Data resource profile : the Scottish national prescribing information system (PIS)

Data Resource Basics: The Prescribing Information System (PIS) covers the prescribed,dispensed and reimbursed prescriptions in community pharmacies from the 5.3 million residents in Scotland. Summary information is available from 1993 and at an individual level from 2009 to the present. Data Collected: The raw data are generated by three data sources: ePrescribed -generated by GPs messages, eDispensed –generated by messages from community pharmacies and Reimbursed messages from scanned paper prescriptions dispensed in the community pharmacies. The four main categories of data collected are: (1) Patient-specific, (2) Prescriber, (3) Dispenser and (4) Drug-specific. PIS data can be linked via a unique identifier to other national databases, including hospital records, maternal and neonatal, the Scottish Cancer Registry and mortality records. The catalogue of databases is available in www.ndc.scot.nhs.uk . Subject to approval of the data controllers other external datasets can also be linked. Data Resource Use: PIS has been used to describe the utilisation of several groups of drugs;factors influencing prescribing and evaluation of interventions to improve it; generation of polypharmacy guidelines; risk of side effects; monitoring of antibiotic use and generation of policy recommendations; associations between community prescription of antimicrobials and deprivation or infection; evaluation of prescription fee abolition; clinical effectiveness, safety and health technology assessment of drugs approved in the last decade. Reasons to be cautious: PIS does not capture information about diagnosis or indication for treatment, over the counter medicines, medicines administered during inpatient hospital stays, upon discharge for short term use, outpatient supplies or some specialist drugs for chronic use. Drug data is currently coded according to the British National Formulary. For longitudinal studies, patient level data is available from 2009 and the frequency of data collection from the three sources is different. Collaboration and data access: PIS data are available upon request to the electronic Data Research and Innovation Service ([email protected]) and project approval by the Public Benefit and Privacy Panel. Funding and competing interests: This dataset is funded from the public monies available to the NHS. Current work to develop an improved PIS research ready analysis platform and this study is supported by the Farr Institute @ Scotland and its 10-funder consortium. The authors declare no conflict of interest

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

Gain-of-Function Mutations in the K_ATP Channel (KCNJ11) Impair Coordinated Hand-Eye Tracking

Background: Gain-of-function mutations in the ATP-sensitive potassium channel can cause permanent neonatal diabetes mellitus (PNDM) or neonatal diabetes accompanied by a constellation of neurological symptoms (iDEND syndrome). Studies of a mouse model of iDEND syndrome revealed that cerebellar Purkinje cell electrical activity was impaired and that the mice exhibited poor motor coordination. In this study, we probed the hand-eye coordination of PNDM and iDEND patients using visual tracking tasks to see if poor motor coordination is also a feature of the human disease.Methods: Control participants (n = 14), patients with iDEND syndrome (n = 6 or 7), and patients with PNDM (n = 7) completed three computer-based tasks in which a moving target was tracked with a joystick-controlled cursor. Patients with PNDM and iDEND were being treated with sulphonylurea drugs at the time of testing.Results: No differences were seen between PNDM patients and controls. Patients with iDEND syndrome were significantly less accurate than controls in two of the three tasks. The greatest differences were seen when iDEND patients tracked blanked targets, i.e. when predictive tracking was required. In this task, iDEND patients incurred more discrepancy errors (p = 0.009) and more velocity errors (p  = 0.009) than controls.Conclusions: These results identify impaired hand-eye coordination as a new clinical feature of iDEND. The aetiology of this feature is likely to involve cerebellar dysfunction. The data further suggest that sulphonylurea doses that control the diabetes of these patients may be insufficient to fully correct their neurological symptoms.</p

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

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. 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. 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. 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. [Abstract copyright: © Author(s) (or their employer(s)) 2021. Re-use permitted under CC BY. Published by BMJ.

Medicines in pregnancy : building a Scottish surveillance system

Some medicines have the potential to cause harm to the developing child if taken during pregnancy. In July 2020, the Cumberlege Report, ‘First do no harm’, included examination of the harms of sodium valproate, an anti-seizure medication, during pregnancy. In March 2021, the Scottish Government published its delivery plan

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. The aim was to design and test an algorithm to codify dose instructions, applied to the NHS Scotland Prescribing Information System (PIS) that records approximately 100 million prescriptions per annum. Methods: a natural language processing (NLP) algorithm was developed enabling free-text dose instructions to be represented by three attributes: quantity; frequency; and qualifier, each specified by a set of variables. This was tested on a sample of 15 593 distinct dose instructions and manually validated. The final algorithm was then applied to the full dataset. Results: the dataset comprised 458 227 687 prescriptions, of which 99.67% had dose instructions represented by 4 964 083 distinct free-text dose instructions; 13 593 (0.27%) of these occurred ≥1000 times accounting for 88.85% of all prescriptions. Reviewers identified 767 (5.83%) instances where the structured output (n=13 152) was incorrect, an accuracy of 94.2%. Application of the final NLP algorithm to the dataset generated an overall structured output of 92.3% which varied by therapeutic area (86.7% central nervous system to 96.8% cardiovascular). Conclusion: We adopted a zero assumption approach to create an NLP algorithm, operational at scale, to produce structured output which enables 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

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

Incident prescribing patterns for hypercholesterolaemia and hypertension in Scotland – recovery from the impact of COVID-19 to inform healthcare improvement

Evidence from the literature indicated that approximately 500,000 diagnoses of hypertension were missed in Great Britain due to the COVID-19 pandemic, over April 2018–July 2021. However, it remains unclear if this trend of misdiagnosis/ undiagnosed cases persisted beyond July 2021 or if the healthcare system successfully caught up with these missed diagnoses. This insight is crucial, as ongoing issues would require urgent attention