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An Examination of the Relationship Between Care Management With Coaching for Activation and Patient Outcomes
Cindy Reistroffer, DSc; Larry R. Hearld, PhD; and Jeff M. Szychowski, PhD
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An Examination of the Relationship Between Care Management With Coaching for Activation and Patient Outcomes

Cindy Reistroffer, DSc; Larry R. Hearld, PhD; and Jeff M. Szychowski, PhD
A health plan—sponsored care management program that included a coaching for activation intervention was associated with reduced emergency department visits and hospital admissions, and better clinical outcomes.
ABSTRACT

Objectives: A growing body of research has established the benefits of patient activation, which is defined as the knowledge, skills, confidence, and motivation to make effective decisions and take action to maintain or improve one’s health. Consequently, healthcare stakeholders of all types continue to seek ways to improve patient activation. The purpose of this study was to empirically examine whether enrollment in a health plan–sponsored care management (CM) program that included coaching for activation (CFA) was associated with utilization, medication adherence, and clinical outcomes.
 
Study Design: Cross-sectional, quantitative study of commercially insured enrollees in a Midwest-based health plan.  
 
Methods: Poisson, logistic, and ordinary least squares regression models were used to test the relationships between CM programs and outcomes.  
 
Results: The benefit of measuring patient activation and offering CFA was associated with reduced healthcare utilization and better clinical outcomes. Relative to respondents in the CFA CM group (ie, intervention), respondents in the usual CM group experienced 18.29% more emergency department visits, 97.78% more hospital admissions, a higher glycated hemoglobin level (β = 0.48; P <.001), and higher systolic blood pressure (β = 1.19; P <.01). 
 
Conclusions: These findings suggest that coaching interventions based on activation level may help care managers engage in more effective interactions that strengthen a patient’s role in managing his or her healthcare. Programs that are more targeted in their application, rather than uniformly developed and implemented, may be an important factor in reducing utilization and improving clinical outcomes.

Am J Manag Care. 2017;23(2):123-128
Takeaway Points

This study investigates the benefits of a coaching for activation intervention and its associated outcomes.  
  • Relative to respondents in the intervention group, the usual care group experienced 18.29% more emergency department visits, 97.78% more hospital admissions, higher glycated hemoglobin levels, and higher systolic blood pressure. 
  • Health plan coaching interventions based on patient activation may increase effective interactions, thereby strengthening a patient’s role in managing his or her healthcare.
  • Programs more targeted in their application, rather than uniformly administered, may be an important factor when implementing policy and healthcare reform, especially in caring for chronically ill populations.
Approximately 117 million—or half of American adults—currently live with a chronic disease, and 1 in 4 live with multiple chronic conditions.1 A major contributor to chronic diseases and their attendant costs is an individual’s poor health behaviors2; additionally, patients with chronic disease often do not adhere to the medication or treatment plans designed by their providers.3 This lack of adherence frequently leads to clinical crisis, unnecessary death, and expensive treatment services, such as preventable emergency department (ED) visits and hospital admissions.4,5 A growing body of research suggests that patient health behaviors that contribute to these problems can be improved by engaging patients so they will take a more active role in their health and healthcare6-16; consequently, an important question in healthcare today is how to engage patients to do so.

Given their financial risk and unique position to facilitate population health management, health plans have an important role to play in engaging patients and improving patient behaviors. One potential means that health plans may use to improve patient engagement entails the use of active care management (CM) programs. Despite the growing use of CM programs17 in general, there is surprisingly little research regarding specific interventions that attempt to promote patient engagement18 and their association with utilization metrics that reflect patient behaviors.

The purpose of this study was to investigate whether enrollment in a health plan–sponsored CM program that included coaching for activation (CFA) was associated with patient outcomes. CFA is an intervention used by care managers that includes tailored coaching based on an individual’s level of patient activation—patient activation refers to the knowledge, skills, confidence, and motivation possessed by patients to not only make effective decisions, but also take action to maintain or improve one’s health.19,20

METHODS

Intervention

Care management is a voluntary program available to patients who require additional clinical services for managing their chronic disease. Patients are enrolled through self-referral, provider-referral, plan-driven population segmentation, or transitions in care (eg, discharge from a hospital). Population segmentation is a health plan–based tool that uses historical claims data and other variables, such as age and gender, to identify at-risk populations based on the complexity of their chronic disease(s) and behavioral risk factors. Enrolled patients are assigned to care managers based on primary care providers.

In May 2013, the CM team at a nonprofit health plan in the Midwest implemented CFA via a program that featured coaching based on an enrollee's level of patient activation. Based on the evidence suggesting a correlation between activation levels and health outcomes, CFA was introduced as a new initiative to enhance patient engagement. Initial assessments were conducted in 1 of 2 ways: interactive voice recognition or directly by a care manager employed by the health plan. Both methods were completed via telephone. Subsequently, patients in CM were assigned to 1 of 2 groups based on the presence of a Patient Activation Measure (PAM) score (ie, if patients had a PAM score, they were assigned to the CFA CM group; if patients did not have a PAM score, they were assigned to the usual CM group).

For both groups, the same care managers worked with patients; however, in the CFA CM group, they tailored their interactions based on the patient’s level of activation. For example, a CFA approach for a patient with diabetes would be different for a level 1 patient compared with a highly activated level 4 patient. An appropriate coaching goal for a level 1 patient with diabetes might be to develop basic knowledge of good and bad foods. On the other hand, an appropriate coaching goal for a level 4 activated patient entails more complicated behaviors, such as replacing bad foods with good and replacing poor eating behaviors with better ones. In contrast, coaching and goal setting occurs in the usual CM program, but it is not conditional based on a PAM level. 

All care managers were either registered nurses or licensed practical nurses with additional PAM training through Insignia Health. The purpose of the training was to increase knowledge about patient activation and its implications for patient outcomes, orient each CM program to the CFA approach, and demonstrate skills through roleplaying. Ongoing in-service activities were used to reinforce this training during monthly team meetings.

Study Population

The study sample was selected from the plan participants over a 19-month timeframe. The analytic sample was restricted to commercially insured enrollees in order to limit variations in utilization across different patient populations reflected in different insurance types (eg, Medicare, Medicaid). The analytic sample was further limited to an adult population (18 years or older). These steps resulted in the inclusion of 17,797 enrollees in the study, with 1520 enrolled in the CFA CM program and the remaining 16,277 patients enrolled in the usual CM group.

Data Sources and Measures

There were 4 primary data sources used in the study: an electronic charting tool, an administrative claims data system, demographic and socioeconomic data extracted from marketing data, and a proprietary data repository that links laboratory results to the patient data file.

The dependent variables included utilization, medication adherence, and clinical outcomes. The outcome variables were constructed based on the 6-month period following enrollment in the CM program. Utilization was quantified with 2 variables: the total number of ED visits and inpatient hospital admissions. Adherence to medication management was defined as ≥80% refill rate for prescribed medications and operationalized as a dichotomous outcome. The 4 clinical measures were: glycated hemoglobin (A1C), low-density lipoprotein (LDL), systolic blood pressure (SBP), and diastolic blood pressure (DBP). In cases where enrollees had multiple measurements, an average was constructed across all eligible values.

The primary independent variable, type of care management, was operationalized dichotomously comparing usual CM with CFA CM as the reference. The analysis controlled for several demographic and socioeconomic characteristics, including age, gender, education, annual household income, and family composition. Table 1 provides more details on how each variable was operationalized.

Analytic Strategy

The unit of analysis was the enrollee. The multivariate analysis assessed whether outcomes varied as a function of the care management group and included 3 multivariable regression models. However, these models differed in their specification based on the different types of dependent variables. In the case of utilization outcomes, a Poisson model was used, as ED visits and hospital admissions were both measured as counts. For adherence, a logistic regression model was used due to the dichotomous nature of the prescription refill variable. Finally, for clinical outcomes, an ordinary least squares (OLS) model was used due to the continuous nature of these outcomes. For ease of interpretation, the incidence rate ratio was calculated for the ED visits and hospital admissions from the Poisson model and odds ratios were calculated for the adherence outcome. Beta coefficients were reported for the OLS models related to the clinical outcomes.

RESULTS

Of the 1520 patients/enrollees in the CFA group, the mean baseline patient activation score was 66.4 (range = 0-100), with a median of 64.9. The largest number of patients/enrollees reported PAM scores at level 4 (n = 695; 49%), followed by level 3 (n = 342; 23%) and level 2 (n = 339; 22%). The fewest number of patients/enrollees reported PAM scores in the level 1 range (n = 144; 9%). This distribution is consistent with the results of other studies that have examined patient activation.18-20

Significant associations were detected between CM groups and utilization outcomes. Relative to enrollees in the CFA CM group, enrollees in the usual CM group experienced 18.29% more ED visits (P <.001) and 97.78% more hospital admissions (P <.001) (Table 2). CFA CM was not significantly associated with medication adherence. Relative to enrollees in the CFA CM, enrollees in the usual CM program had higher A1C levels (β = 0.48; P <.001) and SBP levels (β = 1.19; P <.01), but lower LDL levels (β = –4.25; P <.01) (Table 3). DBP was not significantly associated with the type of coaching received.

Additional analyses were conducted to evaluate the association of activation levels (1-4) on the study outcomes. PAM levels were not associated with better outcomes, with the exception of A1C (results not shown). Specifically, relative to enrollees in PAM level 4, A1C levels were higher for enrollees in PAM level 1 (β = 0.91; P <.001), PAM level 2 (β = 0.27;

P <.001), and PAM level 3 (β = 0.11, P <.01).

DISCUSSION

Our analysis found that CM with CFA was associated with lower healthcare utilization (ie, ED visits, hospital admissions) and better clinical values for 2 outcomes: A1C and SBP. These findings suggest that coaching interventions that are based on activation level may help care managers engage in more effective interactions that strengthen a patient’s role in managing their healthcare. For sponsors and developers of care management programs, these findings suggest that the programs that are more targeted in their application—rather than uniformly developed and implemented—may be more effective at producing desired outcomes.

Given the research showing an association between adherence to treatment care plans6-11 and better health outcomes,12-15 another question that arose from these findings is whether care management with CFA does, in fact, produce higher levels of patient activation, or whether patient activation alone is sufficient. Because the care management program with CFA considered in this study was only recently implemented, the number of enrollees with repeated patient activation scores was small and we were not able to adequately test changes in patient activation following participation in the program. This represents an important area for future research. As mentioned above, results from additional analyses indicated that patient activation by itself was not significantly associated with better outcomes in this patient population, with the exception of A1C levels. Together, these findings suggest that the care management program and patient activation may work synergistically to produce better outcomes; patients may achieve the best outcomes when efforts to improve patient activation are supported by health plan coaching.

 
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