Globally addressing polypharmacy and multimorbidities with computational techniques

polypharmacy and multimorbidity
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Dr Juliana Bowles, School of Computer Science, University of St Andrews, discusses how to tackle polypharmacy and multimorbidities with computational techniques

Healthcare systems worldwide face major challenges as the population grows and ages, and the systems, put in place to manage patients with more than one chronic medical condition (multimorbidity) struggle to accommodate growing demands. Major issues for healthcare globally include multimorbidity and poor communication in healthcare leading to polypharmacy complications, a potential lack of consistency of treatment across different regions, and in some cases also bringing better quality and consistent healthcare into poorer communities, especially in relation to mental health provision.

Increased longevity and multiple treatment options for many medical conditions has led to the potential for people to be in receipt of multiple prescriptions at once (polypharmacy). Many patients suffer from chronic diseases, anxiety and mental health problems, with poorer, older women in society being particularly affected by badly managed multimorbidity. Patients are prescribed an abundance of medications and advice, leaving those with multimorbidity following several clinical guidelines in parallel despite their interactions, and effects on patients being poorly monitored or understood.

Clinical guidelines are evidence-based care plans which detail the essential steps to be followed when caring for patients with a specific clinical problem, usually a chronic disease (e.g. diabetes, cardiovascular disease, chronic kidney disease, cancer, chronic obstructive pulmonary disease, and mental health conditions). Recommendations for chronic diseases include the medications (or group of medications) to be given at different stages of the treatment plan and recommendations relating to lifestyle and, whether individual medications can be taken with or without food.

This leads to patients risking adverse reactions, overdose or reduced efficacy of drugs administered together, particularly if they have a lower level of education and lack the literacy skills to understand patient information leaflets.

The example of LMIC countries

Of major public concern is the lack of adequate mental health provision, which disproportionately affects Low / Middle-Income Countries (LMICs), such as Brazil. From WHO (2019) estimates, it is understood that only 4.7% of patients in Brazil are receiving minimally adequate treatment for mental health conditions. This contributes to significant suffering on an individual and family level, with concurrent impacts on the economic productivity of the country.

It is essential to promote better infrastructure and solutions for public health across primary, secondary, and tertiary healthcare systems across many countries such as Brazil. This includes improving consistency of healthcare across regional boundaries, bringing consistency to healthcare in poorer communities, improving treatment and support of patients with mental health difficulties and, reducing issues surrounding polypharmacy.

It is important to engage a full range of healthcare professionals, patients, carers, funders and Government decision-makers in addressing the challenges faced by the healthcare system. Only then will it be possible to understand and address the context of regional problems and extrapolate this, using appropriate technology in conjunction with new policy and infrastructure, to achieve a countrywide solution.

Research on managing comorbid factors

Research conducted by Bowles’ group at the University of St Andrews, has been inspired by problems in the medical management of comorbid factors, specifically where different clinical guidelines for chronic conditions may be applied to a patient at different points in time and the impact this may have on the prescription and interaction of other medications for comorbidities affecting the same patient.

The research group works on an automated approach, combining constraint solvers and theorem provers to find the best solutions for treatment according to different criteria, avoiding adverse drug reactions as much as possible. The approach was extended to further refine treatment choice(s), avoiding dangerous or undesirable side effects and allowing medical practitioners to use whole patient treatment plan records to choose the most effective and, least damaging treatment protocol for each individual patient.

The system can be fine-tuned to account for additional requirements on the degree of priority that one model, such as chemotherapy within a cancer treatment programme, or certain steps in the treatment of a comorbid disease has over alternatives. Moreover, the approach is able to identify the best course of action with respect to these constraints and prioritises this by prompting the system to display all possible treatment recommendations, sorted by optimality.

There is a recognised move towards more personalised health with citizens at the centre of healthcare provision. In particular, there is an emphasis on the right of citizens to decide who, why and when, should have access to their medical records. The EU Horizon 2020 project SERUMS led by Bowles is developing a tool-chain for the secure access of distributed medical information preserving the privacy levels imposed by GDPR, national and/or organisational regulations. A healthcare system that supports personalised care, should also help to avoid drug prescription conflicts, even when an individual travels across national boundaries, and is assessed and treated by a number of different health professionals.

How can things be changed?

Improving consistency of treatment across regional boundaries and eliminating conflicts in treatment of comorbidities requires an integrated health informatics system, deployed at both regional and national level. A systemised approach to patient records and treatment planning will additionally improve consistency of treatment of those in the poorest communities, helping to improve treatment and outcomes in the most disproportionally affected groups in the UK, in Europe, in the World.

Bowles’ group has received GCRF funding to investigate how their research could be utilised to address issues facing the healthcare system in Brazil in two significant areas.

Firstly, in instances where different clinical guidelines for chronic conditions may be applied to the same patient at different points in time, having an automated technique to identify different solutions in similar but different patient cases, will improve outcomes for patients. For instance, in patients with the same conditions overall but with different orders of diagnosis, priorities or prevailing condition, it will be possible to identify the most effective combination and timing of treatments, ensuring the optimal patient care.

Secondly, in instances of polypharmacy, an automated approach will identify the best solutions for treatment of numerous comorbidities, according to different criteria within clinical guidelines, with the aim of avoiding adverse drug reactions as much as possible, to ensure optimal treatment and the best possible outcome for the patient.


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