Availability, price, and affordability of antiseizure medicines in Addis Ababa, Ethiopia

OBJECTIVE

Up to 70% of people living with epilepsy could become seizure-free with the appropriate use of antiseizure medicines. However, three quarters of people with epilepsy living in low-income countries do not get the treatment they need and also do not access antiseizure medicines. The purpose of this study was to assess the availability, price, and affordability of antiseizure medicines in Addis Ababa, Ethiopia.

METHODS

A cross-sectional study was done in selected pharmacies using a questioner developed after the modification of World Health Organization/Health Action International methodology. Data on the availability and price of lowest-priced generics and originator brand antiseizure medicines from essential medicines list in Ethiopia were collected from seven public sectors, five private sectors, and seven other sectors (five Kenema Public Community and two Red Cross Pharmacies) in Addis Ababa between 09 May and 31 2022. The data were analyzed using the modified World Health Organization/Health Action International workbook part I excel sheet. Descriptive results were reported in text and table format.

RESULTS

The overall availability of lowest-priced generics medication was 52%. The availability of lowest-priced generics was 62.86%, 30%, 55%, and 50% in public, private, Red Cross, and Kenema Public Community Pharmacies, respectively. The median price ratio in the public, private, Red Cross, and Kenema Public Community Pharmacy was 1.45, 3.72, 1.46, and 1.7, respectively. All the medications were unaffordable. Patients may be required to pay more than 6-month wage to purchase standard treatment for 1 month only.

SIGNIFICANCE

The overall availability of antiseizure medicines was lower than the WHO target for noncommunicable diseases. All the available medicines were unaffordable.

Lack of Association of Generic Brittle Status with Genetics and Physiologic Measures in Patients with Epilepsy

PURPOSE

A patient was denoted to be generic brittle (GB) if they had a negative opinion about generics (e.g. prior history of a switch problem) or took the innovator brand of their most problematic anti-epileptic drug (AED) when generic was available. The aim of this hypothesis-generating study was to assess possible genetic and physiologic differences between GB and not GB patients with epilepsy.

METHODS

Patients (n = 148) with epilepsy were previously characterized as being either GB or not GB. Blood was collected from each subject for genotyping and physiologic testing. Genotyping for 24 single nucleotide polymorphisms (SNPs) and two copy number variants (CNVs) was performed across 12 genes in each patient. Forty-four physiologic tests were conducted in each patient. Chi square analysis was performed to assess for associations between genotyping results and GB status, as well as between physiologic test results and GB status.

RESULTS

No SNP or CNV discriminated GB status in genetic analysis (genotype or allele frequency). Physiologic test results in this study were not associated with GB status.

CONCLUSIONS

Questions from neurologists and patients about generics is frequently based on applicability of generic drug standards to individual subjects. However, findings here in patients with epilepsy did not uncover genetic or physiologic reasons that explained which patients were GB and which were not GB.

Effects of an e-Prescribing interface redesign on rates of generic drug prescribing: exploiting default options

Objective Increasing the use of generic medications could help control medical costs. However, educational interventions have limited impact on prescriber behavior, and e-prescribing alerts are associated with high override rates and alert fatigue. Our objective was to evaluate the effect of a less intrusive intervention, a redesign of an e-prescribing interface that provides default options intended to “nudge” prescribers towards prescribing generic drugs.

Methods This retrospective cohort study in an academic ambulatory multispecialty practice assessed the effects of customizing an e-prescribing interface to substitute generic equivalents for brand-name medications during order entry and allow a one-click override to order the brand-name medication.

Results Among drugs with generic equivalents, the proportion of generic drugs prescribed more than doubled after the interface redesign, rising abruptly from 39.7% to 95.9% (a 56.2% increase; 95% confidence interval, 56.0–56.4%; P  < .001). Before the redesign, generic drug prescribing rates varied by therapeutic class, with rates as low as 8.6% for genitourinary products and 15.7% for neuromuscular drugs. After the redesign, generic drug prescribing rates for all but four therapeutic classes were above 90%: endocrine drugs, neuromuscular drugs, nutritional products, and miscellaneous products.

Discussion Changing the default option in an e-prescribing interface in an ambulatory care setting was followed by large and sustained increases in the proportion of generic drugs prescribed at the practice.

Conclusions Default options in health information technology exert a powerful effect on user behavior, an effect that can be leveraged to optimize decision making.

Likelihood approach for evaluating bioequivalence of highly variable drugs

Bioequivalence (BE) is required for approving a generic drug. The two one-sided tests procedure (TOST, or the 90% confidence interval approach) has been used as the mainstream methodology to test average BE (ABE) on pharmacokinetic parameters such as the area under the blood concentration-time curve and the peak concentration. However, for highly variable drugs (%CV > 30%), it is difficult to demonstrate ABE in a standard cross-over study with the typical number of subjects using the TOST because of lack of power. Recently, the US Food and Drug Administration and the European Medicines Agency recommended similar but not identical reference-scaled average BE (RSABE) approaches to address this issue. Although the power is improved, the new approaches may not guarantee a high level of confidence for the true difference between two drugs at the ABE boundaries. It is also difficult for these approaches to address the issues of population BE (PBE) and individual BE (IBE). We advocate the use of a likelihood approach for representing and interpreting BE data as evidence. Using example data from a full replicate 2 × 4 cross-over study, we demonstrate how to present evidence using the profile likelihoods for the mean difference and standard deviation ratios of the two drugs for the pharmacokinetic parameters. With this approach, we present evidence for PBE and IBE as well as ABE within a unified framework. Our simulations show that the operating characteristics of the proposed likelihood approach are comparable with the RSABE approaches when the same criteria are applied.