Poster 09: A pragmatic health informatics systems approach for aiding clinical prioritisation in a hospital-based cohort of 4013 people with diabetes
Background: There is a need for data driven approaches to facilitate risk stratification and clinical prioritisation in diabetes services.
Aim: To develop a pragmatic informatics based approach to guide clinicians to prioritise those at highest risk/need.
Methods: We identified modifiable risk-criteria in 4013 adult people (48% female) with diabetes (type 1 diabetes 20%) attending clinics in a teaching hospital. The 6 risk-criteria agreed by panel of specialists were new events/results occurring after their last diabetes clinic visit: 1. Diabetes related emergency department visit/hospitalisation 2. HbA1c>96 mmol/mol 3. HbA1c rise >20 mmol/mol 4. estimated GFR<30 ml/min 5. eGFR fall >15 ml/min/year 6. Treatment for eye-disease (e.g. photocoagulation). People with ≥1 criteria were defined ‘higher-risk’. Those who did not have any new risks, encouraging HbA1c and eGFR data/trends were categorised as ‘lower-risk’. We documented upcoming appointment dates to enable clinicians to decide if given their ‘risk’ status people could be seen sooner or later than originally intended.
Results: Of the 4013 people, 656 (16.3%) had one or more higher-risk criteria. People with higher-risk were more likely to be non-Caucasian and had greater deprivation. Of these ‘higher-risk’ 248 (6.2%) did not have an appointment within 3-months of the review. Similarly 364 people (9.1%) had ‘lower risk’ and of these 174 (4.3%) were due to be seen within 3-months, and might be considered for rescheduling to enable those at higher risk to be prioritised. The remainder of the cohort (2993, 74.6%) did not have any new risk data and were therefore not scored.
Conclusion: A pragmatic data-driven method is helpful in identifying people with diabetes at highest need for clinical prioritisation.