Comparison of drug prescribing before and during the COVID-19 pandemic: A cross-national European study.

PURPOSE: The COVID-19 pandemic had an impact on health care, with disruption to routine clinical care. Our aim was to describe changes in prescription drugs dispensing in the primary and outpatient sectors during the first year of the pandemic across Europe. METHODS: We used routine administrative data on dispensed medicines in eight European countries (five whole countries, three represented by one region each) from January 2017 to March 2021 to compare the first year of the COVID-19 pandemic with the preceding 3 years. RESULTS: In the 10 therapeutic subgroups with the highest dispensed volumes across all countries/regions the relative changes between the COVID-19 period and the year before were mostly of a magnitude similar to changes between previous periods. However, for drugs for obstructive airway diseases the changes in the COVID-19 period were stronger in several countries/regions. In all countries/regions a decrease in dispensed DDDs of antibiotics for systemic use (from -39.4% in Romagna to -14.2% in Scotland) and nasal preparations (from -34.4% in Lithuania to -5.7% in Sweden) was observed. We observed a stockpiling effect in the total market in March 2020 in six countries/regions. In Czechia the observed increase was not significant and in Slovenia volumes increased only after the end of the first lockdown. We found an increase in average therapeutic quantity per pack dispensed, which, however, exceeded 5% only in Slovenia, Germany, and Czechia. CONCLUSIONS: The findings from this first European cross-national comparison show a substantial decrease in dispensed volumes of antibiotics for systemic use in all countries/regions. The results also indicate that the provision of medicines for common chronic conditions was mostly resilient to challenges faced during the pandemic. However, there were notable differences between the countries/regions for some therapeutic areas.

Improving prescribing through big data approaches-Ten years of the Scottish Prescribing Information System.

Medicines are a major component of modern healthcare delivery, both in resource consumption and as drivers of innovation. The ever-increasing application of digitalisation within day-to-day living and as part of our healthcare systems-with the resultant data generation-presents the opportunity to better define the populations exposed to medicines, and their benefits and harm in real world settings. This article outlines the development of the Scottish National Prescribing Information System (PIS) and describes how this capability is being used to support the safe and effective use of medicines, both nationally and internationally. Since 2009, PIS has included e-prescribed/e-dispensed and reimbursed medicines data, now totalling 976 million prescriptions, with codified structured data on dose instructions. A literature review, covering the period from January 2009 to March 2019, identified 40 full publications using PIS, the first occurring in 2014. The majority involved pharmacoepidemiology/drug-use studies (50%) in cancer and cardiovascular disease. Measuring the value and impact of PIS was extended beyond publication quantification by illustrating the translation of PIS outputs into the learning health system at scale. The developing Scottish capabilities add breadth and depth to the wider evolving international environment, and offer the potential to contribute collegiately to the global effort on medicine safety and effectiveness, including support for the World Health Organisation Global Patient Safety Challenge: Medication Without Harm.

Use of sequence analysis for classifying individual antidepressant trajectories to monitor population mental health.

BACKGROUND: Over the past decade, antidepressant prescriptions have increased in European countries and the United States, partly due to an increase in the number of new cases of mental illness. This paper demonstrates an innovative approach to the classification of population level change in mental health status, using administrative data for a large sample of the Scottish population. We aimed to identify groups of individuals with similar patterns of change in pattern of prescribing, validate these groups by comparison with other indicators of mental illness, and characterise the population most at risk of increasing mental ill health. METHODS: National Health Service (NHS) prescription data were linked to the Scottish Longitudinal Study (SLS), a 5.3% sample of the Scottish population (N = 151,418). Antidepressant prescription status over the previous 6 months was recorded for every month for which data were available (January 2009-December 2014), and sequence dissimilarity was computed by optimal matching. Hierarchical clustering was used to create groups of participants who had similar patterns of change, with multi-level logistic regression used to understand group membership. RESULTS: Five distinct prescription pattern groups were observed, indicating: no prescriptions (76%), occasional prescriptions (10%), continuation of prior use of prescriptions (8%), a new course of prescriptions started (4%) or ceased taking prescriptions (3%). Young, white, female participants, of low social grade, residing in socially deprived neighbourhoods, living alone, being separated/divorced or out of the labour force, were more likely to be in the group that started a new course of antidepressant prescriptions. CONCLUSIONS: The use of sequence analysis for classifying individual antidepressant trajectories offers a novel approach for capturing population-level changes in mental health risk. By classifying individuals into groups based on their anti-depressant medication use we can better identify how over time, mental health is associated with individual risk factors and contextual factors at the local level and the macro political and economic scale.

Data Resource Profile: The Hospital Electronic Prescribing and Medicines Administration (HEPMA) National Data Collection in Scotland.

Introduction: To support both electronic prescribing and documentation of medicines administration in secondary care, hospitals in Scotland are currently implementing the Hospital Electronic Prescribing and Medicines Administration (HEPMA) software. Driven by the COVID-19 pandemic, agreements have been put in place to centrally collate data stemming from the operational HEPMA system. The aim was to develop a national data resource based on records created in secondary care, in line with pre-existing collections of data from primary care. Methods: HEPMA is a live clinical system and updated on a continuous basis. Data is automatically extracted from local systems at least weekly and, in most cases, on a nightly basis, and integrated into the national HEPMA dataset. Subsequently, the data are subject to quality checks including data consistency and completeness. Records contain a unique patient identified (Community Health Index number), enabling linkage to other routinely collected data including primary care prescriptions, hospital admission episodes, and death records. Results: The HEPMA data resource captures and compiles information on all medicines prescribed within the ward/hospital covered by the system; this includes medicine name, formulation, strength, dose, route, and frequency of administration, and dates and times of prescribing. In addition, the HEPMA dataset also captures information on medicines administration, including dates and time of administration. Data is available from January 2019 onwards and held by Public Health Scotland. Conclusion: The national HEPMA data resource supports cross-sectional/point-prevalence studies including drug utilisation studies, and also offers scope to conduct longitudinal studies, e.g., cohort and case-control studies. With the possibility to link to other relevant datasets, additional areas of interest may include health policy evaluations and health economics studies. Access to data is subject to approval; researchers need to contact the electronic Data Research and Innovation Service (eDRIS) in the first instance.

The impact of the COVID-19 pandemic on cardiovascular disease prevention and management.

How the Coronavirus Disease 2019 (COVID-19) pandemic has affected prevention and management of cardiovascular disease (CVD) is not fully understood. In this study, we used medication data as a proxy for CVD management using routinely collected, de-identified, individual-level data comprising 1.32 billion records of community-dispensed CVD medications from England, Scotland and Wales between April 2018 and July 2021. Here we describe monthly counts of prevalent and incident medications dispensed, as well as percentage changes compared to the previous year, for several CVD-related indications, focusing on hypertension, hypercholesterolemia and diabetes. We observed a decline in the dispensing of antihypertensive medications between March 2020 and July 2021, with 491,306 fewer individuals initiating treatment than expected. This decline was predicted to result in 13,662 additional CVD events, including 2,281 cases of myocardial infarction and 3,474 cases of stroke, should individuals remain untreated over their lifecourse. Incident use of lipid-lowering medications decreased by 16,744 patients per month during the first half of 2021 as compared to 2019. By contrast, incident use of medications to treat type 2 diabetes mellitus, other than insulin, increased by approximately 623 patients per month for the same time period. In light of these results, methods to identify and treat individuals who have missed treatment for CVD risk factors and remain undiagnosed are urgently required to avoid large numbers of excess future CVD events, an indirect impact of the COVID-19 pandemic.

Corrigendum to "Utilisation Trend of Long-Acting Insulin Analogues including Biosimilars across Europe: Findings and Implications".

[This corrects the article DOI: 10.1155/2021/9996193.].

Impact of regulatory safety notices on valproate prescribing and pregnancy outcome among women of child-bearing potential in Scotland: a population-based cohort study.

OBJECTIVE: To examine the impact of Medicines and Healthcare products Regulatory Agency (MHRA) safety alerts on valproate prescribing among women aged 14-45 years in Scotland and examine trends in pregnancies exposed to valproate. DESIGN: Population-based cohort study. PARTICIPANTS: 21 983 women of all ages who received valproate between January 2011 and December 2019. METHODS: All valproate prescriptions issued to women in Scotland between January 2011 and December 2019 were identified and prevalence/incidence rates per 10 000 population derived. The impact of regulatory safety alerts on prescribing was analysed using Joinpoint models. Linked pregnancy records for January 2011 to September 2019 were identified and annual rates of pregnancy per 1000 valproate-treated women aged 14-45 years were calculated for each pregnancy outcome: live birth, stillbirth, miscarriage and termination. RESULTS: Annual prevalent and incident rates of valproate prescribing declined in women aged 14-45 years between 2011 and 2019 from 40.5 to 18.3 per 10 000 population (54.8% reduction) and 7.9 to 1.3 per 10 000 population (83.5% reduction), respectively. Statistically significant changes occurred around the times of the MHRA safety alerts. The number of valproate-exposed pregnancies conceived each year fell from 70 in 2011 to 20 in 2018, a 71.4% reduction, and the number of live births fell from 52 to 14, a 73.0% reduction. Expressed as a rate this was a 46.4% decrease from 15.3 to 8.2 per 1000 valproate-treated women aged 14-45 years in 2011 and 2018, respectively. Live birth was the most common pregnancy outcome. CONCLUSION: This study demonstrates, for the first time, the capabilities of national data sets to identify drug exposure and derive pregnancy outcome at scale across Scotland. Building on this as part of an evolving national/UK surveillance capability will continue efforts to minimise in-utero exposure to valproate; enabling ongoing surveillance to understand better long-term outcomes, and to inform better provision of health and wider support services.

Drug prescriptions and dementia incidence: a medication-wide association study of 17000 dementia cases among half a million participants.

BACKGROUND: Previous studies have suggested that some medications may influence dementia risk. We conducted a hypothesis-generating medication-wide association study to investigate systematically the association between all prescription medications and incident dementia. METHODS: We used a population-based cohort within the Secure Anonymised Information Linkage (SAIL) databank, comprising routinely-collected primary care, hospital admissions and mortality data from Wales, UK. We included all participants born after 1910 and registered with a SAIL general practice at ≤60 years old. Follow-up was from each participant's 60th birthday to the earliest of dementia diagnosis, deregistration from a SAIL general practice, death or the end of 2018. We considered participants exposed to a medication if they received ≥1 prescription for any of 744 medications before or during follow-up. We adjusted for sex, smoking and socioeconomic status. The outcome was any all-cause dementia code in primary care, hospital or mortality data during follow-up. We used Cox regression to calculate hazard ratios and Bonferroni-corrected p values. RESULTS: Of 551 344 participants, 16 998 (3%) developed dementia (median follow-up was 17 years for people who developed dementia, 10 years for those without dementia). Of 744 medications, 221 (30%) were associated with dementia. Of these, 217 (98%) were associated with increased dementia incidence, many clustering around certain indications. Four medications (all vaccines) were associated with a lower dementia incidence. CONCLUSIONS: Almost a third of medications were associated with dementia. The clustering of many drugs around certain indications may provide insights into early manifestations of dementia. We encourage further investigation of hypotheses generated by these results.

Assessing medication use patterns in patients hospitalised with COVID-19: a retrospective study.

OBJECTIVE: To describe patterns of medication use-that is, dexamethasone; remdesivir; and tocilizumab-in the management of patients hospitalised with COVID-19. DESIGN AND SETTING: Retrospective observational study, using routinely collected, linked electronic data from clinical practice in Scotland. Data on drug exposure in secondary care has been obtained from the Hospital Electronic Prescribing and Medicines Administration System. PARTICIPANTS: Patients being treated with the drugs of interest and hospitalised for COVID-19 between 1 March 2020 and 10 November 2021. OUTCOMES: Identification of patients subject to the treatments of interest; summary of patients' baseline characteristics; description of medication use patterns and treatment episodes. Analyses were descriptive in nature. RESULTS: Overall, 4063 patients matching the inclusion criteria were identified in Scotland, with a median (IQR) age of 64 years (52-76). Among all patients, 81.4% (n=3307) and 17.8% (n=725) were treated with one or two medicines, respectively; dexamethasone monotherapy accounted for the majority (n=3094, 76.2%) followed by dexamethasone in combination with tocilizumab (n=530, 13.0%). Treatment patterns were variable over time but roughly followed the waves of COVID-19 infections; however, the different drugs were used to varying degrees during the study period.The median (IQR) treatment duration differed by medicine: dexamethasone 5 days (2-9); remdesivir 5 days (2-5); and tocilizumab 1 day (1-1). The overall median (IQR) length of hospital stay among all patients included in the study cohort was 9 days (5-17); 24.7% of patients died in hospital. CONCLUSION: The use of adjuvant medicines in patients hospitalised with COVID-19 appears in line with evolving evidence and changing treatment guidelines. In-hospital electronic prescribing systems are a valuable source of information, providing detailed patient-level data on in-hospital drug use.

Examining the impact of the first wave of COVID-19 and associated control measures on interventions to prevent blood-borne viruses among people who inject drugs in Scotland: an interrupted time series study.

BACKGROUND: COVID-19 has likely affected the delivery of interventions to prevent blood-borne viruses (BBVs) among people who inject drugs (PWID). We examined the impact of the first wave of COVID-19 in Scotland on: 1) needle and syringe provision (NSP), 2) opioid agonist therapy (OAT) and 3) BBV testing. METHODS: An interrupted time series study design; 23rd March 2020 (date of the first 'lockdown') was chosen as the key date. RESULTS: The number of HIV tests and HCV tests in drug services/prisons, and the number of needles/syringes (N/S) distributed decreased by 94% (RR=0.062, 95% CI 0.041-0.094, p < 0.001), 95% (RR=0.049, 95% CI 0.034-0.069, p < 0.001) and 18% (RR = 0.816, 95% CI 0.750-0.887, p < 0.001), respectively, immediately after lockdown. Post-lockdown, an increasing trend was observed relating to the number of N/S distributed (0.6%; RR = 1.006, 95% CI 1.001-1.012, p = 0.015), HIV tests (12.1%; RR = 1.121, 95% CI 1.092-1.152, p < 0.001) and HCV tests (13.2%; RR = 1.132, 95 CI 1.106-1.158, p < 0.001). Trends relating to the total amount of methadone prescribed remained stable, but a decreasing trend in the number of prescriptions (2.4%; RR = 0.976, 95% CI 0.959-0.993, p = 0.006) and an increasing trend in the quantity prescribed per prescription (2.8%; RR = 1.028, 95% CI 1.013-1.042, p < 0.001) was observed post-lockdown. CONCLUSIONS: COVID-19 impacted the delivery of BBV prevention services for PWID in Scotland. While there is evidence of service recovery; further effort is likely required to return some intervention coverage to pre-pandemic levels in the context of subsequent waves of COVID-19.

Retrospective cohort study to evaluate medication use in patients hospitalised with COVID-19 in Scotland: protocol for a national observational study.

INTRODUCTION: COVID-19 has caused millions of hospitalisations and deaths globally. A range of vaccines have been developed and are being deployed at scale in the UK to prevent SARS-CoV-2 infection, which have reduced risk of infection and severe COVID-19 outcomes. Those with COVID-19 are now being treated with several repurposed drugs based on evidence emerging from recent clinical trials. However, there is currently limited real-world data available related to the use of these drugs in routine clinical practice. The purpose of this study is to address the prevailing knowledge gaps regarding the use of dexamethasone, remdesivir and tocilizumab by conducting an exploratory drug utilisation study, aimed at providing in-depth descriptions of patients receiving these drugs as well as the treatment patterns observed in Scotland. METHODS AND ANALYSIS: Retrospective cohort study, comprising adult patients admitted to hospital with confirmed or suspected COVID-19 across five Scottish Health Boards using data from in-hospital ePrescribing linked to the Early Estimation of Vaccine and Anti-Viral Effectiveness (EAVE II) COVID-19 surveillance platform. The primary outcome will be exposure to the medicines of interest (dexamethasone, remdesivir, tocilizumab), either alone or in combination; exposure will be described in terms of drug(s) of choice; prescribed and administered dose; treatment duration; and any changes in treatment, for example, dose escalation and/or switching to an alternative drug. Analyses will primarily be descriptive in nature. ETHICS AND DISSEMINATION: Ethical and information governance approvals have been obtained by the National Research Ethics Service Committee, South East Scotland 02 and the Public Benefit and Privacy Panel for Health and Social Care, respectively. Findings from this study will be presented at academic and clinical conferences, and to the funders and other interested parties as appropriate; study findings will also be published in peer-reviewed journals. Publications will be available on the EAVE II website (https://www.ed.ac.uk/usher/eave-ii/key-outputs/our-publications), alongside lay summaries and infographics aimed at the general public. Press releases will also be considered, if appropriate.

Potential approaches for the pricing of cancer medicines across Europe to enhance the sustainability of healthcare systems and the implications.

Introduction: There are growing concerns among European health authorities regarding increasing prices for new cancer medicines, prices not necessarily linked to health gain and the implications for the sustainability of their healthcare systems.Areas covered: Narrative discussion principally among payers and their advisers regarding potential approaches to the pricing of new cancer medicines.Expert opinion: A number of potential pricing approaches are discussed including minimum effectiveness levels for new cancer medicines, managed entry agreements, multicriteria decision analyses (MCDAs), differential/tiered pricing, fair pricing models, amortization models as well as de-linkage models. We are likely to see a growth in alternative pricing deliberations in view of ongoing challenges. These include the considerable number of new oncology medicines in development including new gene therapies, new oncology medicines being launched with uncertainty regarding their value, and continued high prices coupled with the extent of confidential discounts for reimbursement. However, balanced against the need for new cancer medicines. This will lead to greater scrutiny over the prices of patent oncology medicines as more standard medicines lose their patent, calls for greater transparency as well as new models including amortization models. We will be monitoring these developments.

Utilisation Trend of Long-Acting Insulin Analogues including Biosimilars across Europe: Findings and Implications.

BACKGROUND: Diabetes mellitus rates and associated costs continue to rise across Europe enhancing health authority focus on its management. The risk of complications is enhanced by poor glycaemic control, with long-acting insulin analogues developed to reduce hypoglycaemia and improve patient convenience. There are concerns though with their considerably higher costs, but moderated by reductions in complications and associated costs. Biosimilars can help further reduce costs. However, to date, price reductions for biosimilar insulin glargine appear limited. In addition, the originator company has switched promotional efforts to more concentrated patented formulations to reduce the impact of biosimilars. There are also concerns with different devices between the manufacturers. As a result, there is a need to assess current utilisation rates for insulins, especially long-acting insulin analogues and biosimilars, and the rationale for patterns seen, among multiple European countries to provide future direction. Methodology. Health authority databases are examined to assess utilisation and expenditure patterns for insulins, including biosimilar insulin glargine. Explanations for patterns seen were provided by senior-level personnel. RESULTS: Typically increasing use of long-acting insulin analogues across Europe including both Western and Central and Eastern European countries reflects perceived patient benefits despite higher prices. However, activities by the originator company to switch patients to more concentrated insulin glargine coupled with lowering prices towards biosimilars have limited biosimilar uptake, with biosimilars not currently launched in a minority of European countries. A number of activities were identified to address this. Enhancing the attractiveness of the biosimilar insulin market is essential to encourage other biosimilar manufacturers to enter the market as more long-acting insulin analogues lose their patents to benefit all key stakeholder groups. CONCLUSIONS: There are concerns with the availability and use of insulin glargine biosimilars among European countries despite lower costs. This can be addressed.

Use of text-mining methods to improve efficiency in the calculation of drug exposure to support pharmacoepidemiology studies.

Background: Efficient generation of structured dose instructions that enable researchers to calculate drug exposure is central to pharmacoepidemiology studies. Our aim was to design and test an algorithm to codify dose instructions, applied to the NHS Scotland Prescribing Information System (PIS) that records about 100 million prescriptions per annum. Methods: A natural language processing (NLP) algorithm was developed that enabled free-text dose instructions to be represented by three attributes - quantity, frequency and qualifier - specified by three, three and two variables, respectively. A sample of 15 593 distinct dose instructions was used to test, validate and refine the algorithm. The final algorithm used a zero-assumption approach and was then applied to the full dataset. Results: The initial algorithm generated structured output for 13 152 (84.34%) of the 15 593 sample dose instructions, and reviewers identified 767 (5.83%) incorrect translations, giving an accuracy of 94.17%. Following subsequent refinement of the algorithm rules, application to the full dataset of 458 227 687 prescriptions (99.67% had dose instructions represented by 4 964 083 distinct instructions) generated a structured output for 92.3% of dose instruction texts. This varied by therapeutic area (from 86.7% for the central nervous system to 96.8% for the cardiovascular system). Conclusions: We created an NLP algorithm, operational at scale, to produce structured output that gives data users maximum flexibility to formulate, test and apply their own assumptions according to the medicines under investigation. Text mining approaches can provide a solution to the safe and efficient management and provisioning of large volumes of data generated through our health systems.

Benzodiazepine and z-hypnotic prescribing for older people in primary care: a cross-sectional population-based study.

BACKGROUND: Overall prescribing of benzodiazepines and z-hypnotics (B&Zs) has slowly reduced over the past 20 years. However, long-term prescribing still occurs, particularly among older people, and this is at odds with prescribing guidance. AIM: To compare prescribing of B&Zs between care home and non-care home residents ≥65 years old. DESIGN AND SETTING: Cross-sectional population-based study in primary care in Scotland. METHOD: National patient-level B&Z prescribing data, for all adults aged ≥65 years, were extracted from the Prescribing Information System (PIS) for the calendar year 2011. The PIS gives access to data for all NHS prescriptions dispensed in primary care in Scotland. Data were stratified by health board, residential status, sex, and age (65-74, 75-84, and ≥85 years). To minimise disclosure risk, data from smaller health boards were amalgamated according to geography, thereby reducing the number from 14 to 10 areas. RESULTS: A total of 17% (n = 879 492) of the Scottish population were aged ≥65 years, of which 3.7% (n = 32 368) were care home residents. In total, 12.1% (n = 106 412) of older people were prescribed one or more B&Z: 5.9% an anxiolytic, 7.5% a hypnotic, and 1.3% were prescribed both. B&Zs were prescribed to 28.4% (9199) of care home and 11.5% (97 213) of non-care home residents (relative risk = 2.88, 95% CI = 2.82 to 2.95, P<0.001). Estimated annual B&Z exposure reduced with increasing age of care home residents, whereas non-care home residents' exposure increased with age. CONCLUSION: B&Zs were commonly prescribed for older people, with care home residents approximately three times more likely to be prescribed B&Zs than non-care home residents. However, overall B&Z exposure among non-care home residents was found to rise with increasing age.

Risk-factors for methadone-specific deaths in Scotland's methadone-prescription clients between 2009 and 2013.

AIM: To quantify gender, age-group and quantity of methadone prescribed as risk factors for drugs-related deaths (DRDs), and for methadone-specific DRDs, in Scotland's methadone-prescription clients. DESIGN: Linkage to death-records for Scotland's methadone-clients with one or more Community Health Index (CHI)-identified methadone prescriptions during July 2009 to June 2013. SETTING: Scotland's Prescribing Information System and National Records of Scotland. MEASUREMENTS: Covariates defined at first CHI-identified methadone prescription, and person-years at-risk (pys) thereafter until the earlier of death-date or 31 December 2013. Methadone-specific DRDs were defined as: methadone implicated but neither heroin nor buprenorphine. Hazard ratios (HRs) were assessed using proportional hazards regression. FINDINGS: Scotland's CHI-identified methadone-prescription cohort comprised 33,128 clients, 121,254 pys, 1,171 non-DRDs and 760 DRDs (6.3 per 1,000 pys), of which 362 were methadone-specific. Irrespective of gender, methadone-specific DRD-rate, per 1,000 pys, was higher in the 35+ age-group (4.2; 95% CI: 3.6-4.7) than for younger clients (1.9; 95% CI: 1.5-2.2). For methadone-specific DRDs, age-related HRs (e.g., 2.9 at 45+ years; 95% CI: 2.1-3.9) were steeper than for all DRDs (1.9; 95% CI: 1.5-2.4); there was no hazard-reduction for females; no gender by age-group interaction; and, unlike for all DRDs, the highest quintile for quantity of prescribed methadone at cohort-entry (>1960mg) was associated with increased HR (1.8; 95% CI: 1.3-2.5). CONCLUSION: Higher methadone-specific DRD rates in older clients, irrespective of gender, call for better understanding of methadone's pharmaco-dynamics in older, opioid-dependent clients, many with progressive physical or mental ill-health.

A qualitative study of the relationship between the Scottish Medicines Consortium and their clinical experts.

RATIONALE, AIMS AND OBJECTIVES: Internationally, health technology assessments (HTAs) are ubiquitous drivers to health policy. Within Scotland, the Scottish Medicines Consortium undertakes the medicine review process. Input from clinical experts, involved in frontline care, is an integral component of the assessment process. This paper explores the relationship between the clinical experts and the HTA agency within Scotland to better understand what motivates expert clinicians to devote their time to the medicine review process with no remuneration. METHODS: Twenty-seven clinical experts from 16 different clinical specialties took part in one-to-one interviews at their place of work between October 2011 and March 2012. Data analysis was inductive and comprised the organization of data into a framework and a subsequent thematic analysis. RESULTS: Three distinct themes were identified: (1) recruitment, which identified two types of explanations for the experts' appointment: external justification (nominated by another) and internal justification (being recognized as an expert); (2) flexibility of the procedures, with experts able to determine their own response style and negotiate timelines; (3) health care systems, demonstrating that their affiliation to the health system underpinned the relationship and their motivation to be clinical experts. CONCLUSIONS: The findings of this study provide insight into the elements important to clinicians who voluntarily contribute to HTA processes. Examination of these elements in the context of the organizational citizenship behavior literature provides a foundation on which to improve understanding of this relationship and sustain and improve clinical expert participation in an increasingly intensified clinical environment and within cash-limited HTA systems.

Dabigatran - a continuing exemplar case history demonstrating the need for comprehensive models to optimize the utilization of new drugs.

BACKGROUND: There are potential conflicts between authorities and companies to fund new premium priced drugs especially where there are effectiveness, safety and/or budget concerns. Dabigatran, a new oral anticoagulant for the prevention of stroke in patients with non-valvular atrial fibrillation (AF), exemplifies this issue. Whilst new effective treatments are needed, there are issues in the elderly with dabigatran due to variable drug concentrations, no known antidote and dependence on renal elimination. Published studies showed dabigatran to be cost-effective but there are budget concerns given the prevalence of AF. These concerns resulted in extensive activities pre- to post-launch to manage its introduction. OBJECTIVE: To (i) review authority activities across countries, (ii) use the findings to develop new models to better manage the entry of new drugs, and (iii) review the implications based on post-launch activities. METHODOLOGY: (i) Descriptive review and appraisal of activities regarding dabigatran, (ii) development of guidance for key stakeholder groups through an iterative process, (iii) refining guidance following post launch studies. RESULTS: Plethora of activities to manage dabigatran including extensive pre-launch activities, risk sharing arrangements, prescribing restrictions and monitoring of prescribing post launch. Reimbursement has been denied in some countries due to concerns with its budget impact and/or excessive bleeding. Development of a new model and future guidance is proposed to better manage the entry of new drugs, centering on three pillars of pre-, peri-, and post-launch activities. Post-launch activities include increasing use of patient registries to monitor the safety and effectiveness of new drugs in clinical practice. CONCLUSION: Models for introducing new drugs are essential to optimize their prescribing especially where concerns. Without such models, new drugs may be withdrawn prematurely and/or struggle for funding.