Primary Care Providers’ Perspectives on Using Automated HIV Risk Prediction Models to Identify Potential Candidates for Pre-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 < 0.05). Residents were more likely to test for HIV than attendings (33.3% versus 16%, p < 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

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Primary Care Providers’ Knowledge, Attitudes, and Beliefs About HIV Pre-Exposure Prophylaxis (PrEP): Informing Network-Based Interventions

AIDS Education and Prevention ◽

10.1521/aeap.2021.33.4.325 ◽

2021 ◽

Vol 33 (4) ◽

pp. 325-344

Author(s):

Erik D. Storholm ◽

Allison J. Ober ◽

Matthew L. Mizel ◽

Luke Matthews ◽

Matthew Sargent ◽

...

Keyword(s):

Primary Care ◽

Claims Data ◽

Primary Care Providers ◽

Attitudes And Beliefs ◽

Care Providers ◽

Provider Education ◽

Prescribing Practices ◽

Sexually Transmitted ◽

Primary Care Settings ◽

Exposure Prophylaxis

Increasing access to pre-exposure prophylaxis (PrEP) in primary care settings for patients who may be at risk for HIV could help to increase PrEP uptake, which has remained low among certain key risk populations. The current study conducted interviews with primary care providers identified from national claims data as having either high or low likelihood of serving PrEP-eligible patients based on their prescribing practices for other sexually transmitted infections. The study yielded important information about primary care providers’ knowledge, attitudes, and beliefs about PrEP, as well as the barriers and facilitators to prescribing PrEP. Key recommendations for a provider-focused intervention to increase PrEP prescribing among primary care providers, including increasing patient education to increase demand from providers, enhancing provider education, leveraging technology, and instituting standardized sexual health checks, are provided with the goal of informing network-based interventions.

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Selection of eligible participants for screening for lung cancer using primary care data

Thorax ◽

10.1136/thoraxjnl-2021-217142 ◽

2021 ◽

pp. thoraxjnl-2021-217142

Author(s):

Emma L O'Dowd ◽

Kevin ten Haaf ◽

Jaspreet Kaur ◽

Stephen W Duffy ◽

William Hamilton ◽

...

Keyword(s):

Lung Cancer ◽

Primary Care ◽

Risk Prediction ◽

Prediction Models ◽

Risk Prediction Models ◽

Lung Cancers ◽

Primary Care Data ◽

C Statistic ◽

The Cost ◽

Predicted Risk

Lung cancer screening is effective if offered to people at increased risk of the disease. Currently, direct contact with potential participants is required for evaluating risk. A way to reduce the number of ineligible people contacted might be to apply risk-prediction models directly to digital primary care data, but model performance in this setting is unknown.MethodThe Clinical Practice Research Datalink, a computerised, longitudinal primary care database, was used to evaluate the Liverpool Lung Project V.2 (LLPv2) and Prostate Lung Colorectal and Ovarian (modified 2012) (PLCOm2012) models. Lung cancer occurrence over 5–6 years was measured in ever-smokers aged 50–80 years and compared with 5-year (LLPv2) and 6-year (PLCOm2012) predicted risk.ResultsOver 5 and 6 years, 7123 and 7876 lung cancers occurred, respectively, from a cohort of 842 109 ever-smokers. After recalibration, LLPV2 produced a c-statistic of 0.700 (0.694–0.710), but mean predicted risk was over-estimated (predicted: 4.61%, actual: 0.9%). PLCOm2012 showed similar performance (c-statistic: 0.679 (0.673–0.685), predicted risk: 3.76%. Applying risk-thresholds of 1% (LLPv2) and 0.15% (PLCOm2012), would avoid contacting 42.7% and 27.4% of ever-smokers who did not develop lung cancer for screening eligibility assessment, at the cost of missing 15.6% and 11.4% of lung cancers.ConclusionRisk-prediction models showed only moderate discrimination when applied to routinely collected primary care data, which may be explained by quality and completeness of data. However, they may substantially reduce the number of people for initial evaluation of screening eligibility, at the cost of missing some lung cancers. Further work is needed to establish whether newer models have improved performance in primary care data.

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Missed Opportunities to Prescribe HIV Pre-Exposure Prophylaxis by Primary Care Providers in Saint Louis, Missouri

LGBT Health ◽

10.1089/lgbt.2017.0101 ◽

2018 ◽

Vol 5 (4) ◽

pp. 250-256 ◽

Cited By ~ 14

Author(s):

Rupa R. Patel ◽

Philip A. Chan ◽

Laura C. Harrison ◽

Kenneth H. Mayer ◽

Amy Nunn ◽

...

Keyword(s):

Primary Care ◽

Primary Care Providers ◽

Care Providers ◽

Missed Opportunities ◽

Saint Louis ◽

Exposure Prophylaxis

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1278. Assessing Statewide HIV Pre-exposure Prophylaxis Implementation Using an All Payer Claims Database

Open Forum Infectious Diseases ◽

10.1093/ofid/ofz360.1141 ◽

2019 ◽

Vol 6 (Supplement_2) ◽

pp. S460-S461

Author(s):

Kristen Nocka ◽

Julia Raifman ◽

Christina Crowley ◽

Omar Galárraga ◽

Ira Wilson ◽

...

Keyword(s):

Infectious Disease ◽

Primary Care ◽

Rhode Island ◽

Primary Care Providers ◽

The United States ◽

Island Population ◽

Care Providers ◽

Prep Implementation ◽

Exposure Prophylaxis ◽

Zip Code

Abstract Background Pre-exposure prophylaxis (PrEP) in the form of daily tenofovir disoproxil fumarate (TDF/FTC) is a potentially transformative tool to prevent HIV infection. However, PrEP scale-up in the United States has been slow and difficult to evaluate comprehensively. All payer claims databases (APCDs) are large datasets that contain information on medical and pharmaceutical claims from most public and private payers in each state, and provide an unusual opportunity to evaluate statewide PrEP implementation efforts. Methods We used 2012–2017 data from Rhode Island’s APCD and developed an algorithm to identify individuals prescribed TDF/FTC for PrEP. We compared APCD PrEP data to electronic medical record (EMR) data at the largest dedicated PrEP program in the state, and to other comprehensive pharmaceutical claims data (AIDSVu.org). We calculated the PrEP-to-Need ratio (PnR) based on annual HIV incidence, and used multivariable logistic regression to predict ZIP code-level PrEP use, and specialty of prescribing provider (primary care vs. infectious disease). Results The Rhode Island APCD included insurance claims for 917,633 individuals (87% of the Rhode Island population). PrEP use increased substantially in Rhode Island over the 5-year period, from 13 to 331 prescriptions between 2012 and 2017, with 546 total users during this time period. Users were predominantly male (89%) and privately insured (69.1%), and concentrated in Providence County (71.5%). The PnR ratio increased from 0.2 to 4.0 from 2012–2017. Compared with AIDSVu and EMR Data, the APCD underestimated the number of PrEP users in Rhode Island, but improved over time in documenting users. Infectious diseases specialists had 8.4 times the odds (95% CI: 5.4 to 12.9) of being a PrEP prescriber compared with primary care providers. A total of 2.6% of infectious disease specialists were PrEP prescribers compared with 0.33% of PCPs. The proportion of Black or Hispanic individuals in a ZIP-code was not a significant predictor of PrEP use. Conclusion APCDs offer an innovative approach to evaluate statewide PrEP implementation comprehensively. Engaging PCPs in PrEP implementation is critical to improve overall uptake among populations most at-risk. Disclosures All authors: No reported disclosures.

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Tennessee Healthcare Provider Practices, Attitudes, and Knowledge Around HIV Pre-Exposure Prophylaxis

Journal of Primary Care & Community Health ◽

10.1177/2150132720984416 ◽

2020 ◽

Vol 11 ◽

pp. 215013272098441

Author(s):

Emily Moore ◽

Sean G. Kelly ◽

Leah Alexander ◽

Patrick Luther ◽

Robert Cooper ◽

...

Keyword(s):

Primary Care ◽

Hospital Medicine ◽

Primary Care Providers ◽

Sexual History ◽

Categorical Variables ◽

Future Research ◽

Care Providers ◽

Prescribing Practices ◽

Provider Attitudes ◽

Exposure Prophylaxis

Introduction/Objectives: Pre-exposure prophylaxis (PrEP) use in the southern United States is low despite its effectiveness in preventing HIV acquisition and high regional HIV prevalence. Our objectives were to assess PrEP knowledge, attitudes, and prescribing practices among Tennessee primary care providers. Methods: We developed an anonymous cross-sectional electronic survey from March to November 2019. Survey development was guided by the Capability, Opportunity, Motivation, and Behavior framework and refined through piloting and interviews. Participants included members of professional society and health center listservs licensed to practice in Tennessee. Respondents were excluded if they did not complete the question regarding PrEP prescription in the previous year or were not in a position to prescribe PrEP (e.g., hospital medicine). Metrics included PrEP prescription in the preceding year, PrEP knowledge scores (range 0-8), provider attitudes about PrEP, and provider and practice characteristics. Knowledge scores and categorical variables were compared across PrEP prescriber status with Wilcoxon rank-sum and Fisher’s exact tests, respectively. Results: Of 147 survey responses, 99 were included and 43 (43%) reported PrEP prescription in the preceding year. Compared with non-prescribers: prescribers had higher median PrEP knowledge scores (7.3 vs 5.6, P < .01), a higher proportion had self-reported patient PrEP inquiries (95% vs 21%, P < .01), and a higher proportion had self-reported good or excellent ability to take a sexual history (83% vs 58%, P = .01) and comfort taking a sexual history (92% vs 63%, P < .01) from men who have sex with men, a subgroup with high HIV risk. Most respondents felt obligated to provide PrEP (65%), and felt all primary care providers should provide PrEP (63%). Conclusion: PrEP provision is significantly associated with PrEP knowledge, patient PrEP inquiries, and provider sexual history taking ability and comfort. Future research should evaluate temporal relationships between these associations and PrEP prescription as potential routes to increase PrEP provision.

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Perceptions of Patient HIV Risk by Primary Care Providers in High-HIV Prevalence Areas in the Southern United States

AIDS Patient Care and STDs ◽

10.1089/apc.2019.0219 ◽

2020 ◽

Vol 34 (3) ◽

pp. 102-110

Author(s):

Kathryn Drumhiller ◽

Angelica Geter ◽

Kim Elmore ◽

Zaneta Gaul ◽

Madeline Y. Sutton

Keyword(s):

United States ◽

Primary Care ◽

Hiv Risk ◽

Primary Care Providers ◽

Hiv Prevalence ◽

Southern United States ◽

Care Providers

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Can We and Should We Produce a model for Emergency Admissions derived from Primary Care Data?

International Journal for Population Data Science ◽

10.23889/ijpds.v1i1.295 ◽

2017 ◽

Vol 1 (1) ◽

Author(s):

Kerry Bailey

Keyword(s):

Primary Care ◽

Statistical Model ◽

Risk Prediction ◽

Prediction Models ◽

Structured Interview ◽

Added Value ◽

Emergency Admissions ◽

Risk Prediction Models ◽

Primary Care Data ◽

Literature Reviews

ABSTRACT BackgroundSeveral Risk Prediction models exist for predicting emergency admissions. One exists derived solely from primary care data but this is only available in England. All the models currently available have limitations. The aim was to utilise the SAIL databank to develop a predictive model/tool using only primary care data that has comparable accuracy to the currently used risk stratification tools but overcomes the limitations of the current models available. ApproachA multidimensional approach was taken including literature reviews and qualitative interviews to the model to situate the statistical model. The need was identified to develop the contextual background in order to situate the statistical model development and understand the need for an improved model. Stakeholder groups were identified – patients, managers, General Practitioners and policy makers – and purposive sampling was used to obtain breadth and depth of representation into the subject area. Interviews were carried out in two stages initially to identify key themes and the breadth of the interest in stakeholder and influenced hypothesis generation. The second stage was to provide depth and clarity on specific themes with a more structured interview schedule. Results of the qualitave work triangulated with literature reviews influenced the statistical model build. DiscussionThe statistical challenge of building Risk Prediction models well documented. Understanding the shortcoming of current models as perceived by stakeholders is necessary to produce a model of added value which performs statistically similar however has a different functionality. The qualitative work that was carried out to situate this model added value to the models development but also raised some interesting ethical issues. The validity and performance of the models although important is only one aspect that influences whether GPs would use a risk prediction model and how acceptable it is to stakeholders. None of the patients interviewed in this thought that their data was, or would be without their knowledge, used in risk prediction models yet all were patients at practices where this was happening or had morbidities which would have necessitated the use of several in primary care.

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