Forecasting drug utilization and expenditure: ten years of experience in Stockholm

Drug utilization research in Peru: Is real-world data available?

Background: Drug utilization research (DUR) is used to provide evidence-based data to inform policies and make decisions. The aim of this study was to map and describe available data sources for drug utilization research in Peru. Methods: We performed a search of data sources providing information on medication use on the website of governmental organizations. We also conducted a literature review using PubMed, LILACs, and BVS. Independently, researchers screened eligible data sources. Data characterization included accessibility, coverage data provider, type of data sources, and setting. We performed a descriptive analysis. Results: We identified seven data sources, CENAFyT, ICI, IDI (SISMED), and ENSUSALUD from MINSA, and CRI-ESSALUD, SGSS/ESSI, and ENSSA from ESSALUD. These presented information on adverse drug reactions (n = 2), drug consumption, and distribution (n = 2), prescription and drug dispensing (n = 1), and surveys addressed to medication users (n = 2). ENSUSALUD was the only data source publicly available. VIGIFLOW and ENSUSALUD have a national granularity from the public and private sectors. The setting of the data sources was both hospital and ambulatory care. Two data sources have individual-level data on adverse drug reactions and one on prescriptions. Four studies on drug utilization research in Peru were derived from ENSUSALUD. Conclusion: In Peru, few data sources are available for drug utilization research. There is an increased need to monitor medications for decision-making purposes. Local and international initiatives and partnerships of the government with academic institutions and the private sector might be a good strategy to increase the transparency of health data and for supporting decision-making using drug utilization research.

Evaluation of Pharmacovigilance System in Iran

BACKGROUND

Evaluating a pharmacovigilance system helps identify its deficiencies and could facilitate measures to remedy and improve the quantity and quality of adverse drug reaction (ADR) reports and other opportunities for pharmacovigilance systems strengthening. This study aimed to evaluate the status of pharmacovigilance in Iran using the World Health Organization (WHO) pharmacovigilance indicators with the prospect of identifying the gaps and areas for improvement.

METHODS

This study was conducted in 2 parts. The first part included a secondary analysis of the national data obtained from the Iranian National Pharmacovigilance Center (PVC) using a structured data collection form based on WHO core pharmacovigilance indicators. In the second part, a 3-month prospective study was carried out to investigate 2 outcome indicators, ie, length of stay and costs of medicine-related hospitalization in all patients of 2 main referral hospitals in the southeast and north of Iran.

RESULTS

Iran has a PVC with national policy, trained staff, and a statutory budget. In 2017, the number of ADR reports was 15.0 per 100 000 population, and 262 signals were detected during the preceding 5 years. The average length of stay and costs of medicine-related hospitalization were 5 days and US$817.2 in Afzalipour hospital and 6.6 days and US$306.7 in Razi hospital, respectively. The status of pharmacovigilance in the Iranian public health programs (PHPs) is unknown, and most of the indicators could not be assessed.

CONCLUSION

A robust pharmacovigilance system is a pivotal part of the overall medicines regulatory system. The Iranian pharmacovigilance system has relatively the proper structural condition. Though the underreporting of ADRs, especially medicine-related deaths, is an important issue, and some indicators' status was unclear. The Iranian pharmacovigilance program requires a higher prioritization, particularly in the PHPs, a greater allocation of resources, and cross-sectoral cooperation to bolster and achieve the pharmacovigilance objectives.

Adoption of new therapies in the treatment of Hepatitis: a verification of the accuracy of budget impact analysis to guide investment decisions

OBJECTIVES

While there are good Budget Impact Analysis (BIA) guidelines, studies still register potential bias. To do this, we compared the results between theoretical and real-world evidence (RWE) expenditures for medicines for Hepatitis C: boceprevir (BOC) and telaprevir (TVR). While both are not currently recommended in treatment guidelines following recent developments, this is an emblematic case because for 4 years these medicines consumed considerable resources.

METHODS

Theoretical results and RWE expenditures were compared regarding the incorporation of BOC and TVR in 2013-2014 into the Brazilian Public Health System. Theoretical values were extracted from Commission for Technology Incorporation Report and RWE expenditures were extracted from the administrative data records using deterministic-probabilistic linkage.

RESULTS

The estimated number of patients treated (BOC+TVR) was 13,012 versus 7,641 (real). The estimated purchase price for BOC was US$6.20 versus US$11.07 (real) and for TVR was US$42.21 versus US$84.09 (average/real). The estimated budget impact was US$285.16 million versus US$128.58 million (real).

CONCLUSION

This study demonstrates appreciable divergence (US$156.58 million) between the theoretical budget impact and RWE expenditures due to underestimated purchase prices and overestimated populations. The greater the degree of accuracy the more reliable and usable BIAs become for decision-making.

The Challenge of Sustainability of High-Cost Oncological Drugs: A Budgeting Model in an Italian Cancer Center

In Italy, drug expenditure governance is achieved by setting caps based on the percentage increase in hospital spending compared to the previous year. This method is ineffective in identifying issues and opportunities as it does not consider an analysis of the number of treated cases and per capita consumption in local and regional settings. The IRCCS (Scientific hospitalization and treatment institute) Istituto Romagnolo per lo Studio dei Tumori (IRST) “Dino Amadori” in Meldola, has developed and adopted an effective management model designed to oversee pharmaceutical expenditure, guarantee prescription appropriateness and quality of care to patients. The budget setting follows a structured process which evaluates determining factors of the expenditure such as expected patients calculated according to the epidemiology and to national and regional indications of appropriateness, mean cost per patient calculated on the average period of demonstrated efficacy of the drug and use of drugs with the best cost-effectiveness ratio. Strict monitoring and integrated purchasing processes allow for immediate corrective actions on expenditures, as well as a continuous dialogue with the region in order to guarantee consistent funding of IRST activities. The model, presented in this article is efficient and implements concepts beyond the conventional “silos” approach and national and regional governance tools, in terms of patient centricity.

Durable cell and gene therapy potential patient and financial impact: US projections of product approvals, patients treated, and product revenues

Durable cell and gene therapies potentially transform patient lives, but payers fear unsustainable costs arising from the more than 1000 therapies in the development pipeline. A novel multi-module Markov chain Monte Carlo-based model projects product-indication approvals, treated patients, and product revenues. We estimate a mean 63.5 (54-74 5th to 95th percentile range) cumulative US product-indication approvals through 2030, with a mean 93000 patients treated in 2030 generating a mean US$24.4 billion (US$17.0B-35.0B, US$73.0B extreme) list price product revenues not including ancillary medical costs or cost offsets. Thus, the likely dozens of durable cell and gene therapies developed through 2030 are unlikely to threaten US health system financial sustainability.

Assessing the Accuracy of Sales Forecasts Submitted by Pharmaceutical Companies Applying for Reimbursement in Austria

Objectives: Reimbursement decisions on new medicines require an assessment of their value. In Austria, when applying for reimbursement of new medicines, pharmaceutical companies are also obliged to submit forecasts of future sales. We systematically examined the accuracy of these pharmaceutical sales forecasts and hence the usefulness of these forecasts for reimbursement evaluations. Methods: We retrospectively analyzed reimbursement applications of 102 new drugs submitted between 2005 and 2014, which were accepted for reimbursement outside of hospitals, and for which actual reimbursed sales were available for at least 3 years. The main outcome variable was the accuracy ratio, defined as the ratio of forecasted sales submitted by pharmaceutical companies when applying for reimbursement to actual sales from reimbursement data. Results: The median accuracy ratio [95% confidence interval] was 1.33 [1.03; 1.74, range 0.15–37.5], corresponding to a median overestimation of actual sales by 33%. Forecasts of actual sales for 55.9% of all examined products either overestimated actual sales by more than 100% or underestimated them by more than 50%. The accuracy of sales forecasts did not show systematic change over the analyzed decade nor was it discernibly influenced by reimbursement status (restricted or unrestricted), the degree of therapeutic benefit, or the therapeutic area of the pharmaceutical product. Sales forecasts of drugs with a higher degree of innovation and those within a dynamic market tended to be slightly more accurate. Conclusions: The majority of sales forecasts provided by applicants for reimbursement evaluations in Austria were highly inaccurate and were on average too optimistic. This is in line with published results for other jurisdictions and highlights the need for caution when using such forecasts for reimbursement procedures.

Exploring polypharmacy with artificial intelligence: data analysis protocol

BACKGROUND

Polypharmacy is common among older adults and it represents a public health concern, due to the negative health impacts potentially associated with the use of several medications. However, the large number of medication combinations and sequences of use makes it complicated for traditional statistical methods to predict which therapy is genuinely associated with health outcomes. The project aims to use artificial intelligence (AI) to determine the quality of polypharmacy among older adults with chronic diseases in the province of Québec, Canada.

METHODS

We will use data from the Quebec Integrated Chronic Disease Surveillance System (QICDSS). QICDSS contains information about prescribed medications in older adults in Quebec collected over 20 years. It also includes diagnostic codes and procedures, and sociodemographic data linked through a unique identification number for each individual. Our research will be structured around three interconnected research axes: AI, Health, and Law&Ethics. The AI research axis will develop algorithms for finding frequent patterns of medication use that correlate with health events, considering data locality and temporality (explainable AI or XAI). The Health research axis will translate these patterns into polypharmacy indicators relevant to public health surveillance and clinicians. The Law&Ethics axis will assess the social acceptability of the algorithms developed using AI tools and the indicators developed by the Heath axis and will ensure that the developed indicators neither discriminate against any population group nor increase the disparities already present in the use of medications.

DISCUSSION

The multi-disciplinary research team consists of specialists in AI, health data, statistics, pharmacy, public health, law, and ethics, which will allow investigation of polypharmacy from different points of view and will contribute to a deeper understanding of the clinical, social, and ethical issues surrounding polypharmacy and its surveillance, as well as the use of AI for health record data. The project results will be disseminated to the scientific community, healthcare professionals, and public health decision-makers in peer-reviewed publications, scientific meetings, and reports. The diffusion of the results will ensure the confidentiality of individual data.