Background Meeting chronic patient needs is essential to improve health outcomes.

Purpose To design a pharmaceutical care plan for chronic paediatric patients using a risk stratification tool.

Material and methods The care plan was developed in 4 steps from April to June 2014:

1. 1. Literature review.

2. 2.4 workshops were held with experts. The chronic conditions and the variables of each patient with their corresponding relative weights were defined, varying from 1(low) to 4(high risk) in ascending order of risk, and resulted in a risk matrix with increasing levels, which included the pharmaceutical care actions to be carried out in each level.

3. 3. pre-test was developed and used in 195 patients from 7 hospitals.

4. 4.5 case studies were performed.

Results The care plan was applied to patients with different chronic conditions, classified into 15 groups (autoimmune, gastrointestinal, oncology, etc.). 13 variables divided into 3 categories were defined: demographic (age, obesity/malnutrition, social/cognitive problems); clinical (visits to the emergency room), comorbidities, clinical conditions that require special monitoring);and drug treatment (polypharmacy, complex patterns, changes in regular regimen, suspected non-adherence, suspicion/risk of medication-related problem, high-risk medicine). Afterwards, 4 risk levels were defined according to the total variable score: level 4, for patients with ≤17 points; level 3, 18 to 22 points; level 2, 23 to 26 points; and level 1, for ≥27 points. For each risk level 3 types of care actions were defined: pharmacotherapy monitoring, training/education to patient/parent/caregiver, and coordination activities with the care team.

We evaluated the distribution of 195 real patients into the defined risk levels: 60% were scored into level 4, 20% into level 3, 13% into level 2 and 7 into level 1. This was considered an adequately stratified population distribution.

Conclusion The pharmaceutical care plan adequately stratified chronic paediatric patients into different risk levels and can be used to prioritise those patients that will benefit more from our interventions.

References and/or Acknowledgements We would like to thank Abbvie and Ascendo consulting for their logistic support.

No conflict of interest.