Polypharmacy using multiple medicines for a single individual is a big challenge for health services. It can be associated with difficulties, including side effects and the burden of taking lots of pills. There is considerable interest in trying to improve care for patients who experience polypharmacy. This requires a way of identifying those patients in clinical practice most at risk of experiencing problems. The NHS has recently developed an improved computerised system called ePACT2 to record prescription information. It is now easier to measure how many medicines patients are taking, and whether they are taking combinations of medicines that might cause problems. We call these new measures the ePACT2 polypharmacy prescribing indicators.
For ePACT2 indicators to be useful, we need to improve our understanding of the factors they are associated with, and whether they truly help us to identify people who might experience health problems.
We will use medical records from general practices to find out how the ePACT2 indicators vary between practices and are affected by practice-level factors such as the age, sex, and disease mix and quality of care delivered by the practice. We will then find out whether patients with potentially problematic prescribing measured using the ePACT2 indicators experience additional difficulties (for example, unplanned hospital admissions). Data will be anonymous and individual patients not identified.
Our studys results will help the health service decide how best to use the ePACT2 indicators to guide better care for people experiencing polypharmacy.
Polypharmacy is a major challenge for primary care and can lead to several adverse consequences. Routine primary care prescribing data can be used to identify various aspects of inappropriate prescribing relevant to polypharmacy. These so-called prescribing indicators can facilitate the targeting and monitoring of medication optimisation. Although several sets of indicators (e.g. STOPP/START) can be incorporated into GP clinical systems, they cannot be implemented using the national ePACT prescription dispensing data used by most commissioners to evaluate local prescribing practices. A recent upgrade known as ePACT2 has allowed the development of more sophisticated prescribing metrics. This includes indicators designed specifically to address the issue of polypharmacy.
The objective of this study is to evaluate the utility of the ePACT2 indicators.
We will conduct a retrospective cohort analysis using data from the Clinical Practice Research Datalink (CPRD) on 300,000 patients. We will evaluate the practice case-mix associated with ePACT2 indicators, and the criterion validity with respect to association with key relevant clinical outcomes (inappropriate prescribing, medication adherence, medication complexity, unplanned admissions, death).
The six ePACT2 indicators (number of unique medicines per patient, prescription of ?8 medicines, anticholinergic burden score ?6, multiple prescription of anticoagulants and antiplatelets, prescription of ?2 medicines likely to cause kidney injury, prescription of an NSAID with ?1 medicine likely to cause kidney injury) will be operationalised in CPRD.
Mixed-effect logistic regression models with the covariates of age, sex, socio-economic deprivation, practice size, multi-morbidity score, relevant co-morbidities and concomitant medication will be used to evaluate case-mix associated with the indicators.
Multivariable Poisson/negative binomial/logistic regression analysis, as appropriate, will then be used to model the association between the indicators and relevant clinical outcomes.
Findings will be essential for informing the effective implementation of the ePACT2 polypharmacy indicators in order to best inform prescribing practice and policy.
Outcomes will vary by different ePACT2 indicators, and are detailed in Section N. In general, the key outcomes are:
Potentially inappropriate prescribing
Medication regimen complexity
Medication adherence
Hospitalisation admission
Death
Rupert Payne - Chief Investigator - University of Bristol
Deborah McCahon - Corresponding Applicant - University of Bristol
Evangelos Kontopantelis - Collaborator - University of Manchester
Gary Abel - Collaborator - University of Exeter
Rachel Denholm - Collaborator - University of Bristol
HES Admitted Patient Care;ONS Death Registration Data;Patient Level Index of Multiple Deprivation