Payments to key opinion leader physicians and drug sales of top pharmaceutical companies during the COVID-19 pandemic

Background: The unprecedented context of the COVID-19 pandemic poses the opportunity to study several questions in circumstances that would probably not otherwise occur. We sought to determine the dynamics of pharmaceutical company drug sales revenue, market capitalization and payments to physicians during the pandemic, focusing on payments to so-called key opinion leaders (KOLs). Methods: We analyzed the CMS Open Payments data of 15 top pharmaceutical company general payments to US physicians. We calculated total payments per year for all physicians, KOLs and 2018 KOLs in subsequent years. Drug-related fold changes in payments, drug revenues and company market capitation were calculated using Q1-2018 as reference. Yearly differences in payments, drug sales revenue and market capitalization were tested using generalized estimation equations (GEE). A double-sided p<0.05 was considered significant. Results: The analyzed dataset comprised 8,563,872 payments to 382,779 physicians. In 2020, we observed a reduction in payments to physicians and KOLs compared to prior years. The total amount per KOL physician per company also decreased for each year for KOLs and the 2018 KOLs in the subsequent years. Payments per drug, but neither drug revenues nor pharmaceutical company market capitalization, followed a downward trend in 2020 compared to prior years. GEE analysis confirmed that, compared to 2018, the decrease in payments to KOLs overall and for the top drugs of each company was statistically significant. Yet, no significant differences in drug sales revenue and market capitalization was observed. Conclusions: A substantial and significant reduction in payments to KOLs during the first fiscal year of the COVID-19 pandemic was not associated with a reduction in drug sales revenue of blockbuster drug products and the market capitalization of 15 top pharmaceutical companies. Overall, these findings suggest that a substantial part of pharmaceutical payments to KOLs do not appear to impact top drug sales revenues.

Information provision and retrieval by registered salespersons from consumers during over-the-counter drug sales – a questionnaire survey

Background In Japan, non-pharmacists who are accredited as registered salespersons can sell over-the-counter (OTC) drugs, and they play a very important role in supporting proper OTC drug use by consumers. The purpose of this study was to evaluate information provided to and information collected from consumers, and cooperation with pharmacists during OTC drug sales by registered salespersons, and to clarify their related concerns and behaviors. Methods A cross-sectional questionnaire-based survey of 385 registered salespersons working at 56 drugstores throughout Japan was conducted. Based on the questionnaire survey, the frequency of information provision/collection in various categories was determined for the registered salespersons. The relation between concerns of registered salespersons relating to OTC drug sales and the frequency of information provision/collection was examined. The frequency of consultation of registered salespersons with a pharmacist was calculated for registered salespersons with/without in-store pharmacists. The χ-square test or Fisher’s exact test was performed to assess the significance of differences. Results Two hundred and seven registered salespersons (53.7%) responded completely. A greater number of OTC drug purchasers per day was associated with a greater frequency of information provision about “side effects” and information collection about “favorite items” (alcohol, tobacco, health foods, etc.) (p < 0.05). One hundred and thirty-nine (67.2%) participants had concerns about “interactions between OTC drugs and prescription drugs”, and these concerns were related to the frequency of information provision/collection (p < 0.05). Regarding the frequency of consultation with a pharmacist, 35 of 46 participants (76.1%) working with pharmacists answered “always” or “usually”, whereas only 19 of 161 participants (11.8%) working without full-time pharmacists answered “always” or “usually”. More than half of the registered salespersons thought that cooperation with a pharmacist was necessary when they were “asked about concomitant use with prescription drugs” or “told that side effects happened.” Conclusions The results of this study show that experienced registered salespersons selling OTC drugs are more likely to collect information from consumers and to provide information to consumers. It appears to be important for registered salespersons to cooperate with pharmacists in order to provide and collect appropriate information about concomitant medications.

Penerapan Metode C4.5 Berbasis Particle Swarm Optimization Untuk Memprediksi Penjualan Obat Pada Apotek Bunda Azka

The application of the C4.5 Algorithm based on Particle Swarm Optimization to classify the level of sales of drugs that are often sold at the Bunda Azka Pharmacy, is a strategic thing to reduce the problems experienced by the pharmacy. Classify the level of sales of drugs sold using the C4.5 method. based on particle swarm optimization, to find out whether the C4.5 method based on particle swarm optimization (PSO) can optimize drug sales in the future. This research method uses a descriptive method, namely by conducting case study research by studying activities in the field, observing and interviewing stakeholders. in the initial step of this research is the determination of the attributes that will be processed into data mining with the help of rapidminer tools, this study the author uses the KDD model as a standardization in the data mining process. at the pharmacy. The data will later be processed using the c4.5 algorithm based on Particle Swarm Optimization to find the accuracy results of the prediction of the data. The data sample used is the number of 65 drug transaction records at the Bunda Azka Pharmacy. In the test results, the accuracy of Particle Swarm Optimization was 78.10%, for class recall drug sales was 72.50% and after using Particle Swarm Optimization increased to 78.33%, while precision had an accuracy of 77.92% and after using Particle Swarm Optimization increased to 80.33%. From the results of testing with Particle Swarm Optimization, there is an increase in accuracy of 7.15% from the research application of the C4.5 Method Based on Particle Swarm Optimization to Predict Drug Sales at Bunda Azka Pharmacy.

Rancang Bangun Sistem Informasi Penjualan Obat di Apotek Era Medika Berbasis Website

Handling data by doing this manually has a number of obstacles at the Era Medika Pharmacy, including causing errors in checking drug stock once a week, inaccurate recording of incoming or outgoing drug stocks so that there is a mistake in recording the final stock, as well as the results of sales reports use paper. To overcome this problem the drug sales information system is a solution to the drug sales process, and uses the Click to Chat API Whatsapp to facilitate sending messages to drug suppliers. To obtain the data needed during the study, the author uses several method including: interviews, observation, and literature studies. The data obtained then analyzes using the Waterfall method. The results of this study conducted on testing sales applications that have been designed can help to facilitate managers in the sales process that can be accessed online so that it can work effectively and efficiently. With the Click to Chat feature Whatsapp can facilitate messages to drug suppliers according to the contact you want to reach. The results of this study are expected to be useful in the future.

Exploring Relationships between Tweet Numbers and Over-The-Counter Drug Sales for Allergic Rhinitis: Retrospective Analysis (Preprint)

BACKGROUND Health-related social media data are increasingly being used in disease surveillance studies. In particular, surveillance of infectious diseases such as influenza has demonstrated high correlations between the number of social media posts mentioning the disease and the number of patients who went to the hospital and were diagnosed with the disease. However, the prevalence of some diseases, such as allergic rhinitis, cannot be estimated based on the number of patients alone. Specifically, patients with allergic rhinitis self-medicate by taking over-the-counter (OTC) medications without going to the hospital. Although allergic rhinitis is not a life-threatening disease, it is a major social problem because it reduces patients’ quality of life, making it essential to understand its prevalence and the motives for self-medication behavior. OBJECTIVE To help understand the prevalence of allergic rhinitis and the motives for self-care treatment using social media data, this study investigated the relationship between the number of social media posts mentioning the main symptoms of allergic rhinitis and the sales volume of OTC rhinitis medications in Japan. METHODS We collected tweets over four years from 2017 to 2020 that included keywords corresponding to the main nasal symptoms of allergic rhinitis: “sneezing,” “runny nose,” and “stuffy nose.” We also obtained the sales volume of OTC drugs, including oral medications and nasal sprays, for the same period. We then calculated the Pearson correlation coefficient between time series data on the number of tweets per week and time series data on the sales volume of OTC drugs per week. RESULTS The results showed a much higher correlation (0.8432) between the time series data on the number of tweets mentioning “stuffy nose” and the time series data on the sales volume of nasal sprays than for the other two symptoms. There was also a high correlation (0.9317) between the seasonal components of these time series data. CONCLUSIONS We investigated the relationships between social media data and behavioral patterns, such as OTC drug sales volume. Exploring these relationships would be useful as a marketing indicator to predict sales volume using social media data. In future, in-depth investigations are required to cover other diseases and countries. We investigated the relationships between social media data and behavioral patterns, such as OTC drug sales volume. Exploring these relationships would be useful as a marketing indicator to predict sales volume using social media data. In future, in-depth investigations are required to cover other diseases and countries.

Analysis of Data Mining Associations on Drug Sales at Pharmacies with APRIORI Techniques

The purpose of the research is to utilize artificial intelligence techniques in analyzing drug sales. Sources of data used are observations and interviews with shop owners. The method used as a solution is the Association method with the Apriori technique. By using the RapidMiner software, the test results are obtained using a minimum support of 25% and a minimum of 60% confidence as many as 5 rules with a predetermined itemset. The results of the study are expected to provide information and make it easier for related parties to find combinations of selling items. The results of this analysis can be used by pharmacies for marketing strategies and product promotion.

Juvenile delinquency dimension of child labour: implications for human and capital development in Nigeria

Juvenile delinquency and child labour are related social problems that today plague Nigeria. They both affect young boys and girls, some of whom are children (juveniles). Among these juveniles are children who have been involved in criminal behavior like gangism, banditry, thuggery, drug sales and abuse behaviors which are sometimes developed from participation in child labour activities which have become severe in Nigeria. Majority of these activities take the form of street hawking in the Southern part of the country, and street begging in its northern part by children addressed as Almajirai. These problems if allowed to remain will compromise and jeopardize not only the future of the child, but also that of the nation, Nigeria. Thus this study investigates juvenile delinquency as predated by child labour with a view to explaining causality and effects. Particularly, as it relates to human and capital development, and to make suggestions towards finding solutions.