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Presentation Contents. Introduction to the system System reports.
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Presentation Contents • Introduction to the system • System reports
In the early 1980s paediatrician the late Barbara Starfield MD and her team, recognised that children using the most healthcare resources were not those with a single chronic illness, but rather were those with multiple, seemingly unrelated conditions. • To test their original hypothesis, illnesses found within paediatric populations were grouped into five discrete categories: ACG History Minor - self-limited if treated appropriately More severe - time-limited if treated appropriately Generally chronic - remain incurable even with medical therapy Structural problems - generally not curable even with adequate and appropriate intervention Psychosocial conditions The classification of patients based on the groupings was shown to accurately represent resource use and led to the development of the ACG system.
ACG system tool overview • What: • Metrics/measures representing a persons level of healthcare resource use (this is the ACG). • Prediction of the use of healthcare resource for the following year. And the likelihood of high cost. • A concise and complete coded representation of a persons disease burden (EDCs). • Produces Models based on diagnosis codes (Dx) and prescription codes (Rx). • How • Risk profiling • Predictive modelling
Example ADGs and ACGs • ACG (Adjusted Clinical Group) • 4-5 Other ADG Combinations, Age 18 to 44, 1 Major ADGs • 4-5 Other ADG Combinations, Age 18 to 44, 2+ Major ADGs • 4-5 Other ADG Combinations, Age 45+, no Major ADGs • 4-5 Other ADG Combinations, Age 45+, 1 Major ADGs • 4-5 Other ADG Combinations, Age 45+, 2+ Major ADGs • 6-9 Other ADG Combinations, Age 1 to 5, no Major ADGs • ADG (Adjusted Diagnostic Group) • Likely to Recur: Discrete • Likely to Recur: Discrete-Infections • Likely to Recur: Progressive • Chronic Medical: Stable • Chronic Medical: Unstable • Chronic Specialty: Stable-Orthopedic • Chronic Specialty: Stable-Ear,Nose,Throat
Resource Utilisation Bands (RUBs) • RUBs are aggregations of ACGs based on resource use • RUB variant depending on population of data • RUBs 1-5 each consume 20% of total resource • 0 Non Users • 1 Healthy • 2 Low • 3 Moderate • 4 High • 5 Very High 8
Creating Expanded Diagnosis Clusters (EDCs) And Major Expanded Diagnostic Clusters (MEDCs) 11