Multi-state Markov model for time to treatment changes for HIV/AIDS patients: a retrospective cohort national datasets, Ethiopia.

BACKGROUND: Virological failure, drug resistance, toxicities, and other issues make it difficult for ART to maintain long-term sustainability. These issues would force a modification in the patient's treatment plan. The aim of this research was to determine whether first-line antiretroviral therapy is durable and to identify the factors that lead to patients on HAART changing their first highly active antiretroviral therapy regimen. METHODS: A retrospective cohort study was conducted from October, 2019-March, 2020 across all regional states including Addis Ababa and Dire Dawa administrative cities. The target population is from all health facilities that have been providing ART service for at least the past 6 months as of October 2019. Multi-stage clustered sampling method was used to select study facilities and participants. Simple random selected ART medical records of patients ever enrolled in ART treatment services. We adopted a multi-state survival modelling (msm) approach assuming each treatment regimen as state. We estimate the transition probability of patients to move from one regimen to another for time to treatment change/switch. We estimated the transition probability, prediction probabilities and length of stay and factor associated with treatment modification of patients to move from one regimen to another. RESULTS: Any of the six therapy combinations (14.4%) altered their treatment at least once during the follow-up period for a variety of reasons. Of the patients, 4,834 (13.26%) changed their treatments just once, while 371 (1.1%) changed it more than once. For 38.6% of the time, a treatment change was undertaken due to toxicity, another infection or comorbidity, or another factor, followed by New drugs were then made accessible and other factors 18.3% of the time, a drug was out of supply; 2.6% of those instances involved pregnancy; and 43.1% involved something else. Highly active anti-retroviral therapy (HAART) combinations TDF + 3TC + NVP, d4T + 3TC + NVP, and TDF + 3TC + EFV were high to treatment alterations in all reasons of treatment modifications, with 29.74%, 26.52%, and 19.52% treatment changes, respectively. Early treatment modification or regime change is one of the treatment combinations that include the d4T medication that creates major concern. The likelihood of staying and moving at the the start of s = 0 and 30-month transitions increased, but the likelihood of staying were declined. For this cohort dataset, the presence of opportunistic disease, low body weight, baseline CD4 count, and baseline TB positive were risk factors for therapy adjustment. CONCLUSION: Given that the current study took into account a national dataset, it provides a solid basis for ART drug status and management. The patient had a higher likelihood of adjusting their treatment at some point during the follow-up period due to drug toxicity, comorbidity, drug not being available, and other factors, according to the prediction probability once more. Baseline TB positivity, low CD4 count, opportunistic disease, and low body weight were risk factors for therapy adjustment in this cohort dataset.

Surgical System Efficiency and Operative Productivity in Public and Private Health Facilities in Ethiopia: A Cross-Sectional Evaluation.

BACKGROUND: Global and local health organizations track surgical system efficiency to improve surgical system performance using various efficiency metrics, such as operating room (OR) output, surgical incision start time (SIST), turnover time (TOT), cancellation rate among elective surgeries, and in-hospital surgery wait time. We evaluated the surgical system efficiency and factors affecting the efficiency in health facilities across Ethiopia. METHODS: A cross-sectional study design with retrospective record review was used to evaluate the surgical system efficiency in 163 public and private health facilities in Ethiopia from December 2020 to June 2021. Experienced, trained surgical clinicians abstracted efficiency data from service registers and patient charts using a pretested tool. A bivariable and multivariable regression analysis was conducted. RESULTS: In the study facilities, 84.11% of the operating tables were functional, and 68,596 major surgeries were performed. The aggregate OR output in both public and private health facilities was 2 surgeries per day per OR table. Operating productivity was shown to be affected by first-case SIST (P=.004). However, of the total 881 surgery incision times audited, 19.86% of the first-of-the-day elective surgeries started after 10:01 am. The SIST was strongly associated with an in-hospital wait time for surgery (P=.016). The elective surgery cancellation rate was 5.2%, and aggregate mean TOT was 50.25 minutes. The mean in-hospital surgery wait time was 45.40 hours, longer than the national cutoff for wait time. In a bivariable analysis, the independent variables that demonstrated association operating room productivity were then inputted into a multivariable regression analysis model. However, none of the predictor/independent variables showed significance in the multivariable regression analysis model. CONCLUSION: The volume of surgery and overall OR productivity in Ethiopia is low. This calls for concerted action to optimize OR efficiency and improve access to timely and safe surgical care in Ethiopia and other LMICs.