Comparison of satisfaction with care between two different models of HIV care delivery in St. Petersburg, Russia.

Prior to 2010, medical care for people living with HIV/AIDS was provided at an outpatient facility near the center of St. Petersburg. Since then, HIV specialty clinics have been established in more outlying regions of the city. The study examined the effect of this decentralization of HIV care on patients' satisfaction with care in clinics of St. Petersburg, Russia. We conducted a cross-sectional study with 418 HIV-positive patients receiving care at the St. Petersburg AIDS Center or at District Infectious Disease Departments (centralized and decentralized models, respectively). Face-to-face interviews included questions about psychosocial characteristics, patient's satisfaction with care, and clinic-related patient experience. Abstraction of medical records provided information on patients' viral load. To compare centralized and decentralized models of care delivery, we performed bivariate and multivariate analysis. Clients of District Infectious Disease Departments spent less time in lines and traveling to reach the clinic, and they had stronger relationships with their doctor. The overall satisfaction with care was high, with 86% of the sample reporting high level of satisfaction. Nevertheless, satisfaction with care was strongly and positively associated with the decentralized model of care and Patient-Doctor Relationship Score. Patient experience elements such as waiting time, travel time, and number of services used were not significant factors related to satisfaction. Given the positive association of satisfaction with decentralized service delivery, it is worth exploring decentralization as one way of improving healthcare services for people living with HIV/AIDS.

Beta prime regression with application to risky behavior frequency screening.

Our aim is to model the frequency of certain behavioral acts, especially those that are likely to transmit communicable diseases between persons. We develop a generalized linear model on the basis of the beta prime distribution to model the responses to a survey question of the form, 'When was the last time that you engaged in this behavior?' Intuitively, individuals reporting more recent events are more likely to have greater frequency of the risky behavior. The beta prime distribution is especially suited to this application because of its long tail. We adjust for length-biased sampling. We show how to use this distribution as the basis of a linear regression model that accounts for differences in demographic and psychological characteristics of the respondents. We discuss estimation of parameters, residuals, tests for heterogeneity of these parameters, and jackknife measures of influence. We apply the methods to a survey of alcohol abuse use among individuals who are at high risk for spreading HIV and other communicable diseases in a study conducted in Saint Petersburg, Russia.