1,721,144 research outputs found
Optimizing medication use in older adults with multimorbidity and polypharmacy.
No full textBackground
Globally, societies are ageing. In Switzerland, the population group of adults aged ≥ 65 years is projected to increase from around 17% in 2010 to a third of the population by the year 2050. With ageing societies also come increasing numbers of older adults with chronic conditions. This is mainly due to the fact that certain diseases are more prevalent in older age. With multimorbidity often comes the concurrent use of multiple medications, as patients usually use different medications to manage their different chronic conditions. Patients with polypharmacy are at a higher risk of having inappropriate polypharmacy, which can be a result of both over- and under-prescribing. They are at a higher risk of using potentially inappropriate medications (PIMs), which are medications for which the risk of adverse events outweighs the clinical benefit. While appropriate polypharmacy has a positive effect on patients’ health status, inappropriate polypharmacy and the use of PIMs may have detrimental effects. Due to this, there is the need to regularly review, and if necessary, to optimize the medication use of older adults with multimorbidity and polypharmacy. For different reasons, however, efforts to perform medication reviews in this patient group have been difficult to implement. First, many research efforts have focused on older adults in general or older adults with specific chronic conditions, which is why systematic evidence on the use of PIMs in older adults with multimorbidity and polypharmacy is scarce. Second, medication optimization, and in particular deprescribing, is challenging due to different types of barriers faced by GPs and patients, which result in medication optimization interventions being difficult to translate into clinical practice. Third, conducting clinical research with older adults with multimorbidity and polypharmacy and general practitioners with the aim of optimizing medication use can be challenging. In general, older and multimorbid patients are commonly underrepresented in clinical research. Additionally, only a small share of clinical research takes place in the primary care setting.
Aims
The overall objective of this thesis was to study different aspects related to the optimization of medication use in older patients with polypharmacy and multimorbidity. More specifically, this thesis had three different aims; (1) to investigate the use of PIMs in adults aged ≥ 65 years with multimorbidity and polypharmacy as well as to explore the factors associated with the new prescribing of PIMs in this patient group; (2) to investigate general practitioners’ (GPs) willingness to make deprescribing decisions in older patients with polypharmacy and to examine which patient characteristics are associated with a higher likelihood of making deprescribing decisions; and (3) to explore the conduct of the ‘Optimizing PharmacoTherapy In the Multimorbid Elderly in Primary Care’ (OPTICA) trial in more depth. One the one hand, this entailed comparing the baseline characteristics of GPs and patients from the OPTICA trial with reference cohorts from a Swiss real-world cohort to establish the representativeness of the trial participants. On the other hand, this entailed performing a mixed-methods analysis of the use and implementation of the ‘Systematic Tool to Reduce Inappropriate Prescribing’ (STRIP) assistant, a new electronic clinical decision support system (CDSS) developed in the Netherlands, during the OPTICA trial.
Methods
A series of quantitative and mixed-methods studies were conducted to investigate the different aspects related to the optimization of medication use in older patients with polypharmacy and multimorbidity. To study Aim I, I used a dataset with linked Medicare claims and data from electronic health records from seven hospitals and medical centers in the Boston metropolitan area (RPDR-CMS dataset), which covered the period from 2007 to 2014. Using this data I explored the use of PIMs, defined with the 2019 version of the Beers criteria, in adults aged ≥ 65 years, with ≥ 2 chronic conditions, and ≥ 5 long-term medications. I performed cross-sectional analyses and a retrospective cohort study. I analyzed the retrospective cohort study using Cox regression analysis. For Aim II, I collected and analyzed cross-sectional data from more than 1700 GPs in 31 countries. In this questionnaire we presented hypothetical case-vignettes to GPs, which differed in terms of patient characteristics, and for each case-vignette we asked GPs if they would deprescribe any of the medications and if so, which ones. For Aim III, I performed descriptive analyses to describe the trial participants, including patients’ willingness to have medications deprescribed, and to assess the representativeness of participant characteristics in the OPTICA trial and I conducted an explanatory mixed-methods study. In the descriptive analysis, I compared the characteristics of patients and GPs participating in the OPTICA trial to those the ‘Family medicine ICPC Research using Electronic medical records’ (FIRE) project, which is a database with data from electronic health records from around 700 GPs in the Swiss German part of Switzerland and thus constitutes a real-world cohort. In the mixed-methods study we first collected quantitative data, which we then sought to further explain and understand through qualitative data collection. In the qualitative interviews we explored questions related to the barriers and facilitators linked to using the STRIP assistant during the OPTICA trial.
Results
For Aim I, I found that >69% of older patients with multimorbidity and polypharmacy used ≥ 1 PIMs from 2007 to 2014. Central nervous system drugs and gastrointestinal drugs were found to be the most commonly used PIMs. More than 10% of medication costs were spent on potentially inappropriate medications. Furthermore, I found that 2.5% of PIM-naïve1 older adults with polypharmacy and multimorbidity were prescribed a PIM during the 90-day follow-up period. Male sex (Hazard ratio (HR) = 1.29, 95% confidence interval (CI) 1.06-1.57, reference: female sex), the number of ambulatory visits (18-29 visits: HR = 1.42, 95% CI 1.06-1.92; ≥ 30: HR = 2.12, 95% CI 1.53-2.95, reference: ≤ 9 visits), the number of prescribing orders (HR = 1.02 per unit increase, 95% CI 1.01-1.02), and heart failure (HR = 1.38, 95% CI 1.07-1.78, reference: no heart failure diagnosis) were independently associated with a higher risk of being newly prescribed a PIM. Higher age was independently associated with a lower risk of being newly prescribed a PIM (85 years: HR = 0.75, 95% CI 0.56-0.99, reference: 65-74 years). For Aim II, I found that >80% of GPs reported they would deprescribe ≥ 1 medication(s) in patients aged ≥ 80 years with polypharmacy. There was some variation across countries and GP characteristics with regards to the reported deprescribing decisions. The GPs’ odds of making deprescribing decisions was higher in patients with a higher level of functional dependency in activities of daily living (ADL) (high functional dependency in ADL: odds ratio (OR) = 1.5, 95% CI 1.25-1.80, medium: OR = 1.29, 95% CI 1.09-1.55, reference category: low functional dependency in ADL) and when cardiovascular disease was absent (OR = 3.04, 95% CI 2.58-3.57, reference: history of cardiovascular disease). For Aim III, I found that more than 80% of older multimorbid patients with polypharmacy, who participated in the OPTICA trial, reported being willing to stop ≥ 1 of their medications if their doctor said that this would be possible. The baseline characteristics of GPs participating in the OPTICA trial were similar in terms of sociodemographic characteristics and their work as GPs to those regularly exporting data to the FIRE project database (e.g., age, years of experience as GP, employment status). Patients participating in the OPTICA trial and those from the FIRE database were comparable in terms of age, health services use, and certain clinical characteristics (e.g., systolic blood pressure, body mass index). I also demonstrated that patients recruited based on pre-defined screening lists were similar to those identified by GPs. Finally, we observed an overall good acceptance of the STRIP assistant by general practitioners who used this tool during the OPTICA trial. GPs reported to perceive the STRIP assistant as a useful tool, due to its nature to manage a large amount of data and to generate recommendations. Despite this, some substantial implementation challenges were observed. The qualitative findings showed that the main reasons for the limited implementation of the STRIP assistant are as follows: incomplete data imports, significant time expenditure for preparing the use of the STRIP assistant, technical problems when running the medication review analysis, and occasional lack of quality and inappropriateness of the generated recommendations.
Conclusions
This thesis provides important information for optimizing medication use in older adults with multimorbidity and polypharmacy. First, I found an overall high utilization of PIMs in older adults with multimorbidity and polypharmacy, which is associated with substantial costs. We as researchers should use the information on the factors associated with new PIM prescribing and the information on the most commonly used PIMs when developing interventions targeted at optimizing the medication use in older adults with multimorbidity and polypharmacy that aim at reducing the use of PIMs in this patient group. Second, GPs overall seem to be willing to deprescribe medication in older patients with polypharmacy. However, GPs’ willingness to make deprescribing decisions differed for patients with different levels of functional dependency in activities of daily living and cardiovascular disease. In addition, patients with multimorbidity and polypharmacy also show a high willingness to have medications deprescribed. I conclude that designing deprescribing interventions that build on GPs and patients’ willingness to make deprescribing decisions could be a crucial factor for the implementation and long-term efficacy of such interventions. Finally, I conclude that testing new medication optimization interventions in primary care trials with comparable groups of GPs and older multimorbid patients is possible. However, the implementation of new electronic decision support systems may come with substantial challenges, which have to be addressed to facilitate and enable the future rollout of such tools
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