An epidemiological modeling framework to inform institutional-level response to infectious disease outbreaks: a Covid-19 case study.

Institutions have an enhanced ability to implement tailored mitigation measures during infectious disease outbreaks. However, macro-level predictive models are inefficient for guiding institutional decision-making due to uncertainty in local-level model input parameters. We present an institutional-level modeling toolkit used to inform prediction, resource procurement and allocation, and policy implementation at Clemson University throughout the Covid-19 pandemic. Through incorporating real-time estimation of disease surveillance and epidemiological measures based on institutional data, we argue this approach helps minimize uncertainties in input parameters presented in the broader literature and increases prediction accuracy. We demonstrate this through case studies at Clemson and other university settings during the Omicron BA.1 and BA.4/BA.5 variant surges. The input parameters of our toolkit are easily adaptable to other institutional settings during future health emergencies. This methodological approach has potential to improve public health response through increasing the capability of institutions to make data-informed decisions that better prioritize the health and safety of their communities while minimizing operational disruptions.

Implementation of a mobile health clinic framework for Hepatitis C virus screening and treatment: a descriptive study.

Background: Although treatment for Hepatitis C Virus (HCV) is effective, individuals face access barriers. The utility of mobile health clinics (MHC), effective mechanisms for providing healthcare to underserved populations, is understudied for HCV-related interventions. We aimed to describe implementation of, and factors associated with, screening and treatment via MHCs. Methods: Clemson Rural Health implemented a novel MHC program to reach and treat populations at-risk for HCV with a focus on care for uninsured individuals. We examined HCV screening and treatment initiation/completion indicators between May 2021 and January 2023. Findings: Among 607 individuals screened across 31 locations, 94 (15.5%) tested positive via antibody and viral load testing. Treatment initiation and completion rates were 49.6% and 86.0%, respectively. Among those screened, the majority were male (57.5%), White (61.3%; Black/Hispanic: 28.2%/7.7%), and without personal vehicle as primary transportation mode (54.4%). Injection drug use (IDU) was 27.2% and uninsured rate was 42.8%. Compared to HCV-negative, those infected included more individuals aged 30-44 (52.1% vs. 36.4%, p = 0.023), male (70.2% vs. 55.2%, p = 0.009), White (78.5% vs. 60.2%, p < 0.0001), without personal vehicle (58.5% vs. 43.5%, p = 0.028), IDU (83.7% vs. 21.0%, p < 0.0001), and uninsured (61.2% vs. 48.8%, p = 0.050). Uninsured rates were higher among those initiating compared to not initiating treatment (74.5% vs. 45.3%, p = 0.004). Interpretation: The MHC framework successfully reaching its target population: at-risk individuals with access barriers to healthcare. The high HCV screening and treatment initiation/completion rates demonstrate the utility of MHCs as effective and acceptable intervention settings among historically difficult-to-treat populations. Funding: Gilead Sciences, Inc., and SC Center for Rural and Primary Healthcare.

Systematic examination of methodological inconsistency in operationalizing cognitive reserve and its impact on identifying predictors of late-life cognition.

BACKGROUND: Cognitive reserve (CR) is the ability to maintain cognitive performance despite brain pathology. CR is built through lifecourse experiences (e.g., education) and is a key construct in promoting healthy aging. However, the operationalization of CR and its estimated association with late-life cognition varies. The purpose of this study was to systematically examine the operationalization of CR and the relationship between its operationalization and late-life cognition. METHODS: We performed a comprehensive review of experiences (proxies) used to operationalize CR. The review informed quantitative analyses using data from 1366 participants of the Memory and Aging Project to examine 1) relationships between proxies and 2) the relationship between operationalization and late-life cognition. We also conducted a factor analysis with all identified CR experiences to create a composite lifecourse CR score. Generalized linear mixed models examined the relationship between operationalizations and global cognition, with secondary outcomes of five domains of cognition to examine consistency. RESULTS: Based on a review of 753 articles, we found the majority (92.3%) of the 28 commonly used proxies have weak to no correlation between one another. There was substantial variability in the association between operationalizations and late-life global cognition (median effect size: 0.99, IQR: 0.34 to 1.39). There was not strong consistency in the association between CR operationalizations and the five cognitive domains (mean consistency: 56.1%). The average estimate for the 28 operationalizations was 0.91 (SE = 0.48), compared to 2.48 (SE = 0.40) for the lifecourse score and it was associated with all five domains of cognition. CONCLUSIONS: Inconsistent methodology is theorized as a major limitation of CR research and barrier to identification of impactful experiences for healthy cognitive aging. Based on the weak associations, it is not surprising that the relationship between CR and late-life cognition is dependent on the experience used to operationalize CR. Scores using multiple experiences across the lifecourse may help overcome such limitations. Adherence to a lifecourse approach and collaborative movement towards a consensus operationalization of CR are imperative shifts in the study of CR that can better inform research on risk factors related to cognitive decline and ultimately aid in the promotion of healthy aging.

The Association between Food Security Status and the Home Food Environment among a Sample of Rural South Carolina Residents.

Prior research suggests that food security status may have an effect on the home food environment. Further, the literature suggests that food access factors may function to influence said relationship. The purpose of this research is to fill a gap in the literature on this relationship, as well as to identify potential food access effect modifiers. This research employs linear mixed effects modeling with a random intercept variable (zip codes). Eleven food access variables are included in regression analyses and are tested as potential effect modifiers in the association between food security status and the home food environment. Food security status is significantly associated with the home food environment (95% CI = 0.1-1.38) in the unadjusted model. In the adjusted model, food pantry usage is found to be a significant effect modifier on the association between food security status and the home food environment. This research concludes that food security status has a significant but disparate effect on the home food environment depending on participant food pantry usage. Practical implications from this research would be for relevant stakeholders to potentially improve rural food pantry access in order to increase the home food environment among rural and food insecure populations.

An epidemiological modeling framework to inform institutional-level response to infectious disease outbreaks: A Covid-19 case study.

Institutions have an enhanced ability to implement tailored mitigation measures during infectious disease outbreaks. However, macro-level predictive models are inefficient for guiding institutional decision-making due to uncertainty in local-level model input parameters. We present an institutional-level modeling toolkit used to inform prediction, resource procurement and allocation, and policy implementation at Clemson University throughout the Covid-19 pandemic. Through incorporating real-time estimation of disease surveillance and epidemiological measures based on institutional data, we argue this approach helps minimize uncertainties in input parameters presented in the broader literature and increases prediction accuracy. We demonstrate this through case studies at Clemson and other university settings during the Omicron BA.1 and BA.4/BA.5 variant surges. The input parameters of our toolkit are easily adaptable to other institutional settings during future health emergencies. This methodological approach has potential to improve public health response through increasing the capability of institutions to make data-informed decisions that better prioritize the health and safety of their communities while minimizing operational disruptions.

Keyphrase Identification Using Minimal Labeled Data with Hierarchical Context and Transfer Learning.

Interoperable clinical decision support system (CDSS) rules provide a pathway to interoperability, a well-recognized challenge in health information technology. Building an ontology facilitates creating interoperable CDSS rules, which can be achieved by identifying the keyphrases (KP) from the existing literature. However, KP identification for data labeling requires human expertise, consensus, and contextual understanding. This paper aims to present a semi-supervised KP identification framework using minimal labeled data based on hierarchical attention over the documents and domain adaptation. Our method outperforms the prior neural architectures by learning through synthetic labels for initial training, document-level contextual learning, language modeling, and fine-tuning with limited gold standard label data. To the best of our knowledge, this is the first functional framework for the CDSS sub-domain to identify KPs, which is trained on limited labeled data. It contributes to the general natural language processing (NLP) architectures in areas such as clinical NLP, where manual data labeling is challenging, and light-weighted deep learning models play a role in real-time KP identification as a complementary approach to human experts' effort.

Association between Initial Opioid Prescription and Patient Pain with Continued Opioid Use among Opioid-Naïve Patients Undergoing Elective Surgery in a Large American Health System.

There is growing concern about the over-prescription of opioids and the risks of long-term use. This study examined the relationship between initial need (pre-operative, post-operative, and discharge pain) and dosage of opioids in the first prescription after surgery with continued opioid use through opioid refills over 12 months, while considering patient-level characteristics. A total of 9262 opioid-naïve patients underwent elective surgery, 7219 of whom were prescribed opioids following surgery. The results showed that 17% of patients received at least one opioid refill within one year post-surgery. Higher initial opioid doses, measured in morphine milligram equivalent (MME), were associated with a greater likelihood of continued use. Patients receiving a dose greater than 90 MME were 1.57 times more likely to receive a refill compared to those receiving less than 90 MME (95% confidence interval: 1.30-1.90, p < 0.001). Additionally, patients who experienced pain before or after surgery were more likely to receive opioid refills. Those experiencing moderate or severe pain were 1.66 times more likely to receive a refill (95% confidence interval: 1.45-1.91, p < 0.001). The findings highlight the need to consider surgery-related factors when prescribing opioids and the importance of developing strategies to balance the optimization of pain management with the risk of opioid-related harms.

Head Size in Phelan-McDermid Syndrome: A Literature Review and Pooled Analysis of 198 Patients Identifies Candidate Genes on 22q13.

Phelan-McDermid syndrome (PMS) is a multisystem disorder that is associated with deletions of the 22q13 genomic region or pathogenic variants in the SHANK3 gene. Notable features include developmental issues, absent or delayed speech, neonatal hypotonia, seizures, autism or autistic traits, gastrointestinal problems, renal abnormalities, dolichocephaly, and both macro- and microcephaly. Assessment of the genetic factors that are responsible for abnormal head size in PMS has been hampered by small sample sizes as well as a lack of attention to these features. Therefore, this study was conducted to investigate the relationship between head size and genes on chromosome 22q13. A review of the literature was conducted to identify published cases of 22q13 deletions with information on head size to conduct a pooled association analysis. Across 56 studies, we identified 198 cases of PMS with defined deletion sizes and head size information. A total of 33 subjects (17%) had macrocephaly, 26 (13%) had microcephaly, and 139 (70%) were normocephalic. Individuals with macrocephaly had significantly larger genomic deletions than those with microcephaly or normocephaly (p < 0.0001). A genomic region on 22q13.31 was found to be significantly associated with macrocephaly with CELSR1, GRAMD4, and TBCD122 suggested as candidate genes. Investigation of these genes will aid the understanding of head and brain development.

Evaluation of Policies Limiting Opioid Exposure on Opioid Prescribing and Patient Pain in Opioid-Naive Patients Undergoing Elective Surgery in a Large American Health System.

OBJECTIVES: Overprescribing to opioid-naive surgical patients substantially contributes to opioid use disorders, which have become increasingly prevalent. Opioid stewardship programs (OSPs) within healthcare settings provide an avenue for introducing interventions to regulate prescribing. This study examined the association of OSP policies limiting exposure on changes in surgery-related opioid prescriptions and patient pain. METHODS: We evaluated policies implemented by an OSP in a large American healthcare system between 2016 and 2018: nonopioid medication during surgery, decrease of available opioid dosage vials in operating rooms, standardization of opioid in-patient practices through electronic health record alerts, and limit to postsurgery opioid supply. Generalized linear mixed effects models examined the association of interventions with outcome changes in 9262 opioid-naive patients undergoing elective surgery. Outcomes were discharge pain, morphine milligram equivalent in the first prescription postsurgery, and opioid prescription refills. RESULTS: Decreases in all prescription outcomes and discharge pain were observed following onset of OSP interventions ( P 's < 0.001). Among individual policies, standardization of in-patient prescribing practices was associated with the strongest decrease in prescribed morphine milligram equivalent. Importantly, there was no evidence of an increase in discharge pain related to any intervention. CONCLUSIONS: This study promotes the potential of OSP formation and policies to reduce opioid prescribing without compromising patient pain. The most effective policy, standardization of in-patient prescribing practices through alerts, suggests that reminding prescribers to re-evaluate the patient's need is effective in changing behavior. The findings offer considerations for OSP formation and policy implementation across health systems to improve quality and safety in opioid prescribing.

Health Extension for Diabetes: Impact of a Community-Based Diabetes Self-Management Support Program on Older Adults' Activation.

Objective: The goals of this study were to determine whether completion of a community-based diabetes self-management support (DSMS) program delivered through a university Cooperative Extension network increased Patient Activation Measure (PAM) scores and to examine predictors of improvement in PAM score in individuals participating in the DSMS. Methods: The Health Extension for Diabetes (HED) is a 4-month program delivered via a paraprofessional extension agent in partnership with an established diabetes self-management education and support program. The study population included 148 adults (median age 69 years; interquartile range 60-74 years) with diabetes recruited from local community organizations. Data for the analysis were collected before and after participation in the intervention as part of a longitudinal study, using the PAM and Self-Efficacy for Diabetes instruments. Descriptive statistics were gathered, and hypothesis tests and simple and multivariable regression analyses were conducted. Results: The mean PAM score increased by 6.58 points, with a 5-point change considered clinically significant. From pre- to post-intervention, PAM scores significantly decreased for 23 participants, decreased for 6, did not change for 14, increased for 21, and significantly increased for 84. Higher pre-intervention PAM scores, younger age, greater educational attainment, and higher baseline self-efficacy scores were associated with increased post-intervention PAM scores when not controlling for potential covariates. Age was no longer associated with higher PAM scores after controlling for covariates. Conclusion: Community-based DSMS interventions can be effective in generating positive change in individuals' activation. HED provides a feasible and accessible DSMS option that addresses key diabetes self-management components while effectively improving individuals' activation. It is recommended that people living with diabetes attend a DSMS program such as HED to increase their ability to effectively self-manage various components of their chronic condition.

Covid-19 vaccine effectiveness against general SARS-CoV-2 infection from the omicron variant: A retrospective cohort study.

We aim to estimate the effectiveness of 2-dose and 3-dose mRNA vaccination (BNT162b2 and mRNA-1273) against general Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) infection (asymptomatic or symptomatic) caused by the omicron BA.1 variant. This propensity-score matched retrospective cohort study takes place in a large public university undergoing weekly Coronavirus Disease 2019 (Covid-19) testing in South Carolina, USA. The population consists of 24,145 university students and employees undergoing weekly Covid-19 testing between January 3rd and January 31st, 2022. The analytic sample was constructed via propensity score matching on vaccination status: unvaccinated, completion of 2-dose mRNA series (BNT162b2 or mRNA-1273) within the previous 5 months, and receipt of mRNA booster dose (BNT162b2 or mRNA-1273) within the previous 5 months. The resulting analytic sample consists of 1,944 university students (mean [SD] age, 19.64 [1.42] years, 66.4% female, 81.3% non-Hispanic White) and 658 university employees (mean [SD] age, 43.05 [12.22] years, 64.7% female, 83.3% non-Hispanic White). Booster protection against any SARS-CoV-2 infection was 66.4% among employees (95% CI: 46.1-79.0%; P<.001) and 45.4% among students (95% CI: 30.0-57.4%; P<.001). Compared to the 2-dose mRNA series, estimated increase in protection from the booster dose was 40.8% among employees (P=.024) and 37.7% among students (P=.001). We did not have enough evidence to conclude a statistically significant protective effect of the 2-dose mRNA vaccination series, nor did we have enough evidence to conclude that protection waned in the 5-month period after receipt of the 2nd or 3rd mRNA dose. Furthermore, we did not find evidence that protection varied by manufacturer. We conclude that in adults 18-65 years of age, Covid-19 mRNA booster doses offer moderate protection against general SARS-CoV-2 infection caused by the omicron variant and provide a substantial increase in protection relative to the 2-dose mRNA vaccination series.

Ontologies Applied in Clinical Decision Support System Rules: Systematic Review.

BACKGROUND: Clinical decision support systems (CDSSs) are important for the quality and safety of health care delivery. Although CDSS rules guide CDSS behavior, they are not routinely shared and reused. OBJECTIVE: Ontologies have the potential to promote the reuse of CDSS rules. Therefore, we systematically screened the literature to elaborate on the current status of ontologies applied in CDSS rules, such as rule management, which uses captured CDSS rule usage data and user feedback data to tailor CDSS services to be more accurate, and maintenance, which updates CDSS rules. Through this systematic literature review, we aim to identify the frontiers of ontologies used in CDSS rules. METHODS: The literature search was focused on the intersection of ontologies; clinical decision support; and rules in PubMed, the Association for Computing Machinery (ACM) Digital Library, and the Nursing & Allied Health Database. Grounded theory and PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) 2020 guidelines were followed. One author initiated the screening and literature review, while 2 authors validated the processes and results independently. The inclusion and exclusion criteria were developed and refined iteratively. RESULTS: CDSSs were primarily used to manage chronic conditions, alerts for medication prescriptions, reminders for immunizations and preventive services, diagnoses, and treatment recommendations among 81 included publications. The CDSS rules were presented in Semantic Web Rule Language, Jess, or Jena formats. Despite the fact that ontologies have been used to provide medical knowledge, CDSS rules, and terminologies, they have not been used in CDSS rule management or to facilitate the reuse of CDSS rules. CONCLUSIONS: Ontologies have been used to organize and represent medical knowledge, controlled vocabularies, and the content of CDSS rules. So far, there has been little reuse of CDSS rules. More work is needed to improve the reusability and interoperability of CDSS rules. This review identified and described the ontologies that, despite their limitations, enable Semantic Web technologies and their applications in CDSS rules.

Interventional Radiologists Achieve Equivalent Outcomes and Lower Costs for Totally Implantable Venous Access Device Placement Compared to Operating Room Placement.

PURPOSE: To compare the cost and outcomes of surgical and interventional radiology (IR) placement of totally implantable venous access devices (TIVADs) within a large regional health system to determine the service line with better outcomes and lower costs to the health system. MATERIALS AND METHODS: A retrospective review of all chest port placements performed in the operating room (OR) and IR suite over 12 months was conducted at a large, integrated health system with 6 major hospitals. Secondary electronic health record and cost data were used to identify TIVAD placements, follow-up procedures indicating port malfunction, early adverse events (within 1 month after the surgery), late adverse events (2-12 months after the procedure), and health system cost of TIVAD placement and management. RESULTS: For 799 total port placements included in this analysis, the rate of major adverse events was 1.3% and 1.9% for the IR and OR groups, respectively, during the early follow-up (P = .5655) and 4.9% and 2.8% for the IR and OR groups, respectively, during the late follow-up (P = .5437). Malfunction-related follow-up procedure rates were 1.8% and 2.6% for the IR and OR groups, respectively, during the early follow-up (P = .4787) and 12.4% and 10.5% for the IR and OR groups, respectively, during the late follow-up (P = .4354). The mean cost of port placement per patient was $4,509 and $5,247 for the IR and OR groups, respectively. The difference in per-patient cost of port placement was $1,170 greater for the OR group (P = .0074). CONCLUSIONS: The similar rates of adverse events and follow-up procedures and significant differences in insertion cost suggest that IR TIVAD placement may be more cost effective than surgical placement without affecting the quality.

Effectiveness and protection duration of Covid-19 vaccines and previous infection against any SARS-CoV-2 infection in young adults.

Data on effectiveness and protection duration of Covid-19 vaccines and previous infection against general SARS-CoV-2 infection in general populations are limited. Here we evaluate protection from Covid-19 vaccination (primary series) and previous infection in 21,261 university students undergoing repeated surveillance testing between 8/8/2021-12/04/2021, during which B.1.617 (delta) was the dominant SARS-CoV-2 variant. Estimated mRNA-1273, BNT162b2, and AD26.COV2.S effectiveness against any SARS-CoV-2 infection is 75.4% (95% CI: 70.5-79.5), 65.7% (95% CI: 61.1-69.8), and 42.8% (95% CI: 26.1-55.8), respectively. Among previously infected individuals, protection is 72.9% when unvaccinated (95% CI: 66.1-78.4) and increased by 22.1% with full vaccination (95% CI: 15.8-28.7). Statistically significant decline in protection is observed for mRNA-1273 (P < .001), BNT162b2 (P < .001), but not Ad26.CoV2.S (P = 0.40) or previous infection (P = 0.12). mRNA vaccine protection dropped 29.7% (95% CI: 17.9-41.6) six months post- vaccination, from 83.2% to 53.5%. We conclude that the 2-dose mRNA vaccine series initially offers strong protection against general SARS-CoV-2 infection caused by the delta variant in young adults, but protection substantially decreases over time. These findings indicate that vaccinated individuals may still contribute to community spread. While previous SARS-CoV-2 infection consistently provides moderately strong protection against repeat infection from delta, vaccination yields a substantial increase in protection.

SARS-CoV-2 variants of concern Alpha and Delta show increased viral load in saliva.

BACKGROUND: Higher viral loads in SARS-CoV-2 infections may be linked to more rapid spread of emerging variants of concern (VOC). Rapid detection and isolation of cases with highest viral loads, even in pre- or asymptomatic individuals, is essential for the mitigation of community outbreaks. METHODS AND FINDINGS: In this study, we analyze Ct values from 1297 SARS-CoV-2 positive patient saliva samples collected at the Clemson University testing lab in upstate South Carolina. Samples were identified as positive using RT-qPCR, and clade information was determined via whole genome sequencing at nearby commercial labs. We also obtained patient-reported information on symptoms and exposures at the time of testing. The lowest Ct values were observed among those infected with Delta (median: 22.61, IQR: 16.72-28.51), followed by Alpha (23.93, 18.36-28.49), Gamma (24.74, 18.84-30.64), and the more historic clade 20G (25.21, 20.50-29.916). There was a statistically significant difference in Ct value between Delta and all other clades (all p.adj<0.01), as well as between Alpha and 20G (p.adj<0.05). Additionally, pre- or asymptomatic patients (n = 1093) showed the same statistical differences between Delta and all other clades (all p.adj<0.01); however, symptomatic patients (n = 167) did not show any significant differences between clades. Our weekly testing strategy ensures that cases are caught earlier in the infection cycle, often before symptoms are present, reducing this sample size in our population. CONCLUSIONS: COVID-19 variants Alpha and Delta have substantially higher viral loads in saliva compared to more historic clades. This trend is especially observed in individuals who are pre- or asymptomatic, which provides evidence supporting higher transmissibility and more rapid spread of emerging variants. Understanding the viral load of variants spreading within a community can inform public policy and clinical decision making.

Predictive value of clinical symptoms for COVID-19 diagnosis in young adults.

Objective: Assessment of predictive values of clinical symptoms for COVID-19 diagnosis in young adults. Participants: Nonresidential university students (ages 18-25) participating in surveillance testing and mandatory symptom survey between 9/9/2020 and 11/25/2020. Methods: Retrospective study of test results and symptom survey data. Results: Among 6,489 individuals, 288 (4.4%) tested positive for COVID-19, 90 (31.3%) of whom reported symptoms. COVID-19 prevalence among individuals reporting and not reporting symptoms was 17.2% and 3.3%, respectively. The four symptoms with highest positive predictive values (PPVs) were smell/taste loss (PPV = 38.5%), chills (PPV = 31.5%), muscle/joint pain (PPV = 26.0%), and fever (PPV = 25.9%). Conclusions: Institutions should emphasize COVID-19 risk for highly predictive symptoms in public health messaging to inform individuals on when to seek testing or self-isolation. However, low COVID-19 diagnostic accuracy of clinical symptoms and the high pre-symptomatic/asymptomatic rate (69%) highlight the limitations of voluntary testing strategies employed by higher education institutions during the original strain of SARS-CoV-2.

A Systematic Approach to Configuring MetaMap for Optimal Performance.

BACKGROUND: MetaMap is a valuable tool for processing biomedical texts to identify concepts. Although MetaMap is highly configurative, configuration decisions are not straightforward. OBJECTIVE: To develop a systematic, data-driven methodology for configuring MetaMap for optimal performance. METHODS: MetaMap, the word2vec model, and the phrase model were used to build a pipeline. For unsupervised training, the phrase and word2vec models used abstracts related to clinical decision support as input. During testing, MetaMap was configured with the default option, one behavior option, and two behavior options. For each configuration, cosine and soft cosine similarity scores between identified entities and gold-standard terms were computed for 40 annotated abstracts (422 sentences). The similarity scores were used to calculate and compare the overall percentages of exact matches, similar matches, and missing gold-standard terms among the abstracts for each configuration. The results were manually spot-checked. The precision, recall, and F-measure (ß =1) were calculated. RESULTS: The percentages of exact matches and missing gold-standard terms were 0.6-0.79 and 0.09-0.3 for one behavior option, and 0.56-0.8 and 0.09-0.3 for two behavior options, respectively. The percentages of exact matches and missing terms for soft cosine similarity scores exceeded those for cosine similarity scores. The average precision, recall, and F-measure were 0.59, 0.82, and 0.68 for exact matches, and 1.00, 0.53, and 0.69 for missing terms, respectively. CONCLUSION: We demonstrated a systematic approach that provides objective and accurate evidence guiding MetaMap configurations for optimizing performance. Combining objective evidence and the current practice of using principles, experience, and intuitions outperforms a single strategy in MetaMap configurations. Our methodology, reference codes, measurements, results, and workflow are valuable references for optimizing and configuring MetaMap.

Implementation of a Rural Community Diagnostic Testing Strategy for SARS-CoV-2 in Upstate South Carolina.

By developing a partnership amongst a public university lab, local city government officials and community healthcare providers, we established a drive-through COVID-19 testing site aiming to improve access to SARS-CoV-2 testing in rural Upstate South Carolina. We collected information on symptoms and known exposures of individuals seeking testing to determine the number of pre- or asymptomatic individuals. We completed 71,102 SARS-CoV-2 tests in the community between December 2020-December 2021 and reported 91.49% of results within 24 h. We successfully identified 5,244 positive tests; 73.36% of these tests originated from individuals who did not report symptoms. Finally, we identified high transmission levels during two major surges and compared test positivity rates of the local and regional communities. Importantly, the local community had significantly lower test positivity rates than the regional community throughout 2021 (p < 0.001). While both communities reached peak case load and test positivity near the same time, the local community returned to moderate transmission as indicated by positivity 4 weeks before the regional community. Our university lab facilitated easy testing with fast turnaround times, which encouraged voluntary testing and helped identify a large number of non-symptomatic cases. Finding the balance of simplicity, accessibility, and community trust was vital to the success of our widespread community testing program for SARS-CoV-2.

Parent/Guardian Experiences With the Healthcare System and Community Supports for Pediatric Asthma Management.

Determinants of pediatric asthma management include child, family, healthcare, and community factors. The purpose of this study is to investigate how parents/guardians are impacted by and act on these factors to aid in their child's asthma self-management. Interviews were conducted in Fall 2020 with 12 female parents/guardians of Black/African American children who participated in a community paramedic pilot study with their child in South Carolina. Children in the initial study had an asthma diagnosis of moderate persistent asthma, had Medicaid insurance, and were determined high-risk for emergency room presentation. Inductive and deductive qualitative analysis identified that child management self-efficacy and independence, parent/guardian health literacy, parent and child negative experiences related to asthma diagnosis and management, asthma management tools, and social support from multiple sources impact child self-management. Findings from this study highlight the importance of clear asthma education and management tool recommendations from healthcare and community providers, particularly for parents/guardians with low health literacy. Health literacy impacted parental responses and likely how families comprehend Medicaid and clinical asthma guidance.