The Impact of Chronic Illness

Chronic Illness Analysis Report

Identify one person from the illness group you chose in Week 1. The person should not be a patient at the facility in which you work. You can use friends, family members, or coworkers. Do not use the person’s name in the paper but only initials. Administer the questionnaire you created in Week 1 to that person. Compile the data and analyze the responses to better illustrate where this person, his or her family, and friends are in relation to accepting the diagnosis in relation to the standard health or illness definitions. The analysis should also include coping skills, treatment, and support aspects of the illness. Identify how this will direct care plan development for the chosen illness group.

Compile a report of your interview with the questions you created, the responses you received, your analysis, and your interpretation of how it will affect planning care for the group in a 4- to 5-page Microsoft Word document.

Support your responses with examples.

Assessment of Chronic Illness Care (ACIC): A Practical Tool to Measure Quality Improvement

Objective

To describe initial testing of the Assessment of Chronic Illness Care (ACIC), a practical quality-improvement tool to help organizations evaluate the strengths and weaknesses of their delivery of care for chronic illness in six areas: community linkages, self-management support, decision support, delivery system design, information systems, and organization of care.
Data Sources

(1) Pre-post, self-report ACIC data from organizational teams enrolled in 13-month quality-improvement collaboratives focused on care for chronic illness; (2) independent faculty ratings of team progress at the end of collaborative.
Study design

Teams completed the ACIC at the beginning and end of the collaborative using a consensus format that produced average ratings of their system’s approach to delivering care for the targeted chronic condition. Average ACIC subscale scores (ranging from 0 to 11, with 11 representing optimal care) for teams across all four collaboratives were obtained to indicate how teams rated their care for chronic illness before beginning improvement work. Paired t-tests were used to evaluate the sensitivity of the ACIC to detect system improvements for teams in two (of four) collaboratives focused on care for diabetes and congestive heart failure (CHF). Pearson correlations between the ACIC subscale scores and a faculty rating of team performance were also obtained.
Results

Average baseline scores across all teams enrolled at the beginning of the collaboratives ranged from 4.36 (information systems) to 6.42 (organization of care), indicating basic to good care for chronic illness. All six ACIC subscale scores were responsive to system improvements diabetes and CHF teams made over the course of the collaboratives. The most substantial improvements were seen in decision support, delivery system design, and information systems. CHF teams had particularly high scores in self-management support at the completion of the collaborative. Pearson correlations between the ACIC subscales and the faculty rating ranged from .28 to .52.
Conclusion

These results and feedback from teams suggest that the ACIC is responsive to health care quality-improvement efforts and may be a useful tool to guide quality improvement in chronic illness care and to track progress over time.

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Submission Details

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