The effect of facility-based antiretroviral therapy programs on outpatient services in Kenya and Uganda.

BACKGROUND: Considerable debate exists concerning the effects of antiretroviral therapy (ART) service scale-up on non-HIV services and overall health system performance in sub-Saharan Africa. In this study, we examined whether ART services affected trends in non-ART outpatient department (OPD) visits in Kenya and Uganda. METHODS: Using a nationally representative sample of health facilities in Kenya and Uganda, we estimated the effect of ART programs on OPD visits from 2007 to 2012. We modeled the annual percent change in non-ART OPD visits using hierarchical mixed-effects linear regressions, controlling for a range of facility characteristics. We used four different constructs of ART services to capture the different ways in which the presence, growth, overall, and relative size of ART programs may affect non-ART OPD services. RESULTS: Our final sample included 321 health facilities (140 in Kenya and 181 in Uganda). On average, OPD and ART visits increased steadily in Kenya and Uganda between 2007 and 2012. For facilities where ART services were not offered, the average annual increase in OPD visits was 4·2% in Kenya and 13·5% in Uganda. Among facilities that provided ART services, we found average annual OPD volume increases of 7·2% in Kenya and 5·6% in Uganda, with simultaneous annual increases of 13·7% and 12·5% in ART volumes. We did not find a statistically significant relationship between annual changes in OPD services and the presence, growth, overall, or relative size of ART services. However, in a subgroup analysis, we found that Ugandan hospitals that offered ART services had statistically significantly less growth in OPD visits than Ugandan hospitals that did not provide ART services. CONCLUSIONS: Our findings suggest that ART services in Kenya and Uganda did not have a statistically significant deleterious effects on OPD services between 2007 and 2012, although subgroup analyses indicate variation by facility type. Our findings are encouraging, particularly given recent recommendations for universal access to ART, demonstrating that expanding ART services is not inherently linked to declines in other health services in sub-Saharan Africa.

The potential to expand antiretroviral therapy by improving health facility efficiency: evidence from Kenya, Uganda, and Zambia.

BACKGROUND: Since 2000, international funding for HIV has supported scaling up antiretroviral therapy (ART) in sub-Saharan Africa. However, such funding has stagnated for years, threatening the sustainability and reach of ART programs amid efforts to achieve universal treatment. Improving health system efficiencies, particularly at the facility level, is an increasingly critical avenue for extending limited resources for ART; nevertheless, the potential impact of increased facility efficiency on ART capacity remains largely unknown. Through the present study, we sought to quantify facility-level technical efficiency across countries, assess potential determinants of efficiency, and predict the potential for additional ART expansion. METHODS: Using nationally-representative facility datasets from Kenya, Uganda and Zambia, and measures adjusting for structural quality, we estimated facility-level technical efficiency using an ensemble approach that combined restricted versions of Data Envelopment Analysis and Stochastic Distance Function. We then conducted a series of bivariate and multivariate regression analyses to evaluate possible determinants of higher or lower technical efficiency. Finally, we predicted the potential for ART expansion across efficiency improvement scenarios, estimating how many additional ART visits could be accommodated if facilities with low efficiency thresholds reached those levels of efficiency. RESULTS: In each country, national averages of efficiency fell below 50 % and facility-level efficiency markedly varied. Among facilities providing ART, average efficiency scores spanned from 50 % (95 % uncertainty interval (UI), 48-62 %) in Uganda to 59 % (95 % UI, 53-67 %) in Zambia. Of the facility determinants analyzed, few were consistently associated with higher or lower technical efficiency scores, suggesting that other factors may be more strongly related to facility-level efficiency. Based on observed facility resources and an efficiency improvement scenario where all facilities providing ART reached 80 % efficiency, we predicted a 33 % potential increase in ART visits in Kenya, 62 % in Uganda, and 33 % in Zambia. Given observed resources in facilities offering ART, we estimated that 459,000 new ART patients could be seen if facilities in these countries reached 80 % efficiency, equating to a 40 % increase in new patients. CONCLUSIONS: Health facilities in Kenya, Uganda, and Zambia could notably expand ART services if the efficiency with which they operate increased. Improving how facility resources are used, and not simply increasing their quantity, has the potential to substantially elevate the impact of global health investments and reduce treatment gaps for people living with HIV.

US Spending on Personal Health Care and Public Health, 1996-2013.

Importance: US health care spending has continued to increase, and now accounts for more than 17% of the US economy. Despite the size and growth of this spending, little is known about how spending on each condition varies by age and across time. Objective: To systematically and comprehensively estimate US spending on personal health care and public health, according to condition, age and sex group, and type of care. Design and Setting: Government budgets, insurance claims, facility surveys, household surveys, and official US records from 1996 through 2013 were collected and combined. In total, 183 sources of data were used to estimate spending for 155 conditions (including cancer, which was disaggregated into 29 conditions). For each record, spending was extracted, along with the age and sex of the patient, and the type of care. Spending was adjusted to reflect the health condition treated, rather than the primary diagnosis. Exposures: Encounter with US health care system. Main Outcomes and Measures: National spending estimates stratified by condition, age and sex group, and type of care. Results: From 1996 through 2013, $30.1 trillion of personal health care spending was disaggregated by 155 conditions, age and sex group, and type of care. Among these 155 conditions, diabetes had the highest health care spending in 2013, with an estimated $101.4 billion (uncertainty interval [UI], $96.7 billion-$106.5 billion) in spending, including 57.6% (UI, 53.8%-62.1%) spent on pharmaceuticals and 23.5% (UI, 21.7%-25.7%) spent on ambulatory care. Ischemic heart disease accounted for the second-highest amount of health care spending in 2013, with estimated spending of $88.1 billion (UI, $82.7 billion-$92.9 billion), and low back and neck pain accounted for the third-highest amount, with estimated health care spending of $87.6 billion (UI, $67.5 billion-$94.1 billion). The conditions with the highest spending levels varied by age, sex, type of care, and year. Personal health care spending increased for 143 of the 155 conditions from 1996 through 2013. Spending on low back and neck pain and on diabetes increased the most over the 18 years, by an estimated $57.2 billion (UI, $47.4 billion-$64.4 billion) and $64.4 billion (UI, $57.8 billion-$70.7 billion), respectively. From 1996 through 2013, spending on emergency care and retail pharmaceuticals increased at the fastest rates (6.4% [UI, 6.4%-6.4%] and 5.6% [UI, 5.6%-5.6%] annual growth rate, respectively), which were higher than annual rates for spending on inpatient care (2.8% [UI, 2.8%-2.8%] and nursing facility care (2.5% [UI, 2.5%-2.5%]). Conclusions and Relevance: Modeled estimates of US spending on personal health care and public health showed substantial increases from 1996 through 2013; with spending on diabetes, ischemic heart disease, and low back and neck pain accounting for the highest amounts of spending by disease category. The rate of change in annual spending varied considerably among different conditions and types of care. This information may have implications for efforts to control US health care spending.

Improving Hospital Performance Rankings Using Discrete Patient Diagnoses for Risk Adjustment of Outcomes.

OBJECTIVE: To assess the changes in patient outcome prediction and hospital performance ranking when incorporating diagnoses as risk adjusters rather than comorbidity indices. DATA SOURCES: Healthcare Cost and Utilization Project State Inpatient Databases for New York State, 2005-2009. STUDY DESIGN: Conducted tree-based classification for mortality and readmission by incorporating discrete patient diagnoses as predictors, comparing with traditional comorbidity indices such as those used for Centers for Medicare and Medicaid Services (CMS) outcome models. PRINCIPAL FINDINGS: Diagnosis codes as predictors increased predictive accuracy 5.6 percent (95% CI: 4.5-6.9 percent) relative to CMS condition categories for heart failure 30-day mortality. Most other outcomes exhibited statistically significant accuracy gains and facility ranking shifts. Sensitivity analysis showed improvements even when predictors were limited to only the diagnoses included in CMS models. CONCLUSIONS: Discretizing patient severity information beyond the levels of traditional comorbidity indices improves patient outcome predictions and substantially shifts facility rankings.

The clock is ticking: the rate and timeliness of antiretroviral therapy initiation from the time of treatment eligibility in Kenya.

INTRODUCTION: Understanding the determinants of timely antiretroviral therapy (ART) initiation is useful for HIV programmes intent on developing models of care that reduce delays in treatment initiation while maintaining a high quality of care. We analysed patient- and facility-level determinants of time to ART initiation among patients who initiated ART in Kenya. METHODS: We collected facility-level information and conducted a retrospective chart review of adults initiating ART between 2007 and 2012 at 51 health facilities in Kenya. We evaluated the association between patient- and facility-level covariates at the time of ART eligibility and time to ART initiation. We also explored the determinants associated with timeliness of ART initiation. RESULTS: The analysis included 11,942 patients. The median age at the time eligibility was first determined was 37 years (interquartile range [IQR] 31-45). Overall, 75% of patients initiated ART within two months of eligibility. The median CD4 cell count at the time eligibility was first determined rose from 132 (IQR 51-217) in 2007 to 195 (IQR 91-286) in 2011 to 2012 (p<0.001). The cumulative probability of ART initiation among treatment-eligible patients increased over time: 87.1% (95% confidence interval [CI] 85.1-89.0%) in 2007; 96.8% (96.0-97.5%) in 2008; 97.1% (96.3-97.7%) in 2009; 98.5% (98.0 -98.9%) in 2010; and 99.7% (95% CI 99.4 -99.8%) in 2011 to 2012 (p<0.0001). In multivariate analyses, attending a health facility with high ART patient volumes within two months of eligibility was considered the key facility-level determinant of ART initiation (adjusted odds ratio 0.57, 95% CI 0.45-0.72, p<0.001). Patient-level determinants included being eligible for ART in the years subsequent to 2007, advanced World Health Organization clinical stage and low CD4 cell count at the time eligibility was first determined. CONCLUSIONS: Overall, the time between treatment eligibility and ART initiation decreased substantially in Kenya between 2007 and 2012, with uniform gains across different types of health facilities. Our findings highlight the slow increase in CD4 cell counts at the time of ART eligibility over time, indicating that a large number of patients are still beginning ART with advanced HIV disease. Our findings also support the decentralisation of ART services at all health facilities that have the capacity to initiate treatment. Continued evaluation of programme- and country-level data is needed to monitor timeliness of ART initiation as countries continue to expand treatment access.

Uptake of WHO recommendations for first-line antiretroviral therapy in Kenya, Uganda, and Zambia.

INTRODUCTION: Antiretroviral therapy (ART) guidelines were significantly changed by the World Health Organization in 2010. It is largely unknown to what extent these guidelines were adopted into clinical practice. METHODS: This was a retrospective observational analysis of first-line ART regimens in a sample of health facilities providing ART in Kenya, Uganda, and Zambia between 2007-2008 and 2011-2012. Data were analyzed for changes in regimen over time and assessed for key patient- and facility-level determinants of tenofovir (TDF) utilization in Kenya and Uganda using a mixed effects model. RESULTS: Data were obtained from 29,507 patients from 146 facilities. The overall percentage of patients initiated on TDF-based therapy increased between 2007-2008 and 2011-2012 from 3% to 37% in Kenya, 2% to 34% in Uganda, and 64% to 87% in Zambia. A simultaneous decrease in stavudine (d4T) utilization was also noted, but its use was not eliminated, and there remained significant variation in facility prescribing patterns. For patients initiating ART in 2011-2012, we found increased odds of TDF use with more advanced disease at initiation in both Kenya (odds ratio [OR]: 2.78; 95% confidence interval [CI]: 1.73-4.48) and Uganda (OR: 2.15; 95% CI: 1.46-3.17). Having a CD4 test performed at initiation was also a significant predictor in Uganda (OR: 1.43; 95% CI: 1.16-1.76). No facility-level determinants of TDF utilization were seen in Kenya, but private facilities (OR: 2.86; 95% CI: 1.45-5.66) and those employing a doctor (OR: 2.86; 95% CI: 1.48-5.51) were more likely to initiate patients on TDF in Uganda. DISCUSSION: d4T-based ART has largely been phased out over the study period. However, significant in-country and cross-country variation exists. Among the most recently initiated patients, those with more advanced disease at initiation were most likely to start TDF-based treatment. No facility-level determinants were consistent across countries to explain the observed facility-level variation.

Trends and Determinants of Antiretroviral Therapy Patient Monitoring Practices in Kenya and Uganda.

INTRODUCTION: Patients receiving antiretroviral therapy (ART) require routine monitoring to track response to treatment and assess for treatment failure. This study aims to identify gaps in monitoring practices in Kenya and Uganda. METHODS: We conducted a systematic retrospective chart review of adults who initiated ART between 2007 and 2012. We assessed the availability of baseline measurements (CD4 count, weight, and WHO stage) and ongoing CD4 and weight monitoring according to national guidelines in place at the time. Mixed-effects logistic regression models were used to analyze facility and patient factors associated with meeting monitoring guidelines. RESULTS: From 2007 to 2012, at least 88% of patients per year in Uganda had a recorded weight at initiation, while in Kenya there was a notable increase from 69% to 90%. Patients with a documented baseline CD4 count increased from 69% to about 80% in both countries. In 2012, 83% and 86% of established patients received the recommended quarterly weight monitoring in Kenya and Uganda, respectively, while semiannual CD4 monitoring was less common (49% in Kenya and 38% in Uganda). Initiating at a more advanced WHO stage was associated with a lower odds of baseline CD4 testing. On-site CD4 analysis capacity was associated with increased odds of CD4 testing at baseline and in the future. DISCUSSION: Substantial gaps were noted in ongoing CD4 monitoring of patients on ART. Although guidelines have since changed, limited laboratory capacity is likely to remain a significant issue in monitoring patients on ART, with important implications for ensuring quality care.

Pharmaceutical availability across levels of care: evidence from facility surveys in Ghana, Kenya, and Uganda.

OBJECTIVE: In this study we use facility-level data from nationally representative surveys conducted in Ghana, Kenya, and Uganda to understand pharmaceutical availability within the three countries. METHODS: In 2012, we conducted a survey to capture information on pharmaceuticals and other facility indicators from over 200 facilities in each country. We analyze data on the availability of pharmaceuticals and quantify its association with various facility-level indicators. We analyze both availability of essential medicines, as defined by the various essential medicine lists (EMLs) of each respective country, and availability of all surveyed pharmaceuticals deemed important for treatment of various high-burden diseases, including those on the EMLs. RESULTS: We find that there is heterogeneity with respect to availability across the three countries with Ghana generally having better availability than Uganda and Kenya. To analyze the relationship between facility-level factors and pharmaceutical stock-out we use a binomial regression model. We find that the factors associated with stock-out vary by country, but across all countries both presence of a laboratory at the facility and presence of a vehicle at the facility are significantly associated with reduced stock-out. CONCLUSION: The results of this study highlight the poor availability of essential medicines across these three countries and suggest more needs to be done to strengthen the supply system so that stock remains uninterrupted.