Does patient activation level affect the cancer patient journey?

OBJECTIVES: We assess how patient activation is associated with behaviors and experiences of people with cancer, including: understanding risks; making treatment decisions; communicating with providers; coping with symptoms; and adhering to regimens. METHODS: The study utilizes survey data from six surveys each including 500 cancer survivors. Multivariate analyses are presented. RESULTS: Higher activated patients are more than 9 times more likely to feel their treatment plans reflect their values, 4.5 times more likely to cope with side effects, and almost 3.3 times more likely to initiate a healthier diet after their diagnosis, than are less activated patients. Less activated patients are less likely understand their diagnosis, to follow treatment regimens, and to be satisfied with their care. CONCLUSIONS: The findings show that all along the care continuum, patient activation is associated with differences in experiences. PRACTICE IMPLICATIONS: The findings point to the value of assessing patients' activation levels at the beginning of their cancer experience.

Measuring team development in clinical care settings.

BACKGROUND AND OBJECTIVES: Our objective was to describe the psychometric properties of a measure of team development that can be used to assess and guide team functioning in health care settings. METHODS: The Team Development Measure (TDM) is a 31-item questionnaire constructed using the Rasch rating scale measurement model. We conducted an Mplus exploratory factor analysis using data collected from 1,194 individuals representing 120 different teams. Team size ranged from three to 39 members from rural and urban inpatient and ambulatory health care settings. Here we characterize the domains of teamness, while taking into account the development of teams over time. RESULTS: The TDM was found to have good psychometric properties with little measurement error and a Rasch person reliability of 0.95. Overall Cronbach's alpha was 0.97. An Mplus exploratory factor analysis combined with the stochastic nature of the Rasch model suggests a developmental sequence in building teams consisting of four sub-domains with the following mean item difficulty scores: cohesion=40.5, standard deviation (SD)=2.68, communication=49.3 (SD=2.78), roles and goals=52.7 (SD=2.74), and team primacy=53.3 (SD=1.06). This pattern suggests cohesiveness is an initial element for team development, followed by communication, roles and goals clarity, and team primacy. CONCLUSIONS: We developed and tested a measure of team development that has strong psychometric properties. This tool could be used to study how team functioning affects clinical outcomes and as a quality improvement tool to improve team function.

Toward a theory of patient and consumer activation.

OBJECTIVE: The purpose of this study is to begin the process of developing a theory of activation, to inform educational efforts and the design of interventions. Because the experience of positive emotions in daily life, tends to widen the individual's array of behavioral responses and increase their openness to new information, we examine how emotions relate to activation levels. METHODS: A web survey was carried out in 2008 with a National sample of respondents between the ages of 25-75. The study achieved a 63% response rate with a final sample size of 843. RESULTS: The findings indicate that activation is linked with the experience of positive and negative emotion in daily life. Those low in activation are weighted down by negative affect and negative self-perception. CONCLUSIONS: Bringing about change in activation, likely means breaking this cycle of negative self-perception and emotions. PRACTICE IMPLICATIONS: Experiencing success can start a positive upward cycle, just like failure produces the opposite. By encouraging small steps toward improving health, ones that are realistic, given the individuals level of activation, it is possible to start that positive cycle. Effective educational efforts should focus on improving self-efficacy and the individual's self-concept as a self-manager.

The development and testing of a measure assessing clinician beliefs about patient self-management.

BACKGROUND: Clinicians have been slow to embrace support for patient self-management. OBJECTIVE: To explore clinicians' beliefs about patient self-management and specifically assess which patient competencies clinicians believe are most important for their patients. METHODS: Using items adapted from the Patient Activation Measure (PAM) as a basis, a new measure that assesses clinicians' beliefs about patient self-management was created using Rasch analysis. The development and testing of the new measure Clinician Support for Patient Activation Measure (CS-PAM) is described here. Primary care clinicians from the UK and the USA were recruited to participate in the survey (n = 175). FINDINGS: The CS-PAM reliably measures clinician attitudes about the patient role in the care process. Clinicians strongly endorse that patients should follow medical advice but are less likely to endorse that patients should be able to make independent judgements or take independent actions. Endorsed to a lesser degree was the idea that patients should be able to function as a member of the care team. Least endorsed was the notion that patients should be independent information seekers. DISCUSSION: Clinicians' views appear to be out of step with current policy directions and professional codes. Clinicians need support to transition to understand the need to support patients as independent actors.

Technical note: prediction of sex based on five skull traits using decision analysis (CHAID).

Osteologists commonly assess the sex of skeletal remains found in forensic and archaeological contexts based on ordinal scores of subjectively assessed sexually dimorphic traits. Using known-sex samples, logistic regression (LR) discriminant functions have been recently developed, which allow sex probabilities to be determined. A limitation of LR is that it emphasizes main effects and not interactions. Chi-square automatic interaction detection (CHAID) is an alternative classification strategy that emphasizes the information in variable interactions and uses decision trees to maximize the probability of correct sex determinations. We used CHAID to analyze the predictive value of the 31 possible combinations of five sexually dimorphic skull traits that Walker used previously to develop logistic regression sex determination equations. The samples consisted of 304 individuals of known sex of English, African American, and European American origin. Based on practical considerations, selection criteria for the best sex predictive trait combinations (SPTCs) were set at accuracies for both sexes of 75% or greater and sex biases lower than 5%. Although several of the trees meeting these criteria were produced for the English and European American samples, none met them for the African American sample. In the series of out-of-sample tests we performed, the trees from the English and combined sample of all groups predicted best.

Developing a senior healthcare practice using the chronic care model: effect on physical function and health-related quality of life.

An ambulatory senior health clinic was developed using the chronic care model (CCM), with emphasis on an interdisciplinary team approach. To determine the effect of this care model approach in a nonprofit healthcare system, an observational, longitudinal panel study of community-dwelling Medicare beneficiaries was performed to examine the effect on physical function and health-related quality of life (HRQL). Participants in the study were recruited from a community sample of 6,864 eligible Medicare beneficiaries. Informed consent and baseline data were obtained from 1,709 individuals (recruitment response rate=25%) and complete data across 30 months from 1,307 (completion response rate=76%). Participants receiving care in the CCM-based senior healthcare practice (n=318) were compared with patients of primary care physicians supported by care managers (n=598) and a group without care managers (n=391). Self-reported data were collected over the telephone to measure physical function and HRQL at baseline and 6, 18, and 30 months. A multiple group mixture growth model was used to analyze physical function and HRQL across the 30 months. Physical function and HRQL mean scores decreased across time in all participants and were moderately correlated at each wave (correlation coefficient=0.74-0.79). Two latent growth classes were identified. In class 1, physical function decreased, and HRQL remained stable across time. In class 2, physical function and HRQL decreased in parallel. Ninety-seven percent of intervention group patients were in class 1, and 99% of patients in comparison groups 1 and 2 were in class 2. Despite physical function decline, patients in a senior health clinic care model maintained HRQL over time, whereas patients receiving traditional care had physical function and HRQL decline. An interdisciplinary team CCM approach appears to have a positive effect on HRQL in this population.

Assessing the quality of transitional care: further applications of the care transitions measure.

BACKGROUND: The Institute of Medicine has identified care transitions as a priority area for performance measurement. OBJECTIVES: To examine the performance of the Care Transitions Measure (CTM) in more diverse populations and to introduce a 3-item CTM. RESEARCH DESIGN: Cross-sectional study with purposive sampling of traditionally underserved populations. Confirmatory factor analyses, internal consistency reliability analyses, and differential item function tests were performed to explore the stability and performance of the 15-item CTM. Regression assessed the ability of the 3-item CTM to predict the 15-item CTM total score. Analysis of variance tests were conducted to explore CTM performance in different populations with respect to health and demographics. SUBJECTS: A total of 225 patients age 18-90 who were hospitalized in the past 12 months and were African American, Hispanic American, or rural-dwelling. MEASURES: CTM-15, CTM-3, age, gender, education, and health status. RESULTS: Mplus confirmatory factor analysis supported the CTM-15 factor structure in more diverse population (Comparative Fit Index [CFI] = 0.954). The 3-item CTM explained 88% of the variance in the 15-item CTM score. Differential item function analysis did not reveal any differential item difficulty by age, gender, education, self-rated health, or group (African American, Hispanic American, and rural-dwelling). CONCLUSIONS: Following endorsement by National Quality Forum, findings support use of the CTM in national public reporting efforts. The 3-item CTM closely approximates the 15-item instrument and may be attractive to purchasers and health care organizations that want to assess quality in this area while minimizing cost and response burden.

The central role of performance measurement in improving the quality of transitional care.

The objectives of this study were: (1) to demonstrate the ability of the Care Transitions Measure (CTM) to identify care deficiencies; (2) to devise and implement a quality improvement approach designed to remedy these deficiencies; (3) to assess the impact of the quality improvement approach on CTM scores; and (4) to test whether the CTM-3 predicts return to the emergency department. The CTM was found to be a sensitive tool able to capture changes in performance. The 3-item CTM was found to significantly predict post-hospital return to the emergency department within the first 30 days (p = 0.004).

Do increases in patient activation result in improved self-management behaviors?

OBJECTIVE: The purpose of this study is to determine whether patient activation is a changing or changeable characteristic and to assess whether changes in activation also are accompanied by changes in health behavior. STUDY METHODS: To obtain variability in activation and self-management behavior, a controlled trial with chronic disease patients randomized into either intervention or control conditions was employed. In addition, changes in activation that occurred in the total sample were also examined for the study period. Using Mplus growth models, activation latent growth classes were identified and used in the analysis to predict changes in health behaviors and health outcomes. DATA SOURCES: Survey data from the 479 participants were collected at baseline, 6 weeks, and 6 months. PRINCIPAL FINDINGS: Positive change in activation is related to positive change in a variety of self-management behaviors. This is true even when the behavior in question is not being performed at baseline. When the behavior is already being performed at baseline, an increase in activation is related to maintaining a relatively high level of the behavior over time. The impact of the intervention, however, was less clear, as the increase in activation in the intervention group was matched by nearly equal increases in the control group. CONCLUSIONS: Results suggest that if activation is increased, a variety of improved behaviors will follow. The question still remains, however, as to what interventions will improve activation.

Development and testing of a short form of the patient activation measure.

OBJECTIVE: The Patient Activation Measure (PAM) is a 22-item measure that assesses patient knowledge, skill, and confidence for self-management. The measure was developed using Rasch analyses and is an interval level, unidimensional, Guttman-like measure. The current analysis is aimed at reducing the number of items in the measure while maintaining adequate precision. STUDY METHODS: We relied on an iterative use of Rasch analysis to identify items that could be eliminated without loss of significant precision and reliability. With each item deletion, the item scale locations were recalibrated and the person reliability evaluated to check if and how much of a decline in precision of measurement resulted from the deletion of the item. DATA SOURCES: The data used in the analysis were the same data used in the development of the original 22-item measure. These data were collected in 2003 via a telephone survey of 1,515 randomly selected adults. Principal Findings. The analysis yielded a 13-item measure that has psychometric properties similar to the original 22-item version. The scores for the 13-item measure range in value from 38.6 to 53.0 (on a theoretical 0-100 point scale). The range of values is essentially unchanged from the original 22-item version. Subgroup analysis suggests that there is a slight loss of precision with some subgroups. CONCLUSIONS: The results of the analysis indicate that the shortened 13-item version is both reliable and valid.

Assessing the quality of preparation for posthospital care from the patient's perspective: the care transitions measure.

BACKGROUND: Evidence that both quality and patient safety are jeopardized for patients undergoing transitions across care settings continues to expand. Performance measurement is one potential strategy towards improving the quality of transitional care. A valid and reliable self-report measure of the quality of care transitions is needed that is both consistent with the concept of patient-centeredness and useful for the purpose of performance measurement and quality improvement. OBJECTIVE: We sought to develop and test a self-report measure of the quality of care transitions that captures the patient's perspective and has demonstrated utility for quality improvement. SUBJECTS: Patients aged 18 years and older discharged from one of the 3 hospitals of a vertically integrated health system were included. RESEARCH DESIGN: Cross-sectional assessment of factor structure, dimensionality, and construct validity. RESULTS: The Care Transitions Measure (CTM), a 15-item uni-dimensional measure of the quality of preparation for care transitions, was found to have high internal consistency, reliability, and reflect 4 focus group-derived content domains. The measure was shown to discriminate between patients discharged from the hospital who did and did not have a subsequent emergency department visit or rehospitalization for their index condition. CTM scores were significantly different between health care facilities known to vary in level of system integration. CONCLUSIONS: The CTM not only provides meaningful, patient-centered insight into the quality of care transitions, but because of the association between CTM scores and undesirable utilization outcomes, it also provides information that may be useful to clinicians, hospital administrators, quality improvement entities, and third party payers.

Development of the Patient Activation Measure (PAM): conceptualizing and measuring activation in patients and consumers.

BACKGROUND: Controlling costs and achieving health care quality improvements require the participation of activated and informed consumers and patients. OBJECTIVES: We describe a process for conceptualizing and operationalizing what it means to be "activated" and delineate the process we used to develop a measure for assessing "activation," and the psychometric properties of that measure. METHODS: We used the convergence of the findings from a national expert consensus panel and patient focus groups to define the concept and identify the domains of activation. These domains were operationalized by constructing a large item pool. Items were pilot-tested and initial psychometric analysis performed using Rasch methodology. The third stage refined and extended the measure. The fourth stage used a national probability sample to assess the measure's psychometric performance overall and within different subpopulations. STUDY SAMPLE: Convenience samples of patients with and without chronic illness, and a national probability sample (N=1,515) are included at different stages in the research. CONCLUSIONS: The Patient Activation Measure is a valid, highly reliable, unidimensional, probabilistic Guttman-like scale that reflects a developmental model of activation. Activation appears to involve four stages: (1) believing the patient role is important, (2) having the confidence and knowledge necessary to take action, (3) actually taking action to maintain and improve one's health, and (4) staying the course even under stress. The measure has good psychometric properties indicating that it can be used at the individual patient level to tailor intervention and assess changes.