Exploring cost drivers to improve disease management: the case of type 2 diabetes at a tertiary hospital in Burundi, Africa.

Background: In Burundi, the International Diabetes Federation estimated the prevalence of diabetes mellitus (DM) as high as 2.4% in adults aged between 20 and 79 years old. Thus, the healthcare expenditure for the treatment of diabetic patients is considerably high. Objective: This study explores the economic burden of type 2 DM and its cost drivers at a tertiary hospital in 2018. It included adult type 2 DM patients who received treatment from a tertiary hospital (Hospital Prince Regent Charles) in 2018. In this study, 81 patients were included. Methods: Data on illness treatment and complications were collected through patient interviews and by reviewing patients' medical and financial records. A stepwise multiple linear regression model was used to explore factors affecting the cost of type 2 diabetes mellitus. Results: The average total cost per patient per year was estimated at $2621.06. The fitted cost model had an adjusted R2 of 0.427, which explained up to 43% of the variation in the total cost. The results suggest primary cost drivers such as treatment regimen, duration of the disease, payment method, and number of complications. Conclusion: The findings confirm the profound economic burden of type 2 DM and the need to improve patient care and prevent disease progression. The establishment of a special clinic for patients with diabetes is recommended, as is financial support for underprivileged patients. A specific focus on cost drivers could help establish appropriate disease management programs to control the costs for type 2 diabetes patients.

Exploring cost drivers for improving disease management: the case of type 2 diabetes at a tertiary hospital in Burundi, Africa

Globally, the covid-19 pandemic has seriously impacted access to healthcare facilities across the world, although there is little evidence on how the pandemic affects the use of essential healthcare in the world. This study sought to evaluate the impact of the covid-19 pandemic on antenatal indicators in the region of Guelmim Oued Noun, Morocco using the interrupted time-series analysis. The aggregated data was delivered by regional health authorities covering the period from January 2017 to December 2020. The descriptive results revealed a steady decline after the Covid-19 pandemic in Antenatal indicators. The results of the regression model showed a negative impact of the pandemic on the antenatal recruitment rate (ß2 = - 16.14; p < 0.01), recruitment rate of women in antenatal visits the 1st quarter of pregnancy (ß2 = -2.09; p < 0.01), antenatal visit completion rate (ß2= -18.10, p>0.05), average number of visits/pregnancies (ß2 = -15.65, p<0,05). The effect of thecovid-19 pandemic on antenatal rates was significant for almost the indicators studied. Future studies should be focused on the impact of the pandemic on postnatal and immunization services on the national scale.

Effect of a computerized decision support system on potentially inappropriate medication prescriptions for elderly patients in Thailand.

RATIONALE, AIMS, AND OBJECTIVES: The prescription of potentially inappropriate medication (PIM) is a global issue associated with increased adverse drug events, mortality, and health care expenditure. Computerized decision support system (CDSS) for the detection of PIM is a novel alert system in Thailand for reducing PIM prescriptions. The aim of this study was to evaluate the effect of a CDSS on PIM prescriptions for elderly patients in Thai community hospitals. METHODS: The study design comprised two phases with a duration of 12 months each: pre-CDSS implementation (October 2015-March 2016) and post-CDSS implementation (October 2016-March 2017). Medical services and prescription claims data from four hospitals were used to calculate the prevalence of PIM prescriptions among elderly patients aged 60 years and older. Chi-square tests were used to analyse changes in PIM prescriptions across hospitals post CDSS. RESULTS: The overall prevalence of PIM prescriptions post-CDSS implementation significantly decreased from 87.7% to 74.4%. The severity of mild and moderate PIMs was significantly reduced from 71.9% to 49.0% and from 64.5% to 48.7%, respectively. All hospitals had only one severe PIM, which was hyoscine. It was reduced from 4.7% to 1.5%, but the change was not significant (P = 0.74). The proportion of frequently prescribed PIMs in all PIM levels was significantly decreased, regardless of existing alternative medications. CONCLUSIONS: Specific CDSS for PIM in community hospital setting was associated with a reduction of PIM prescription in elderly patients. This CDSS can change physician's prescription behaviour to avoid inappropriate medications.

Applying the Lists of Risk Drugs for Thai Elderly (LRDTE) as a mechanism to account for patient age and medicine severity in assessing potentially inappropriate medication use.

BACKGROUND: Potential inappropriate medication (PIM) prescribing is a medication that puts patients at risk rather than having benefits. PIM use has been associated with hospitalization, morbidity, and mortality resulting from ADRs in elderly patients. The Lists of Risk Drugs for Thai Elderly (LRDTE) was developed as the new screening tool to identify PIMs use. The prevalence of PIM use using the LRDTE has not been determined in Thailand. PURPOSE: The main purpose of this study was to examine the prevalence of PIM use based on the LRDTE. In addition, this aimed to address the PIM problem by identifying factors that influenced PIM use among elderly patients in Thailand. METHODS: A retrospective cross-sectional descriptive study was conducted using the computerized database at four community hospitals in Thailand during fiscal year 2014. The LRDTE criteria were used as a screening tool for identifying the medicine items of PIM use. Descriptive statistics and multivariate logistic regression were used to identify common and Thai region-specific predictors of PIM use. RESULTS: Of a total of 13274 elderly patients, 79% were prescribed at least one PIM, as indicated by the LRDTE criteria. Amlodipine (32%), omeprazole (30%), and tramadol (18%) were the most commonly prescribed PIMs in elderly patients aged 60 years and older. Hospital and physician characteristics were identified as independent predictors after adjustment for patient and utilization factors. CONCLUSION: PIM use in Thai elderly patients was highly prevalent in community hospitals because the LRDTE criteria reflected clinical practice in Thailand. Hospital and physician factors were identified as region-specific factors that were highly associated with PIM use. Revision of hospital formularies and educational programs for physicians are needed to improve prescribing and avoid PIM use.

Budget impact analysis of pemetrexed introduction: case study from a teaching hospital perspective, Thailand.

OBJECTIVE: Thailand does not currently require Budget Impact Analysis (BIA) assessment. The present study aimed to estimate the annual drug cost and the incremental impact on the hospital pharmaceutical budget of the introduction of pemetrexed to a Thai teaching hospital. MATERIAL AND METHOD: The budget impact model was conducted in accordance with the Guidelines for preparing submissions to the Pharmaceutical Benefits Advisory Committee (PBAC). The model variables consisted of number of patients, growth rate of lung cancer, uptake rate of pemetrexed over time, unit prices of drugs, and the length and cost of treatment. Sensitivity analysis was performed to determine changes in budgetary impact due to variation of parameters or assumptions in the model. RESULTS: The introduction of pemetrexed was estimated to cause considerable costs for the teaching hospital. In the base-case analysis, the incremental costs were estimated at 8,553,984 Baht in the first year increasing to 12, 118, 144 Baht, 17,820,800 Baht and 17,820,800 Baht in the following years. The 4-year net budgetary impact was 20,154,480 Baht or approximately 127,560 Baht per patient. Sensitivity analyses found that number of treatment cycles andproportion of patients assumed to be treated with pemetrexed were the two most important influencing factors in the model. CONCLUSION: New costly innovative interventions should be evaluated using the BIA model to determine whether they are affordable. The Thai government should consider requiring the BIA study as one of the requirements for drug submission to assist in the determination of listing and subsidizing decision for medicines.