Does patient activation predict the course of type 2 diabetes? A longitudinal study.

OBJECTIVE: To examine whether patient activation is predictive of the course of diabetes over a three year period among patients with and without diabetes. METHODS: Longitudinal analyses utilized electronic health record data from 2011 to 2014. We examined how the patient activation measure (PAM) was predictive of 2014 diabetes-related outcomes among patients with diabetes (n=10,071); pre-diabetes (n=1804); and neither diabetes nor pre-diabetes (n=46,402). Outcomes were clinical indicators (blood pressure, cholesterol, and trigylcerides), costly utilization, and progression from no diabetes to pre-diabetes or diabetes. RESULTS: Higher PAM level predicted better clinical indicator control in patients with diabetes. In patients with pre-diabetes, PAM level predicted better clinical indicator control, and those in the highest level of PAM in 2011 had lower odds of having a hospitalization compared to those in the lowest level. In patients without diabetes or pre-diabetes in 2011, higher PAM level was associated with lower odds of developing pre-diabetes. CONCLUSIONS: More activated patients with diabetes and pre-diabetes had better outcomes than less activated patients. More activated patients without diabetes or pre-diabetes were less likely to develop pre-diabetes over a three year period. PRACTICE IMPLICATIONS: Strategies to improve patient activation may be useful to help curb the diabetes epidemic.

Improving Population Health Management Strategies: Identifying Patients Who Are More Likely to Be Users of Avoidable Costly Care and Those More Likely to Develop a New Chronic Disease.

OBJECTIVE: To explore using the Patient Activation Measure (PAM) for identifying patients more likely to have ambulatory care-sensitive (ACS) utilization and future increases in chronic disease. DATA SOURCES: Secondary data are extracted from the electronic health record of a large accountable care organization. STUDY DESIGN: This is a retrospective cohort design. The key predictor variable, PAM score, is measured in 2011, and is used to predict outcomes in 2012-2014. Outcomes include ACS utilization and the likelihood of a new chronic disease. DATA: Our sample of 98,142 adult patients was drawn from primary care clinic users. To be included, patients had to have a PAM score in 2011 and at least one clinic visit in each of the three subsequent years. PRINCIPAL FINDINGS: PAM level is a significant predictor of ACS utilization. Less activated patients had significantly higher odds of ACS utilization compared to those with high PAM scores. Similarly, patients with low PAM scores were more likely to have a new chronic disease diagnosis over each of the years of observation. CONCLUSIONS: Assessing patient activation may help to identify patients who could benefit from greater support. Such an approach may help ACOs reach population health management goals.

How much do clinicians support patient self-management? The development of a measure to assess clinician self-management support.

BACKGROUND: Primary care provider (PCP) support of patient self-management may be important mechanism to improving patient health outcomes. In this paper we develop a PCP-reported measure of clinician strategies for supporting patient self-management, and we psychometrically test and validate the measure. METHODS: We developed survey items based upon effective self-management support strategies identified in a prior mixed methods study. We fielded a survey in the fall of 2014 with 139 Fairview Health Services PCPs, and conducted exploratory factor analysis and Cronbach's Alpha to test for scale reliability. To validate the measure, we examined the Self-Management Support (SMS) scale's relationship to survey items on self-management support, as well as clinicians' patient panel rates of smoking cessation and weight loss. RESULTS: Nine survey items clustered reliably to create a single factor (Cronbach's Alpha=0.73). SMS scores ranged from 2.1 to 4.9. The SMS was related to each of the validation variables. PCPs who reported spending 60% percent or more of their time counseling, educating, and coaching patients had a mean SMS score of 4.0, while those who reported spending less than 30% of their time doing so had mean SMS scores 15% lower. PCPs' SMS scores exhibited significant but modest associations with their patients' smoking cessation and weight loss (among obese patients) (r=0.21 and r=0.13 respectively). CONCLUSIONS: This study develops and tests a promising measure of PCPs' strategies to support patient self-management. It highlights variation across PCPs. Future work should examine whether increasing scores of PCPs low on the SMS improves chronic care quality outcomes.

The role of primary care providers in patient activation and engagement in self-management: a cross-sectional analysis.

BACKGROUND: The increasing burden of chronic illness highlights the importance of self-care and shifts from hierarchical and patriarchal models to partnerships. Primary care providers (PCPs) play an important role in supporting patients in self-management, enabling activation and supporting chronic care. We explored the extent to which PCPs' beliefs about the importance of the patients' role relate to the frequency in which they report engaging in collaborative and partnership-building behaviors with patients. METHODS: PCPs' beliefs were measured using the Clinician Support for Patient Activation Measure (CS-PAM). We also assessed whether PCPs' CS-PAM scores were positively associated with changes in their patients' Patient Activation Measure (PAM) scores. Participants included 181 PCPs from a single accountable care organization in Minnesota who completed an online survey. We conducted bivariate analyses and multivariate regression models to examine relationships between CS-PAM and PCP self-management support behaviors and changes in level of patient activation. RESULTS: PCPs with high CS-PAM scores were much more likely to engage in supportive self-management and patient behavior change approaches, such as involving the patient in agenda-setting, problem-solving, and collaboratively setting behavioral goals, than were PCPs with low CS-PAM scores. More positive PCPs' belief in the patients' role in self-management was positively correlated with improvements in their patients' level of patient activation. CONCLUSIONS: More positive PCP beliefs about the patients' role in self-management was strongly related to PCP behaviors geared towards increasing patient activation.

Adding A Measure Of Patient Self-Management Capability To Risk Assessment Can Improve Prediction Of High Costs.

We explored whether supplementing a clinical risk score with a behavioral measure could improve targeting of the patients most in need of supports that reduce their risk of costly service utilization. Using data from a large health system that determines patient self-management capability using the Patient Activation Measure, we examined utilization of hospital and emergency department care by the 15 percent of patients with the highest clinical risk scores. After controlling for risk scores and placing patients within segments based on their level of activation in 2011, we found that the lower the activation level, the higher the utilization and cost of hospital services in each of the following three years. These findings demonstrate that adding a measure of patient self-management capability to a risk assessment can improve prediction of high care costs and inform actions to better meet patient needs.

Supporting Patient Behavior Change: Approaches Used by Primary Care Clinicians Whose Patients Have an Increase in Activation Levels.

PURPOSE: We aimed to identify the strategies used to support patient behavior change by clinicians whose patients had an increase in patient activation. METHODS: This mixed methods study was conducted in collaboration with Fairview Health Services, a Pioneer Accountable Care Organization. We aggregated data on the change in patient activation measure (PAM) score for 7,144 patients to the primary care clinician level. We conducted in-depth interviews with 10 clinicians whose patients' score increases were among the highest and 10 whose patients' score changes were among the lowest. Transcripts of the interviews were analyzed to identify key strategies that differentiated the clinicians whose patients had top PAM change scores. RESULTS: Clinicians whose patients had relatively large activation increases reported using 5 key strategies to support patient behavior change (mean = 3.9 strategies): emphasizing patient ownership; partnering with patients; identifying small steps; scheduling frequent follow-up visits to cheer successes, problem solve, or both; and showing caring and concern for patients. Clinicians whose patients had lesser change in activation were far less likely to describe using these approaches (mean = 1.3 strategies). Most clinicians, regardless of group, reported developing their own approach to support patient behavior change. Those whose patients showed high activation change reported spending more time with patients on counseling and education than did those whose patients showed less improvement in activation. CONCLUSIONS: Clinicians vary in the strategies they use to promote behavior change and in the time spent with patients on such activities. The 5 key strategies used by clinicians with high patient activation change are promising approaches to supporting patient behavior change that should be tested in a larger sample of clinicians to validate their effectiveness.

Working under a clinic-level quality incentive: primary care clinicians' perceptions.

BACKGROUND: A key consideration in designing pay-for-performance programs is determining what entity the incentive should be awarded to-individual clinicians or to groups of clinicians working in teams. Some argue that team-level incentives, in which clinicians who are part of a team receive the same incentive based on the team's performance, are most effective; others argue for the efficacy of clinician-level incentives. This study examines primary care clinicians' perceptions of a team-based quality incentive awarded at the clinic level. METHODS: This research was conducted with Fairview Health Services, where 40% of the primary care compensation model was based on clinic-level quality performance. We conducted 48 in-depth interviews to explore clinicians' perceptions of the clinic-level incentive, as well as an online survey of 150 clinicians (response rate 56%) to investigate which entity the clinicians would consider optimal to target for quality incentives. RESULTS: Clinicians reported the strengths of the clinic-based quality incentive were quality improvement for the team and less patient "dumping," or shifting patients with poor outcomes to other clinicians. The weaknesses were clinicians' lack of control and colleagues riding the coattails of higher performers. There were mixed reports on the model's impact on team dynamics. Although clinicians reported greater interaction with colleagues, some described an increase in tension. Most clinicians surveyed (73%) believed that there should be a mix of clinic and individual-level incentives to maintain collaboration and recognize individual performance. CONCLUSION: The study highlights the important advantages and disadvantages of using incentives based upon clinic-level performance. Future research should test whether hybrid incentives that mix group and individual incentives can maintain some of the best elements of each design while mitigating the negative impacts.

Does Compensating Primary Care Providers to Produce Higher Quality Make Them More or Less Patient Centric?

Both payment reform and patient engagement are key elements of health care reform. Yet the question of how incentivizing primary care providers (PCPs) on quality outcomes affects the degree to which PCPs are supportive of patient activation and patient self-management has received little attention. In this mixed-methods study, we use in-depth interviews and survey data from PCPs working in a Pioneer Accountable Care Organization that implemented a compensation model in which a large percentage of PCP salary is based on quality performance. We assess how much PCPs report focusing their efforts on supporting patient activation and self-management, and whether or not they become frustrated with patients who do not change their behaviors. The findings suggest that most PCPs do not see the value in investing their own efforts in supporting patient self-management and activation. Most PCPs saw patient behavior as a major obstacle to improving quality and many were frustrated that patient behaviors affected their compensation.

Large performance incentives had the greatest impact on providers whose quality metrics were lowest at baseline.

This study examined the impact of Fairview Health Services' primary care provider compensation model, in which 40 percent of compensation was based on clinic-level quality outcomes. Fairview Health Services is a Pioneer accountable care organization in Minnesota. Using publicly reported performance data from 2010 and 2012, we found that Fairview's improvement in quality metrics was not greater than the improvement in other comparable Minnesota medical groups. An analysis of Fairview's administrative data found that the largest predictor of improvement over the first two years of the compensation model was primary care providers' baseline quality performance. Providers whose baseline performance was in the lowest tertile improved three times more, on average, across the three quality metrics studied than those in the middle tertile, and almost six times more than those in the top tertile. As a result, there was a narrowing of variation in performance across all primary care providers at Fairview and a narrowing of the gap in quality between providers who treated the highest-income patient panels and those who treated the lowest-income panels. The large quality incentive fell short of its overall quality improvement aim. However, the results suggest that payment reform may help narrow variation in primary care provider performance, which can translate into narrowing socioeconomic disparities.

When patient activation levels change, health outcomes and costs change, too.

Patient engagement has become a major focus of health reform. However, there is limited evidence showing that increases in patient engagement are associated with improved health outcomes or lower costs. We examined the extent to which a single assessment of engagement, the Patient Activation Measure, was associated with health outcomes and costs over time, and whether changes in assessed activation were related to expected changes in outcomes and costs. We used data on adult primary care patients from a single large health care system where the Patient Activation Measure is routinely used. We found that results indicating higher activation in 2010 were associated with nine out of thirteen better health outcomes-including better clinical indicators, more healthy behaviors, and greater use of women's preventive screening tests-as well as with lower costs two years later. Changes in activation level were associated with changes in over half of the health outcomes examined, as well as costs, in the expected directions. These findings suggest that efforts to increase patient activation may help achieve key goals of health reform and that further research is warranted to examine whether the observed associations are causal.

How well do patient activation scores predict depression outcomes one year later?

BACKGROUND: This study examines the relationship between patient activation, a measure of individuals׳ knowledge, skill, and confidence for managing their health, and rates of depression remission and response among patients with depression. METHODS: Patients from Fairview Health Services in Minnesota with moderate to severe depression in 2011 and a PHQ-9 score in 2012 were included in the analysis (n=5253). Patient activation in 2011 and other health and demographic features were extracted from the electronic health record. We examined how patient activation predicted depression remission and response rates and changes in depression severity over one year using regression models. We also explored how activation predicted healthy behaviors among depressed patients. RESULTS: Higher baseline patient activation predicted lower depression severity and higher depression remission and response rates a year later. The most activated patients had PHQ-9 scores in 2012 two points lower than the lowest activated patients, and they had twice the odds of remission. Activation also predicted increase in healthy behaviors. LIMITATIONS: We were unable to examine the use of mental health services or control for the number of prior depressive episodes and duration of the current depressive episode in the analysis. CONCLUSIONS: We found that higher patient activation predicted better depression outcomes. While we are unable to explore the mechanism of this association, we observed that more activated patients are also engaged in more healthy behaviors, suggesting that the mechanism may be behavioral. Support of patient activation may be an effective approach for providers to reduce patients׳ depression severity.

A case study of a team-based, quality-focused compensation model for primary care providers.

In 2011, Fairview Health Services began replacing their fee-for-service compensation model for primary care providers (PCPs), which included an annual pay-for-performance bonus, with a team-based model designed to improve quality of care, patient experience, and (eventually) cost containment. In-depth interviews and an online survey of PCPs early after implementation of the new model suggest that it quickly changed the way many PCPs practiced. Most PCPs reported a shift in orientation toward quality of care, working more collaboratively with their colleagues and focusing on their full panel of patients. The majority reported that their quality of care had improved because of the model and that their colleagues' quality had to. The comprehensive change did, however, result in lower fee-for-service billing and reductions in PCP satisfaction. While Fairview's compensation model is still a work in progress, their early experiences can provide lessons for other delivery systems seeking to reform PCP compensation.

When seeing the same physician, highly activated patients have better care experiences than less activated patients.

Measures of the patient care experience are now routinely used in public reports and increasingly influence health provider payment. We examined data from 5,002 patients of forty-nine primary care providers to explore the relationship between patient activation-a term referring to the knowledge, skills, and confidence a patient has for managing his or her health care-and the patient care experience. We found that patients at higher levels of activation had more positive experiences than patients at lower levels seeing the same clinician. The observed differential was maintained when we controlled for demographic characteristics and health status. We did not find evidence that patients at higher levels of activation selected providers who were more patient-centric. The findings suggest that the care experience is transactional, shaped by both providers and patients. Strategies to improve the patient experience, therefore, should focus not only on providers but also on improving patients' ability to elicit what they need from their providers.

Patients with lower activation associated with higher costs; delivery systems should know their patients' 'scores'.

Patient activation is a term that describes the skills and confidence that equip patients to become actively engaged in their health care. Health care delivery systems are turning to patient activation as yet another tool to help them and their patients improve outcomes and influence costs. In this article we examine the relationship between patient activation levels and billed care costs. In an analysis of 33,163 patients of Fairview Health Services, a large health care delivery system in Minnesota, we found that patients with the lowest activation levels had predicted average costs that were 8 percent higher in the base year and 21 percent higher in the first half of the next year than the costs of patients with the highest activation levels, both significant differences. What's more, patient activation was a significant predictor of cost even after adjustment for a commonly used "risk score" specifically designed to predict future costs. As health care delivery systems move toward assuming greater accountability for costs and outcomes for defined patient populations, knowing patients' ability and willingness to manage their health will be a relevant piece of information integral to health care providers' ability to improve outcomes and lower costs.