A recent UK Government Review of Overprescribing of Medicines suggested that at least 10% of the current volume of medicines in the UK may be unnecessary. Some patients may receive many medicines if, for example, they suffer from multiple diseases (this is known as polypharmacy). Taking multiple medicines at the same time may increase the risk of side-effects. Patients may also receive multiple courses of antibiotics over time, which could cause the patient’s bacteria becoming resistant to the antibiotics. This study will help to target clinical improvement activities to those who need it most. An example of this is to help clinicians to find patients whose medications should be reviewed and checked by the clinicians. Anonymised electronic health records of frequent medication users will be analysed. The outcomes of interest will be emergency hospital admissions, particularly those admissions that may be related to the medicines. This study will look at the characteristics of frequent medication users and their patterns of medication use. We will evaluate possible risks of medication effects and explore methods that can help to determine whether these outcomes are likely to be related to the medications or to the patient’s diseases. We have already held discussions with primary clinicians on what information, in general, they would like to see to help their care of frequent medication users.
A recent UK Government Review of Overprescribing of medicines highlighted the need to reduce prescribing as at least 10% of the current volume of medicines in the UK may be unnecessary. Elderly patients frequently receive multiple medicines, also known as polypharmacy. Patients may also receive multiple courses of antibiotics over time, while there are concerns of patient’s bacteria becoming resistant to antibiotics. Problematic polypharmacy can is associated with an increased risk of drug interactions and adverse drug reactions. A recent review concluded that evidence of the extent of problematic polypharmacy in the UK, and what interventions are effective is limited. The overall objective of this study is to identify opportunities to better target clinical improvement activities for polypharmacy patients and antibiotic users in general practice in order to provide tailored actionable feedback to clinicians. Specific aims of this study include to evaluate the characteristics of frequent medication users, their possible risks of medication effects and to Identify patient groups with specific medication exposures to be prioritised for clinical improvement activities such as structured medication reviews. This study type will be a cohort study with nested case-control studies and be hypothesis generating. The primary outcomes of interest will be emergency hospital admissions as recorded in the Hospital Episode Statistics. The main exposure of interest will be pattern of medication use (extent, dosage and type of polypharmacy and medicine class and type). Several analysis techniques will be used in this study including descriptive analyses, regression analyses evaluating the odds of hospital admission in exposed patients, estimating individual risks of outcomes, with assessment of fairness and bias of these medication-related risk prediction models, and clustering analyses of prescribing patterns over time including number of medications prescribed and changes in medication over time. This study is a continuation of three previously approved CPRD projects.
The primary outcomes of interest will be emergency hospital admissions as recorded in the Hospital Episode Statistics (HES) and, for the antibiotic cohort, infection-related complications. All-cause mortality will be based on the death recording in the GP EHRs (with sensitivity analyses conducted with death certificate records, where available). The definition for emergency hospital admissions will be similar to that used for the prediction tool QAdmissions. The emergency admission information will be derived from the method of admission field recorded for each hospitalisation including code 21 (accident and emergency), 22 (GP direct to hospital), 23 (GP via a bed bureau); 24 (consultant clinic), 25 (mental health crisis resolution team), and 28 (other means). Only emergency admissions where the admission date and discharge date were both recorded and where the admission date was on or before the discharge date will be included. The definition for infection-related complications will be similar as used in previous studies, including infection-related hospital admissions as recorded in HES and GP-recorded complications and adverse outcomes associated with either the infection or a possible adverse drug reaction to an antibiotic (such as renal failure). Secondary outcomes of interest will include the distribution of admission and discharge ICD diagnoses as recorded in HES.
Tjeerd van Staa - Chief Investigator - University of Manchester
Tjeerd van Staa - Corresponding Applicant - University of Manchester
Darren Ashcroft - Collaborator - University of Manchester
Munir Pirmohamed - Collaborator - University of Liverpool
Yuqi Wang - Collaborator - University of Manchester
HES Accident and Emergency;HES Admitted Patient Care;ONS Death Registration Data;Patient Level Index of Multiple Deprivation;CPRD Aurum Ethnicity Record