The primary purpose of this dissertation was to understand if emergency department utilization patterns are associated with subsequent drug overdose death. Specifically, it was hypothesized that that increasing emergency department (ED) utilization (as measured by such indices as two or more visits in 72-hours, two or more visits in a 30-day period, four or more visits in a 365-day period) was associated with increasing risk of fatal unintentional drug overdose compared with patients without two or more visits in a given time frame. Using ED data from the New York State Department of Health's (NYSDOH) Statewide Planning and Research Cooperative System (SPARCS) for the years 2006-2010 linked with unintentional fatal prescription drug overdose data from death certificates and medical examiner case files from the New York City Department of Health and Mental Hygiene (NYC DOHMH) and the NYSDOH for the years 2006-2010, a retrospective dynamic cohort of ED encounter data was conducted. In the first study, the patient population consisted of 1,755,734 New York State residents who were 18-64 years of age and had selected diagnoses on their entry visit. Extended Cox proportional hazards regression models were conducted to estimate the association of ED utilization patterns and subsequent drug overdose death. Compared to time periods in which patients had no visits within a year, patients who had 3, 4-10, or > 10 visits in a year had elevated risks of prescription drug overdose death after adjustment for demographic characteristics: 3 visits (adjusted hazard ratio (aHR 4.77, 95% CI 3.60, 6.15)), 4 - 10 (aHR 7.39, 95%CI 5.81, 9.41), and > 10 ED (aHR 18.37, 95% CI 13.38, 25.23). ED utilization patterns are strong predictors of subsequent overdose death. Understanding the timing of overdose death in relation to ED utilization is essential to recognizing which patients to target with overdose prevention interventions. Identifying time-periods of increased risk may be used as an indicator for developing prediction tools to classify patients at increased risk for overdose.

published_or_final_version / Community Medicine / Master / Master of Public Health

The dissertation is intended to guide the selection and implementation of health department-led interventions with a long-term goal of reducing opioid overdose deaths. This dissertation is comprised of three aims. First, a narrative review describes models of buprenorphine treatment, summarizes retention in buprenorphine treatment, and includes descriptions of how each study defined and measured retention in treatment to aid cross-study comparisons. Trends in buprenorphine retention, as well as heterogeneity in trends, are described, and sub-analyses examine the role clinician experience in inducting patients on buprenorphine treatment may play in promoting retention. Lastly, the effect of a specific intervention—academic detailing—aimed at reducing the prescribing of opioid analgesics is measured using methods aimed at isolating the impact of a policy intervention that occurred at the same time as the detailing campaign. Overall, this dissertation finds a lack of consistency in how retention in buprenorphine treatment is measured, which precludes easy identification of the most effective models and interventions for retention in buprenorphine treatment. Additionally, significant variation in buprenorphine treatment retention and trends in buprenorphine treatment was observed, suggesting opportunities for improvement. From 2015 to 2019, retention in buprenorphine increased among New York City residents; however, in 2019, the predicted prevalence of retention for three months was 52.7% and 34.6% for six months, below rates observed in other studies. Lastly, this dissertation should prompt public health officials to reconsider using academic detailing campaigns to decrease opioid analgesic prescribing, given that decreases in prescribing practices were only observed following one detailing campaign, which coincided with a policy change, and did not occur following another campaign, which took place two years after the policy change.

The rise in America’s drug poisoning rates has been described as a public health crisis and has long been attributed to the rapid rise in opioid supply due to increased volumes of medical prescribing in the United States that began in the mid-1990s and peaked in 2012. In 2016, the introduction of the “deaths of despair” hypothesis provided a more nuanced explanation for the rising rates of drug poisoning deaths: increasing income inequality and stagnation of middle-class worker wages, driven by long-term shifts in the labor market, reduced employment opportunities and overall life prospects for persons with a high school degree or less, driving increases in “deaths of despair” (i.e., deaths from suicide, cirrhosis of the liver, and drug poisonings). This focus on economic and social conditions as capable of shaping geospatial differences in drug demand and attendant drug-related harms (e.g., drug poisonings) provides a larger context to factors potentially underlying the heterogeneous distribution of prescription opioid supply across the United States. However, despite the likelihood that economic and social conditions may be important demand-side factors that also interact with supply-side factors to produce the rates of fatal drug poisonings, little information exists about the effect of area-level socioeconomic conditions on fatal drug poisoning rates, and no study has investigated whether socioeconomic conditions interact with prescription opioid supply to affect area-level rates of fatal drug poisonings. The overarching goal of this dissertation was to test the independent and joint effects of supply- and demand-side factors, operationalized as prescription opioid supply and socioeconomic conditions, on fatal drug poisoning in the U.S. First, a systematic review of the literature was conducted to critically evaluate the evidence on the ecological relationship of prescription opioid supply and socioeconomic conditions on rates of drug poisoning deaths. The systematic review provides robust evidence of the independent effect of each prescription opioid supply and socioeconomic conditions on rates of drug poisoning deaths. The gap in the literature on the joint effects of prescription opioid supply and socioeconomic conditions was clear, with no study examining the interaction between supply- and demand-side factors on rates of fatal drug poisonings. Moreover, although greater prescription opioid supply was associated with higher rates of fatal drug poisonings in most of the studies, two studies presented contradictory findings, with one study showing no effect of supply on drug poisoning deaths and the other showing locations with higher levels of prescription opioid supply were associated with fewer drug-related deaths. Three limitations were also identified in the reviewed studies that could partially explain the observed associations. First, although studies aggregated data on drug poisoning deaths to a range of administrative spatial levels, including census tract, 5-digit ZIP code, county, 3-digit ZIP code, and state, no study investigated the sensitivity of findings to the level of geographic aggregation. Second, spatial modeling requires the assessment of spatial autocorrelation in both the unadjusted and adjusted data, but few studies even assessed spatial autocorrelation in the data, and fewer still incorporated spatial dependencies in the model. This is important because when spatial autocorrelation is present, the independence assumption in standard statistical regression models is violated, potentially causing bias and loss of efficiency. Third, studies operationalized prescription opioid supply and socioeconomic conditions using a variety of different measures, and no study assessed the sensitivity of findings to the different measures of supply and socioeconomic conditions. Second, the ecological relationship between prescription opioid supply and fatal drug poisonings was examined. For this, pooled cross-sectional time series data from 3,109 U.S. counties in 49 states (2006-2016) were used in Bayesian Poisson conditional autoregressive models to estimate the effect of county prescription opioid supply on four types of drug poisoning deaths: any drug (drug-related death), any opioid (opioid-related death), any prescription opioid but not heroin (prescription opioid-related death), and heroin (heroin-related death), adjusting for compositional and contextual differences across counties. Comparisons were made by type of drug poisoning (any drug, any opioid, prescription opioids only, heroin), level of geographic aggregation (county versus state), and measure of prescription opioid supply (rate of opioid-prescribing per 100 persons and morphine milligram equivalents per-capita). Results indicated a positive association between prescription opioid supply and rates of fatal drug poisonings consistent across changes in type of drug poisoning, level of aggregation, and measure of prescription opioid supply. However, removing confounders from the model caused the direction of the effect estimate to reverse for drug poisoning deaths from any drug, any opioid, and heroin. These results suggested that differences in adjustment for confounding could explain most of the inconsistent findings in the literature. Finally, a rigorous test of the hypothesis that worse socioeconomic conditions increase risk of fatal drug poisonings at the county level, and interact with prescription opioid supply was conducted. This analysis used the same pooled cross-sectional time series data from 3,109 U.S. counties in 49 states (2006-2016). The analysis modeled the effect of five key socioeconomic variables, including three single socioeconomic variables (unemployment, poverty rate, income inequality) and two index variables (Rey index, American Human Development Index [HDI]) on four types of drug poisoning deaths: any drug (drug-related death), any opioid (opioid-related death), any prescription opioid but not heroin (prescription opioid-related death), and heroin (heroin-related death). Using a hierarchical Bayesian modeling approach to account for spatial dependence and the variability of fatal drug poisoning rates due to the small number of events, the independent effect of socioeconomic conditions on rates of drug poisoning deaths and their joint multiplicative and additive effect with prescription opioid supply were estimated. Results showed that rates of fatal drug poisonings were higher in more economically and socially disadvantaged counties; the five key indicator variables were differentially associated with drug poisoning rates; and the American Human Development Index (HDI) and income inequality were most strongly associated with fatal drug poisoning rates. Finally, the results indicate that both HDI and income inequality interact with county-level prescription opioid supply to affect drug poisoning rates. Specifically, the effect of higher prescription opioid supply on rates of fatal drug poisonings was greater in counties with higher HDI and more equal income distributions than counties with lower HDI and less equal income distributions. Overall, this dissertation increased knowledge about the separate and conjoint roles of supply- and demand-side factors in the geospatial distribution of fatal drug poisonings in the U.S. The idea that area-level prescription opioid supply are key drivers of prescription drug use, misuse, and addiction and the attendant consequences, including nonfatal and fatal drug poisonings, has been in the literature for well over a decade. However, no study to date has shown that area-level socioeconomic conditions modify the effect of prescription opioid supply on fatal drug poisonings. By identifying important contextual factors capable of modifying the effect of prescription opioid supply reductions on mortality, high-risk geographic areas can be prioritized for interventions to counter any unintended effects of reducing the prescription opioid supply in an area. As federal and state policies continue to target the rising rates of fatal drug poisonings, these findings show that area-level socioeconomic conditions may represent an important target for policy intervention during the current drug poisoning crisis and a critical piece of information necessary for predicting any future drug-related crises.

The purpose of this study was to determine the factors that cause resistance in older adults to participation in substance abuse treatment programs.

Thesis (Ph.D. (Pharmacy)) -- University of Limpopo, 2022 / Antiretroviral (ARV) management in children is considered a challenging process, and patients receiving ARVs remain at risk of medication errors. Recently, there has also been a noticeable increase in Treatment Failure (TF) and the development of drug resistance amongst children on ART. However, ART failure amongst children seems to be an under-recognised issue, and adherence to treatment guidelines is reported to be a challenge among nurses caring for People Living with HIV (PLWHIV). Hence, the aim of this study was to explore the prescribing practices, and to determine the knowledge, understanding, and competence levels of NIMART-trained nurses’ in the management of children on Antiretroviral Therapy (ART) in Public Health Care (PHC) facilities located in a rural district of Limpopo Province. To attain the purpose of the study, the researcher in this study adopted a mixed-method, in an explanatory sequential manner. The quantitative phase adopted a descriptive cross-sectional and retrospective census of medical records to determine whether or not the children on ART were prescribed the correct ARV regimen, dose, strength, dosing frequency and received the correct quantities to last until the next appointment date. Whereas the qualitative phase embraced a total purposive sampling of the NIMART-trained professional nurses to explore their knowledge, understanding and views of ART management in children. The results highlighted that these children under study even though they were prescribed a correct ARV regimen in (n=7045; 96%) of the cases;they were only correctly dosed in (n=7797; 53%); and prescribed the correct strength (n=9539; 77%), with only (n=2748; 36.9%) having received the correct quantity of treatment to last them until the next appointment date. Most nurses even though they rated themselves very knowledgeable and competent in paediatric HIV/AIDS management. This finding was contradicting the results obtained from the medical records, as well as their responses to the given case scenario depicted some level of non-adherence to treatment guidelines as well as a lack of understanding of ARV management. From the findings of this ARV utilisation review and the implementation of the developed ART dosing and dispensing training programme. The study concludes that the nurse's prescribing practice was irrational in this cohort of children, and most prescriptions did not entirely comply with the 2014/15 HIV/AIDs treatment recommendations. Since, this cohort of children was found to be susceptible to medication related errors such as; Drug omissions in ARV regimens; Incorrect dosing & dosing frequencies; as well as incorrectly supplied quantities. From the study findings it is recommended that ARV stewardship programs should be considered in order to develop and establish a core strategy for enhancing quality improvement in the management of HIV-infected children on ART in resource-limited settings, not only to inundate viral suppression and maintain it, but also to help achieve the UNAIDS 95- 95-95 target in children under 15 year / National Research Foundation (NRF)