A pioneering behavioral diagnostic tool designed to help people with type 2 diabetes take their medications as prescribed is based on extensive research by Kingston University and partners, including healthcare technology company Observia. I was.

The World Health Organization estimates that only half of people with chronic diseases take their medications correctly, and reports say this could cost the global economy as much as $290 billion. Diabetes affects approximately 8.5% of the world’s adult population, and previous studies suggest poor medication adherence in people with type 2 diabetes, resulting in higher hospitalization rates and longer hospital stays Kingston University and Observia decided to focus their research on that group. .

The SPUR tool was developed by Observia and is used to better understand the reasons for non-adherence, defined as the extent to which patients are not taking their medications as prescribed. A test by Kingston University’s School of Pharmacy found that the tool can reliably identify patients who are struggling with medications and why.

A peer-reviewed study comparing SPUR to other patient-reported outcome measures is now published in the British Medical Journal Open. We found that it not only measures the degree to which patients do not take their medications as prescribed, but also identifies the reasons. This is something previously developed tools have not been able to do.

The SPUR model work is part of an effort by technology companies to shed light on the complexities of patient health behavior, decipher reasons for non-adherence, and support the design and delivery of tailored health interventions to address individuals. started in 2017 as patient needs.

The principal investigator of the study, Joshua Wells, a PhD candidate at Kingston University who collaborated on the project with Professor Reem Kayyali, dean of pharmacy and principal investigator at Kingston University, said patients had difficulty taking their medications as prescribed. He said that understanding the reasons for feeling allows for individualized intervention. for individual patients to be developed.

“Developing a holistic tool that can measure how much and why patients stop taking their medications will help bring personalized patient care to patients with chronic conditions who may be struggling with medications. It’s an important next step in our journey to deliver. SPUR has helped us understand the specific behavioral, environmental and social factors that contribute to non-compliance,” he said. .

The study to test the model was divided into three phases. The first established the basis for his SPUR, and the second reviewed over 100 health questionnaires to inform the 45 questions testing the model in the final phase of a project led by Kingston University. did.

In this final phase, questions were used to assess the effectiveness of the SPUR tool in measuring medication adherence in 378 people with type 2 diabetes. The patient was recruited through Kingston Hospital and community pharmacies in South West London with the support of the National Pharmacy Association and Health Education. Foundation.

As people around the world face additional challenges as part of the cost of living crisis, it is more important than ever to have access to tools like SPUR to support patients, said Wells. . “Patients with certain vulnerabilities, especially those experiencing social deprivation, are more exposed and at risk for chronic disease, which only worsens with age.” In addition, an aging population requiring more extensive and complex medicines and rising costs to the health system will only continue to exacerbate health inequalities in the UK, as these patients face an ever-growing list of patients. It only exacerbates the challenge of administering drugs,” he said.

Kingston University and Observia will work closely to forge further relationships within the NHS to support wider integration of the SPUR model to improve daily care for patients on medications for chronic diseases has been and continues to be. Validate the model in other languages, patient populations, and conditions beyond type 2 diabetes.