Long-term impact of patient navigation (PN) for breast cancer (BCA) screening in an urban academic medical center.

2020 ◽  
Vol 38 (29_suppl) ◽  
pp. 130-130
Author(s):  
Lisa Phuong ◽  
Jesus Del Santo Anampa Mesias ◽  
Melanie Lozada ◽  
Della F. Makower
Keyword(s):  
Median Time ◽  
Health Care Disparities ◽  
Medical Center ◽  
Demographic Data ◽  
Academic Medical Center ◽  
Primary Care Providers ◽  
Rank Test ◽  
Care Providers ◽  
Long Term Impact

130 Background: PN improves BCA screening rates in underserved women, and decreases health care disparities. However, there is limited data regarding the ability of PN effect sustained change. We evaluated the long-term impact of PN for BCA screening at our institution, by assessing the rate at which women who underwent screening mammogram (SM) in 2017, with the aid of PN, completed subsequent (f/u) SM within guideline-concordant time frames. Methods: Patients (pts) consisted of women seen by our institution’s primary care providers, with referral for SM in the electronic medical record (EMR), but without scheduled appointment, who received PN between June 1 and September 30, 2017, and successfully completed SM in 2017. Pts were identified from the screening navigation database. EMR was reviewed to obtain demographic data, rate of f/u SM, and time from 2017 SM to prior and f/u SM. Wilcoxon signed-rank test was used for analysis. Results: 179 pts completed SM with the aid of PN in 2017. Median age was 58 (range 37-77), 52.5% were Hispanic, 26.8% Black; and 2.8% Asian. Preferred languages were English (70.4%) and Spanish (25.7%). 6 pts had never had prior SM; 30 had no prior SM at our institution. Median time between 2017 SM and prior SM was 29 months (mo) (range 12-104); only 20 pts (11.2%) had a prior SM within 24 mo. 177 pts were eligible for f/u SM in 2018 and 2019 (1 diagnosed with BCA on 2017 SM; 1 died in 2017). 85 pts (48%) completed f/u SM; 68 (39%) completed within 24 mo. Only 2 pts required PN to complete f/u SM. In pts with time to screening data available for both 2017 SM and f/u SM (n = 80), median time to SM improved from 24 to 16 mo (p < 0.01). Decreases were seen in Black (22 to 14 mo, p < 0.01), White (31 to 16 mo, p = 0.03), and Hispanic pts (28 to 18.5 mo, p < 0.01), and in English (22 to 15 mo, p < 0.01) and Spanish speakers (26 to 20 mo, p < 0.01). Conclusions: A single episode of PN for BCA screening had a sustained impact on pts at our institution, leading to improved compliance with future SM. Improvement was seen in pts of diverse races, ethnicities, and language preferences. Focused PN for pts who did not complete f/u SM is planned.

scholarly journals 864. Adolescent Primary Care Provider Knowledge of HIV Pre-Exposure Prophylaxis (PrEP) and Universal Screening at a Midwest Academic Medical Center

2021 ◽  
Vol 8 (Supplement_1) ◽  
pp. S523-S524
Author(s):  
Genevieve Allen ◽  
Jamie Riddell
Keyword(s):  
Internal Medicine ◽  
Primary Care ◽  
Family Medicine ◽  
Hiv Testing ◽  
Medical Center ◽  
Academic Medical Center ◽  
Primary Care Providers ◽  
Care Providers ◽  
Academic Medical ◽  
Exposure Prophylaxis

Abstract Background HIV remains a problem for adolescents with 21% of new infections in the United States in 2018 occurring in youth. In this study we attempted to assess the knowledge of and comfort with pre-exposure prophylaxis and universal HIV testing among adolescent primary care providers affiliated with one academic medical center. Methods We conducted a survey of internal medicine/pediatrics, pediatrics, and family medicine residents and attending physicians affiliated with an academic medical center. Data collected included provider prescribing and referring habits for PrEP and information on their universal HIV testing habits. A “test your knowledge” section followed the survey which asked participants to name PrEP medications and to correctly select laboratory monitoring required for PrEP. Correct answers and prescribing resources were provided on completion of the survey. Results 138 (76%) respondents were aware that PrEP is approved for adolescents. There was no significant difference across specialties or between residents and attendings. 44.8% of respondents felt uncomfortable prescribing PrEP and two thirds had never prescribed PrEP. Reasons for not prescribing PrEP included: not seeing adolescents who qualify (n=80), not having enough training (66), confidentiality concerns (22), forgetting to address PrEP (19), and concern incidence of HIV is too low to recommend PrEP (15). Pediatricians were the least likely to test for HIV with 11% of pediatrician, 32% of internal medicine/pediatric, and 38% of family medicine respondents reported universal HIV testing for patients 15 years and older (p &lt; 0.05). Residents were more likely to test for HIV than attendings (33.3% versus 16%, p &lt; 0.05). 111 participants completed the “test your knowledge” section. 31.5% correctly named two approved PrEP medications. There were 183 responses to the survey (49% response rate). Conclusion Adolescent primary care providers are aware that PrEP is FDA approved for adolescents but a gap in PrEP prescribing and HIV testing persists. There remain perceptions that HIV incidence is too low to discuss PrEP and that providers are not seeing patients who qualify. Next steps include developing an institutional PrEP guideline and creating an electronic medical record order set to facilitate PrEP prescribing. Disclosures All Authors: No reported disclosures

Lung cancer screening knowledge and beliefs among primary care providers and pulmonologists.

2016 ◽  
Vol 34 (7_suppl) ◽  
pp. 191-191
Author(s):  
Katie Marsh ◽  
Mikael Anne Greenwood-Hickman ◽  
Laura Jones ◽  
M. Patricia Rivera ◽  
J. Michael Bowling ◽  
...  
Keyword(s):  
Internal Medicine ◽  
Lung Cancer ◽  
Response Rate ◽  
Screening Program ◽  
Medical Center ◽  
Academic Medical Center ◽  
Lung Cancer Screening ◽  
Primary Care Providers ◽  
Care Providers ◽  
The Family

191 Background: In response to the National Lung Screening Trial’s findings, numerous professional organizations have published guidelines recommending annual lung cancer (LC) screening with low dose computed tomography (LDCT) for eligible patients. In the wake of these guidelines, we sought to assess LC screening practices and beliefs among providers at a large academic medical center. Methods: In 2015, we surveyed 54 physicians and 9 residents in pulmonology (27% response rate) and 86 physicians and 100 residents in family/internal medicine (39% response rate). The 23 question Qualtrics survey focused on beliefs and knowledge about LC screening recommendations, guidelines, and practices. Results: Survey respondents in both groups were mostly White non-Hispanic clinicians with a mean age of 40 (range 28-67). Pulmonology respondents were mostly male (69%) and family/internal medicine respondents were mostly female (53%). The pulmonology group was more likely than family/internal medicine to believe that LC screening is beneficial for patients (p < 0.0001) and cost effective (p = 0.02). Over 76% of the pulmonology group reported ordering a LDCT for an asymptomatic patient in the past 12 months compared to 41% in the family/internal medicine group (p = 0.012). Additionally, 76% in pulmonology were aware of the American College of Chest Physicians recommendations versus 38% in family/internal medicine (p = 0.02). The majority of both groups agreed that an electronic prompt would increase the likelihood of referring a patient for LC screening. While both groups agreed that a LC screening registry would benefit the quality of patient care (100% pulmonology; 65% family/internal medicine; p = 0.02) and make them more likely to refer patients to a LC screening program (88%; 54%; p = 0.04), a significantly larger majority of the pulmonology group held these beliefs. Conclusions: Pulmonology respondents had more knowledge of guidelines and more favorable opinions of LC screening than family/internal medicine respondents. Our findings suggest future studies should focus on educating providers about recommendations and understanding why the family/internal medicine group is less likely to refer patients for LC screening.

scholarly journals Using electronic health records to characterize prescription patterns: focus on antidepressants in nonpsychiatric outpatient settings

JAMIA Open ◽  
2018 ◽  
Vol 1 (2) ◽  
pp. 233-245 ◽  
Author(s):  
Joseph J Deferio ◽  
Tomer T Levin ◽  
Judith Cukor ◽  
Samprit Banerjee ◽  
Rozan Abdulrahman ◽  
...  
Keyword(s):  
New York ◽  
Drug Product ◽  
Medical Center ◽  
Academic Medical Center ◽  
Primary Care Providers ◽  
Evidence Based ◽  
Care Providers ◽  
Prescription Patterns ◽  
Off Label ◽  
Electronic Health

Abstract Objective To characterize nonpsychiatric prescription patterns of antidepressants according to drug labels and evidence assessments (on-label, evidence-based, and off-label) using structured outpatient electronic health record (EHR) data. Methods A retrospective analysis was conducted using deidentified EHR data from an outpatient practice at a New York City-based academic medical center. Structured “medication–diagnosis” pairs for antidepressants from 35 325 patients between January 2010 and December 2015 were compared to the latest drug product labels and evidence assessments. Results Of 140 929 antidepressant prescriptions prescribed by primary care providers (PCPs) and nonpsychiatry specialists, 69% were characterized as “on-label/evidence-based uses.” Depression diagnoses were associated with 67 233 (48%) prescriptions in this study, while pain diagnoses were slightly less common (35%). Manual chart review of “off-label use” prescriptions revealed that on-label/evidence-based diagnoses of depression (39%), anxiety (25%), insomnia (13%), mood disorders (7%), and neuropathic pain (5%) were frequently cited as prescription indication despite lacking ICD-9/10 documentation. Conclusions The results indicate that antidepressants may be prescribed for off-label uses, by PCPs and nonpsychiatry specialists, less frequently than believed. This study also points to the fact that there are a number of off-label uses that are efficacious and widely accepted by expert clinical opinion but have not been included in drug compendia. Despite the fact that diagnosis codes in the outpatient setting are notoriously inaccurate, our approach demonstrates that the correct codes are often documented in a patient’s recent diagnosis history. Examining both structured and unstructured data will help to further validate findings. Routinely collected clinical data in EHRs can serve as an important resource for future studies in investigating prescribing behaviors in outpatient clinics.

scholarly journals Early Implementation and Evaluation of a Teledermatology Virtual Clinic Within an Academic Medical Center

Iproceedings ◽  
10.2196/35432 ◽  
2021 ◽  
Vol 6 (1) ◽  
pp. e35432
Author(s):  
Ethan D Borre ◽  
Suephy C Chen ◽  
Matilda W Nicholas ◽  
Edward W Cooner ◽  
Donna Phinney ◽  
...  
Keyword(s):  
Primary Care ◽  
Conflicts Of Interest ◽  
Medical Center ◽  
Academic Medical Center ◽  
Primary Care Providers ◽  
Care Providers ◽  
Primary Care Clinics ◽  
Number Of Patients ◽  
Virtual Clinic

Background Teledermatology can increase patient access; however, its optimal implementation remains unknown. Objective This study aimed to describe and evaluate the implementation of a pilot virtual clinic teledermatology service at Duke University. Methods Leaders at Duke Dermatology and Duke Primary Care identified a teledermatology virtual clinic to meet patients’ access needs. Implementation was planned over the exploration, preparation, implementation, and sustainment phases. We evaluated the implementation success of teledermatology using the Reach, Effectiveness, Adoption, Implementation, and Maintenance framework and prioritized outcome collection through a stakeholder survey. We used the electronic health record and patient surveys to capture implementation outcomes. Results Our process consisted of primary care providers (PCPs) who sent clinical and dermatoscopic images of patient lesions or rashes via e-communication to a teledermatology virtual clinic, with a subsequent virtual clinic scheduling of a video visit with the virtual clinic providers (residents or advanced practice providers, supervised by Duke Dermatology attending physicians) within 2-5 days. The teledermatology team reviews the patient images on the day of the video visit and gives their diagnosis and management plan with either no follow-up, teledermatology nurse follow-up, or in-person follow-up evaluation. Implementation at 4 pilot clinics, involving 19 referring PCPs and 5 attending dermatologists, began on September 9, 2021. As of October 31, 2021, a total of 68 e-communications were placed (50 lesions and 18 rashes) and 64 virtual clinic video visits were completed. There were 3 patient refusals and 1 conversion to a telephonic visit. Participating primary care clinics differed in the number of patients referred with completed visits (range 2-32) and the percentage of providers using e-communications (range 13%-53%). Patients were seen soon after e-communication placement; compared to in-person wait times of >3 months, the teledermatology virtual clinic video visits occurred on average 2.75 days after e-communication. In total, 20% of virtual clinic video visits were seen as in-person visit follow-up, which suggests that the majority of patients were deemed treatable at the virtual clinic. All patients who returned the patient survey (N=10, 100%) agreed that their clinical goals were met during the virtual clinic video visits. Conclusions Our virtual clinic model for teledermatology implementation resulted in timely access for patients, while minimizing loss to follow-up, and has promising patient satisfaction outcomes. However, participating primary care clinics differ in their volume of referrals to the virtual clinic. As the teledermatology virtual clinics scale to other clinic sites, a systematic assessment of barriers and facilitators to its implementation may explain these interclinic differences. Acknowledgments We are grateful to the Private Diagnostic Clinic and Duke Institute for Health Innovation for their support. Conflicts of Interest None declared.

scholarly journals Primary care provider approaches to preventive health delivery: a qualitative study

2018 ◽  
Vol 19 (5) ◽  
pp. 464-474
Author(s):  
Hemalatha Murugan ◽  
Clarence Spigner ◽  
Christy M. McKinney ◽  
Christopher J. Wong
Keyword(s):  
Primary Care ◽  
Decision Making ◽  
Medical Center ◽  
Academic Medical Center ◽  
Primary Care Clinic ◽  
Primary Care Providers ◽  
Preventive Health ◽  
Care Providers ◽  
Care Clinic ◽  
Health Delivery

AimThe objective of this study was to seek decision-making insights on the provider level to gain understanding of the values that shape how providers deliver preventive health in the primary care setting.BackgroundThe primary care clinic is a core site for preventive health delivery. While many studies have identified barriers to preventive health, less is known regarding how primary care providers (PCPs) make preventive health decisions such as what services to provide, under what circumstances, and why they might choose one over another.MethodsQualitative methods were chosen to deeply explore these issues. We conducted semi-structured, one-on-one interviews with 21 PCPs at clinics affiliated with an academic medical center. Interviews with providers were recorded and transcribed. We conducted a qualitative analysis to identify themes and develop a theoretical framework using Grounded Theory methods.FindingsThe following themes were revealed: longitudinal care with an established PCP–patient relationship is perceived as integral to preventive health; conflict and doubt accompany non-preventive visits; PCPs defer preventive health for pragmatic reasons; when preventive health is addressed, providers use multiple contextual factors to decide which interventions are discussed; and PCPs desired team-based preventive health delivery, but wish to maintain their role when shared decision-making is required. We present a conceptual framework called Pragmatic Deferral.

scholarly journals Pediatric primary care and subspecialist providers’ comfort, attitudes and practices screening and referring for social determinants of health

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Yonit Lax ◽  
Eleanor Bathory ◽  
Sandra Braganza
Keyword(s):  
Primary Care ◽  
Low Income ◽  
Primary Care Physicians ◽  
Medical Center ◽  
Academic Medical Center ◽  
Primary Care Providers ◽  
Pediatric Primary Care ◽  
Care Providers ◽  
Low Income Children ◽  
Academic Medical

Abstract Background Early detection and management of poverty-related disorders is a recommended pediatric practice; however, little is known about variations of practice between pediatric primary care physicians and subspecialists. The objectives of this study were to assess (1) provider perceptions and attitudes toward caring for low-income children in an urban academic medical center, and (2) variations between primary care physicians and subspecialists in social and financial needs screening and referral practices for low-income children. Design/Methods Primary care providers (pediatric and family medicine) and subspecialists providing direct patient care in an urban academic medical center (response rate = 24 %, n = 85/356) completed a 24-item survey (adapted with permission from the AAP Periodic Survey of Fellows No.90) assessing feasibility and comfort screening and addressing social and financial needs, rates of screening for financial hardship, and referrals to local resources. Chi-square tests were performed. Results Among respondents, 88 % (75/85) reported comfort caring for low-income children, while 28 % (24/85) reported comfort inquiring about social and financial needs and 34 % (29/85) referring to community resources. Primary care providers more commonly than subspecialists screened for childcare (80 % vs. 59 %, p = 0.04), parental: employment (84 % vs. 59 %, p = 0.01), education (40 % vs. 17 %, p = 0.02) and mental health (86 % vs. 46 %, p = 0.0001), and less commonly screened for transportation (47 % vs. 73 %, p = 0.01). Primary care providers more commonly referred for public health insurance (74 % vs. 39 %, p = 0.001), public food assistance (30 % vs. 12 %, p = 0.04), and adult mental health services (65 % vs. 44 %, p < 0.05). Conclusions In an urban academic institution serving a population with high poverty rates, pediatric providers feel comfortable providing medical care for low-income children but lack comfort screening and addressing SDH. Though most feel it is their job to refer to resources, less than half felt it was feasible to screen for or address financial needs. Pediatric primary care providers report higher rates of screening and referring than subspecialists. Understanding variations in practice and perceptions among primary care providers and subspecialists may aid in creating interventions to increase screening and referral rates.

scholarly journals Early Implementation and Evaluation of a Teledermatology Virtual Clinic Within an Academic Medical Center (Preprint)

2021 ◽  
Author(s):  
Ethan D Borre ◽  
Suephy C Chen ◽  
Matilda W Nicholas ◽  
Edward W Cooner ◽  
Donna Phinney ◽  
...  
Keyword(s):  
Primary Care ◽  
Medical Center ◽  
Academic Medical Center ◽  
Primary Care Providers ◽  
Management Plan ◽  
Care Providers ◽  
Primary Care Clinics ◽  
Number Of Patients ◽  
Virtual Clinic

BACKGROUND Teledermatology can increase patient access; however, its optimal implementation remains unknown. OBJECTIVE This study aimed to describe and evaluate the implementation of a pilot virtual clinic teledermatology service at Duke University. METHODS Leaders at Duke Dermatology and Duke Primary Care identified a teledermatology virtual clinic to meet patients’ access needs. Implementation was planned over the exploration, preparation, implementation, and sustainment phases. We evaluated the implementation success of teledermatology using the Reach, Effectiveness, Adoption, Implementation, and Maintenance framework and prioritized outcome collection through a stakeholder survey. We used the electronic health record and patient surveys to capture implementation outcomes. RESULTS Our process consisted of primary care providers (PCPs) who sent clinical and dermatoscopic images of patient lesions or rashes via e-communication to a teledermatology virtual clinic, with a subsequent virtual clinic scheduling of a video visit with the virtual clinic providers (residents or advanced practice providers, supervised by Duke Dermatology attending physicians) within 2-5 days. The teledermatology team reviews the patient images on the day of the video visit and gives their diagnosis and management plan with either no follow-up, teledermatology nurse follow-up, or in-person follow-up evaluation. Implementation at 4 pilot clinics, involving 19 referring PCPs and 5 attending dermatologists, began on September 9, 2021. As of October 31, 2021, a total of 68 e-communications were placed (50 lesions and 18 rashes) and 64 virtual clinic video visits were completed. There were 3 patient refusals and 1 conversion to a telephonic visit. Participating primary care clinics differed in the number of patients referred with completed visits (range 2-32) and the percentage of providers using e-communications (range 13%-53%). Patients were seen soon after e-communication placement; compared to in-person wait times of &gt;3 months, the teledermatology virtual clinic video visits occurred on average 2.75 days after e-communication. In total, 20% of virtual clinic video visits were seen as in-person visit follow-up, which suggests that the majority of patients were deemed treatable at the virtual clinic. All patients who returned the patient survey (N=10, 100%) agreed that their clinical goals were met during the virtual clinic video visits. CONCLUSIONS Our virtual clinic model for teledermatology implementation resulted in timely access for patients, while minimizing loss to follow-up, and has promising patient satisfaction outcomes. However, participating primary care clinics differ in their volume of referrals to the virtual clinic. As the teledermatology virtual clinics scale to other clinic sites, a systematic assessment of barriers and facilitators to its implementation may explain these interclinic differences.

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