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ABSTRACT
ObjectivesThe Prescribing Information System (PIS) datamart, hosted by NHS National Services Scotland receives around 90 million electronic prescription messages per year from GP practices across Scotland. Prescription messages contain information including drug name, quantity and strength stored as coded, machine readable, data while prescription dose instructions are unstructured free text and difficult to interpret and analyse in volume.
The aim, using Natural Language Processing (NLP), was to extract drug dose amount, unit and frequency metadata from freely typed text in dose instructions to support calculating the intended number of days' treatment. This then allows comparison with actual prescription frequency, treatment adherence and the impact upon prescribing safety and effectiveness.
ApproachAn NLP algorithm was developed using the Ciao implementation of Prolog to extract dose amount, unit and frequency metadata from dose instructions held in the PIS datamart for drugs used in the treatment of gastrointestinal, cardiovascular and respiratory disease. Accuracy estimates were obtained by randomly sampling 0.1% of the distinct dose instructions from source records, comparing these with metadata extracted by the algorithm and an iterative approach was used to modify the algorithm to increase accuracy and coverage.
ResultsThe NLP algorithm was applied to 39,943,465 prescription instructions issued in 2014, consisting of 575,340 distinct dose instructions. For drugs used in the gastrointestinal, cardiovascular and respiratory systems (i.e. chapters 1, 2 and 3 of the British National Formulary (BNF)) the NLP algorithm successfully extracted drug dose amount, unit and frequency metadata from 95.1%, 98.5% and 97.4% of prescriptions respectively. However, instructions containing terms such as 'as directed' or 'as required' reduce the usability of the metadata by making it difficult to calculate the total dose intended for a specific time period as 7.9%, 0.9% and 27.9% of dose instructions contained terms meaning 'as required' while 3.2%, 3.7% and 4.0% contained terms meaning 'as directed', for drugs used in BNF chapters 1, 2 and 3 respectively.
ConclusionThe NLP algorithm developed can extract dose, unit and frequency metadata from text found in prescriptions issued to treat a wide range of conditions and this information may be used to support calculating treatment durations, medicines adherence and cumulative drug exposure. The presence of terms such as 'as required' and 'as directed' has a negative impact on the usability of the metadata and further work is required to determine the level of impact this has on calculating treatment durations and cumulative drug exposure.

IntroductionTo 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.
MethodsHEPMA 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.
ResultsThe 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.
ConclusionThe 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.

Sales of medicines continue to grow world-wide driven in part by increasing expenditures on biological medicines leading to concerns with the long-term sustainability of European healthcare systems. The increasing use of biosimilars at lower costs can potentially address this. However, there can be concerns with their prescribing. There are also concerns with biosimilar insulin glargine including concerns with different devices despite increasing sales of longacting insulin analogues worldwide. Consequently, a need to appraise the European biosimilar market incorporating measures to enhance their use including potential ways to increase the prescribing of biosimilars of insulin glargine at lower costs. Multiple approaches were used to undertake the study including researching measures to enhance biosimilar use and their impact across Europe. In addition, undertake cross national research on the utilization and expenditure of long-acting insulin analogues, which includes biosimilars, principally among Central and Eastern European countries. Multiple demand-side measures across the countries have enhanced the use of biosimilars. There was variable use of biosimilar insulin glargine 100 IU/ml driven by increasing use of patented 300 IU/ml formulations and small price differences between the originator and biosimilars in practice. Overall, multiple demand-side initiatives can appreciably increase biosimilar use benefiting all groups. Additional measures are needed to enhance future prescribing of long-acting biosimilar insulin analogues. ; peer-reviewed

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.

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. ; peer-reviewed