A partnership model for children with complex medical conditions: The Champlain Complex Care Programme in Canada

Performance indicators

Overall, results from the pilot show improved access to care, increasing system throughput and providing long awaited coordination of services for families in Ottawa and surrounding areas, allowing them to “normalize” their households, return to work and lead a family life as close as possible to normal.

In particular, the programme has demonstrated statistically significant decreases in in-patient services and increases in out-patient services. The programme was also able to improve the response time for consultations, and reduced duplication of services. 

Similarly, the programme was seen to have beneficial outcomes and impacts on the health of the participating young people, as demonstrated through measurement of scales indicating increases in the strength of children and young people, and decreases in their needs (as demonstrated by Children & Adolescent Needs and Strengths (CANS) assessment).

Change in CANS scores

The results of the change in CANS scores for those individuals who were administered the 5-16 year old CANS-CC demonstrate positive impacts. Reductions in the CANS score and sub-scores indicate improvements for the individuals in the project.

As evident from Table 1, statistically significant decreases in the CANS subscale scores of Functioning (medical and psychosocial), Strengths and the Total score were seen, providing some evidence that the CCCP is improving the functioning and identified strengths in these individuals. Though not statistically significant, a noticeable improvement also occurred in the intensity of health care needs with the initiation of the intervention. This provides further evidence that the CCCP does impact health outcomes in the children/youth that participate.

Due to the small sample size once the population was stratified, it was decided to carry out a further statistical test. Cohen’s d effect sizes were calculated to complement the test statistic. For this statistic, 0.2-0.5 is small; 0.5-0.8 is moderate; and 0.8 and higher is considered a large effect size.. A glance at these effect sizes in Table 1 shows that even with the small sample sizes, large effects were evident, further confirming the impact of this service on the health outcomes of individuals.

Table 1.