Faculty Bibliography

To mitigate the negative impact of resource needs on child health, practices serving low-income immigrant families have implemented screening programs to connect families to community resources. Little is known about how duration of US residence relates to patterns of resource needs and indicators of acculturation such as community resource knowledge/experience or self-efficacy. We conducted a cross-sectional analysis of a convenience sample of immigrant families with young children at an urban primary care clinic. These families were seen 5/2018-1/2020 for well child care, screening positive for ≥1 social need using a tool derived from Health Leads. Analysis of 114 families found that newly arrived families with a shorter duration of US residence (≤5 years) were more likely to report immediate material hardships like food insecurity and need for essential child supplies. Newly arrived families were also less likely to have access to technology resources such as a computer or smartphone. Long-term families with a longer duration of US residence (≥15 years) were more likely to report chronic needs like poor housing conditions, but also reported increased community resource knowledge/experience and increased self-efficacy. Primary care pediatric practices should assess immigration contextual factors to identify subgroups such as newly arrived families with young children to target resources (e.g., increase screening frequency) or enhance services (e.g., patient navigators) to relieve resource needs.

BACKGROUND:In contrast to the current broad dissemination of telemedicine across medical specialties, previous research focused on the effectiveness of telemedicine in special populations and for behavioral health encounters; demonstrating that both physician and patient factors impact the efficacious use of telemedicine. OBJECTIVE:We evaluated physician perceptions of the appropriateness of telemedicine for patients attending the primary care practices of a federally qualified health center in New York City. METHODS:Anonymous cross-sectional survey including closed and open-ended questions. We used chi-square to test whether providers from certain specialties were more likely to state they would use telemedicine in the future. We used t-test to compare age between those who would vs. would not use telemedicine. Then, we used logistic regression to test whether age and specialty were both correlated with desire to use telemedicine in the future. We used thematic content analysis to describe the reasons providers felt they would not want to use telemedicine in the future, and to describe the situations for which they felt telemedicine would be appropriate. RESULTS:Of 272 FHC providers who were sent the electronic survey, 159(58%) responded within the 2-week survey time frame. Mean age of providers was 45 years (range 28-75). Overall, 81% stated they would use telemedicine in the future. Compared to the Family Medicine, Internal Medicine, Behavioral Health, Dental, and OB/GYN specialties, providers from Pediatrics, Med-Peds, Subspecialties and Surgery [Pro-telemedicine specialties] were more likely to believe telemedicine would be useful post pandemic (94% vs. 72%, p<0.05). Providers who reported they would use telemedicine in the future were younger [mean age 44(42-46) vs. 50(46-55), p<0.01). In regression analysis, both pro-telemedicine specialties and age were significantly associated with odds of reporting they would use telemedicine in the future [pro-specialties: 5.2(1.7-16.2); younger age: 1.05(1.01-1.08)]. Providers who did not want to use telemedicine in the future cited concerns about inadequate patient care, lack of physical patient interaction, technology issues, and lack of necessity. Providers who felt telemedicine would be useful cited the following situations: follow up visits, medication refills, urgent care, patient convenience, and specific conditions such has behavioral health, dermatology visits, and chronic care management. CONCLUSIONS:The majority of health providers in this resource poor setting in a federally qualified health center believed that telemedicine would be useful for providing care after the pandemic is over. CLINICALTRIAL/UNASSIGNED/:

BACKGROUND:Enhanced literacy and increased vocabulary related to Reach Out and Read (ROR) are well described. Less is known about clinicians' experience with the program. OBJECTIVE:Understand clinician experiences of implementing ROR. DESIGN/METHODS/METHODS:This study was a collaboration between ROR and the Academic Pediatric Association's Continuity Research Network. Participants completed an anonymous online survey to evaluate literacy promotion activities and training, and asked "What has been the most meaningful experience you have encountered with using ROR?" and "Is there anything else you would like to add?" Responses were evaluated by researchers and four themes were generated through discussion. All responses were then divided and coded by researchers working in pairs and then by all researchers until consensus was reached. Data were organized into themes. FINDINGS/RESULTS:Responses were provided by 592 (35%) participants. Qualitative analysis revealed benefits to participation in ROR within four themes: (1) Child/Family Impact (60%): "Seeing a child read for the first time" (2) Physician Impact (16%): "I... use the books... to connect with patients." (3) Impact on clinic practice (25%): "I... enjoy modeling for parents and use the books to assess... development" (4) Social Determinants of Health (2%): "The books... are an invaluable resource to our under-served population." CONCLUSION(S)/CONCLUSIONS:Clinicians who implement ROR report positive impact on patients, families, and their own satisfaction and methods in practice. Clinicians value that the program addresses social determinants of health and facilitates developmental surveillance. Further study is needed to understand how clinician's perspectives affect and are affected by their experiences.

BACKGROUND:The COVID-19 pandemic has resulted in significant morbidity and mortality, with large numbers of patients requiring intensive care threatening to overwhelm healthcare systems globally. 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, non-laboratory data to help determine whether biomarker-based testing and/or hospitalization is necessary. Tier 2 predicts probability of mortality using biomarker measurements (CRP, PCT, D-dimer) and age. Both 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 that died vs. those that were not hospitalized or discharged (P < .001). The Tier 1 and Tier 2 internal validation had AUC (95% confidence interval) of 0.79 (0.74-0.84) and 0.95 (0.92-0.98), respectively. The Tier 1 and Tier 2 external validation had AUCs of 0.79 (0.74-0.84) and 0.97 (0.95-0.99), respectively. CONCLUSIONS:Our results demonstrate validity of the clinical decision support system and mobile app, which are now ready to assist healthcare providers in making evidence-based decisions in managing COVID-19 patient care. The deployment of these new capabilities has potential for immediate impact in community clinics, sites whereby application of such tools could lead to improvements in patient outcomes and cost containment. CLINICALTRIAL/UNASSIGNED/:

BACKGROUND:Despite endorsement by the American Academy of Pediatrics, there are no national data on Literacy Promotion (LP) training and behaviors. OBJECTIVE:To describe LP training experiences and behaviors of pediatric and internal medicine/pediatrics residents and faculty nationally, and the association between LP training and behaviors. METHODS:The Academic Pediatric Association's Continuity Research Network (CORNET) and Reach Out and Read (ROR) National Center sent an online survey to faculty and residents at participating CORNET clinics. Respondents were asked about LP training experiences and behaviors. Data were analyzed using descriptive statistics, chi square tests, and logistic regression modeling. RESULTS:473 faculty and 1,216 residents at 42 institutions participated. More faculty than residents reported completing online ROR training (63% vs 45%, p<0.0001). More residents reported learning in clinic from others (92% vs 89%, p=0.04). Training experiences did not differ otherwise. More faculty reported providing anticipatory guidance (87% vs 77%, p<0.0001); modeling shared reading (69% vs 45%, p<0.0001); and using books for developmental assessment (80% vs 62%, p<0.0001). Both groups (97%) reported distributing books. The training modality most often endorsed as "very/extremely influential" was learning in clinic from others. Some LP behaviors were associated more strongly with online training while others were associated more strongly with in-person training. CONCLUSIONS:Online training and in-person training are both associated with high quality delivery of LP. Faculty members are more likely to have completed online training and to report engaging in the full range of recommended LP behaviors. These data have implications for LP training.

BACKGROUND: Payors are increasingly recognizing that social determinants of health(SDH) impact on health outcomes and healthcare costs. Z codes can be used to document and stratify patients into risk pools according to SDH. We report on the impact of SDH screening implementation in a federally qualified health center network on the use of Z codes to document SDH. In this study, we describe the prevalence of SDH screening by department, the prevalence of documented SDH, and the prevalence of documented Z codes for each SDH.
METHOD(S): In October 2017, we initiated SDH screening throughout, but focusing on the internal medicine and women's health departments of a large FQHC network (12 service delivery sites) using the OCHIN tool embedded in the elecrtonic health record. In November 2019, we retrieved the following variables from record: % of all patients who were screened, number of patients screened annually by department, % of positive screens (+ response to any question), % abnormal screens(response that triggers a best practice alert to the treating provider), and documentation of a Z code for positive or abnormal screens.
RESULT(S): There were 624,007 encounters over a 2 year study period; 2,844 patients were screened: 194 in 2017, 1068 in 2018;1644 in 2019. Overall, there were 3052 screening events (some patients received multiple screens). The majority of screening events occurred in women's health [1961(64%)], followed by adult medicine[874(29%)]. Overall, 2350(77%) of screens were "positive", of which 433 had no "abnormal" results and hence did not trigger a best practice alert. Of these 433, the most common positive items were: social isolation(63%), stress(44%), financial resource strain(8%), moved 2+ times(7%). There were 1923(63%) abnormal screens. The top 10 abnormal items in Women's Health and Adult Medicine were: Education less than high school(36% and 37%), physical activity <140 minutes(23% and 25%), hard to pay for medicine/medical care(13% and 26%), hard to pay for utilities(14% and 23%), hard to pay for food(13% and 21%), hard to pay for health insurance(11% and 22%), concerns about housing quality(3% and 9%), hard to pay child care(5% and 5%), exposure to violence(4% and 3%), never get together with family/friends(3% and 3%). Overall, encounters with an SDH screen were more likely to have a documented Z code:26% vs. 1%. Z codes were documented for the following documented needs: insufficient social insurance(53%); lack of access to health care(51%), homelessness(49%), inadequate family support(40%), lack of physical exercise(37%), underachievement in school(34%), personal history of abuse(31%), lack of assistance for care at home(29%), inadequate food supply(1%).
CONCLUSION(S): Presence of a documented SDH screen was associated with documentation of Z codes, however documentation was missing more than half the time for most documented needs. The drivers of Z code documentation deserve further exploration. Qualitative interviews and focus groups with providers may be useful

BACKGROUND: Patient Portals(PP) allow access to medical records and interaction with providers; however activation(PPA) and use (PPU) are limited by language barriers, low health/computer literacy, and poor internet access which are prevalent issues in Federally Qualified Health Centers(FQHC). Little is known of the drivers and patterns of PPA in such settings. We aimed to describe the prevalence of PPA and PPU in adult patients of an FQHC; describe PPU activity, and test demographic, condition, and utilization-related correlates of PPA and PPU.
METHOD(S):We conducted a retrospective chart review in an FQHC that launched a PP in September 2016. We extracted demographics, PPA status(active/not) at data pull, PPU activities, presence of a chronic condition on the problem list, # emergency department, inpatient, subspecialty visits over past year (utilization summed, dichotomized >1 vs. 0-1 visit). Missing values for homelessness were coded to majority category( 0). Analyses included descriptive statistics, bivariate analyses, then logistic regression to test odds of PPA and PPU by. demographics, chronic conditions, and utilization. We report [adjusted odds ratios(confidence interval)].
RESULT(S): Data were analyzed for 62,610 adults [mean age 45(SD 17), 21% Black, 47% Hispanic, 46% Medicaid, 25% Selfpay, speaking English( 60%), Spanish (31%), Chinese(6%), Other(3%), with: hypertension( 19%), diabetes(11%), depression(8%), asthma(6%), CVD(5%); 21% had utilization>1. Overall 23,104(37%) activated the PP. PPU included viewing test results(69%), medications(62% ), immunizations( 51%), billing (38%), asking advice (29%), and scheduling appointments( 16%). PPA and PPU varied by demographics, chronic condition, and utilization, but were consistently higher for females, those who were not Medicaid recipients or Self-pay, English speakers and those with asthma, hypertension, and depression.
CONCLUSION(S): PPA was lower for non-whites and poorer patients, but higher for patients speaking the predominant languages of this FQHC, suggesting that language concordance helps engage patients. Patients with chronic conditions and more healthcare utilization had greater odds of PPA and PPU. On the other hand, Spanish-speakers were less likely to actively use the portal for functions such as scheduling appointments, suggesting that improvements in language capabilities of the platform are needed

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.

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.

OBJECTIVE:Understanding differences between trainee and faculty experience with and confidence caring for children with special health care needs (CSHCN) can inform pediatric resident education. METHODS:Residents and faculty across the Continuity Research Network (CORNET) reported on a consecutive series of 5 primary care encounters. Respondents answered questions about visit characteristics, patient demographics, and applied the CSHCN Screener. Respondents also reported on how confident they felt addressing the patient's healthcare needs over time. We dichotomized confidence at "very confident" vs. all other values. We used logistic regression to describe the correlates of provider confidence managing the patient's care. RESULTS:We collected data on 381 (74%) resident-patient and 137 (26%) attending-patient encounters. A higher proportion of attending encounters compared to resident encounters were with CSHCN (49% vs. 39%, p<0.05), including children with complex needs (17% vs. 10%, p<0.05). The odds of feeling "very confident" [AOR(95%CI)] was lower with increasing CSHCN score [0.61(0.51-0.72)] and was lower for resident vs. attending encounters [0.39(0.16-0.95)]. Confidence was higher if the provider had previously seen that patient [2.07 (1.15-3.72)], and for well [2.50(1.35-4.64)] or sick visits [3.18(1.46-6.94)] (vs. follow-up). Differences between residents and attending pediatricians regarding the relationship between confidence and visit characteristics for subsets of CSHCN are reported. CONCLUSION/CONCLUSIONS:All providers felt less confident caring for CSHCN; however for certain needs, resident confidence did not increase with level of training. The data suggest potential educational/programmatic opportunities.