Deprescribing is a process by which medications are reduced or stopped under the care of a healthcare professional. The purpose of deprescribing is to improve patient outcomes, and to stop medications which might be causing more harm than good or no longer have any benefit to the individual. The process enables healthcare personnel to manage medications in a more controlled manner improving the quality of patients’ lives. Individuals with cardiometabolic conditions are more likely to have associated cardiovascular health outcomes, with this risk increasing when multiple medications are used. The aim of this study is to deduce the patterns of medication prescribing throughout the final 12 months of life in patients aged 50 years and older with a cardiometabolic condition. The study aims to assess the patterns of medication prescribing and the mean number of medications used at 12, 6, and 1 month prior to death, 7 days before death and on the day of death. The study also aims to assess if there is a reduction in medications used per patient 12 months prior to death and 1 month prior to death, along with the duration of use of the medications prescribed. Research into the impacts of medication prescribing patterns in patients nearing the end of their life is needed to better understand the complications that arise in this cohort. The study will also help towards the development of policies and guidance for deprescribing practices in primary care.
The study aims to deduce the associations of preventive medication deprescribing and the number of adverse events that occur as a result of preventive medication deprescribing in patients with a cardiometabolic condition using UK CPRD data for patients aged 50 years old and over. The cohort will include patients with a previous diagnosis of a cardiometabolic condition (listed in section "exposures, outcomes and covariates"), diagnosed between 2011 and 2021 who have had their medications deprescribed in accordance with one of the outlined deprescribing strategies, with follow up until the point of death. The study aims to look at the trends in preventive medication deprescribing in the last year of life at 5 key stages in the follow up period: 12 months, 6 months, 1 month, 7 days prior to death and on the day of death. Determinants to be extracted include age, age at diagnosis, ethnicity, diagnosis, number of ‘active’ medications (i.e. number of medications currently prescribed, which if being taken as directed would still be being taken on the day of measurement), deprivation index and geographic area will be collated. A comparison will then be made on the mean number of active prescribed preventive medications in use 1 year prior to death and at 1 month prior to death. The number of adverse events (falls, hospitalisations, complications (hyper-/hypo-glycaemia, diabetic ketoacidosis, hyperosmolar hyperglycaemic state, retinopathy, neuropathy, renal function, stroke, MI)) associated with the types of preventive medications deprescribed will also be determined. Missing data will be addressed via the use of complete-case analysis and multiple imputation. This study will provide information into the number of preventive medications being prescribed to patients in their final year of life and how these change over the course of the final 12 months. This will help influence deprescribing guidelines to better improve patient outcomes.
The broad outcomes for the study include:
• Identifying the mean number of preventive medications prescribed and in use at 12 months, 6 months, 1 month and 7 days prior to death, along with on the day of death
• To deduce the number of active (in use) prescribed preventive medications 1 year before death versus 1 month before death
• To identify the duration of use of preventive medications in the final 12 months of life
• To assess associated biomarkers on risk factor controls such as HbA1c, lipids (high-density lipoproteins, low-density lipoproteins, total cholesterol, and triglycerides), estimated GFR, systolic and diastolic blood pressure values
• To assess the event rates associated with the types of medications deprescribed
Samuel Seidu - Chief Investigator - University of Leicester
Elizabeth Hickman - Corresponding Applicant - University of Leicester
Clare Gillies - Collaborator - University of Leicester
Kamlesh Khunti - Collaborator - University of Leicester
Sharmin Shabnam - Collaborator - University of Leicester
HES Admitted Patient Care;ONS Death Registration Data;Patient Level Index of Multiple Deprivation;Practice Level Index of Multiple Deprivation