SPUR as a predictor of admission and early readmission in patients living with Type 2 Diabetes

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We are very happy to be able to share this new publication in Patient Preference and Adherence
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Even though SPUR is now a validated Patient Reported Outcome Measure (PROM) predictive of non-adherence and able to explain the reasons behind chronic patients' health behaviors, Observia has made the choice to lead exploratory research around the possibilities of the tool. 
The aim of this study was to evaluate the SPUR™ as a predictor of hospital admission and early readmission (occurring within 30 days of discharge) in patients living with type 2 diabetes.

The 3 main outputs to keep in mind

  • A higher SPUR™ score (indicating increased medication adherence) was significantly associated with a lower rate of general admission, both as a count variable and as a binary variable.
  • Other factors of clinical relevance were associated to a higher rate of general admission such as age > 80 years, GCSE education level, number of medical conditions and a positive Covid-19 diagnosis during the follow-up.
  • A higher SPUR™ score (increased medication adherence) was the only factor significantly correlated with a lower risk of early readmission as a binary variable, which was not the case of the other factors such as age, ethnicity, gender, education level, number of medicines or medical conditions and Covid-19 diagnosis during the follow-up.


A 6-month retrospective and prospective patient monitoring were conducted to assess the number of hospital admissions and early readmissions.

200 adult patients suffering from type 2 diabetes were recruited from a large London NHS Trust.
Patients were surveyed with the SPUR questionnaire and provided demographic and health-related information including:

  • Age
  • Ethnicity
  • Gender
  • Education level
  • Income
  • Number of medicines
  • Number of medical conditions
  • Covid-19 diagnose

A Poisson or negative binomial model was employed for count outcomes.
A logistic regression model was developed for binary outcomes.


The study successfully developed a predictive model for both hospital general admission and early readmissions in patients with type 2 diabetes using the SPUR tool and several other socio-demographic and clinical factors.

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See also

Scientific communications

A multiple-cohort analysis of the SPUR 6/24 patient-reported adherence tool


Clinical Ink and Observia: Pioneering Personalized Patient Engagement in Clinical Trials


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