INTRODUCTION
Given high rates of HIV infection worldwide, biomedical prevention interventions have recently become a cornerstone of HIV prevention efforts. Preexposure prophylaxis (PrEP), a biomedical intervention, has proven effective among key high-risk populations, including men who have sex with men, high-risk heterosexuals, and injection drug users.1–4 1–4 1–4 1–4 In clinical trials, daily oral PrEP using emtricitbine + tenofovir disoproxil fumarate (Truvada, Gilead Sciences, Foster City, CA) has been between 74% and 92% effective in reducing one's HIV risk, depending on the population studied and measures of detectable drug levels.5
PrEP is a promising approach to reducing HIV incidence. Its real-world use, which has been limited,6 may be due to several factors. First, potential PrEP users must know about it, understand its risks and benefits, and be willing to take it.7 Studies have shown that certain high-risk populations have limited knowledge of PrEP but want to learn more about it.8 Furthermore, appropriate PrEP administration is available by prescription only and requires specialized counseling, regular HIV testing, close clinical monitoring for side effects, and follow-up beyond routine clinical care.5 These tasks require a significant commitment from both patients and providers and may make both groups apprehensive about using PrEP. Using PrEP without consistent clinical monitoring or patient adherence may increase the risk of side effects such as renal toxicity and future drug resistance.5
HIV providers will be essential in the scale-up and delivery of PrEP as they are most familiar with antiretrovirals (ARVs) and may therefore be frontline providers of PrEP. Previous studies in the United States and abroad have assessed HIV providers' knowledge and perceptions of PrEP and perceived barriers to PrEP uptake.9–17 9–17 9–17 9–17 9–17 9–17 9–17 9–17 9–17 Commonly cited issues have included: (1) comfort with prescribing ARVs for prevention and debate over whether this role is better suited for HIV specialists or primary care providers16 ; (2) ability and willingness to identify potential PrEP users by evaluating patients' HIV risk18 ; (3) levels of real-world PrEP effectiveness and adherence balanced with the potential for risk compensation and drug resistance10,13,16 10,13,16 10,13,16 ; (4) costs related to medications and the availability of insurance coverage8,10,13,14 8,10,13,14 8,10,13,14 8,10,13,14 ; and (5) ethical allocation of ARVs.8,13 8,13
Findings from studies of providers highlight the complexities of scaling-up and delivering PrEP in real-world settings.8,9,19 8,9,19 8,9,19 Although general knowledge about and support for PrEP have increased since the Food and Drug Administration (FDA) approved Truvada and the Centers for Disease Control and Prevention (CDC) released the prescribing guidelines, knowledge of PrEP among providers has increased only slightly,13 and actual prescribing rates remain relatively low.6 Understanding providers' perceptions of PrEP and gauging their willingness to provide it will help to inform the implementation process and to make PrEP a more useful tool against HIV.
In Miami, Florida and Washington, District of Columbia, 2 US cities with high HIV prevalence rates,20 PrEP availability may help to significantly reduce HIV incidence. The CDC funded both cities through the Enhanced Comprehensive HIV Prevention Planning Initiative (ECHPP) to maximize uptake of high-impact HIV prevention methods.21 The ECHPP initiative predated the release of many of the sentinel PrEP studies, and therefore did not include an initiative on PrEP, but did include “provision of Post-Exposure Prophylaxis (PEP) to populations at greatest risk.” The District of Columbia and Miami-Dade Departments of Health collaborated with District of Columbia and University of Miami Center for AIDS Research to assist with implementation of this initiative. While assessing the potential scale-up of PEP,22 the District of Columbia and Miami Center for AIDS Research ECHPP teams also conducted a provider assessment evaluating the potential for PrEP uptake. Our objective was to use latent class analysis (LCA) techniques to identify subgroups of providers, based on their attitudes toward prescribing PrEP, to characterize which types of providers perceive fewer barriers to PrEP implementation and may therefore be more likely to intend to prescribe PrEP.
METHODS
Survey Administration
Surveys were administered between March 2012 and March 2013 to HIV providers in Washington, District of Columbia and Miami-Dade County, Florida, assessing provider knowledge, attitudes, and beliefs regarding PrEP and who should receive it, as well as perceived barriers and facilitators to PrEP provision. Survey methods varied slightly between cities, but identical survey items were administered in both cities.22 The target study population included infectious disease providers and HIV providers who had treated at least 1 HIV-positive patient in the previous year. Listings of HIV providers from physician societies, training centers, and health departments in both cities were used to identify potential participants.22 A brief, internet-based, anonymous survey was administered to 124 providers in District of Columbia and 107 HIV providers in Miami-Dade County using Research Electronic Data Capture (REDCap, Vanderbuilt University, Nashville, TN) and Survey Monkey, respectively, or a mailed hard copy survey. In both cities, providers received periodic mail, telephone, and e-mail reminders to encourage participation. Online or written informed consent was obtained and providers completing the survey received a $20 incentive. IRB approval was obtained from the George Washington University, the District of Columbia Department of Health, the University of Miami, and Columbia University.
Survey Domains and Analytic Methods
Survey requests were sent to 231 providers; 142 providers (District of Columbia, n = 63; Miami, n = 79) responded (overall response rate 61%). Data from the 2 cities were subsequently merged and aggregated for analysis purposes.
PrEP Knowledge/Experience
There were 5 questions regarding knowledge of and experience with PrEP (familiarity with iPrEX results1 CDC guidelines,23 practice having written PrEP protocols in place, frequency of PrEP requests, and ever having prescribed PrEP). These questions were combined into a single, “lack of PrEP knowledge/experience” scale with higher values indicating less knowledge/experience. This scale had an implied composite reliability of 0.83.24
Patient Factors Associated With Intended PrEP Prescription
The survey assessed how several factors might influence providers' decisions to prescribe PrEP, on a scale from 1 (“least likely to prescribe”) to 5 (“most likely to prescribe”). Variables included whether patients had: multiple sex partners; history of failing to use condoms; partners with known HIV; history of sexually transmitted diseases; history of noninjection drug use; history of injection drug use; history of not returning for medical visits; and history of medication nonadherence. Although this survey question did not specifically ask about PrEP prescribing among men who have sex with men, it was presumed that this population would be captured through the other patient populations included in the survey question. These factors were combined into a “likelihood of prescribing PrEP” scale, with higher values reflecting higher likelihood of prescribing PrEP. This scale's composite reliability was 0.94.
Provider Perceptions, and Intentions Regarding PrEP
LCA was used to classify providers based on their attitudes toward prescribing PrEP. Nine survey items were used to identify the latent categories. Each variable was coded, so that lower scores represented the “lowest likelihood to prescribe PrEP.” Latent class indicators included 2 items asking providers to rate on a 1–5 scale the effectiveness of oral PrEP and vaginal microbicides, gels, and creams in preventing HIV transmission. Another 7 items measured providers' level of agreement using a Likert scale ranging from 1—strongly agree to 5—strongly disagree with the following statements: (1) it is feasible to provide PrEP in practice; (2) there is adequate time to provide PrEP in practice; (3) PrEP will promote HIV resistance; (4) PrEP will promote risky behavior; (5) I will provide PrEP to HIV discordant couples; (6) the availability of PrEP may empower women who are unable to negotiate consistent condom use with their partners; and (7) the cost of PrEP will still be a significant barrier for those who may benefit, even if PrEP is safe, efficacious, and made available.
Covariates
The following covariates were examined to identify the provider characteristics of each of the latent classes: age, sex, race/ethnicity, years of practice, field of practice, number of patients seen in the clinician's practice in the previous month, number of HIV patients seen in the clinician's practice in the previous 3 months, number of HIV patients seen by the clinicians in the previous 3 months, and the “lack of PrEP knowledge/experience” and “likelihood of prescribing PrEP” scales.
Rationale and Methods for the LCA
LCA aims to identify subgroups of individuals who respond differently on a series of categorical or ordered categorical variables. We used this method to see whether there were distinct subgroups of providers with different response patterns. The LCA was conducted using Mplus version 7.25 First, we determined the number of classes to include by comparing the fit of models including different numbers of classes. We used Bayesian information criteria,26 Akaike information criteria (AIC),27 the sample size adjusted Bayesian information criteria (ABIC),28 and entropy statistic as the criteria to compare model fitting with different numbers of classes assigned. To avoid having local maxima, each model was originally estimated with 500 starting values, with the 50 runs with the highest likelihood after 20 iterations continued to full maximization. If the maximum likelihood solution was not repeated numerous times in the set of 50, this was raised to 1500 initial starts and 500 to completion, and then 3000 and 1000, thereby ensuring that a substantial proportion converged to the same maximum. Because of the missing data, the LCA was completed with multiple imputation with 30 sets of imputed data and results combined within Mplus.25
Survey participants' demographics and practice characteristics were described using univariate analysis. The latent class solution is described by the unconditional probability of each class and the conditional probability of endorsing a 4 or 5 on each of the 9 input items for each class. We used a classify–analyze strategy to compare the other variables by latent class membership, which is most appropriate with high entropy models. Entropy with values approaching 1 indicates clear delineation of classes.29 For categorical variables, χ2 tests were combined across imputations using the method described by Li et al,30 which results in an F-statistic and associated P value. The equality of our 2 scales across classes was tested using Proc MIanalyze in SAS 9.3, which results in a t test statistic. In tables, we present the observed data means and frequencies; however, all overall statistical tests reported are based on the combined, multiply imputed data. We report the significance of the individual items composing the scales based on the observed data using a χ2 statistic.
RESULTS
Participant Characteristics
There were slightly more respondents from Miami than from Washington (Table 1 ). There were slightly more male respondents (59%), with modal age category of 40–49. Most participants were non-Hispanic white (49%), followed by Hispanic (25%), and black (13%). Half of the respondents self-identified as infectious disease specialists, and more than 25% as primary care physicians (18% internal medicine, 11% family medicine) who provided some HIV care. Nearly half (47%) of providers had been practicing for more than 20 years, 82% had seen more than 200 HIV-positive patients in their practices, and 73% had seen more than 20 HIV-positive patients in the previous 3 months. More than half of providers (53%) agreed that PrEP was effective or most effective and 24 (17%) had prescribed PrEP before completing the survey. Those providers who had previously prescribed PrEP were more likely to come from practices with a written PrEP protocol, had more patients ask for PrEP, and had lower scores on the “lack of PrEP knowledge scale” (data not shown).
TABLE 1-a: Provider Demographics and Practice Characteristics
TABLE 1-b: Provider Demographics and Practice Characteristics
Latent Class Analysis
The LCA identified 2 distinct classes of providers. The comparisons of LCA model fit (Table 2 ) show that no solution was favored by all 3 information criteria, but the 2-class solution was favored by 2 of the 3 criteria (AIC, ABIC) over the single class solution. The 3-class solution had lower AIC and ABIC than did the 2-class solution. However, whereas the 2-class solution was replicated in 41 of 50 solutions of the random-start process, the 3-class solution was only replicated in 6 of 1000 random starts. Furthermore, when moving from 1000 to 1500 and then 3000 initial random starts, a new maximum was found each time. As this is indicative of local maxima, we focused on the 2-class solution. The entropy of the 2-class solution was good (0.904); the average probability of being in class 1 for those classified in class 1 was 0.968 and that of being in class 2 for those classified in class 2 was 0.978. There were no differences in the proportions from each site across the 2 classes (χ2 (1) = 0.003, P = 0.958).
TABLE 2: LCA Model Fit Statistics
Comparison of the 2 Provider Classes
Table 3 shows the probability and 95% confidence intervals of either agreeing or strongly agreeing with the statements by the 2 classes of respondents. This information is presented as a response profile in Figure 1 . Class 1, the larger class (95 respondents), tended to agree less with statements that oral PrEP and microbicides can decrease the risk of HIV acquisition than did class 2 (47 respondents). A significantly higher proportion of class 2 vs. 1 agreed that PrEP was feasible in their clinics and that they had adequate time to prescribe PrEP. A higher proportion of class 2 vs. 1 respondents also agreed that they would prescribe PrEP to serodiscordant couples and that it might empower women unable to negotiate condom use. With respect to perceived barriers, class 2 also had a slightly higher probability of agreeing that cost might pose a significant barrier.
TABLE 3: Predicted Probabilities of Agreeing or Strongly Agreeing With LCA Variables by Class*
FIGURE 1: Probability of agreement with statements by latent class analysis groups.
PrEP Knowledge and Experience Scale
There were no differences across classes with respect to demographic characteristics, medical specialty, years of, or size of practice (Table 4 ). There was, however, a significant difference in the PrEP knowledge/experience scale. Class 2 showed the higher score, indicating less experience with PrEP (t (22.7) = 2.88, P = 0.009). Differences were explained by class 2 being significantly more likely than class 1 to be working in practices without written PrEP protocols (96% vs. 76%; χ2 (2) = 11.41, P = 0.003); significantly less likely to have had PrEP requests in the previous 6 months (71% vs. 41%; χ2 (2) = 13.62, P = 0.004); and significantly less likely to have ever prescribed PrEP (90% vs. 63%; χ2 (2) = 18.74, P < 0.001).
TABLE 4-a: Demographic and Clinical Characteristics of the LCA Groups
TABLE 4-b: Demographic and Clinical Characteristics of the LCA Groups
Likelihood of Prescribing PrEP to Certain Patients
There was a moderate but not statistically significant difference in the likelihood of prescribing PrEP to patients of differing characteristics scale (t (21.5) = 1.95, P < 0.07). More clinicians in class 2 than class 1 were likely to prescribe to individuals with multiple sex partners (43% vs. 20%; χ2 (4) = 10.13, P = 0.04), and a history of noninjection drug abuse (24% vs. 7%; χ2 (2) = 18.08, P = 0.001). Both classes, however, reported low likelihood of intending to prescribe to patients with a history of missing medical visits (4.0%–4.8%) or a history of medication nonadherence (2.4%–4.0%).
DISCUSSION
Our survey of HIV providers' knowledge and attitudes about PrEP and willingness to provide it in 2 high HIV prevalence cities found that most (53%) agreed that PrEP is an effective HIV prevention approach. However, a small percentage of providers (17%) reported ever prescribing PrEP. In 1 national survey conducted in June 2013, several months after this survey and after the release of the updated CDC guidelines, 74% of infectious disease specialists supported PrEP as a prevention strategy, but only 9% reported actually prescribing PrEP.31 Though our study found twice this rate of prescribing (17%) even before this national study and the final CDC guidelines, this is still quite a low rate of prescribing.
We identified 2 distinct groups of providers: one found PrEP to be moderately effective, and perceived fewer barriers to prescribing PrEP than did the other group, in which participants considered PrEP to be less effective. Interestingly, no significant differences were found between the 2 classes of providers in their demographic characteristics or field of, size of, or years in practice. However, there were significant differences between them regarding their knowledge about and familiarity with PrEP. For example, the providers finding PrEP to be moderately effective with fewer prescribing barriers were more likely to have received requests for PrEP or have ever prescribed it. Thus, those with more experience with PrEP perceived fewer barriers.
Perceptions regarding practice-related barriers also set the 2 provider groups apart. Class 1, the group that found PrEP to be less effective and with barriers, was more likely to agree with statements regarding practice-related barriers. Previously conducted studies have documented that practice-related perceived barriers to PrEP provision are common among providers caring for HIV-infected or high-risk persons. For example, providers in a California-based survey frequently expressed belief that their clinics' current care models were insufficient to adequately support PrEP provision.9 Other studies have also found that one of the most common perceived barriers to PrEP provision among infectious disease physicians was its time-consuming nature.31 In our study, nearly all providers in class 2 expressed high levels of agreement with statements related to the feasibility of PrEP delivery and the time required for it as compared with only half of class 1, but class 1 participants generally had less experience with PrEP than those in class 2, and were more likely to work for medical practices without written PrEP protocols. Although class 1 providers expressed sentiments that providing PrEP could be burdensome, there are no studies that we are aware of that have systematically assessed provider experiences during the provision of PrEP. These findings highlight the need for education about PrEP and assistance in implementing structural or procedural changes needed in clinics to facilitate efficient and effective PrEP delivery. Such interventions may prevent potential misconceptions of providers with little PrEP experience about the ability to provide this service.
Another important difference between the provider groups was that those who found PrEP moderately effective and perceived fewer barriers had comparatively more knowledge about and experience with PrEP, and were more likely to prescribe it to persons with multiple sex partners and noninjection drug users. As noninjection drug use is neither a direct risk factor for HIV nor a current risk behavior meeting the criteria for PrEP use, future studies should examine whether providers are more likely to prescribe to noninjection drug users whose partners are HIV positive or who have multiple sex partners, for example. These findings suggest physicians may exhibit the same reluctance to prescribe PrEP to drug users as they did with prescription of ART to drug users early in the HIV epidemic.32,33 32,33 Despite the fact that the current CDC PrEP guidelines do not recommend prescribing solely based on noninjection drug use, there is sufficient evidence to suggest that this may be a factor for consideration in assessing one's high-risk behaviors and the need for PrEP. Both groups, however, had clear concerns about prescribing PrEP to individuals with characteristics indicative of nonadherence15 ; less than 5% of providers were likely to prescribe PrEP to patients who miss medical appointments or who have been nonadherent with other medications. Ensuring high rates of adherence with PrEP use is essential to maximizing its efficacy,5 and providers' responses may reflect this concern.
Both groups of providers also identified potential barriers to PrEP use related to the risk for drug resistance and risk compensation that were consistent with findings from other studies of potential physician providers of PrEP. A 2013 study of US infectious disease physicians found that, while most (74%) supported PrEP provision, 77% of those who expressed reluctance were worried about adherence and the potential for future drug resistance. Furthermore, 53% were concerned about the cost of the drug and reimbursement procedures.31 Similarly, a 2013 survey of HIV health care providers in the United States found that drug resistance, risk compensation, and adherence were respondents' top 3 concerns; drug cost was the fourth most common concern.15 Potential providers of PrEP ought to be familiar with the results of the sentinel PrEP efficacy studies and their follow-on open label studies. These studies have found very low rates of transmitted resistance and no increase in risky behavior among PrEP users.1,2,4,34,35 1,2,4,34,35 1,2,4,34,35 1,2,4,34,35 1,2,4,34,35 However, as real-world implementation and scale-up begin, continued monitoring of these issues will be essential.
This study has some potential limitations. This study used a convenience sample and we are unable to compare the characteristics of respondents to those who did not respond. However, based on the practice characteristics provided, the participants in this study represent experienced HIV providers in 2 major urban areas. It does not reflect the perspectives of providers not treating HIV-positive patients and therefore may not be generalizable to the broader provider population who may turn out to be the primary PrEP prescribers.36–38 36–38 36–38 Furthermore, it only includes providers in areas of high HIV prevalence and thus may not represent the perceptions and intentions of providers in lower HIV prevalence areas. Primary care provider perspectives may vary with respect to familiarity, concerns, and experience with PrEP and HIV prevention . Given the limited number of HIV providers, primary care providers' participation in PrEP provision will be necessary to maximize scale-up of PrEP. Therefore, future studies should elicit the perspectives and prescribing experiences of non-HIV primary care providers.
As PrEP becomes more widely available and its use potentially increases, providers will need to learn about PrEP and determine how best to deliver it in their practices. Notably, when our survey was administered efficacy results were only available from the iPrEX study,1 and soon thereafter the US FDA approved Truvada for the use of PrEP. Additionally, the surveys were administered before release of both the CDC interim23,39,40 23,39,40 23,39,40 and final guidelines5 on PrEP as well as the release of findings from key studies of PrEP efficacy among heterosexuals2,4 2,4 and injection drug users.3 As the official guidelines are now available, provider familiarity with PrEP and overall uptake will likely increase and a follow-up survey of providers would be warranted given the evolution of our knowledge of PrEP since this survey was initially administered.12,13,17,18 12,13,17,18 12,13,17,18 12,13,17,18 Although provider knowledge of PrEP increased following the release of the iPrEx trial results,13 as of 2013, as many as 25% of providers in some settings were still unaware of the FDA approval or CDC guidance.41 It is therefore important to monitor future changes in provider knowledge, attitudes, and practice.5 Providing technical support to facilitate implementation of clinical guidelines and resources for billing and insurance coverage will help providers make PrEP accessible.
PrEP should be considered a tool in the armament for HIV prevention . Providers must be comfortable with and have the tools to identify persons at high risk for HIV infection and be prepared to assist them with determining the most appropriate HIV prevention method for them while taking into consideration their lifestyle and risk profile. In anticipation of patient requests for PrEP, providers must have protocols to properly identify and monitor PrEP users. They must also be comfortable identifying persons who are not PrEP candidates but may benefit from other HIV prevention methods, including behavior modification and condom use.13 Finally, monitoring and evaluating PrEP implementation and provider attitudes over time is essential to addressing barriers to uptake, so that PrEP is accessible to patients who may benefit from it.
ACKNOWLEDGMENTS
The authors thank the staff at the DC Department of Health HIV/AIDS Hepatitis, STD, TB Administration, the Florida Department of Health, the Miami-Dade County Health Department Office of HIV/AIDS, and the study participants in both DC and Miami, without whom these data would not be possible. The authors also acknowledge the DC Developmental Center for AIDS Research (P30AI087714) and Miami Center for AIDS Research (P30AI073961), and the ECHPP study teams in both cities.
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