The Effects of Cost Containment and Price Policies on Pharmaceutical Expenditure in South Korea

Background: Policymakers have proposed and implemented various cost-containment policies for drug prices and quantities to regulate rising pharmaceutical spending. Our study focused on a major change in pricing policy and several incentive schemes for curbing pharmaceutical expenditure growth during the 2010s in Korea. Methods: We constructed the longitudinal dataset from 2008-2017 for 11,849 clinics to track the prescriber behavior before and after the implemented policies. Applying an interrupted time series model, we analyzed changes in trends in overall monthly drug expenditure and antibiotic drug expenditure per prescription for outpatient claims diagnosed with three major diseases before and after the policies’ implementation. Results: Significant price reductions and incentives for more efficient drug prescriptions resulted in an immediate decrease in monthly drug expenditures in clinics. However, we found attenuated effects over the long run. The top-spending clinics showed the highest rate of increase in drug costs. Conclusion: Future policy interventions can maximize their effects by targeting high-spending providers.

COVID-19 and the Drug Overdose Crisis: Uncovering the Deadliest Months in the United States, January‒July 2020

Objectives. To determine the magnitude of increases in monthly drug-related overdose mortality during the COVID-19 pandemic in the United States. Methods. We leveraged provisional records from the Centers for Disease Control and Prevention provided as rolling 12-month sums, which are helpful for smoothing, yet may mask pandemic-related spikes in overdose mortality. We cross-referenced these rolling aggregates with previous monthly data to estimate monthly drug-related overdose mortality for January through July 2020. We quantified historical errors stemming from reporting delays and estimated empirically derived 95% prediction intervals (PIs). Results. We found that 9192 (95% PI = 8988, 9397) people died from drug overdose in May 2020—making it the deadliest month on record—representing a 57.7% (95% PI = 54.2%, 61.2%) increase over May 2019. Most states saw large-magnitude increases, with the highest in West Virginia, Kentucky, and Tennessee. We observed low concordance between rolling 12-month aggregates and monthly pandemic-related shocks. Conclusions. Unprecedented increases in overdose mortality occurred during the pandemic, highlighting the value of presenting monthly values alongside smoothed aggregates for detecting shocks. Public Health Implications. Drastic exacerbations of the US overdose crisis warrant renewed investments in overdose surveillance and prevention during the pandemic response and postpandemic recovery efforts. (Am J Public Health. Published online ahead of print April 15, 2021: e1–e8. https://doi.org/10.2105/AJPH.2021.306256 )

Rancang Bangun Aplikasi Rekapitulasi Obat dengan Menerapkan Tanda Tangan Digital

The current condition experienced by the XYZ Polyclinic is that there is no application built to simplify the service process contained in the polyclinic so that all service processes are still manual. An example is the calculation of the number of drugs that are in and out of use. This calculation takes a long time, is prone to errors in accounting, and consumes many papers. To solve this problem, we develop an application to recap drugs. The drug recapitulation application is based on a website with the WebML method using the CodeIgniter framework and MySQL database. The application produces the result in the form of a PDF file of the drug recapitulation report per month and day. As a security feature, the monthly drug recapitulation report results include a digital signature as proof of authentication, integrity, and anti-denial. The application built has been tested using web testing methods and user acceptance testing to be applied.

Estimated Cost of Anticancer Therapy Directed by Comprehensive Genomic Profiling in a Single-Center Study

Purpose Comprehensive genomic profiling (CGP) detects several classes of genomic alterations across numerous genes simultaneously and can match more patients with genomically targeted therapies than conventional molecular profiling. The current study estimated the costs of anticancer drugs and overall survival (OS) for patients who were treated with matched and unmatched therapy. Methods Costs were estimated for patients with complete data (188 of 500 patients) from a prospective, nonrandomized study of patients with diverse refractory cancers who underwent CGP and were treated with matched or unmatched therapy. We assessed mean time to treatment failure (TTF) and mean observed OS. Patient-specific drug and administration costs were imputed for the first regimen after CGP on the basis of drug classes, unit costs, and time on treatment. Results Patients on matched (n = 122) versus unmatched (n = 66) therapy had longer mean TTF (+1.5 months) and observed OS (+2.4 months) and higher drug costs (+$38,065; all P < .01). Increased drug costs were largely attributable to the longer duration of therapy associated with extended TTF (66.3%) rather than higher monthly drug costs (33.7%). Incremental increases in TTF (+1.9 months v +1.2 months) and observed OS (+2.5 months v +2.1 months) between matched and unmatched therapies were larger for those who underwent CGP in earlier- versus later-line therapy. Incremental increases in drug costs between matched and unmatched therapies were lower for earlier- compared with later-line therapy (+$27,000 v +$43,000, respectively). Conclusion Matched therapy was associated with longer TTF, increased OS, and manageable incremental cost increases compared with unmatched therapy. Most of these increased costs were a result of the longer duration of therapy rather than higher monthly drug costs. The benefits of matching were numerically greater in earlier versus later lines of therapy, which is consistent with the value of early use of CGP.

Delivery of meaningful cancer care: Evaluating benefit and cost of cancer therapies using ASCO and ESMO frameworks.

6609 Background: ASCO and ESMO have developed frameworks to evaluate the benefit of cancer therapies. Here, we apply the frameworks to a cohort of contemporary randomized controlled trials (RCTs) to explore agreement and to evaluate the relationship between treatment benefit and cost. Methods: Characteristic and outcome data from RCTs evaluating systemic therapies in non-small cell lung cancer (NSCLC), breast cancer, colorectal cancer (CRC), and pancreatic cancer published and cited in PubMed between 2011-2015 were abstracted. Trial endpoints were evaluated using ASCO and ESMO frameworks. Cohen’s kappa statistic was calculated to determine agreement between the two frameworks, using the median ASCO score as a benefit threshold. Differences in monthly drug cost between RCT experimental and control arms were derived from 2016 average wholesale prices. Analyses included Pearson chi-square tests, Fisher’s Exact tests, independent samples t-tests, and Pearson correlation to assess the association between continuous variables. Results: Fifty percent (136/271) of published RCTs favoured the experimental arm; scoring rubrics were applicable to 109 RCTs (39% NSCLC, 33% breast, 23% CRC, 5% pancreas). ASCO scores ranged from 2 to 72; median score was 25. Thirty seven percent (40/109) of RCTs met benefit thresholds using the ESMO framework. Agreement between frameworks was fair at best (κ = 0.28, p = 0.002). When stratified by treatment intent (19 curative, 90 palliative RCTs), agreement remained poor (κ = 0.23, p = 0.115; κ = 0.34, p < 0.001). Major differences leading to limited agreement includes the relative weights each framework places on HR, endpoints, and toxicity/QOL analysis. Smaller RCT sample size was the only trial characteristic associated with higher ASCO scores (p = 0.015). Among the 100 RCTs for whom drug costing data were available, there was no association between ASCO benefit score and monthly drug costs (r = -0.12, p = 0.22); those meeting ESMO thresholds had a lower mean drug cost than those who did not (p = 0.046). Conclusions: There is only fair correlation between ASCO and ESMO clinical benefit frameworks. Drug costs are not associated with ESMO/ASCO measures of magnitude of clinical benefit.

Estimated cost of anticancer therapy directed by comprehensive genomic profiling (CGP) in a single-center study.

6605 Background: Accumulating evidence supports the clinical benefit of targeted therapies matched to cancer patients based on genomic alterations. CGP, which detects all classes of alterations (base pair substitutions, copy number, insertions/deletions, and rearrangements), can match more patients with available and investigational therapies. This study estimated anti-cancer drug costs and overall survival (OS) for matched vs. unmatched therapy. Methods: Costs were estimated for patients with complete data (N = 188/500) from a prospective, nonrandomized, phase I oncology center study of patients with diverse refractory cancers who underwent CGP and were treated with matched or unmatched therapy (PMID: 27197177). Average time to treatment failure and average OS were assessed during the observation period. Patient-specific drug and administration costs were imputed for the first regimen after CGP based on drug classes, unit costs, and times to treatment failure. Results: Patients onmatched (N = 122) vs. unmatched (N = 66) therapy had, on average, longer time on treatment (+1.5 mos), longer observed survival (+2.4 mos), and higher anti-cancer drug costs (+$38K) (all p < 0.01); 66% of increased drug costs were attributable to longer time on treatment as opposed to higher monthly drug costs. Combination therapy was used for 71% of matched and 53% of unmatched patients. Those undergoing CGP in earlier-line (1-3; N = 58) vs. later-line (4+; N = 130) therapy had numerically larger incremental increases in average times on treatment (+1.9 vs. +1.2 mos) and survival (+2.5 vs. +2.1 mos), and numerically lower incremental drug costs (+$27K vs. +$43K), with matched vs. unmatched therapy. Conclusions: For patients cared for in a phase I clinic, matched vs. unmatched therapy was associated with longer treatment durations, longer survival times, and manageable incremental costs. Despite frequent use of combination therapy, most of the increased costs of matched therapy were due to longer treatment times rather than higher monthly drug costs. Benefits of matching were numerically greater in earlier- vs. later-lines, consistent with the value of earlier-line use of CGP to guide treatment.

Global differences in cancer drug prices: A comparative analysis.

LBA6500 Background: Cancer drug prices are different in every country in the world, however, little is known about the magnitude of these differences. The primary objective of this study was to describe the differences in prices globally. The secondary objective was to understand ability to pay, using gross domestic product per capita at purchasing power parity (GDPcap), as a surrogate. Methods: We calculated monthly drug doses for 23 cancer drugs, 15 of which are available generically. We then calculated monthly drug prices from 6 countries on 5 different continents: Australia (AUS), China (CHI), India (IND), South Africa (SA), United Kingdom (UK), and United States (US). Given the lack of availability of discounted prices, we used list prices in order to make appropriate comparisons. Prices were obtained from locally and nationally recognized institutions. The monthly cost was converted to US$ at the exchange rate ruling on 19 January 2016. We obtained GDPcap data for each country from the International Monetary Fund, in order to estimate the monthly drug price as a percentage of GDPcap. Results: Results are displayed in the table. The median monthly patented drug price ranged from US$1515 (IND) to $8694 (US). The median monthly generic drug price ranged from US$120 (SA) to $654 (US). The median monthly % of GDPcap for patented drugs ranged from 71% (AUS) to 313% (IND). The median monthly % of GDPcap for generic drugs ranged from 3% (AUS) to 48% (CHI). Detailed information regarding specific drugs will be presented. Conclusions: There is a wide variation in drug prices globally. Despite lower prices in poorer countries, both generic and patented drugs appear to be less affordable in poorer countries. Price differences likely have some impact on access to care within individual countries. [Table: see text]