Patient-perceived barriers to early initiation of prenatal care at a large, urban federally qualified health center: a mixed-methods study.

BACKGROUND: Early initiation of prenatal care is widely accepted to improve the health outcomes of pregnancy for both mothers and their infants. Identification of the various barriers to entry into care that patients experience may inform and improve health care provision and, in turn, improve the patient's ability to receive necessary care. AIM: This study implements a mixed-methods approach to establish methods and procedures for identifying barriers to early entry to prenatal care in a medically-vulnerable patient population and areas for future quality improvement initiatives. METHODS: An initial chart review was conducted on obstetrics patients that initiated prenatal care after their first trimester at a large federally qualified health center in Brooklyn, NY, to determine patient-specified reasons for delay. A thematic analysis of these data was implemented in combination with both parametric and non-parametric analyses to characterize the population of interest, and to identify the primary determinants of delayed entry. RESULTS: The age of patients in the population of interest (n = 169) was bimodal, with a range of 15 - 43 years and a mean of 28 years. The mean gestational age of entry into prenatal care was 19 weeks. The chart review revealed that 8% recently moved to Brooklyn from outside of NYC or the USA. Nine percent had difficulty scheduling an initial prenatal visit within their first trimester. Teenage pregnancy accounted for 7%. Provider challenges with documentation (21%) were noted. The most common themes identified (n = 155) were the patient being in transition (21%), the pregnancy being unplanned (17%), and issues with linkage to care (15%), including no shows or patient cancellations. Patients who were late to prenatal care also differed from their peers dramatically, as they were more likely to be Spanish-speaking, to be young, and to experience a relatively long delay between pregnancy confirmation and entry into care. Moreover, the greatest determinant of delayed entry into care was patient age. CONCLUSION: Our study provides a process for other like clinics to identify patients who are at risk for delayed entry to prenatal care and highlight common barriers to entry. Future initiatives include the introduction of a smart data element to document reasons for delay and use of community health workers for dedicated outreach after no show appointments or patient cancellations.

Application of the FRAME-IS to a multifaceted implementation strategy.

BACKGROUND: Research demonstrates the importance of documenting adaptations to implementation strategies that support integration of evidence-based interventions into practice. While studies have utilized the FRAME-IS [Framework for Reporting Adaptations and Modifications for Implementation Strategies] to collect structured adaptation data, they are limited by a focus on discrete implementation strategies (e.g., training), which do not reflect the complexity of multifaceted strategies like practice facilitation. In this paper, we apply the FRAME-IS to our trial evaluating the effectiveness of PF on implementation fidelity of an evidence-based technology-facilitated team care model for improved hypertension control within a federally qualified health center (FQHC). METHODS: Three data sources are used to document adaptations: (1) implementation committee meeting minutes, (2) narrative reports completed by practice facilitators, and (3) structured notes captured on root cause analysis and Plan-Do-Study-Act worksheets. Text was extracted from the data sources according to the FRAME-IS modules and inputted into a master matrix for content analysis by two authors; a third author conducted member checking and code validation. RESULTS: We modified the FRAME-IS to include part 2 of module 2 (what is modified) to add greater detail of the modified strategy, and a numbering system to track adaptations across the modules. This resulted in identification of 27 adaptations, of which 88.9% focused on supporting practices in identifying eligible patients and referring them to the intervention. About half (52.9%) of the adaptations were made to modify the context of the PF strategy to include a group-based format, add community health workers to the strategy, and to shift the implementation target to nurses. The adaptations were often widespread (83.9%), affecting all practices within the FQHC. While most adaptations were reactive (84.6%), they resulted from a systematic process of reviewing data captured by multiple sources. All adaptations included the FQHC in the decision-making process. CONCLUSION: With modifications, we demonstrate the ability to document our adaptation data across the FRAME-IS modules, attesting to its applicability and value for a range of implementation strategies. Based on our experiences, we recommend refinement of tracking systems to support more nimble and practical documentation of iterative, ongoing, and multifaceted adaptations. TRIAL REGISTRATION: Clinicaltrials.gov NCT03713515, Registration date: October 19, 2018.

Patient and Clinician Satisfaction with the Early Implementation of Telemental Health Services in an Urban Behavioral Health Clinic During the COVID-19 Pandemic.

Objective: The COVID-19 pandemic served as an impetus for the rapid expansion of telehealth. In this study, we examined the experience of rapid transition to telemental health (TMH) within The Family Health Centers at NYU Langone, a large, urban, Federally Qualified Health Center, in the 3 months after the onset of the COVID-19 pandemic. Methods: We administered surveys to clinicians and patients who utilized TMH between March 16, 2020 and July 16, 2020. Patients were sent a web-based survey via email or received a phone survey (for those without email) with four languages choices: English, Spanish, Traditional Chinese, or Simplified Chinese. Results: The majority (79%) of clinicians (n = 83) rated the experience of TMH as "excellent" or "good," and felt that they could establish and maintain the patient relationship through TMH. Four thousand seven hundred seventy-two survey invitations were sent out to patients, and 654 (13.7%) responded. Ninety percent reported that they were satisfied with the service they received and rated TMH as better or the same as in-person care (81.6%) with a high mean satisfaction score (4.5 out of 5). Patients were more likely to rate TMH as better or the same as in-person care relative to the clinicians. Conclusions: These results are consistent with several recent studies that have explored patient satisfaction with TMH during the COVID-19 pandemic and demonstrate that both clinicians and patients experienced a high degree of satisfaction with mental health care delivered virtually compared with face-to-face encounters.

Managing COVID-19 With a Clinical Decision Support Tool in a Community Health Network: Algorithm Development and Validation.

BACKGROUND: The coronavirus disease (COVID-19) pandemic has resulted in significant morbidity and mortality; large numbers of patients require intensive care, which is placing strain on health care systems worldwide. There is an urgent need for a COVID-19 disease severity assessment that can assist in patient triage and resource allocation for patients at risk for severe disease. OBJECTIVE: The goal of this study was to develop, validate, and scale a clinical decision support system and mobile app to assist in COVID-19 severity assessment, management, and care. METHODS: Model training data from 701 patients with COVID-19 were collected across practices within the Family Health Centers network at New York University Langone Health. A two-tiered model was developed. Tier 1 uses easily available, nonlaboratory data to help determine whether biomarker-based testing and/or hospitalization is necessary. Tier 2 predicts the probability of mortality using biomarker measurements (C-reactive protein, procalcitonin, D-dimer) and age. Both the Tier 1 and Tier 2 models were validated using two external datasets from hospitals in Wuhan, China, comprising 160 and 375 patients, respectively. RESULTS: All biomarkers were measured at significantly higher levels in patients who died vs those who were not hospitalized or discharged (P<.001). The Tier 1 and Tier 2 internal validations had areas under the curve (AUCs) of 0.79 (95% CI 0.74-0.84) and 0.95 (95% CI 0.92-0.98), respectively. The Tier 1 and Tier 2 external validations had AUCs of 0.79 (95% CI 0.74-0.84) and 0.97 (95% CI 0.95-0.99), respectively. CONCLUSIONS: Our results demonstrate the validity of the clinical decision support system and mobile app, which are now ready to assist health care providers in making evidence-based decisions when managing COVID-19 patient care. The deployment of these new capabilities has potential for immediate impact in community clinics and sites, where application of these tools could lead to improvements in patient outcomes and cost containment.

A Telemedicine Approach to Covid-19 Assessment and Triage.

Covid-19 is a new highly contagious RNA viral disease that has caused a global pandemic. Human-to-human transmission occurs primarily through oral and nasal droplets and possibly through the airborne route. The disease may be asymptomatic or the course may be mild with upper respiratory symptoms, moderate with non-life-threatening pneumonia, or severe with pneumonia and acute respiratory distress syndrome. The severe form is associated with significant morbidity and mortality. While patients who are unstable and in acute distress need immediate in-person attention, many patients can be evaluated at home by telemedicine or videoconferencing. The more benign manifestations of Covid-19 may be managed from home to maintain quarantine, thus avoiding spread to other patients and health care workers. This document provides an overview of the clinical presentation of Covid-19, emphasizing telemedicine strategies for assessment and triage of patients. Advantages of the virtual visit during this time of social distancing are highlighted.

Application of the FRAME-IS to a Multifaceted Implementation Strategy.

Background: Research demonstrates the importance of documenting adaptations to implementation strategies that support integration of evidence-based interventions into practice. While studies have utilized the FRAME-IS [Framework for Reporting Adaptations and Modifications for Implementation Strategies] to collect structured adaptation data, they are limited by a focus on discrete implementation strategies (e.g., training), which do not reflect the complexity of multifaceted strategies like practice facilitation (PF). In this paper, we apply the FRAME-IS to our trial evaluating the effectiveness of PF on implementation fidelity of an evidence-based technology-facilitated team care model for improved hypertension control within a federally qualified health center (FQHC). Methods: Three data sources are used to document adaptations: (1) implementation committee meeting minutes, (2) narrative reports completed by practice facilitators, and (3) structured notes captured on root cause analysis and Plan-Do-Study-Act worksheets. Text was extracted from the data sources according to the FRAME-IS modules and inputted into a master matrix for content analysis by two authors; a third author conducted member checking and code validation. Results: We modified the FRAME-IS to include part 2 of module 2 (what is modified) to add greater detail of the modified strategy, and a numbering system to track adaptations across the modules. This resulted in identification of 27 adaptations, of which 88.9% focused on supporting practices in identifying eligible patients and referring them to the intervention. About half (52.9%) of the adaptations were made to modify the context of the PF strategy to include a group-based format, add community health workers to the strategy, and to shift the implementation target to nurses. The adaptations were often widespread (83.9%), affecting all practices within the FQHC. While most adaptations were reactive (84.6%), they resulted from a systematic process of reviewing data captured by multiple sources. All adaptations included the FQHC in the decision-making process. Conclusion: With modifications, we demonstrate the ability to document our adaptation data across the FRAME-IS modules, attesting to its applicability and value for a range of implementation strategies. Based on our experiences, we recommend refinement of tracking systems to support more nimble and practical documentation of iterative, ongoing, and multifaceted adaptations. Trial Registration: clinicaltrials.gov NCT03713515, Registration date: October 19, 2018.

"Hypertension is such a difficult disease to manage": federally qualified health center staff- and leadership-perceived readiness to implement a technology-facilitated team-based hypertension model.

BACKGROUND: Despite decades of evidence demonstrating the efficacy of hypertension care delivery in reducing morbidity and mortality, a majority of hypertension cases remain uncontrolled. There is an urgent need to elucidate and address multilevel facilitators and barriers clinical staff face in delivering evidence-based hypertension care, patients face in accessing it, and clinical systems face in sustaining it. Through a rigorous pre-implementation evaluation, we aimed to identify facilitators and barriers bearing the potential to affect the planned implementation of a multilevel technology-facilitated hypertension management trial across six primary care sites in a large federally qualified health center (FQHC) in New York City. METHODS: During a dedicated pre-implementation period (3-9 months/site, 2021-2022), a capacity assessment was conducted by trained practice facilitators, including (1) online anonymous surveys (n = 124; 70.5% of eligible), (2) hypertension training analytics (n = 69; 94.5% of assigned), and (3) audio-recorded semi-structured interviews (n = 67; 48.6% of eligible) with FQHC leadership and staff. Surveys measured staff sociodemographic characteristics, adaptive reserve, evidence-based practice attitudes, and implementation leadership scores via validated scales. Training analytics, derived from end-of-course quizzes, included mean score and number attempts needed to pass. Interviews assessed staff-reported facilitators and barriers to current hypertension care delivery and uptake; following audio transcription, trained qualitative researchers employed a deductive coding approach, informed by the Consolidated Framework for Implementation Research (CFIR). RESULTS: Most survey respondents reported moderate adaptive reserve (mean = 0.7, range = 0-1), evidence-based practice attitudes (mean = 2.7, range = 0-4), and implementation leadership (mean = 2.5, range = 0-4). Most staff passed training courses on first attempt and demonstrated high scores (means > 80%). Findings from interviews identified potential facilitators and barriers to implementation; specifically, staff reported that complex barriers to hypertension care, control, and clinical communication exist; there is a recognized need to improve hypertension care; in-clinic challenges with digital tool access imposes workflow delays; and despite high patient loads, staff are motivated to provide high-quality cares. CONCLUSIONS: This study serves as one of the first to apply the CFIR to a rigorous pre-implementation evaluation within the understudied context of a FQHC and can serve as a model for similar trials seeking to identify and address contextual factors known to impact implementation success. TRIAL REGISTRATION: ClinicalTrials.gov NCT03713515 , date of registration: October 19, 2018.

Simultaneous Quantitative SARS-CoV-2 Antigen and Host Antibody Detection and Pre-Screening Strategy at the Point of Care.

As COVID-19 pandemic public health measures are easing globally, the emergence of new SARS-CoV-2 strains continue to present high risk for vulnerable populations. The antibody-mediated protection acquired from vaccination and/or infection is seen to wane over time and the immunocompromised populations can no longer expect benefit from monoclonal antibody prophylaxis. Hence, there is a need to monitor new variants and its effect on vaccine performance. In this context, surveillance of new SARS-CoV-2 infections and serology testing are gaining consensus for use as screening methods, especially for at-risk groups. Here, we described an improved COVID-19 screening strategy, comprising predictive algorithms and concurrent, rapid, accurate, and quantitative SARS-CoV-2 antigen and host antibody testing strategy, at point of care (POC). We conducted a retrospective analysis of 2553 pre- and asymptomatic patients who were tested for SARS-CoV-2 by RT-PCR. The pre-screening model had an AUC (CI) of 0.76 (0.73-0.78). Despite being the default method for screening, body temperature had lower AUC (0.52 [0.49-0.55]) compared to case incidence rate (0.65 [0.62-0.68]). POC assays for SARS-CoV-2 nucleocapsid protein (NP) and spike (S) receptor binding domain (RBD) IgG antibody showed promising preliminary results, demonstrating a convenient, rapid (<20 min), quantitative, and sensitive (ng/mL) antigen/antibody assay. This integrated pre-screening model and simultaneous antigen/antibody approach may significantly improve accuracy of COVID-19 infection and host immunity screening, helping address unmet needs for monitoring vaccine effectiveness and severe disease surveillance.

Key Principles Underlying a Research-Practice Alignment in a Federally Qualified Health Center.

Context: Minoritized populations such as racial and ethnic minorities and individuals of less privileged socioeconomic status experience a disproportionate burden of poor hypertension (HTN) control in the United States. Multilevel systems interventions have been shown to improve patient-level outcomes in minoritized populations; however, there remains a large translational gap in implementing these approaches into federally qualified health centers (FQHC), which serve those at highest risk of HTN-related morbidity and mortality. The paucity of purposeful collaborations between academic researchers and practice staff throughout the research process remains a significant roadblock to the timely translation of evidence to practice. Design: This commentary describes the key principles and best practices that underlie the development and sustainment of an equitable research-practice alignment, which is supporting the implementation of multilevel systems intervention for improved HTN care in a large FQHC in Brooklyn, New York. The key principles, which are derived from the central tenants of relationship development and maintenance in community-engaged participatory research, patient-centered outcomes research, and organizational alignment theory include (1) cocreation of a shared mental model, (2) bridging multilevel communication, (3) ensuring mutual accountability, and (4) creating a culture of continuous improvement. Conclusions: Together, the principles guide how the research and practice teams work together to achieve a shared goal of improving the health and well-being of minoritized patients through the provision of high quality, community-oriented HTN care. Best practices to sustain our alignment require an ongoing and deliberate investment in honest and transparent communication by all members.

A feasibility and acceptability study of screening the parents/guardians of pediatric dental patients for the social determinants of health.

BACKGROUND: The social determinants of health (SDOH) are the conditions in which people are born, grow, work, live, and age. Lack of SDOH training of dental providers on SDOH may result in suboptimal care provided to pediatric dental patients and their families. The purpose of this pilot study is to report the feasibility and acceptability of SDOH screening and referral by pediatric dentistry residents and faculty in the dental clinics of Family Health Centers at NYU Langone (FHC), a Federally Qualified Health Center (FQHC) network in Brooklyn, NY, USA. METHODS: Guided by the Implementation Outcomes Framework, 15 pediatric dentists and 40 pediatric dental patient-parent/guardian dyads who visited FHC in 2020-2021 for recall or treatment appointments participated in this study. The a priori feasibility and acceptability criteria for these outcomes were that after completing the Parent Adversity Scale (a validated SDOH screening tool), ≥ 80% of the participating parents/guardians would feel comfortable completing SDOH screening and referral at the dental clinic (acceptable), and ≥ 80% of the participating parents/guardians who endorsed SDOH needs would be successfully referred to an assigned counselor at the Family Support Center (feasible). RESULTS: The most prevalent SDOH needs endorsed were worried within the past year that food would run out before had money to buy more (45.0%) and would like classes to learn English, read better, or obtain a high school degree (45.0%). Post-intervention, 83.9% of the participating parents/guardians who expressed an SDOH need were successfully referred to an assigned counselor at the Family Support Center for follow-up, and 95.0% of the participating parents/guardians felt comfortable completing the questionnaire at the dental clinic, surpassing the a priori feasibility and acceptability criteria, respectively. Furthermore, while most (80.0%) of the participating dental providers reported being trained in SDOH, only one-third (33.3%) usually or always assess SDOH for their pediatric dental patients, and most (53.8%) felt minimally comfortable discussing challenges faced by pediatric dental patient families and referring patients to resources in the community. CONCLUSIONS: This study provides novel evidence of the feasibility and acceptability of SDOH screening and referral by dentists in the pediatric dental clinics of an FQHC network.

The impact of COVID-19 monoclonal antibodies on clinical outcomes: A retrospective cohort study.

PURPOSE: Despite progress in the treatment of coronavirus disease 2019 (COVID-19), including the development of monoclonal antibodies (mAbs), more clinical data to support the use of mAbs in outpatients with COVID-19 is needed. This study is designed to determine the impact of bamlanivimab, bamlanivimab/etesevimab, or casirivimab/imdevimab on clinical outcomes within 30 days of COVID-19 diagnosis. METHODS: A retrospective cohort study was conducted at a single academic medical center with 3 campuses in Manhattan, Brooklyn, and Long Island, NY. Patients 12 years of age or older who tested positive for COVID-19 or were treated with a COVID-19-specific therapy, including COVID-19 mAb therapies, at the study site between November 24, 2020, and May 15, 2021, were included. The primary outcomes included rates of emergency department (ED) visit, inpatient admission, intensive care unit (ICU) admission, or death within 30 days from the date of COVID-19 diagnosis. RESULTS: A total of 1,344 mAb-treated patients were propensity matched to 1,344 patients with COVID-19 patients who were not treated with mAb therapy. Within 30 days of diagnosis, among the patients who received mAb therapy, 101 (7.5%) presented to the ED and 79 (5.9%) were admitted. Among the patients who did not receive mAb therapy, 165 (12.3%) presented to the ED and 156 (11.6%) were admitted (relative risk [RR], 0.61 [95% CI, 0.50-0.75] and 0.51 [95% CI, 0.40-0.64], respectively). Four mAb patients (0.3%) and 2.64 control patients (0.2%) were admitted to the ICU (RR, 01.51; 95% CI, 0.45-5.09). Six mAb-treated patients (0.4%) and 3.37 controls (0.3%) died and/or were admitted to hospice (RR, 1.61; 95% CI, 0.54-4.83). mAb therapy in ambulatory patients with COVID-19 decreases the risk of ED presentation and hospital admission within 30 days of diagnosis.

Homelessness and Medicaid Churn.

Objectives: To identify ICD-10-CM diagnostic codes associated with the social determinants of health (SDOH), determine frequency of use of the code for homelessness across time, and examine the frequency of interrupted periods of Medicaid eligibility (ie, Medicaid churn) for beneficiaries with and without this code. Design: Retrospective data analyses of New York State (NYS) Medicaid claims data for years 2006-2017 to determine reliable indicators of SDOH hypothesized to affect Medicaid churn, and for years 2016-2017 to examine frequency of Medicaid churn among patients with and without an indicator for homelessness. Main Outcome Measures: Any interruption in the eligibility for Medicaid insurance (Medicaid churn), assessed via client identification numbers (CIN) for continuity. Methods: Analyses were conducted to assess the frequency of use and pattern of New York State Medicaid claims submission for SDOH codes. Analyses were conducted for Medicaid claims submitted for years 2016-2017 for Medicaid patients with and without a homeless code (ie, ICD-10-CM Z59.0) in 2017. Results: ICD-9-CM / ICD-10-CM codes for lack of housing / homelessness demonstrated linear reliability over time (ie, for years 2006-2017) with increased usage. In 2016-2017, 22.9% of New York Medicaid patients with a homelessness code in 2017 experienced at least one interruption of Medicaid eligibility, while 18.8% of Medicaid patients without a homelessness code experienced Medicaid churn. Conclusions: Medicaid policies would do well to take into consideration the barriers to continued enrollment for the Medicaid population. Measures ought to be enacted to reduce Medicaid churn, especially for individuals experiencing homelessness.

Clinical decision support tool and rapid point-of-care platform for determining disease severity in patients with COVID-19.

SARS-CoV-2 is the virus that causes coronavirus disease (COVID-19) which has reached pandemic levels resulting in significant morbidity and mortality affecting every inhabited continent. The large number of patients requiring intensive care threatens to overwhelm healthcare systems globally. Likewise, there is a compelling need for a COVID-19 disease severity test to prioritize care and resources for patients at elevated risk of mortality. Here, an integrated point-of-care COVID-19 Severity Score and clinical decision support system is presented using biomarker measurements of C-reactive protein (CRP), N-terminus pro B type natriuretic peptide (NT-proBNP), myoglobin (MYO), D-dimer, procalcitonin (PCT), creatine kinase-myocardial band (CK-MB), and cardiac troponin I (cTnI). The COVID-19 Severity Score combines multiplex biomarker measurements and risk factors in a statistical learning algorithm to predict mortality. The COVID-19 Severity Score was trained and evaluated using data from 160 hospitalized COVID-19 patients from Wuhan, China. Our analysis finds that COVID-19 Severity Scores were significantly higher for the group that died versus the group that was discharged with median (interquartile range) scores of 59 (40-83) and 9 (6-17), respectively, and area under the curve of 0.94 (95% CI 0.89-0.99). Although this analysis represents patients with cardiac comorbidities (hypertension), the inclusion of biomarkers from other pathophysiologies implicated in COVID-19 (e.g., D-dimer for thrombotic events, CRP for infection or inflammation, and PCT for bacterial co-infection and sepsis) may improve future predictions for a more general population. These promising initial models pave the way for a point-of-care COVID-19 Severity Score system to impact patient care after further validation with externally collected clinical data. Clinical decision support tools for COVID-19 have strong potential to empower healthcare providers to save lives by prioritizing critical care in patients at high risk for adverse outcomes.

Clinical Decision Support Tool and Rapid Point-of-Care Platform for Determining Disease Severity in Patients with COVID-19.

SARS-CoV-2 is the virus that causes coronavirus disease (COVID-19) which has reached pandemic levels resulting in significant morbidity and mortality affecting every inhabited continent. The large number of patients requiring intensive care threatens to overwhelm healthcare systems globally. Likewise, there is a compelling need for a COVID-19 disease severity test to prioritize care and resources for patients at elevated risk of mortality. Here, an integrated point-of-care COVID-19 Severity Score and clinical decision support system is presented using biomarker measurements of C-reactive protein (CRP), N-terminus pro B type natriuretic peptide (NT-proBNP), myoglobin (MYO), D-dimer, procalcitonin (PCT), creatine kinase-myocardial band (CK-MB), and cardiac troponin I (cTnI). The COVID-19 Severity Score combines multiplex biomarker measurements and risk factors in a statistical learning algorithm to predict mortality. The COVID-19 Severity Score was trained and evaluated using data from 160 hospitalized COVID-19 patients from Wuhan, China. Our analysis finds that COVID-19 Severity Scores were significantly higher for the group that died versus the group that was discharged with median (interquartile range) scores of 59 (40-83) and 9 (6-17), respectively, and area under the curve of 0.94 (95% CI 0.89-0.99). These promising initial models pave the way for a point-of-care COVID-19 Severity Score system to impact patient care after further validation with externally collected clinical data. Clinical decision support tools for COVID-19 have strong potential to empower healthcare providers to save lives by prioritizing critical care in patients at high risk for adverse outcomes.