Chronic Care Management Intervention: Effects on Patient Activation, Health Status, and Depressive Symptoms

Tuesday, 31 October 2017: 9:00 AM

Cynthia Corbett, PhD
Washington State University College of Nursing, Spokane, WA, USA


Non-communicable diseases (NCDs) are a global epidemic that account for 68% of deaths worldwide.1 While NCDs have been the primary source of disease burden in high income countries for decades, in 2012, NCDs accounted for 48% of deaths in low and middle income countries.1 Health care use and costs for patients with multiple NCDs are disproportionately high.2II In the United States, for example, patients with multiple NCDs have more than double the avoidable emergency department visits as persons with only one NCD.2 To improve care quality and patient outcomes and reduce health care costs for high need patients, multidisciplinary care management programs are being implemented.3,4 Despite increased prevalence of care management programs in the United States, of which nurses are often core members,4 high quality evidence about their effectiveness is negligible.


The purpose of this presentation is to communicate results of an evaluation of the effectiveness of a chronic care management intervention (CCMI) on patient activation, perceived health status, and depressive symptoms.


Conceptual framework: The Chronic Care Model served as the conceptual framework for the study.5,6 

Design: A single-center, randomized controlled, single blind (investigator) clinical trial was completed.

Intervention: The CCMI was developed in a Washington state demonstration project with promising results.7 The CCMI is patient-centered with the goal of facilitating patients’ abilities to achieve their personally identified goals. In the current study, the CCMI was delivered over 12 months by a nurse and a social worker through home visits, telephone contacts and joint visits with participants to primary care and behavioral health care appointments when indicated and desired by the participant. The nurse interventionist also regularly collaborated with a pharmacist consultant from the patients’ Federally Qualified Health Center (FQHC) to promote safe and effective medication management. The CCMI protocol required initial in-home visits by both interventionists, followed by monthly alternating visits/telephone contacts. Thus, participants received, at minimum, a visit from the nurse or social worker each month. On the months when a visit was not scheduled for that discipline, participants were contacted by telephone. Depending on the needs of the participant, more frequent home visits and/or telephone contacts were delivered. During the 12th month of the intervention, a final home visit with each participant was jointly made by the interventionists. 

Attention control: Participants randomized to the attention-control group received usual care from their healthcare providers plus an attention control intervention. Following study enrollment, a social services aide scheduled a home visit with participants to meet them and explain the purpose of the attention control intervention, which wasto provide information about community resources to enable the participant to promote their own health. Thereafter, during the 12-month study, attention control participants received a telephone call from a social services aide every two months. The purpose the telephone calls was to ask participants whether they had any need for community resources/services (e.g., information about assistance with transportation to healthcare appointments; information about support groups). When participants responded to the open ended question by identifying a need, information about resources they could access was mailed to their home address.

Setting and participants: Participants (n=290) were recruited from a FQHC in the northwestern United States with 12 primary care clinics and a patient census of over 60,000 persons. Inclusion criteria were adults aged 45 and older with at least 2 NCDs who had visited the emergency department and/or been hospitalized at least twice during the preceding 12 months. Exclusion criteria were evidence of a condition that would likely lead to death within 6 months, evidence of prior violence or sexual assault that could place the research team at risk, lack of a permanent residence, or enrollment in a different care management program.

Measures: Patient activation was measured using the 13-item Patient Activation Measure (PAM) which has demonstrated reliability and validity,8 and has been shown to correlate with health outcomes.9,10 Patient health status was measured using a 5-item self-perception scale with 1 equating to very poor health and 5 equating to excellent health.11 The Patient Health Questionnaire (PHQ) 9 was used to measure depressive symptoms in participants who were 64 years of age or younger.12 The Geriatric Depression Scale (GDS) was used to measure depressive symptoms in persons 65 years and older.13

Analyses: Descriptive statistics were calculated for the total sample and for each group separately. Student’s t-tests for continuous factors, and chi square tests for categorical variables were used to establish equivalence of baseline variables between the two randomized groups. We also used t-tests as a preliminary evaluation of the differences between baseline and 12-month measures of patient activation, perceived health status, and depressive symptoms in each group and between groups. Comparisons are reported below. Prior to presentation at the conference, should the abstract be accepted, random-effects regression will be performed. These multi-level models use the identity link for continuous data to determine whether the intervention was associated with an increase in patient activation or perceived health status and a reduction in depressive symptoms for those in the intervention arm of the study as compared to those in the attention control arm of the study. The models will include main effects for treatment, time, and the treatment by time interaction and be adjusted for comorbidities.14 Because the trial was completed less than 1 month ago, the research team has not had the opportunity to the complete complex regression analyses.


Overall sample baseline: The average age of the sample was 55 years. The majority (64%) were female, and most participants were white (85%) and Non-Hispanic/Non-Latino (99%). Educational attainment was primarily either high school graduate (29%) or some attendance at a technical school/college (39%). Our participants were largely insured through Medicare (20%) or Medicaid (54%).

At baseline, the mean patient activation score was 56.26 which corresponds to a patient activation level 2. People with patient activation levels of 2 lack basic knowledge about their conditions, treatment options, and/or self-care, and have little experience or success with behavior change, have low confidence in their own abilities to manage health and rely on their health care providers to be in charge. Participants rated their overall health status as 2.0 on a scale of 1-5 (very poor – excellent) which corresponds with a perception of ‘poor’ health. At baseline, average depressive symptom scores using the Patient Health Questionnaire (PHQ 9) for participants 64 years old or less or the Geriatric Depression Scale for participants 65 years and older both resulted in depressive symptom scores that suggested participants were likely to be depressed. Participants’ in the control and intervention group did not differ significantly in demographic characteristics, PAM scores or levels, or health status ratings, however there were differences in PHQ scores. This will be accounted for statistically in the upcoming analysis.

Clinical trial outcomes: Initial t-tests and chi-square tests within subjects indicated significant changes between baseline and 12 months for both treatment and control groups on measures of PAM score [treatment group: t(97) = -4.74, p < .001; control group: t(107) = -2.56, p < .05], PAM level [treatment group: c2 (9, N = 98) = 19.27, p < .05; control group: c2 (9, N = 108) = 28.29, p < .001], health status rating [treatment group: c2 (12, N = 101) = 25.72, p < .01; control group: c2 (12, N = 109) = 32.41, p < .001], and PHQ 9 depression symptoms [treatment group: t(89) = 4.86, p < .001; control group: t(99) = 2.41, p < .05]. GDS scores for the control group did not significantly differ and we were unable to calculate statistics for treatment group due to constants.

Between groups tests at 12 months (study completion) on all three measures (PAM, health status, and depressive symptoms) lacked statistical significance.

More comprehensive results using multi-level modeling will be completed prior to the November 2017 conference.


Advanced analyses will allow us to control for multiple covariates which may be able to parse out differences that will allow us to better understand the similarities and differences in effect between groups, and therefore elucidate participant sub-groups that respond or do not respond to the CCMI. Results of this research will provide foundational knowledge for future nursing research and have implications for future nurse education and techniques for intervention, particularly in NCD management.


These preliminary results indicate that participants may need a modified or less intensive intervention than anticipated to create significant change in respect to measures of activation, health status, and depression. Of the interventionists included in this study, our nurse was the most integral and the only interventionist who could deliver all aspects of the intervention. As we identify the best steps to take to modify this intervention to increase efficiency and effectiveness, the nurse interventionist will remain an integral part of promoting interprofessional teamwork in an effort to reduce the burden of NCDs.