Engagement with the provider is essential for the patient receiving health care. It is the cornerstone for the active engagement of the patient in all aspects of the decision-making processes in HIV care. Patient-provider engagement has been defined as “patient-provider relationships that promote the use of health care services and are characterized by active listening and supportive decision making - - - associated with antiretroviral therapy (ART) maintenance and viral suppression” (Mitchell et al., 2017, p.1768). The 90-90-90 approach to HIV care entails 90% of HIV infected persons being aware of their HIV status, 90% of this number linked to care and receiving HIV treatment, and 90% of those enrolled in care having an undetectable viral load. To achieve this ambitious goal, patient engagement with the provider is fundamental. The question of whether this engagement varies by sociodemographic and psychosocial factors related to the patient has taken on added significance as we work toward attaining the goal of 90% of those receiving ART maintaining an undetectable viral load.
The purpose of this secondary data analysis is to examine the relationship of sociodemographic and psychosocial variables with patient-health care provider engagement in care. Identifying what is key to this complex relationship will contribute to our knowledge and ability to develop improved patient-provider relationships. Such improvement may be vital to patients’ commitment to achieve and remain virally undetectable.
Methods:
This analysis was conducted with 1811 persons from Canada, China, Namibia, and the mainland U.S. and Puerto Rico living with HIV. In this analysis, we evaluated the patient reports of engagement with their healthcare provider as measured by the 13-item, 4-point Healthcare Provider (HCP) Engagement Scale in which a lower scores indicates greater provider engagement. We compared means by sociodemographic variables including age, gender (Male, Female, and Gender non-conforming) race/ethnicity (White, Black, Hispanic, and Other [Asian, Hawaiian Islander, Alaska Native]), education, (High school or less, and College or more) and the inability to pay for needed health care. We then regressed the HCP Scale with all of the sociodemographic categories. Finally, we conducted a step-wise regression which forced in the sociodemographic variables and then tested the psychosocial indices including the Chronic Disease Self-Efficacy Scale, the Sign and Symptom Checklist, the Center for Epidemiologic Studies Depression Scale (CESD) and the Marginalization and Social Capital Scale.
Results:
The average of the HCP engagement scale was 17.5 (standard deviation 7.0). Males had a 1.0 higher score than females (p<.01) but no difference with the gender non-conforming category (p=.35). Whites had a 1.6 lower score than Other race (p<.01), but differences with Black and Hispanic groups were not significant (p=.55 and p=.25, respectively). Those who stated that they previously needed healthcare but could not pay had a 1.3 higher score (p<.01) compared with those who denied problems with affordability. HCP engagement did not differ by education (p=.98), but there was a r=-0.05 correlation (p=.03) with age.
Associations that were significant in bivariate analysis were robust to adjustment in regression analysis in a model that included all of the sociodemographic variables and explained 1.4% of the variance in the HCP engagement scale. Associations that were not significant in bivariate testing were not significant in the regression models. In a stepwise model that forced all demographic variables and tested the psychosocial scales and indices, age and ability to pay were no longer significant predictors but Other Race (B=2.8; p<.01 with White reference group) and Female (B=-1.1; p<.01 with Male reference group) remained significant. The addition of the Sign and Symptom Checklist (B=.07; p<.01), Chronic Disease Self-Efficacy scale (B=-0.38; p<.01), Marginalization and Social Capital scale (B=-0.37; p<.01), and CESD (B=.04; p=.02) increased the amount of variance explained to 11%.
Conclusions:
These findings have implications for nurses and nursing. The significant difference between White vs. Other racial/ethnicity category (Asian/ Pacific Islander, Hawaiian Islander, Alaska Native) indicates that individuals of these races/ethnicities have less engagement with their providers and require more attention from health care personnel. It is not clear whether this finding is a consequence of physical distance to health care resources, cultural aspects concerning maintenance of personal privacy, or barriers related to interpersonal and/or cultural factors regarding the provider and/or health care facility. Distance from the health care facility may be one of the keys to patient engagement but this requires further research.
The differences by gender as well as ability to pay are significant and require further investigation. Lack of access to medication at what is an affordable rate for those who are not privy to no-cost or low-cost medications may be an impediment to achieving 90% adherence as are the hours of the pharmacy and its’ distance from the person living with HIV. The question of access to medication requires a solution if 90-90-90 is to be achieved. Given that the percentage of variance explained by these variables was 11%, our study indicates the complexity of the issue of patient-health care provider engagement and the need for further research.