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. 2010 Sep;25 Suppl 4(Suppl 4):S593-609.
doi: 10.1007/s11606-010-1385-y.

Assessing Chronic Illness Care Education (ACIC-E): a tool for tracking educational re-design for improving chronic care education

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Assessing Chronic Illness Care Education (ACIC-E): a tool for tracking educational re-design for improving chronic care education

Judith L Bowen et al. J Gen Intern Med. 2010 Sep.

Abstract

Background: Recent Breakthrough Series Collaboratives have focused on improving chronic illness care, but few have included academic practices, and none have specifically targeted residency education in parallel with improving clinical care. Tools are available for assessing progress with clinical improvements, but no similar instruments have been developed for monitoring educational improvements for chronic care education.

Aim: To design a survey to assist teaching practices with identifying curricular gaps in chronic care education and monitor efforts to address those gaps.

Methods: During a national academic chronic care collaborative, we used an iterative method to develop and pilot test a survey instrument modeled after the Assessing Chronic Illness Care (ACIC). We implemented this instrument, the ACIC-Education, in a second collaborative and assessed the relationship of survey results with reported educational measures.

Participants: A combined 57 self-selected teams from 37 teaching hospitals enrolled in one of two collaboratives.

Analysis: We used descriptive statistics to report mean ACIC-E scores and educational measurement results, and Pearson's test for correlation between the final ACIC-E score and reported educational measures.

Results: A total of 29 teams from the national collaborative and 15 teams from the second collaborative in California completed the final ACIC-E. The instrument measured progress on all sub-scales of the Chronic Care Model. Fourteen California teams (70%) reported using two to six education measures (mean 4.3). The relationship between the final survey results and the number of educational measures reported was weak (R(2) = 0.06, p = 0.376), but improved when a single outlier was removed (R(2) = 0.37, p = 0.022).

Conclusions: The ACIC-E instrument proved feasible to complete. Participating teams, on average, recorded modest improvement in all areas measured by the instrument over the duration of the collaboratives. The relationship between the final ACIC-E score and the number of educational measures was weak. Further research on its utility and validity is required.

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Figures

Figure 1
Figure 1
Distribution of mean Assessment of Chronic Illness Care Education (ACIC-E) self-assessment scores for California Collaborative teams at kickoff, mid-point, and final survey time points.
Figure 2
Figure 2
Collaborative teams’ self-assessment using the Assessment of Chronic Illness Care Education (ACIC-E)*. *Legend indicates number of teams completing the instrument at three points during the collaborative. Data points are mean scores for each sub-component of the ACIC-E for all reporting teams. For the national collaborative, the first assessment was done at the second learning session (“baseline”); for the California collaborative, the first assessment was done at the initial meeting called the “Kickoff” session.
Figure 3
Figure 3
Relationship between final ACIC-E self-assessment score and number of educational measures reported for 15 California collaborative teams.

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