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Official websites use. Share sensitive information only on official, secure websites. Correspondence to Jules M Janssen Daalen; jules. In this systematic review on drug price comparison studies, we report on recent determinants of drug prices in a national and international context to facilitate regulation of drug prices by purchasers and policymakers worldwide. We performed a best-evidence synthesis of these associations for determinants covered in at least three studies. Only one publication described net drug prices and 30 described retail drug prices. Five modifiable determinants were associated with lower retail prices: generic market portion, discounts, tendering policies, central governmental purchasing and pricing regulation schemes. The originators market portion and a system in which mark-ups are common were associated with higher retail prices. Retail prices were highest in the USA, even compared with other high-income countries. A positive association between national income level and drug retail prices could not be established among middle-income and high-income countries. Retail prices were highest in low-income countries when adjusted for purchasing power parity. Literature on determinants of net drug prices is extremely sparse. Various healthcare system interventions, market-specific and governmental regulations are consistently associated with lower retail prices. Some interventions are easily implementable in developing or middle-income countries, such as tendering, central purchasing and fixed pricing regulation schemes. Net drug price comparison studies are needed to overcome the lack of price transparency and to quantify the effectiveness of policy measures on net drug prices. A systematic review on drug price comparison studies in peer-reviewed literature was conducted to assess all recently identified modifiable and non-modifiable determinants of drug prices. Only one published study conducted determinant analyses with net drug prices, while the rest included retail drug prices. The structured best-evidence synthesis is able to quantify heterogeneous evidence and summarises the association between drug price variance and the reported determinants. This study design only allows for correlative analysis and cannot establish direct causal associations between determinants and price variance. The global average share of healthcare costs in gross domestic product GDP increased from 4. Consequently, countries worldwide face the challenge of decreasing this healthcare cost burden. A significant driver of rising healthcare costs is pharmaceutical expenditure, so interventions to decrease drug costs through lower drug prices are warranted. Pharmaceutical expenditure is expected to reach 1. Net drug prices are the prices actually paid by the purchasing healthcare institute, while retail prices exclude various individual pricing agreements such as rebates. By comparing drug prices within and across different countries, determinants of drug prices can be identified. We make a distinction between determinants that are modifiable by policymakers and determinants that are not. Modifiable determinants could act as a target for potential interventions to decrease drug costs. Present drug policies are highly heterogeneous and have varying effects on drug prices. Therefore, identifying and harmonising effective price management strategies may aid in accomplishing lower prices. However, international and national price comparison studies of net drug prices are scarce in the literature, which forms a bottleneck to compare drug prices. To our knowledge, the first publication that quantified drug price differences was performed in in the USA. Since then, research on drug prices excluding price ratios and, more specifically, net drug prices has been very limited, but in recent years some determinants of retail drug prices were identified. However, some are modifiable. In individual studies, systems allowing for mark-ups eg, processing costs or profit passed on to purchaser , degree of market competitiveness, the generics market proportion and degree of governmental intervention reference pricing and education about efficacy of generics have been found to influence drug prices in some countries. Therefore, in this systematic review, we aim to identify determinants of drug prices and more specifically modifiable determinants that may serve as potential targets for drug price optimisation. In addition, we give an overview of the recent literature in drug price comparisons and execute a best-evidence synthesis of all reported determinants of drug prices. We aimed to investigate which determinants influence drug prices by using comparison studies that measure at least one such determinant. All peer-reviewed articles that reported drug prices excluding price ratios in a benchmark or comparative study were included. We did not include primary grey literature documents, such as documents of non-governmental organisations NGOs , as our aim was to assess academic evidence of modifiable determinants, written by independent observers and published in peer-reviewed journals. Both national and international studies were included, as well as pharmacy or hospital comparisons, prospective, transverse and retrospective studies. Only articles published between until and including were included for two reasons. First, our aim is to investigate current determinants of drug prices. Second, articles on this topic published before were scarce and likely less relevant, as the pharmaceutical market underwent significant changes in the last 15 years. We executed a two-way process of reference and citation checking of the included articles. The PICO research format of population, intervention, control, outcome consisted of drug or drug group P , present determinant I , non-present determinant C , drug price or price variance O. Therefore, all peer-reviewed studies that reported a measure of association between drug prices meaning: not relative prices or price indices or price variance dependent variable and one or more determinants independent variable s were included. The full texts of potentially relevant articles were independently assessed for inclusion by two researchers JMJD and AdA. Discrepancies between the researchers were resolved through discussion and consensus. If no consensus was reached, a third researcher BvdB was consulted. A standardised extraction worksheet was used to collect study characteristics, methods and outcome information from all included articles by both AdA and JMJD. The extraction worksheet was ultimately cross-checked. This specific assessment tool was used because studies were mostly cross-sectional, sometimes observational and generally heterogeneous. In compliance with the assessment tool methods, studies were categorised in three quality levels: good all relevant qualifications met , fair one or two not met or poor three or more not met. Within the studies, selective reporting was assessed by carefully exploring the entire Results section and supplemental material for non-reported associations. A qualitative best-evidence synthesis was performed to identify determinants of drug prices and variance in drug prices. Drug price variance reflects the potentiality of price differences of the same drug arising with comparable exposure to the analysed determinant. Unfortunately, the heterogeneity between studies meant a quantitative analysis was not feasible. Determinants measured in every study were counted. If a determinant was studied three times or more, then it was analysed and a best-evidence synthesis was conducted. If the determinant was studied once or twice, it was only shortly discussed, as the data were considered to be of insufficient robust quality for qualitative analysis. Level of evidence was based on the combination of study quality together with the total number of studies that measured the determinant. After duplication removal and title-abstract screening, 85 full-text articles were screened for eligibility. After full-text screening, 31 of these 85 articles were included in this systematic review. The reason for exclusion was often an irrelevant study outcome, such as drug efficacy, affordability or study design, such as reviews discussing policy. A detailed process outline is visualised in eFigure 1 of the Supplemental Materials. Ten articles of good quality, 16 articles of fair quality and 5 articles of poor quality were identified. Table 1 presents a summary of the risk of bias assessment. Of the 31 included studies, most had a cross-sectional design. Seven studies measured drug prices over a period of 1—17 years, most often with more than one follow-up. Only the study by Van Harten et al reported net drug prices. Therefore, unless otherwise specified, drug prices indicate retail prices. Table 1 displays study characteristics. Table 1 describes all determinants measured per study and categorises the scope of the study in international versus national context. Table 2 depicts the best-evidence synthesis to which this section refers. Below, the most common determinants of drug prices and drug price variance are described in further detail. Determinants in European countries were often studied because of comparable national wealth but fairly different drug pricing policies, allowing for more accurate evaluation of pricing policy efficacy. Three studies compared the most affluent European regions to other European countries, of which one included net drug prices. Seven studies compared the USA to other high-income countries. These studies addressed differences between hospitals, pharmacies, subregions and states, respectively. Medication in Northern Europe was often more expensive compared with southern Europe, although this finding was inconsistent across studies and there was no consistent association between cancer drug prices and GDP in high-income European countries. Across a broad spectrum in high-income countries as well as high-income versus middle-income countries, an association between GDP and drug prices could not be established. After PPP adjustment, there was a direct relationship between GDP category and the frequency of lowest prices: across high, middle and low-income countries, high-income countries most often had the lowest prices. Various studies assessed market influence in the form of a high proportion of generics or originators nine studies or patent expiry three studies. Price-technical constructs such as discounts and mark-ups were common in five studies, of which the study by Van Harten et al included net drug prices and four described retail prices. Occasionally, drugs were a random representative sample of widely used drugs, such as statins, analgesics and broad-spectrum antibiotics, most often including generics and originator drugs. High market proportions of originator drugs led to high prices as well as price variance in all countries. In low-middle and low-middle income countries, price variance is already significant. This association is not observed for generic substitutes. Drug prices in systems allowing for mark-ups tend to be higher than systems without. Strong evidence for price reduction was found in countries with a high generics proportion in the pharmaceutical market. Patent expiry was always accompanied by price reduction. Conflicting evidence suggests that a more independent status of pharmacies compared with a chain is associated with lower drug prices. Of all price regulating policy measures, the strongest evidence exists for tendering. This effect, however, does not hold for net cancer drug prices across European countries with the exception of France. This study was conducted to systematically review drug price comparison studies about the modifiable determinants of drug prices. We found that literature on net drug prices is very scarce and that there is very limited insight in drug pricing mechanisms, which makes it impossible for purchasers and policymakers to transparently compare drug prices. These findings are indicative of an opaque price market. As the literature only delivers anecdotal evidence for differences in net drug prices, this study is unable to comment on determinants of net drug prices to accomplish insight in pricing mechanisms which can fuel the global drug price discussion. Retail prices in an international and national context display a high degree of variance and not all variance can be explained by the measured determinants in this study. Despite this, we found that modifiable determinants that were associated with lower prices are as follows: a higher generics market portion, discounts, tendering policies, central governmental purchasing and pricing regulation schemes. Modifiable determinants that were associated with higher prices are markets with higher originators market portion and systems in which mark-ups were common. In addition, the highest and most persistently increasing prices were seen in the USA, even compared with other high-income countries. A higher GDP was associated with higher prices in middle-income versus low-income countries, but not in high-income versus middle-income countries. After PPP adjustment, highest relative prices were consistently reported in low-income countries. The drug market has been subject to dramatic inflation in size as well as price over the last decades, in which expensive drugs such as anticancer drugs stand out. Our findings about generics and originator market portions indicate that increasing the supply of generics is associated with price reductions, but this is often not the case as a stand-alone measure. For example, high-income countries with a relatively open market entry consistently experience higher initial prices for generics compared with countries with a more regulated generics market, such as Scandinavian countries with mandatory generic substitution. Direct price control by regulation on expensive drugs such as anticancer drugs likely has more influence than percentage discounts. Tendering led to lower prices and more specifically, lower generic-originator differences in various European countries. The risks of tendering include a too narrow focus on price and not quality. This may be of even higher importance in countries with limited quality control than in Europe and the USA, where market approval is granted after a diligent selection process by the European Medicines Agency and Food and Drug Administration. Conversely, because of this exact reason, too high tender frequency reduces competitive pressure. Each intervention has different consequences based on the timing and sequence of implementation. Moreover, many interdependencies exist between existing measures and new interventions. An earlier extensive review on determinants of pharmaceutical expenditure has also shed light on these dynamic properties of market interventions and governmental regulation on drug prices as well as on investments in research and development. Therefore, we recommend future policy effectivity studies to include a careful assessment of external validity of their results; an extensive description of the healthcare system, governmental regularisation and market properties. Due to the lack of significant price differences between middle-income and high-income countries, prices did not linearly increase with GDP throughout the entire GDP spectrum. This variance is largely explained by the relatively unorganised market and lack of pricing regulation. In contrast, developed countries generally have more organised price referencing systems and direct agreements with pharmaceutical companies, which means more expensive drugs can be purchased in large-scale volumes. A large portion of the observed price differences between high-income countries originates from the USA, likely because of the unregulated free-market approach. The findings are to be interpreted with caution because it is likely that large heterogeneity and the lack of net pricing data added significantly to the weighting in this best-evidence analyses and the outcomes of the synthesis. Nonetheless, a significant number of studies reported no association between the measured determinant s and drug price s , indicating that not only positive findings were published. The lack of net pricing is likely partly due to the fact that we excluded primary grey literature documents from our main research corpus. Various institutions, most prominently the WHO, are increasing their efforts in assessing pharmaceutical expenditure and its determinants as shown by a recent overview of grey literature. We recognise that the included studies only establish associations. For identifying causal associations, controlled trials are needed which are very hard to execute due to a lack of transparency and collaborative effort, as well as the difficulty of conducting an intervention ceteris paribus. Many studies reported large measures of uncertainty due to non-disclosure of data such as discounts, net prices paid, volumes sold, negotiations and arrangements with pharmaceutical companies. Therefore, many studies did not report an exact representation of the pharmaceutical market. Net prices may have been more economical than the retail prices reported in the literature on which this review is based, but current literature is insufficient to give further insight in net drug price determinants. This exacerbates the challenge of reducing healthcare costs, as real price comparisons are can never be made in this state of affairs. In addition, selection bias medication selection is likely significant as the most complete or readily available data are used, instead of drug price data that might be less available, such as price data on confidential pricing agreements. On the contrary, the total set of included studies comprises a large variety of drugs and countries, increasing external validity of these findings. The lack of transparency and the high prevalence of non-disclosure agreements are likely two of the major drivers for drug price differences. We call for an elimination of non-disclosure agreements to better understand underlying drug price determinants and mechanisms. In addition, we identified a gap in the representation of national studies, as only six national within-country analyses were identified. Therefore, we were unable to solidly identify determinants of price in the national setting. Additional transparent, open-access research into price variance using net drug prices is needed to identify determinants of national and international price variance, which can be helpful to governments and regional institutes such as hospitals alike to improve their purchasing strategy and methods. Uniform introduction of pricing regulation and publication of net drug prices may ultimately lead to more price transparency and a more balanced playing field of countries with a significant budget constrain. Such a situation allows for fair negotiations and, ultimately, a more sustainable and transparent healthcare sector. Peer-reviewed literature on the determinants of net drug paid prices and corresponding pricing mechanisms is very scarce. This is remarkable given the rising healthcare costs and in particular rising pharmaceutical costs, as well the growing societal discussion on mitigating healthcare expenditure. Retail drug prices display a high degree of variance, both within and between countries. Policymakers may be particularly interested in the policy-related determinants of lower retail prices. Drug prices in low-income countries are consistently higher after adjustment for PPP, indicating that lower-income countries still pay the highest relative retail prices. Various easily implementable governmental interventions and regulations, as well as modifiable market system-related characteristics, are consistently associated with lower retail prices and thus potential price reduction, such as increasing the generic portions of the drug market, governmental policies such as tendering, central purchasing and regulation schemes targeting annual price inflation, patent regulation and mark-ups, which might aid developing countries in closing the gap of purchasing power-adjusted prices with high-income countries in the future. Most prominently, national and international net price studies are necessary to quantify the effectiveness of these policy measures on net drug prices. We call for openness of net drug price data, as this is our key to change the healthcare cost burden. All used data are published and available online. Contributors: All authors contributed to the conception and design of the research. BvdB and MVH provided in multiple sessions conceptual and detailed feedback for every version of the manuscript. Funding: The authors have not declared a specific grant for this research from any funding agency in the public, commercial or not-for-profit sectors. Supplemental material: This content has been supplied by the author s. Any opinions or recommendations discussed are solely those of the author s and are not endorsed by BMJ. BMJ disclaims all liability and responsibility arising from any reliance placed on the content. All data relevant to this study are included in the article or available as supplementary material. This article is a systematic review of previously published peer-reviewed literature. It does not concern human research and does not use or generate data regarding characteristics or state of health of individuals. This section collects any data citations, data availability statements, or supplementary materials included in this article. As a library, NLM provides access to scientific literature. BMJ Open. Find articles by Jules M Janssen Daalen. Find articles by Anouk den Ambtman. Find articles by Mark Van Houdenhoven. Find articles by Bart J F van den Bemt. No commercial re-use. See rights and permissions. Published by BMJ. Open in a new tab. Price category listed as mentioned or as described in the article. Provenance and peer review: Not commissioned; externally peer reviewed. Similar articles. Add to Collections. Create a new collection. Add to an existing collection. Choose a collection Unable to load your collection due to an error Please try again. Add Cancel. Bulfone Cameron et al Clarke and Fitzgerald Cuomo et al Goldstein e t al Van Harten et al 5. Hill et al Iyengar et al Leopold et al Mahlich et al Manova et al Muzumdar et al Roughead et al Salmasi et al Lowest available price and target price. Rheumatoid arthritis biologicals and biosimilars. Etanercept, adalimumab, certolizumab, ustekinumab. Geographic : NS. Savage et al Schlenker et al Simoens et al Srivastava and McGuire Suh et al Vogler et al Wouters and Kanavos Gong et al Kolasani et al Ongarora et al Scott et al Theisen et al Wholesale, commercial, governmental health plan prices. Moderate for positive association Conflicting evidence Strong for positive association.

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