ≥6 months should receive updated 2023-2024 COVID-19 vaccination; persons with immunocompromising conditions may get additional updated COVID-19 vaccine doses ≥2 months after the last recommended COVID-19 vaccine.

Real world performance of the 21st Century Cures Act population-level application programming interface.

OBJECTIVE: To evaluate the real-world performance of the SMART/HL7 Bulk Fast Health Interoperability Resources (FHIR) Access Application Programming Interface (API), developed to enable push button access to electronic health record data on large populations, and required under the 21st Century Cures Act Rule. MATERIALS AND METHODS: We used an open-source Bulk FHIR Testing Suite at 5 healthcare sites from April to September 2023, including 4 hospitals using electronic health records (EHRs) certified for interoperability, and 1 Health Information Exchange (HIE) using a custom, standards-compliant API build. We measured export speeds, data sizes, and completeness across 6 types of FHIR. RESULTS: Among the certified platforms, Oracle Cerner led in speed, managing 5-16 million resources at over 8000 resources/min. Three Epic sites exported a FHIR data subset, achieving 1-12 million resources at 1555-2500 resources/min. Notably, the HIE's custom API outperformed, generating over 141 million resources at 12 000 resources/min. DISCUSSION: The HIE's custom API showcased superior performance, endorsing the effectiveness of SMART/HL7 Bulk FHIR in enabling large-scale data exchange while underlining the need for optimization in existing EHR platforms. Agility and scalability are essential for diverse health, research, and public health use cases. CONCLUSION: To fully realize the interoperability goals of the 21st Century Cures Act, addressing the performance limitations of Bulk FHIR API is critical. It would be beneficial to include performance metrics in both certification and reporting processes.

Risk of COVID-19 Hospitalization and Protection Associated With mRNA Vaccination Among US Adults With Psychiatric Disorders.

BACKGROUND: Although psychiatric disorders have been associated with reduced immune responses to other vaccines, it remains unknown whether they influence COVID-19 vaccine effectiveness (VE). This study evaluated risk of COVID-19 hospitalization and estimated mRNA VE stratified by psychiatric disorder status. METHODS: In a retrospective cohort analysis of the VISION Network in four US states, the rate of laboratory-confirmed COVID-19-associated hospitalization between December 2021 and August 2022 was compared across psychiatric diagnoses and by monovalent mRNA COVID-19 vaccination status using Cox proportional hazards regression. RESULTS: Among 2,436,999 adults, 22.1% had ≥1 psychiatric disorder. The incidence of COVID-19-associated hospitalization was higher among patients with any versus no psychiatric disorder (394 vs. 156 per 100,000 person-years, p < 0.001). Any psychiatric disorder (adjusted hazard ratio [aHR], 1.27; 95% CI, 1.18-1.37) and mood (aHR, 1.25; 95% CI, 1.15-1.36), anxiety (aHR, 1.33, 95% CI, 1.22-1.45), and psychotic (aHR, 1.41; 95% CI, 1.14-1.74) disorders were each significant independent predictors of hospitalization. Among patients with any psychiatric disorder, aHRs for the association between vaccination and hospitalization were 0.35 (95% CI, 0.25-0.49) after a recent second dose, 0.08 (95% CI, 0.06-0.11) after a recent third dose, and 0.33 (95% CI, 0.17-0.66) after a recent fourth dose, compared to unvaccinated patients. Corresponding VE estimates were 65%, 92%, and 67%, respectively, and were similar among patients with no psychiatric disorder (68%, 92%, and 79%). CONCLUSION: Psychiatric disorders were associated with increased risk of COVID-19-associated hospitalization. However, mRNA vaccination provided similar protection regardless of psychiatric disorder status, highlighting its benefit for individuals with psychiatric disorders.

Electronic Health Records for Population Health Management: Comparison of Electronic Health Record-Derived Hypertension Prevalence Measures Against Established Survey Data.

BACKGROUND: Hypertension is the most prevalent risk factor for mortality globally. Uncontrolled hypertension is associated with excess morbidity and mortality, and nearly one-half of individuals with hypertension do not have the condition under control. Data from electronic health record (EHR) systems may be useful for community hypertension surveillance, filling a gap in local public health departments' community health assessments and supporting the public health data modernization initiatives currently underway. To identify patients with hypertension, computable phenotypes are required. These phenotypes leverage available data elements-such as vitals measurements and medications-to identify patients diagnosed with hypertension. However, there are multiple methodologies for creating a phenotype, and the identification of which method most accurately reflects real-world prevalence rates is needed to support data modernization initiatives. OBJECTIVE: This study sought to assess the comparability of 6 different EHR-based hypertension prevalence estimates with estimates from a national survey. Each of the prevalence estimates was created using a different computable phenotype. The overarching goal is to identify which phenotypes most closely align with nationally accepted estimations. METHODS: Using the 6 different EHR-based computable phenotypes, we calculated hypertension prevalence estimates for Marion County, Indiana, for the period from 2014 to 2015. We extracted hypertension rates from the Behavioral Risk Factor Surveillance System (BRFSS) for the same period. We used the two 1-sided t test (TOST) to test equivalence between BRFSS- and EHR-based prevalence estimates. The TOST was performed at the overall level as well as stratified by age, gender, and race. RESULTS: Using both 80% and 90% CIs, the TOST analysis resulted in 2 computable phenotypes demonstrating rough equivalence to BRFSS estimates. Variation in performance was noted across phenotypes as well as demographics. TOST with 80% CIs demonstrated that the phenotypes had less variance compared to BRFSS estimates within subpopulations, particularly those related to racial categories. Overall, less variance occurred on phenotypes that included vitals measurements. CONCLUSIONS: This study demonstrates that certain EHR-derived prevalence estimates may serve as rough substitutes for population-based survey estimates. These outcomes demonstrate the importance of critically assessing which data elements to include in EHR-based computer phenotypes. Using comprehensive data sources, containing complete clinical data as well as data representative of the population, are crucial to producing robust estimates of chronic disease. As public health departments look toward data modernization activities, the EHR may serve to assist in more timely, locally representative estimates for chronic disease prevalence.

Interim Effectiveness of Updated 2023-2024 (Monovalent XBB.1.5) COVID-19 Vaccines Against COVID-19-Associated Emergency Department and Urgent Care Encounters and Hospitalization Among Immunocompetent Adults Aged ≥18 Years - VISION and IVY Networks, September 2023-January 2024.

In September 2023, CDC's Advisory Committee on Immunization Practices recommended updated 2023-2024 (monovalent XBB.1.5) COVID-19 vaccination for all persons aged ≥6 months to prevent COVID-19, including severe disease. However, few estimates of updated vaccine effectiveness (VE) against medically attended illness are available. This analysis evaluated VE of an updated COVID-19 vaccine dose against COVID-19-associated emergency department (ED) or urgent care (UC) encounters and hospitalization among immunocompetent adults aged ≥18 years during September 2023-January 2024 using a test-negative, case-control design with data from two CDC VE networks. VE against COVID-19-associated ED/UC encounters was 51% (95% CI = 47%-54%) during the first 7-59 days after an updated dose and 39% (95% CI = 33%-45%) during the 60-119 days after an updated dose. VE estimates against COVID-19-associated hospitalization from two CDC VE networks were 52% (95% CI = 47%-57%) and 43% (95% CI = 27%-56%), with a median interval from updated dose of 42 and 47 days, respectively. Updated COVID-19 vaccine provided increased protection against COVID-19-associated ED/UC encounters and hospitalization among immunocompetent adults. These results support CDC recommendations for updated 2023-2024 COVID-19 vaccination. All persons aged ≥6 months should receive updated 2023-2024 COVID-19 vaccine.

Treatment Rates for Chlamydia trachomatis and Neisseria gonorrhoeae in a Metropolitan Area: Observational Cohort Analysis.

BACKGROUND: Chlamydia trachomatis (CT) and Neisseria gonorrhoeae (GC) are the 2 most common sexually transmitted infections (STIs) in the United States. The Centers for Disease Control and Prevention regularly publishes and updates STI Treatment Guidelines. The purpose of this study was to measure and compare treatment rates for CT and GC among public and private providers. METHODS: Data from multiple sources, including electronic health records and Medicaid claims, were linked and integrated. Cases observed during 2016-2020 were defined based on positive laboratory results. We calculated descriptive statistics and odd ratios based on characteristics of providers and patients, stratifying by public versus private providers. Univariate logistic regression models were used to examine the factors associated with recommended treatment. RESULTS: Overall, we found that 82.2% and 63.0% of initial CT and GC episodes, respectively, received Centers for Disease Control and Prevention-recommended treatment. The public STI clinic treated more than 90% of CT and GC cases consistently across the 5-year period. Private providers were significantly less likely to treat first episodes for CT (79.6%) and GC (53.3%; P < 0.01). Other factors associated with a higher likelihood of recommended treatment included being male, being HIV positive, and identifying as Black or multiracial. Among GC cases, 10.8% received nonrecommended treatment; all CT cases with treatment occurred per guidelines. CONCLUSIONS: Although these treatment rates are higher than previous studies, there remain significant gaps in STI treatment that require intervention from public health.

Non-microcystin extracellular metabolites of Microcystis aeruginosa impair viability and reproductive gene expression in rainbow trout cell lines.

Microcystis aeruginosa is a ubiquitous freshwater cyanobacterium best known for producing hepatotoxic microcystins; however, this common bloom-forming species also produces myriad biologically active and potentially deleterious other metabolites. Our understanding of the effects of these non-microcystin metabolites on fish is limited. In this study, we evaluated cytotoxicity of extracellular metabolites harvested from both microcystin-producing (MC+) and non-producing (MC-) strains of M. aeruginosa on rainbow trout (Oncorhynchus mykiss) cell lines derived from tissues of the brain, pituitary, heart, gonads, gills, skin, liver, and milt. We also examined the influence of M. aeruginosa exudates (MaE) on the expression of critical reproduction-related genes using the same cell lines. We found that exudates of the MC- M. aeruginosa strain significantly reduced viability in RTBrain, RTgill-W1, and RT-milt5 cell lines and induced significant cellular stress and/or injury in six of the eight cell lines-highlighting potential target tissues of cyanobacterial cytotoxic effects. Observed sublethal consequences of Microcystis bloom exposure occurred with both MC+ and MC- strains' exudates and significantly altered expression of developmental and sex steroidogenic genes. Collectively, our results emphasize the contributions of non-MC metabolites to toxicity of Microcystis-dominated algal blooms and the need to integrate the full diversity of M. aeruginosa compounds-beyond microcystins-into ecotoxicological risk assessments.

Cumulus: A federated EHR-based learning system powered by FHIR and AI.

Objective: To address challenges in large-scale electronic health record (EHR) data exchange, we sought to develop, deploy, and test an open source, cloud-hosted app 'listener' that accesses standardized data across the SMART/HL7 Bulk FHIR Access application programming interface (API). Methods: We advance a model for scalable, federated, data sharing and learning. Cumulus software is designed to address key technology and policy desiderata including local utility, control, and administrative simplicity as well as privacy preservation during robust data sharing, and AI for processing unstructured text. Results: Cumulus relies on containerized, cloud-hosted software, installed within a healthcare organization's security envelope. Cumulus accesses EHR data via the Bulk FHIR interface and streamlines automated processing and sharing. The modular design enables use of the latest AI and natural language processing tools and supports provider autonomy and administrative simplicity. In an initial test, Cumulus was deployed across five healthcare systems each partnered with public health. Cumulus output is patient counts which were aggregated into a table stratifying variables of interest to enable population health studies. All code is available open source. A policy stipulating that only aggregate data leave the institution greatly facilitated data sharing agreements. Discussion and Conclusion: Cumulus addresses barriers to data sharing based on (1) federally required support for standard APIs (2), increasing use of cloud computing, and (3) advances in AI. There is potential for scalability to support learning across myriad network configurations and use cases.

Immunostimulant effects of Pituitary Adenylate Cyclase-Activating Polypeptide and double-stranded (ds)RNA in Orconectes propinquus.

Disease outbreaks in crustacean aquaculture caused by opportunistic and obligate pathogens cause severe economic losses to the industry. Antibiotics are frequently used as prophylactic treatments worldwide, although its overuse and misuse has led to microbial resistance, which has driven the search for novel molecules with immunostimulant and antibacterial activities. Antimicrobial peptides (AMP) and double-stranded (ds)RNAs constitute promising immunostimulants in the fight against infectious diseases in aquaculture. Scientists have made significant progress in testing these molecules in aquatic organisms as potential candidates for replacing conventional antibiotics. However, most studies have been conducted in teleost fish, thus little is known about the immunostimulatory effects in crustaceans, especially in freshwater crayfishes. Consequently, in the present work, we evaluate the immunomodulatory effects of the AMP Pituitary Adenylate Cyclase Activating Polypeptide (PACAP) and high molecular weight (HMW) Poly (I:C) in the northern clearwater crayfish Orconectes propinquus. Two bioassays were conducted to evaluate the effects of different doses of PACAP and Poly (I:C) HMW, different administration routes, as well as the effects of the combined treatment on the crayfish immune system. Results showed the immunostimulatory role of PACAP and Poly (I:C) HMW with effects depending on the dose, the site of injection and the treatment assessed. These findings offer new insights into the crayfish immune system and contribute to the development of effective broad-spectrum immune therapies in aquaculture.

Using electronic health records to enhance surveillance of diabetes in children, adolescents and young adults: a study protocol for the DiCAYA Network.

INTRODUCTION: Traditional survey-based surveillance is costly, limited in its ability to distinguish diabetes types and time-consuming, resulting in reporting delays. The Diabetes in Children, Adolescents and Young Adults (DiCAYA) Network seeks to advance diabetes surveillance efforts in youth and young adults through the use of large-volume electronic health record (EHR) data. The network has two primary aims, namely: (1) to refine and validate EHR-based computable phenotype algorithms for accurate identification of type 1 and type 2 diabetes among youth and young adults and (2) to estimate the incidence and prevalence of type 1 and type 2 diabetes among youth and young adults and trends therein. The network aims to augment diabetes surveillance capacity in the USA and assess performance of EHR-based surveillance. This paper describes the DiCAYA Network and how these aims will be achieved. METHODS AND ANALYSIS: The DiCAYA Network is spread across eight geographically diverse US-based centres and a coordinating centre. Three centres conduct diabetes surveillance in youth aged 0-17 years only (component A), three centres conduct surveillance in young adults aged 18-44 years only (component B) and two centres conduct surveillance in components A and B. The network will assess the validity of computable phenotype definitions to determine diabetes status and type based on sensitivity, specificity, positive predictive value and negative predictive value of the phenotypes against the gold standard of manually abstracted medical charts. Prevalence and incidence rates will be presented as unadjusted estimates and as race/ethnicity, sex and age-adjusted estimates using Poisson regression. ETHICS AND DISSEMINATION: The DiCAYA Network is well positioned to advance diabetes surveillance methods. The network will disseminate EHR-based surveillance methodology that can be broadly adopted and will report diabetes prevalence and incidence for key demographic subgroups of youth and young adults in a large set of regions across the USA.

Fostering Governance and Information Partnerships for Chronic Disease Surveillance: The Multi-State EHR-Based Network for Disease Surveillance.

CONTEXT: Electronic health records (EHRs) are an emerging chronic disease surveillance data source and facilitating this data sharing is complex. PROGRAM: Using the experience of the Multi-State EHR-Based Network for Disease Surveillance (MENDS), this article describes implementation of a governance framework that aligns technical, statutory, and organizational requirements to facilitate EHR data sharing for chronic disease surveillance. IMPLEMENTATION: MENDS governance was cocreated with data contributors and health departments representing Texas, New Orleans, Louisiana, Chicago, Washington, and Indiana through engagement from 2020 to 2022. MENDS convened a governance body, executed data-sharing agreements, and developed a master governance document to codify policies and procedures. RESULTS: The MENDS governance committee meets regularly to develop policies and procedures on data use and access, timeliness and quality, validation, representativeness, analytics, security, small cell suppression, software implementation and maintenance, and privacy. Resultant policies are codified in a master governance document. DISCUSSION: The MENDS governance approach resulted in a transparent governance framework that cultivates trust across the network. MENDS's experience highlights the time and resources needed by EHR-based public health surveillance networks to establish effective governance.

Dentists' Information Needs and Opinions on Accessing Patient Information via Health Information Exchange: Survey Study.

BACKGROUND: The integration of medical and dental records is gaining significance over the past 2 decades. However, few studies have evaluated the opinions of practicing dentists on patient medical histories. Questions remain on dentists' information needs; their perception of the reliability of patient-reported medical history; satisfaction with the available information and the methods to gather this information; and their attitudes to other options, such as a health information exchange (HIE) network, to collect patient medical history. OBJECTIVE: This study aims to determine Indiana dentists' information needs regarding patients' medical information and their opinions about accessing it via an HIE. METHODS: We administered a web-based survey to Indiana Dental Association members to assess their current medical information-retrieval approaches, the information critical for dental care, and their willingness to access or share information via an HIE. We used descriptive statistics to summarize survey results and multivariable regression to examine the associations between survey respondents' characteristics and responses. RESULTS: Of the 161 respondents (161/2148, 7.5% response rate), 99.5% (n=160) respondents considered patients' medical histories essential to confirm no contraindications, including allergies or the need for antibiotic prophylaxis during dental care and other adverse drug events. The critical information required were medical conditions or diagnosis, current medications, and allergies, which were gathered from patient reports. Furthermore, 88.2% (n=142) of respondents considered patient-reported histories reliable; however, they experienced challenges obtaining information from patients and physicians. Additionally, 70.2% (n=113) of respondents, especially those who currently access an HIE or electronic health record, were willing to use an HIE to access or share their patient's information, and 91.3% (n=147) shared varying interests in such a service. However, usability, data accuracy, data safety, and cost are the driving factors in adopting an HIE. CONCLUSIONS: Patients' medical histories are essential for dentists to optimize dental care, especially for those with chronic conditions. In addition, most dentists are interested in using an HIE to access patient medical histories. The findings from this study can provide an alternative option for improving communications between dental and medical professionals and help the health information technology system or tool developers identify critical requirements for more user-friendly designs.

Interoperability in the Wild: Comparison of Real-World Electronic C-CDA Documents from Two Sources.

Although health information exchange (HIE) networks exist in multiple nations, providers still require access multiple sources to obtain medical records. We sought to measure and compare differences in data presence and concordance across regional HIE and EHR vendor-based networks. Using 1,054 randomly selected patients from a large health system in the US, we generated consolidated clinical document architecture (C-CDA) documents from each network. 778 (74%) patients had at least one C-CDA document present from either source. Among these patients, two-thirds had information in only one source. All documents contained demographics, but less than half of patients had data in clinical data domains. Moreover, data across HIE networks were not concordant. Results suggest that HIE networks have different, likely complementary, data available for the same patient, suggesting the need for better integration and deduplication for national HIE efforts.

Increasing Visibility of Sickle Cell Disease in Indiana: Establishing Baseline Prevalence Using Integrated Data From Multiple Sources.

OBJECTIVE: The Indiana Sickle Cell Data Collection (IN-SCDC) program aims to provide timely, reliable, and locally relevant information on the sickle cell disease (SCD) population in Indiana to inform public health interventions, research, and policy development. We describe the development of the IN-SCDC program and report the prevalence and geographic distribution of people with SCD in Indiana using an integrated data collection approach. METHODS: Using multiple integrated data sources and case definitions established by the Centers for Disease Control and Prevention, we classified cases of SCD in Indiana during 2015-2019. We calculated the prevalence and incidence of SCD and described characteristics of people with SCD. RESULTS: We identified 1695 people living with SCD in Indiana during the study period. The median age of people living with SCD was 21 years, and 1474 (87.0%) were Black or African American. Most (n = 1596, 91%) resided in metropolitan counties. The age-adjusted prevalence of SCD was 24.7 cases per 100 000 people. The prevalence of SCD among Black or African American people was 209.3 per 100 000 people. The incidence was 1 in 2608 live births overall and 1 in 446 live births among Black or African American people. Eighty-six deaths were confirmed in this population during 2015-2019. CONCLUSIONS: Our results establish a baseline for the IN-SCDC program. Baseline and future surveillance program efforts will help accurately inform standards of care for treatments, identify gaps in coverage and access to care, and provide guidance for legislators and community-based organizations.

Clinical Epidemiology and Risk Factors for Critical Outcomes Among Vaccinated and Unvaccinated Adults Hospitalized With COVID-19-VISION Network, 10 States, June 2021-March 2023.

BACKGROUND: The epidemiology of coronavirus disease 2019 (COVID-19) continues to develop with emerging variants, expanding population-level immunity, and advances in clinical care. We describe changes in the clinical epidemiology of COVID-19 hospitalizations and risk factors for critical outcomes over time. METHODS: We included adults aged ≥18 years from 10 states hospitalized with COVID-19 June 2021-March 2023. We evaluated changes in demographics, clinical characteristics, and critical outcomes (intensive care unit admission and/or death) and evaluated critical outcomes risk factors (risk ratios [RRs]), stratified by COVID-19 vaccination status. RESULTS: A total of 60 488 COVID-19-associated hospitalizations were included in the analysis. Among those hospitalized, median age increased from 60 to 75 years, proportion vaccinated increased from 18.2% to 70.1%, and critical outcomes declined from 24.8% to 19.4% (all P < .001) between the Delta (June-December, 2021) and post-BA.4/BA.5 (September 2022-March 2023) periods. Hospitalization events with critical outcomes had a higher proportion of ≥4 categories of medical condition categories assessed (32.8%) compared to all hospitalizations (23.0%). Critical outcome risk factors were similar for unvaccinated and vaccinated populations; presence of ≥4 medical condition categories was most strongly associated with risk of critical outcomes regardless of vaccine status (unvaccinated: adjusted RR, 2.27 [95% confidence interval {CI}, 2.14-2.41]; vaccinated: adjusted RR, 1.73 [95% CI, 1.56-1.92]) across periods. CONCLUSIONS: The proportion of adults hospitalized with COVID-19 who experienced critical outcomes decreased with time, and median patient age increased with time. Multimorbidity was most strongly associated with critical outcomes.

Identification of Hypertension in Electronic Health Records Through Computable Phenotype Development and Validation for Use in Public Health Surveillance: Retrospective Study.

BACKGROUND: Electronic health record (EHR) systems are widely used in the United States to document care delivery and outcomes. Health information exchange (HIE) networks, which integrate EHR data from the various health care providers treating patients, are increasingly used to analyze population-level data. Existing methods for population health surveillance of essential hypertension by public health authorities may be complemented using EHR data from HIE networks to characterize disease burden at the community level. OBJECTIVE: We aimed to derive and validate computable phenotypes (CPs) to estimate hypertension prevalence for population-based surveillance using an HIE network. METHODS: Using existing data available from an HIE network, we developed 6 candidate CPs for essential (primary) hypertension in an adult population from a medium-sized Midwestern metropolitan area in the United States. A total of 2 independent clinician reviewers validated the phenotypes through a manual chart review of 150 randomly selected patient records. We assessed the precision of CPs by calculating sensitivity, specificity, positive predictive value (PPV), F1-score, and validity of chart reviews using prevalence-adjusted bias-adjusted κ. We further used the most balanced CP to estimate the prevalence of hypertension in the population. RESULTS: Among a cohort of 548,232 adults, 6 CPs produced PPVs ranging from 71% (95% CI 64.3%-76.9%) to 95.7% (95% CI 84.9%-98.9%). The F1-score ranged from 0.40 to 0.91. The prevalence-adjusted bias-adjusted κ revealed a high percentage agreement of 0.88 for hypertension. Similarly, interrater agreement for individual phenotype determination demonstrated substantial agreement (range 0.70-0.88) for all 6 phenotypes examined. A phenotype based solely on diagnostic codes possessed reasonable performance (F1-score=0.63; PPV=95.1%) but was imbalanced with low sensitivity (47.6%). The most balanced phenotype (F1-score=0.91; PPV=83.5%) included diagnosis, blood pressure measurements, and medications and identified 210,764 (38.4%) individuals with hypertension during the study period (2014-2015). CONCLUSIONS: We identified several high-performing phenotypes to identify essential hypertension prevalence for local public health surveillance using EHR data. Given the increasing availability of EHR systems in the United States and other nations, leveraging EHR data has the potential to enhance surveillance of chronic disease in health systems and communities. Yet given variability in performance, public health authorities will need to decide whether to seek optimal balance or declare a preference for algorithms that lean toward sensitivity or specificity to estimate population prevalence of disease.

Real World Performance of the 21st Century Cures Act Population Level Application Programming Interface.

Objective: To evaluate the real-world performance in delivering patient data on populations, of the SMART/HL7 Bulk FHIR Access API, required in Electronic Health Records (EHRs) under the 21st Century Cures Act Rule. Materials and Methods: We used an open-source Bulk FHIR Testing Suite at five healthcare sites from April to September 2023, including four hospitals using EHRs certified for interoperability, and one Health Information Exchange (HIE) using a custom, standards-compliant API build. We measured export speeds, data sizes, and completeness across six types of FHIR resources. Results: Among the certified platforms, Oracle Cerner led in speed, managing 5-16 million resources at over 8,000 resources/min. Three Epic sites exported a FHIR data subset, achieving 1-12 million resources at 1,555-2,500 resources/min. Notably, the HIE's custom API outperformed, generating over 141 million resources at 12,000 resources/min. Discussion: The HIE's custom API showcased superior performance, endorsing the effectiveness of SMART/HL7 Bulk FHIR in enabling large-scale data exchange while underlining the need for optimization in existing EHR platforms. Agility and scalability are essential for diverse health, research, and public health use cases. Conclusion: To fully realize the interoperability goals of the 21st Century Cures Act, addressing the performance limitations of Bulk FHIR API is critical. It would be beneficial to include performance metrics in both certification and reporting processes.