Grant List
Represents Grant table in the DB
GET /v1/grants?page%5Bnumber%5D=1385&sort=-funder_divisions
{ "links": { "first": "https://cic-apps.datascience.columbia.edu/v1/grants?page%5Bnumber%5D=1&sort=-funder_divisions", "last": "https://cic-apps.datascience.columbia.edu/v1/grants?page%5Bnumber%5D=1397&sort=-funder_divisions", "next": "https://cic-apps.datascience.columbia.edu/v1/grants?page%5Bnumber%5D=1386&sort=-funder_divisions", "prev": "https://cic-apps.datascience.columbia.edu/v1/grants?page%5Bnumber%5D=1384&sort=-funder_divisions" }, "data": [ { "type": "Grant", "id": "10553", "attributes": { "award_id": "1U01IP001189-01", "title": "Component A _ Credible Effectiveness Measures of Seasonal Influenza, COVID-19 and Other Respiratory Virus Vaccines against Ambulatory Care for Acute Illness in Texas (and Component D).", "funder": { "id": 4, "ror": "https://ror.org/01cwqze88", "name": "National Institutes of Health", "approved": true }, "funder_divisions": [], "program_reference_codes": [], "program_officials": [], "start_date": "2022-09-30", "end_date": "2027-09-29", "award_amount": 2000000, "principal_investigator": { "id": 26566, "first_name": "Manjusha", "last_name": "Gaglani", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] }, "other_investigators": [], "awardee_organization": { "id": 1944, "ror": "", "name": "BAYLOR RESEARCH INSTITUTE", "address": "", "city": "", "state": "TX", "zip": "", "country": "United States", "approved": true }, "abstract": "COMPONENT A - PROJECT SUMMARY/ABSTRACT: Influenza (Flu) viruses are constantly evolving, requiring vaccines to be reformulated every season. New SARS- CoV-2 (SC2) variants have caused recurrent Coronavirus Infectious Disease – 2019 (COVID) surges in different regions of the United States through the winter of 2021-22. Estimating ongoing real-world Flu and COVID vaccine effectiveness (VE) against ambulatory care for acute illness (ACAI) are essential in evaluating the protection provided by nationwide vaccination programs and for monitoring the duration of protection afforded by respective vaccines each of which are high priorities for fulfilling the CDC’s mission of serving as the nation’s health protection agency. Our long-term research goal is to advance the understanding of the epidemiology and prevention of respiratory virus (RV) infections (i.e., seasonal and pandemic influenza, SC2 and Other Respiratory Viruses (ORVs) such as Respiratory Syncytial Virus [RSV]) while reducing the burden of disease and improving the health of the population. We plan to systematically evaluate the VE against ACAI associated with lab-confirmed influenza, COVID and vaccine-preventable ORVs with respective CDC recommended vaccinations in the Baylor Scott & White Health, Central Texas (BSWCTX) enrollment eligible population. The objective is to obtain reliable vaccination information and to provide accurate interim and annual estimates of VE to prevent ACAI in respective RV vaccine age-eligible population. Our central hypothesis is that timely and accurate measurement of VE and burden of illness due to vaccine preventable RVs is sustainable. The rationale is that by assessing the interim and annual VE against vaccine preventable RVs, the CDC ACIP can modify recommendations for receiving the vaccines and booster doses as well as use of appropriate antiviral agents. The specific aims are to: 1) Measure effectiveness of seasonal and pandemic Flu, COVID and vaccine-preventable ORV vaccines against ACAI for respective lab-confirmed mild to moderate infection in at least 1,000 children and adults from the 2022-23 to 2026-27 seasons. 2) Monitor ongoing Flu and SC2 viral evolution by genomic sequencing among at least 1,000 enrolled children and adults from the 2022-23 to 2026-27 seasons. 3) Perform potentially year-round SC2 surveillance during periods when Flu viruses are not circulating to measure current COVID VE against ACAI for lab-confirmed mild to moderate SC2 infection in children and adults from the 2022-23 to 2026-27 seasons. To accomplish these aims, we will estimate real-time VE in the ambulatory setting using a test-negative design, estimate burden of illness of vaccine preventable RVs in the BSWCTX burden subset, and examine factors affecting VE. The proposed research is innovative as we have adapted methods to include verified vaccinations and accurate lab diagnosis of RV infections with one or both influenza and SC2 in participants who are systematically screened for eligibility and enrolled using a well-defined ACAI case-definition in our approach, enabling us to aptly measure VE and burden of illness of influenza, COVID, and ORVs in the West South Central United States.", "keywords": [], "approved": true } }, { "type": "Grant", "id": "10571", "attributes": { "award_id": "1U01IP001182-01", "title": "RFA-IP-22-004, Multidisciplinary Approach to Understanding Vaccine Efficacy and Transmission of Viral Respiratory Tract Infections in the Real World", "funder": { "id": 4, "ror": "https://ror.org/01cwqze88", "name": "National Institutes of Health", "approved": true }, "funder_divisions": [], "program_reference_codes": [], "program_officials": [], "start_date": "2022-09-30", "end_date": "2027-09-29", "award_amount": 2483947, "principal_investigator": { "id": 26592, "first_name": "Stacey", "last_name": "House", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] }, "other_investigators": [], "awardee_organization": { "id": 827, "ror": "", "name": "WASHINGTON UNIVERSITY", "address": "", "city": "", "state": "MO", "zip": "", "country": "United States", "approved": true }, "abstract": "– COMPONENT A Influenza and SARS-CoV-2 are major causes of morbidity and mortality and constitute the leading causes of vaccine preventable deaths in the United States. A better understanding of vaccine effectiveness for these viral pathogens is critical to drive public health decisions and interventions. We propose utilizing a multidisciplinary approach to conduct a test-negative study to determine influenza and SARS-CoV-2 vaccine effectiveness in ambulatory patients with respiratory tract infections. The team of investigators includes experts in emergency medicine, infectious disease, pediatrics, epidemiology, information technology, molecular microbiology, virology, and genetics. This team has extensive experience in automated electronic medical record alerts, high-volume subject recruitment of ambulatory patients with respiratory tract infections, rapid escalation/de-escalation of recruitment efforts to match viral circulation patterns, respiratory and blood sample processing and shipment, quality data collection and verification, and viral genomic sequencing necessary to ensure the success of this project. The proposed study will encompass the following specific aims: 1)Utilize innovative automated alerting strategies to identify and recruit a diverse population of ambulatory patients with acute respiratory illnesses; 2) Estimate influenza and SARS-CoV-2 vaccine effectiveness using a test- negative study design in the general population as well as different demographic subgroups.; 3) Explore factors that influence influenza and SARS-CoV-2 vaccine effectiveness such as co-morbidities, vaccination type and schedule, and social determinants of health; 4) Determine effect of viral vaccination status on health outcomes in ambulatory patients with influenza and SARS-CoV-2 infection; 5) Contribute biospecimens and viral genomic sequencing data to a national repository of subjects with PCR-confirmed influenza or SARS-CoV-2 infection. To accomplish these goals, we will enroll at least 1000 ambulatory patients/year with acute respiratory tract infections in the proposed study. The subject population will be identified from the emergency departments of 3 large hospitals in the St. Louis area and their associated outpatient clinics. The available patient population at these enrolling sites is diverse with respect to race, ethnicity, age, socioeconomic status, and medical care access which will enhance the generalizability of the study outcomes to the US population.", "keywords": [], "approved": true } }, { "type": "Grant", "id": "10575", "attributes": { "award_id": "1R43GH002389-01A1", "title": "Rapid COVID-19 Mutation Discrimination Test for Global SARS-CoV-2 Variant Surveillance", "funder": { "id": 4, "ror": "https://ror.org/01cwqze88", "name": "National Institutes of Health", "approved": true }, "funder_divisions": [], "program_reference_codes": [], "program_officials": [], "start_date": "2022-09-30", "end_date": "2023-03-31", "award_amount": 275766, "principal_investigator": { "id": 26597, "first_name": "Janet L", "last_name": "Huie", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] }, "other_investigators": [], "awardee_organization": { "id": 1947, "ror": "", "name": "JAN BIOTECH, INC.", "address": "", "city": "", "state": "NY", "zip": "", "country": "United States", "approved": true }, "abstract": "Public Health Problem. Covid-19 variant tracking and prevalence is greatly hindered by the lack of quick, high- throughput methods for variant detection. Covid-19 genetic variants are a current and ongoing concern, due to greater transmissibility, morbidity and potential resistance to immunity provided by vaccines. Successful surveillance will likely require full coverage: 100% of people tested (not an extrapolation of sparse or region- specific data). Jan Biotech’s proposed assay quickly detects both known variants and new variants (by detecting unknown sequences through negative results and indicating the need for sequencing) and the probes are easily adapted to detect newly emerging variants of concern and interest. The assay will allow remote and low resource area hospitals and medical centers to quickly and fully assess their community’s SARS-CoV-2 variant index for real-time, evidence-based health mandates. This is both an urgent and very likely a long term need as new variants emerge. Issues with Current Solutions & How Product Meets Unmet Needs. RT-PCR Covid-19 tests provide only a positive or negative result and do not identify genetic variants. Rapid antibody tests for Covid-19 also do not reveal variants. DNA Sequencing of the Covid-19 genome is challenging. The genome is almost 30,000 nucleotides in length and combinations of mutations in different areas of the genome are functional and identifying features of Covid-19 variants. High-throughput RNAseq methods for next-generation sequencing (NGS) require RNA purification, RT-PCR RNAseq library preparation and time-consumptive sequencing and genome assembly. Covid-19 sequencing in any format for identification of variants has not yet been CLIA- or FDA-approved. RT-qPCR assays mined for variant data rely on altered Ct curves, which are nonspecific and can be caused by variations in the assay run. The proposed rapid Covid-19 variant detection and discrimination test, performed in a multiwell plate, is variant-specific and high-throughput. Summary of Approach. We will create RNAamp oligonucleotide-templated photoreduction probe sets specific to the current most prevalent and clinically-significant Covid-19 RNA variants. We will multiplex the Covid-19 variant discrimination RNAamp tests, using different profluorophores for each target and evaluate sensitivity and reliability of multiplex results using negative human saliva samples spiked with multiple Covid-19 variant RNAs. Human samples will be used to assess commercial potential of the multiplexed Covid-19 variant RNAamp test. Covid-19 negative samples will serve as negative controls and the same negative samples spiked with Covid- 19 variant control RNAs will serve as positive controls for each variant test to achieve a statistical correlation of >0.9 with comparison assays as the metric of success. Collaborators and Unique Resources. Jan Biotech, Inc., with expertise in molecular diagnostic development, will obtain human Covid-19 positive and negative test samples from the University of Rochester Medical Center, and, as needed, from Precision for Medicine and BocaBiolistics. Specific Aims Specific Aim 1: Develop multiplexed variant discrimination RNAamp test for Covid-19 strain detection Objective 1.1: Develop and test RNAamp probe sets to differentiate Covid-19 variants of concern. Objective 1.2: Multiplex and test the Covid-19 variant discrimination RNAamp tests. Specific Aim 2: Evaluate variant discrimination RNAamp test on Covid-19 human samples Objective 2.1: Test human samples to assess commercial potential of multiplexed Covid-19 variant RNAamp. Objective 2.2: Statistical determination of assay limit of detection and specificity for each Covid-19 variant will evaluate the utility of the rapid Covid-19 variant discrimination test, including its application to pooled samples. The end result of the project will be a multiplexed Covid-19 variant discrimination test and computational software providing proof-of-concept for Phase II preclinical and clinical evaluation leading towards CLIA or 510(k) approval, clinical trials and commercialization.", "keywords": [], "approved": true } }, { "type": "Grant", "id": "10580", "attributes": { "award_id": "2R01FD006071-03", "title": "Establishing Biomarkers and Clinical Endpoints in Myotonic Dystrophy Type-1 (Renewal)", "funder": { "id": 4, "ror": "https://ror.org/01cwqze88", "name": "National Institutes of Health", "approved": true }, "funder_divisions": [], "program_reference_codes": [], "program_officials": [ { "id": 26600, "first_name": "Katherine", "last_name": "Needleman", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] } ], "start_date": "2022-09-15", "end_date": "2026-08-31", "award_amount": 386995, "principal_investigator": { "id": 26601, "first_name": "Nicholas Elwood", "last_name": "Johnson", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] }, "other_investigators": [ { "id": 26602, "first_name": "CHARLES A", "last_name": "THORNTON", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] } ], "awardee_organization": { "id": 672, "ror": "https://ror.org/02nkdxk79", "name": "Virginia Commonwealth University", "address": "", "city": "", "state": "VA", "zip": "", "country": "United States", "approved": true }, "abstract": "Myotonic dystrophy type-1 (DM1) is the most common form of muscular dystrophy in adults. The genetic basis is an expansion of CTG repeats in the non-coding region of DMPK, the gene encoding DM protein kinase. Individuals with myotonic dystrophy develop progressive muscle weakness, early cataracts, cardiac arrhythmias, and other symptoms. The disease mechanism involves a deleterious gain-of-function by the mutant DMPK mRNA, a process first described in DM1, known as RNA toxicity. RNA binding proteins become trapped on repetitive RNA, causing loss of splicing regulatory functions. Splicing changes contribute to DM1 symptoms and also may serve as biomarkers of disease severity. The discovery that DM1 is instigated by toxicity of one RNA species and characterized by misregulated splicing of other RNAs has furnished good therapeutic targets and candidate biomarkers. Several therapeutic approaches are under development and two are in early phase clinical trials. However, the design and conduct of clinical trials is limited by disease heterogeneity, scarcity of natural history data, and the lack of proven clinical endpoints or biomarkers of drug impact. We have begun a natural history study to define clinical endpoints, biomarkers, and patient characteristics for clinical trials. This study, END-DM1, has enrolled 277 participants but early progress was hampered by the COVID-19 pandemic. The current renewal application seeks to complete the study of clinical outcome assessments (Aim 1) and biomarkers (Aim 2) in DM1. We will complete enrollment of 700 adults with DM1 at 16 sites of the Myotonic Dystrophy Clinical Research Network with return visits at 12 and 24 months. Based on preliminary data, we selected a concise set of clinical measures showing acceptable reliability and responsivity to disease progression. The proposed study is designed to establish minimal clinically important differences for different measures in this population, identify baseline characteristics that predict future progression, and provide a rational basis for stratification, selection of sample size, or enrichment in future trials. Aim 2 will build on our previous efforts to develop RNA splicing biomarkers of DM1 severity and therapeutic response. This Aim is focused on tissue biomarkers that provide direct evidence of target engagement in skeletal muscle. We will assess a panel of DM1-affected splice events using a novel method that involves targeted high-throughput sequencing. Completion of this study is the logical next step to lay the groundwork for effective clinical trials in DM1, and keep pace with the rapidly expanding preclinical efforts to develop an effective drug treatment.", "keywords": [], "approved": true } }, { "type": "Grant", "id": "10583", "attributes": { "award_id": "1U01CK000675-01", "title": "TRANSMIT: Training Research Acumen iN Students Modeling Infectious Threats", "funder": { "id": 4, "ror": "https://ror.org/01cwqze88", "name": "National Institutes of Health", "approved": true }, "funder_divisions": [], "program_reference_codes": [], "program_officials": [], "start_date": "2022-09-30", "end_date": "2025-09-29", "award_amount": 297120, "principal_investigator": { "id": 26605, "first_name": "Frederick R.", "last_name": "Adler", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] }, "other_investigators": [ { "id": 26606, "first_name": "Lindsay T.", "last_name": "Keegan", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] }, { "id": 26607, "first_name": "DAMON", "last_name": "TOTH", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] }, { "id": 26608, "first_name": "YUE", "last_name": "ZHANG", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] } ], "awardee_organization": { "id": 202, "ror": "https://ror.org/03r0ha626", "name": "University of Utah", "address": "", "city": "", "state": "UT", "zip": "", "country": "United States", "approved": true }, "abstract": "The ongoing COVID-19 pandemic has overwhelmed healthcare and public health systems, underscoring the need to anticipate disease outbreaks and prepare resources such as hospital beds and staff. One cost-effective and timely way to prepare resources to respond to these outbreaks is through the use of mathematical modeling. Models can act as a virtual laboratory to explore a variety of scenarios, interventions, or applications in a timely manner to inform policy interventions. While the COVID-19 pandemic highlighted the gaps that models can fill, it also highlighted a considerable gap in modeling: there is a lack of modeling professionals trained in developing and applying transmission models to healthcare settings. In this proposal, we detail three projects aimed to train three predoctoral fellows in different aspects of mathematical modeling of healthcare associated pathogens. These projects tackle different pathogens and components of disease transmission in a healthcare setting; and, while each project is distinct, they dovetail nicely, resulting in a cohesive research program. Project 1 tackles a critical component of disease transmission in healthcare settings: COVID-19 in long-term care facilities (LTCFs). Throughout the pandemic, LTCFs bore a disproportionate burden of mortality. Yet, while it is clear that LTCFs important with regards to disease outcomes, whether or not they exert selective forces on SARS-CoV-2 that have shaped global patterns of pathogen evolution is not yet known. Here, we will develop models to quantify the phylogenetic relationships between community and long-term care facility lineages to understand the viral diversification attributable to healthcare settings. Project 2 explores the risk factors of patients hospitalized with SARS-CoV-2 for acquiring multi-drug resistant organisms (MDROs). The rapid spread of SARS-CoV-2 has changed to hospital infection control and antimicrobial stewardship policies. One such change has been widespread potentially unnecessary antibiotic use among hospitalized patients. Here, we will identify the characteristics of the sub-population disproportionately impacted by co-infections with MDROs for patients hospitalized with SARS- CoV-2. Project 3 integrates with both Project 1 and 2, to explore the evolution of antibiotic resistance due to variable dose and off-target antibiotic use in healthcare settings. Patients in hospitals and residents of LTCFs are exposed to a wide range of pathogens and treatments, and many of these organisms have themselves been exposed to a wide range of environmental antibiotics. Here, we will develop models of evolution to investigate the conditions that lead to the most intractable infections.", "keywords": [], "approved": true } }, { "type": "Grant", "id": "10584", "attributes": { "award_id": "1R43GH002391-01A1", "title": "Development of rapid, low-cost, and high throughput COVID-19 antibody assays", "funder": { "id": 4, "ror": "https://ror.org/01cwqze88", "name": "National Institutes of Health", "approved": true }, "funder_divisions": [], "program_reference_codes": [], "program_officials": [], "start_date": "2022-09-30", "end_date": "2023-03-29", "award_amount": 256131, "principal_investigator": { "id": 26609, "first_name": "Maung K", "last_name": "Khaing Oo", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] }, "other_investigators": [], "awardee_organization": { "id": 1948, "ror": "", "name": "OPTOFLUIDIC BIOASSAY LLC", "address": "", "city": "", "state": "MI", "zip": "", "country": "United States", "approved": true }, "abstract": "Millions have developed COVID-19 antibodies through infection or vaccines, and this number will continue to increase. However, antibodies (via infection or vaccines) decay rapidly and vary among individuals. Previous studies have shown decreased protection efficacy because of reduced antibody levels, which, in combination with muted strains, has led to recent wide spread of Delta variant (and other variants) worldwide. A third dose of vaccine is now recommended by the CDC. Regular monitoring of COVID-19 neutralizing antibodies can identify individuals requiring booster vaccines, inform incidence studies, and guide policies regarding vaccination frequency for the population. Although lateral flow assays can potentially be used for rapid COVID- 19 neutralizing antibody tests, they do not provide an accurate level of neutralizing antibodies and has large variations, making them a poor tool to track and predict susceptibility to future infections. More accurate antibody tests done at centralized labs take 2-3 days to turnaround and have a high cost ($150). OptoBio has developed a general purpose microfluidic 96-well ELISA plate (MicroFluere®) technology that reduces assay time 5-10 fold, reduces sample and reagent consumption 5-6 fold, and increases dynamic range by up to 10 fold as compared to traditional 96-well ELISA plate. The goal of Phase I study is to demonstrate the feasibility of leveraging MicroFluere® to develop an inexpensive (<$10), rapid (20 min), and high throughput (240 tests/hour) assay for COVID-19 neutralizing antibodies of different variants. Currently no product exists that is able to quantify neutralizing antibody at a high throughput and low cost at point-of-care for mass screening. There are two specific aims in Phase 1. Aim #1. Design, test, and optimize neutralizing antibody assays for 6 types of COVID-19 strains. We will first select internal standards for all 6 types of SARS-CoV-2 variants. Then we will optimize the assay parameters such as the plate surface coating, sample dilution factors, and incubation time. Finally, we will evaluate the assay performance such as recovery rate and plate-to-plate repeatability. Aim #2. Validate applicability with human blood samples and benchmark. The assay developed in Aim #1 will be tested at a BSL-2 lab at OptoBio using 75 human serum samples purchased commercially. Five other virus infections will also be included for cross-reactivity evaluation. All the results will be compared with those obtained with SARS-CoV-2 neutralizing antibody kits commercially available. In Phase II, OptoBio will test more samples and add more variants, complete a high throughput automated system, develop pre-coated MicroFluere® plates with adequate shelf lifetime, and develop assays using more convenient matrices such as finger-prick whole blood. Our envisioned product will address the unmet need for rapid, accurate, and low cost COVID-19 antibody detection at clinical labs and point-of-care testing sites. The same product and technology can also be adapted for other viral pandemics that may occur.", "keywords": [], "approved": true } }, { "type": "Grant", "id": "10593", "attributes": { "award_id": "1R01HS028978-01", "title": "Learning from Hospital Preparedness during COVID: Chronically Under-Resourced Nurses and Patient Safety", "funder": { "id": 4, "ror": "https://ror.org/01cwqze88", "name": "National Institutes of Health", "approved": true }, "funder_divisions": [], "program_reference_codes": [], "program_officials": [ { "id": 25171, "first_name": "Monika", "last_name": "Haugstetter", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] } ], "start_date": "2022-09-06", "end_date": "2025-08-31", "award_amount": 399292, "principal_investigator": { "id": 26621, "first_name": "Karen Blanchette", "last_name": "Lasater", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] }, "other_investigators": [], "awardee_organization": { "id": 232, "ror": "https://ror.org/00b30xv10", "name": "University of Pennsylvania", "address": "", "city": "", "state": "PA", "zip": "", "country": "United States", "approved": true }, "abstract": "Learning from Hospital Preparedness during COVID: Chronically Under-Resourced Nurses and Patient Safety This study will evaluate how hospital nurses weathered the COVID-19 public health emergency, whether and to what extent hospital nurse resources (staffing, work environment, Magnet designation) buffered nurses from poor outcomes (such as burnout) during the pandemic and facilitated recovery 3 years after the onset of the COVID emergency, and the extent to which patient outcomes, safety, quality, and value of care indicators paralleled changes in nurse outcomes and hospital nurse resources over the study period. We will accomplish these objectives by leveraging already existing data from over 33,000 hospital nurses in 244 hospitals in New York and Illinois, [Wave 1 data collected just before COVID (Dec 2019-Feb 2020); Wave 2 collected 1 year after COVID onset] and by conducting primary data collection of repeat measures [Wave 3 to be collected 3 years after COVID onset (Oct 2022-Dec 2022)]. Each Wave includes repeated measures of nurse outcomes (e.g., burnout, job dissatisfaction, intent to leave job), hospital nurse resources (staffing, work environment, Magnet), measures of patient safety and quality of care, including items from the AHRQ Patient Safety Culture survey. These cross-sections of data will be linked with contemporaneous (1) patient-level data from CMS MedPAR Medicare to study risk-adjusted patient outcomes among patients hospitalized for common medical, surgical, and COVID diagnoses; (2) Hospital Compare data to evaluate hospital-level measures of patient satisfaction and healthcare value (Medicare spending per beneficiary), (3) American Hospital Association data for considering organizational features of hospitals, and (4) publicly available COVID hospitalization data to account for variation in COVID burden across hospitals. In combination, we will have 3 cross-sections of data from 244 hospitals (with fluctuating nurse and patient populations) just before, 1 year and 3 years after the onset of the COVID emergency. Our analytic approach uses multi-level nested (hierarchically-related) linear and logistic regression models (with interaction terms). The COVID emergency offers a unique opportunity to make a major advance in our scientific understanding of the potentially causal relationships between nurse outcomes and patient outcomes, which have until now largely only been rigorously evaluated in the cross- section. The tremendous shock imposed by the COVID emergency, combined with our propitiously timed data, enable us to evaluate how the pandemic impacted hospital nurses and what hospital factors contribute to a more favorable recovery in the years following the COVID emergency. Together, this evidence will inform high- impact actionable policy and organizational solutions for building and sustaining safe, high value healthcare systems that can endure future public health emergencies and thrive during ordinary times.", "keywords": [], "approved": true } }, { "type": "Grant", "id": "10596", "attributes": { "award_id": "1R01HS028651-01A1", "title": "COVID-19, health systems and vulnerable populations: Policies affecting maternal opioid use during pregnancy", "funder": { "id": 4, "ror": "https://ror.org/01cwqze88", "name": "National Institutes of Health", "approved": true }, "funder_divisions": [], "program_reference_codes": [], "program_officials": [ { "id": 24559, "first_name": "Kamila", "last_name": "Mistry", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] } ], "start_date": "2022-09-30", "end_date": "2025-09-29", "award_amount": 378365, "principal_investigator": { "id": 26625, "first_name": "CYNTHIA H", "last_name": "CHUANG", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] }, "other_investigators": [ { "id": 26626, "first_name": "DOUGLAS L.", "last_name": "LESLIE", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] } ], "awardee_organization": { "id": 1103, "ror": "", "name": "PENNSYLVANIA STATE UNIV HERSHEY MED CTR", "address": "", "city": "", "state": "PA", "zip": "", "country": "United States", "approved": true }, "abstract": "Abstract: The current COVID-19 pandemic creates many challenges for individuals and health care systems in the United States. To make matters worse, the pandemic is occurring in the midst of a public health crisis of opioid use disorder and overdose during pregnancy. Between 2010 and 2017, the incidence of maternal opioid-related diagnoses increased from 3.5 to 8.2 per 1000 hospital live births per year. Maternal opioid use during pregnancy is associated with increased risks of prolonged hospital stay, placental abruption, poor fetal growth, preterm labor, premature delivery, stillbirth, neonatal abstinence syndrome, and maternal death. State responses regarding maternal opioid use during pregnancy prior to the COVID-19 pandemic have varied widely and included: 1) creation of funded drug-treatment programs specifically for pregnant women, 2) priority access to state-funded treatment programs, 3) mandated reporting and drug screening by healthcare professionals, and 4) criminalization of opioid use during pregnancy or grounds for commitment. However, these policies are unlikely to remain static, especially during the current COVID-19 pandemic. The need for social distancing has led to policy changes related to treatment of opioid use disorder more generally, such as easing methadone dispensing rules and making it easier for patients to initiate buprenorphine treatment from an opioid treatment center. These changes are not mandatory, however, and system-level gains in access to medication assisted treatment (MAT) may be eliminated as the pandemic subsides. In addition, little is known about the extent to which policies related to maternal opioid use during pregnancy are changing during the COVID-19 pandemic, or the extent to which such changes affect maternal and child healthcare treatment, outcomes and costs. Thus, the aims of this study are to 1) examine how state policies related to maternal opioid use during pregnancy have changed in response to the COVID-19 pandemic, and 2) examine the effects of COVID-19-related changes in state policies regarding maternal opioid use on patterns of healthcare service use, maternal and child outcomes, and healthcare costs. By thoroughly examining the policy responses to the COVID-19 pandemic and linking these data to detailed claims data describing healthcare service use of women who use opioids during pregnancy and their newborns, we will be able to provide critical data to providers, insurers, health systems, and policymakers as they design treatment processes and policies to provide adequate pregnancy and substance use care to this vulnerable population to mitigate these two public health crises.", "keywords": [], "approved": true } }, { "type": "Grant", "id": "10602", "attributes": { "award_id": "1U01DP006698-01", "title": "Georgians Organized Against Lupus: The GOAL of Better Understanding Social Determinants of Health in Lupus", "funder": { "id": 4, "ror": "https://ror.org/01cwqze88", "name": "National Institutes of Health", "approved": true }, "funder_divisions": [], "program_reference_codes": [], "program_officials": [ { "id": 26642, "first_name": "Sue", "last_name": "Shaw", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] } ], "start_date": "2022-09-30", "end_date": "2027-09-29", "award_amount": 900000, "principal_investigator": { "id": 26643, "first_name": "SUNG Sam", "last_name": "LIM", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] }, "other_investigators": [], "awardee_organization": { "id": 265, "ror": "https://ror.org/03czfpz43", "name": "Emory University", "address": "", "city": "", "state": "GA", "zip": "", "country": "United States", "approved": true }, "abstract": "Limitations in the ability to assemble large population-based cohorts of patients with systemic and/or cutaneous lupus with validated diagnoses and with significant representation from previously underrepresented sociodemographic groups have been a significant barrier to better understanding the true clinical burden of lupus, as well as the many unanswered questions related to the natural history, treatment, and health care access and gaps. The Georgia Lupus Registry (GLR) is one of five completed Centers for Disease Control and Prevention–funded population-based lupus registries designed to minimize many of these limitations. The Georgians Organized Against Lupus (GOAL) Cohort was born out of the efforts of the GLR to create a population-based prospective cohort of validated and consented systemic lupus (SLE) and primary cutaneous lupus erythematosus (P-CLE) patients, reflecting “real world” lupus in the community in and around Atlanta, Georgia. The GOAL Cohort has followed 1135 consented participants: over 1,000 with SLE and over 135 with P-CLE. Our proposal will utilize this unique and powerful population-based lupus cohort that has been successfully followed over time to collect individual and geographic-based information in areas not previously possible. Specifically, we propose we propose three projects: Project 1 will continue to explore important and innovative components of social determinants of health (SDH) in those with systemic and cutaneous lupus erythematosus (SLE, P-CLE) and will specifically explore the role of SDH as predictors of work loss, end stage kidney disease, and mortality in people with SLE. Project 2 will explore the burden and impact of the Covid-19 pandemic in people with SLE and P-CLE on a population level for the first time in the U.S. Project 3 will, also for the first time, establish incidence and prevalence rate estimates and evaluate outcomes in SLE and P-CLE in a rural population with large numbers of African Americans.", "keywords": [], "approved": true } }, { "type": "Grant", "id": "10603", "attributes": { "award_id": "1R01HS029152-01", "title": "Comparing Family Decision Making Engagement in Telehealth versus In-person Primary Care for Children with Chronic Conditions", "funder": { "id": 4, "ror": "https://ror.org/01cwqze88", "name": "National Institutes of Health", "approved": true }, "funder_divisions": [], "program_reference_codes": [], "program_officials": [ { "id": 26644, "first_name": "Maya", "last_name": "Gerstein", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] } ], "start_date": "2022-09-30", "end_date": "2025-09-29", "award_amount": 399999, "principal_investigator": { "id": 26645, "first_name": "Ellen A", "last_name": "Lipstein", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] }, "other_investigators": [], "awardee_organization": { "id": 897, "ror": "", "name": "CINCINNATI CHILDRENS HOSP MED CTR", "address": "", "city": "", "state": "OH", "zip": "", "country": "United States", "approved": true }, "abstract": "The COVID-19 pandemic led to unprecedented changes to healthcare delivery during the spring of 2020, including the rapid and wide implementation of telehealth. This expansion included areas in which telehealth had not previously been broadly applied, such as pediatric primary care. By its very nature, telehealth changes the communication and structure of the healthcare interaction, perhaps especially in pediatrics where both the parent and patient need to be engaged in the visit. Such changes may directly affect shared decision making, an essential component of high-quality care and a strategy to improve outcomes. Children with asthma and attention deficit hyperactivity disorder, the most common chronic conditions in pediatric primary care, are especially vulnerable to changes in health care delivery. These conditions are highly prevalent among urban, underserved children and while some barriers to care are alleviated by telehealth new ones may emerge. Understanding the impact of telehealth on an underserved, inner-city, primary care population is critical to prevent worsening disparities. Our long-term goal is to improve pediatric primary care by ensuring delivery of chronic disease care that meets families’ goals and improves children’s health and well-being. The overall objective of this proposal is to compare the decision-making processes and outcomes between telehealth and in-person pediatric primary care for children with chronic conditions. This proposal consists of three distinct aims that build upon one another by triangulating perceived and observed decision-making, parents’ and adolescent patients’ perceptions, and quantitative and qualitative data to achieve breadth and depth of understanding about shared decision making in pediatric primary care. In Aims 1 and 2 we will evaluate the quality of pediatric primary care delivered via telehealth compared to in-person care. Aim 1 will use rigorous survey methods to understand families’ perceptions of decision making that occurs during either a telehealth or in-person pediatric primary care visit. This will be coupled with chart review to understand the contribution of telehealth or in-person care to clinical outcomes. Aim 2 will build upon the first by video-recording healthcare visits so the extent of observed shared decision making can be assessed both quantitatively and qualitatively. Finally, in aim 3 we will use qualitative interviews to “feed forward” the data from aims 1 and 2 to parents, adolescents and healthcare providers to gain a more in-depth understanding regarding experiences of decision making in telehealth compared to in-person care. The expected outcome of this proposal is an understanding of the impact of telehealth delivery in pediatric primary care on decision making processes for children with chronic conditions. These results will have a positive impact on care delivery by facilitating the development of targeted approaches to supporting shared decision making as healthcare systems continue evolve and integrate telehealth.", "keywords": [], "approved": true } } ], "meta": { "pagination": { "page": 1385, "pages": 1397, "count": 13961 } } }