Use of Well-Being in Identification of Members With Future Health Risk Factors and Future Diagnosed Chronic Disease.

OBJECTIVE: To evaluate if well-being is associated with the development of future health risks or incidence of new chronic disease. METHODS: A retrospective cohort study was employed using longitudinal well-being assessment survey data from participants of a Fortune 500 US company wellness program, claims based International Classification of Diseases, Ninth Revision diagnoses, and Cox proportional hazards models to assess associations between well-being and well-being change with future health risk and chronic disease incidence. RESULTS: Individuals who maintained high well-being and those who increased their level of well-being displayed a significantly decreased hazard of accruing new health risk and new chronic disease incidence; those whose well-being worsened over time showed significant increases in health risk and hazard of new chronic disease incidence. CONCLUSIONS: Well-being levels and change over time are significantly associated with future development of health risk and disease incidence.

Effect of post-hospital discharge telephonic intervention on hospital readmissions in a privately insured population in Australia.

Objective The aim of the present study was to evaluate the effect of telephone support after hospital discharge to reduce early hospital readmission among members of the disease management program My Health Guardian (MHG) offered by the Hospitals Contribution Fund of Australia (HCF). Methods A quasi-experimental retrospective design compared 28-day readmissions of patients with chronic disease between two groups: (1) a treatment group, consisting of MHG program members who participated in a hospital discharge (HODI) call; and (2) a comparison group of non-participating MHG members. Study groups were matched for age, gender, length of stay, index admission diagnoses and prior MHG program exposure. Adjusted incidence rate ratios (IRR) and odds ratios (OR) were estimated using zero-inflated negative binomial and logistic regression models respectively. Results The treatment group exhibited a 29% lower incidence of 28-day readmissions than the comparison group (adjusted IRR 0.71; 95% confidence interval (CI) 0.59-0.86). The odds of treatment group members being readmitted at least once within 28 days of discharge were 25% lower than the odds for comparison members (adjusted OR 0.75; 95% CI 0.63-0.89). Reduction in readmission incidence was estimated to avoid A$713730 in cost. Conclusions The HODI program post-discharge telephonic support to patients recently discharged from a hospital effectively reduced the incidence and odds of hospital 28-day readmission in a diseased population. What is known about the topic? High readmission rates are a recognised problem in Australia and contribute to the over 600000 potentially preventable hospitalisations per year. What does this paper add? The present study is the first study of a scalable intervention delivered to an Australian population with a wide variety of conditions for the purpose of reducing readmissions. The intervention reduced 28-day readmission incidence by 29%. What are the implications for practitioners? The significant and sizable effect of the intervention support the delivery of telephonic support after hospital discharge as a scalable approach to reduce readmissions.

The well-being valuation model: a method for monetizing the nonmarket good of individual well-being.

The objective of this research is to advance the evaluation and monetization of well-being improvement programs, offered by population health management companies, by presenting a novel method that robustly monetizes the entirety of well-being improvement within a population. This was achieved by utilizing two employers' well-being assessments with medical and pharmacy administrative claims (2010-2011) across a large national employer (n = 50,647) and regional employer (n = 6170) data sets. This retrospective study sought to monetize both direct and indirect value of well-being improvement across a population whose medical costs are covered by an employer, insurer, and/or government entity. Logistic regression models were employed to estimate disease incidence rates and input-output modelling was used to measure indirect effects of well-being improvement. These methodological components removed the burden of specifying an exhaustive number of regression models, which would be difficult in small populations. Members who improved their well-being were less likely to become diseased. This reduction saved, per avoided occurrence, US$3060 of total annual health care costs. Of the members who were diseased, improvement in well-being equated to annual savings of US$62 while non-diseased members saved US$26. The method established here demonstrates the linkage between improved well-being and improved outcomes while maintaining applicability in varying populations.

What's Mine is Yours: Evaluation of Shared Well-Being Among Married Couples and the Dyadic Influence on Individual Well-Being Change.

OBJECTIVE: To evaluate the relationship between partner well-being and outcomes of chronically diseased individuals participating in an employer sponsored well-being improvement program. METHODS: Using the Actor Partner Interdependence Model, we evaluated whether prior partner well-being was associated with well-being change among 2025 couples. Logistic regression models were then used to explore how spousal well-being risks relate to development and elimination of risks among program participants. RESULTS: High well-being partners were associated with positive well-being change. Specifically, the partner effect for spouses' high well-being on disease management participants was a 1.5 point higher well-being in the following time period (P = 0.001) while the partner effect of participants' high well-being on spouses was nearly 1.1 points (P = 0.010). CONCLUSIONS: Well-being within couples is interdependent, and partner well-being is an important predictor of individual well-being change.

Population Well-Being Measures Help Explain Geographic Disparities In Life Expectancy At The County Level.

Geographic disparities in life expectancy are substantial and not fully explained by differences in race and socioeconomic status. To develop policies that address these inequalities, it is essential to identify other factors that account for this variation. In this study we investigated whether population well-being-a comprehensive measure of physical, mental, and social health-helps explain geographic variation in life expectancy. At the county level, we found that for every 1-standard-deviation (4.2-point) increase in the well-being score, life expectancy was 1.9 years higher for females and 2.6 years higher for males. Life expectancy and well-being remained positively associated, even after race, poverty, and education were controlled for. In addition, well-being partially mediated the established associations of race, poverty, and education with life expectancy. These findings highlight well-being as an important metric of a population's health and longevity and as a promising focus for intervention.

Integrating Well-Being Information and the Multidimensional Adaptive Prediction Process to Estimate Individual-Level Future Health Care Expenditure Levels.

Decades of research exist focusing on the utility of self-reported health risk and status data in health care cost predictive models. However, in many of these studies a limited number of self-reported measures were considered. Compounding this issue, prior research evaluated models specified with a single covariate vector and distribution. In this study, the authors incorporate well-being data into the Multidimensional Adaptive Prediction Process (MAPP) and then use a simulation analysis to highlight the value of these findings for future cost mitigation. Data were collected on employees and dependents of a nationally based employer over 36 months beginning in January 2010. The first 2 years of data (2010, 2011) were utilized in model development and selection; 51239 and 54085 members were included in 2010 and 2011, respectively. The final results were based on prospective prediction of 2012 cost levels using 2011 data. The well-being-augmented MAPP results showed a 5.7% and 13% improvement in accurate cost capture relative to a reference modeling approach and the first study of MAPP, respectively. The simulation analysis results demonstrated that reduced well-being risk across a population can help mitigate the expected upward cost trend. This research advances health care cost predictive modeling by incorporating well-being information within MAPP and then leveraging the results in a simulation analysis of well-being improvement.

Direct and Mediated Relationships Between Participation in a Telephonic Health Coaching Program and Health Behavior, Life Satisfaction, and Optimism.

OBJECTIVE: The aim of this study was to examine the direct and mediated effects of a telephonic health coaching program on changes to healthy behaviors, life satisfaction, and optimism. METHODS: This longitudinal correlational study of 4881 individuals investigated simple and mediated relationships between participation in a telephonic health risk coaching program and outcomes from three annual Well-being Assessments. RESULTS: Program participation was directly related to improvements in healthy behaviors, life satisfaction and optimism, and indirect effects of coaching on these variables concurrently and over a one-year time lag were also supported. CONCLUSIONS: Given previous research that improvements to life satisfaction, optimism, and health behaviors are valuable for individuals, employers, and communities, a clearer understanding of intervention approaches that may impact these outcomes simultaneously can drive greater program effectiveness and value on investment.

Impact of a scalable care transitions program for readmission avoidance.

OBJECTIVES: To evaluate the Care Transition Solution (CTS) as a means to improve quality through reduction of preventable hospital readmissions among patients with readmission-sensitive conditions subject to penalties imposed by the Affordable Care Act. STUDY DESIGN: A retrospective quasi-experimental evaluation of the impact of the CTS among admitted patients diagnosed with heart failure, acute myocardial infarction, chronic obstructive pulmonary disease, and/or pneumonia (CMS readmission-penalty diagnoses) in 14 acute care hospitals in Texas. The program, designed for scalable delivery, incorporated identification of high readmission-risk patients, assessment of individual needs, medication reconciliation, discharge planning, care coordination, and telephonic postdischarge follow-up. METHODS: The treatment group of program enrollees (N = 560) and the comparison group with no program contact (N = 3340) were matched on 8 coarsened demographic, diagnosis, and severity variables associated with readmission risk. Assessed outcomes included relative risk and odds of readmission within 30 days postdischarge and overall within the 6-month evaluation period. Zero-inflated Poisson multivariate models were used to estimate intervention effects controlling for matching-generated weights, age, disease status, and period of evaluation. RESULTS: Treatment group risk of readmission was 22% lower overall (incidence rate ratio [IRR], 0.78; P < .01) and 30-day readmission risk was 25% lower (IRR, 0.75; P = .01) relative to the comparison group. Odds of any or 30-day readmission were 0.47 (95% CI, 0.35-0.65) and 0.56 (95% CI, 0.41-0.77), respectively, for treatment relative to comparison. CONCLUSIONS: Participation in the CTS resulted in significantly lower rates of readmissions among patients with readmission-sensitive conditions, offering a scalable and sustainable approach to reduce the number of preventable hospital readmissions.

Overall Well-Being and Supervisor Ratings of Employee Performance, Accountability, Customer Service, Innovation, Prosocial Behavior, and Self-Development.

OBJECTIVE: The aim of this study was to study the effects of overall well-being and well-being change on six supervisor-rated indicators of employee performance valued by organizations: overall performance, accountability, customer service, innovation, prosocial behavior, and self-development. METHODS: The current study used two waves of well-being survey data collected over 2 years and supervisor performance ratings for 5691 employees. Ordinary least squares regression was conducted. RESULTS: Both well-being at baseline and two-year change in well-being were related to all six supervisor-rated performance dimensions, controlling for other employee characteristics. CONCLUSION: Overall well-being likely functioned as a resource enabling people to successfully perform across the specific areas highly valued by their company. Given this connection, well-being interventions could be used as a means to accomplish improved performance in dimensions that contribute to organizational performance.

Comparison of the Utility of Two Assessments for Explaining and Predicting Productivity Change: Well-Being Versus an HRA.

OBJECTIVE: To compare utility of employee well-being to health risk assessment (HRA) as predictors of productivity change. METHODS: Panel data from 2189 employees who completed surveys 2 years apart were used in hierarchical models comparing the influence of well-being and health risk on longitudinal changes in presenteeism and job performance. Absenteeism change was evaluated in a nonexempt subsample. RESULTS: Change in well-being was the most significant independent predictor of productivity change across all three measures. Comparing hierarchical models, well-being models performed significantly better than HRA models. The HRA added no incremental explanatory power over well-being in combined models. Alone, nonphysical health well-being components outperformed the HRA for all productivity measures. CONCLUSIONS: Well-being offers a more comprehensive measure of factors that influence productivity and can be considered preferential to HRA in understanding and addressing suboptimal productivity.

Adaptive Measurement of Well-Being: Maximizing Efficiency and Optimizing User Experience during Individual Assessment.

Well-being is linked to important societal factors such as health care costs and productivity and has experienced a surge in development activity of both theories and measurement. This study builds on validation of the Well-Being 5 survey and for the first time applies Item Response Theory, a modern and flexible measurement paradigm, to form the basis of adaptive population well-being measurement. Adaptive testing allows survey questions to be administered selectively, thereby reducing the number of questions required of the participant. After the graded response model was fit to a sample of size N = 12,035, theta scores were estimated based on both the full-item bank and a simulation of Computerized Adaptive Testing (CAT). Comparisons of these 2 sets of score estimates with each other and of their correlations with external outcomes of job performance, absenteeism, and hospital admissions demonstrate that the CAT well-being scores maintain accuracy and validity. The simulation indicates that the average survey taker can expect a reduction in number of items administered during the CAT process of almost 50%. An increase in efficiency of this extent is of considerable value because of the time savings during the administration of the survey and the potential improvement of user experience, which in turn can help secure the success of a total population-based well-being improvement program. (Population Health Management 2016;19:284-290).

The Value of a Well-Being Improvement Strategy: Longitudinal Success across Subjective and Objective Measures Observed in a Firm Adopting a Consumer-Driven Health Plan.

OBJECTIVE: The objective of this study is to evaluate effectiveness of a firm's 5-year strategy toward improving well-being while lowering health care costs amidst adoption of a Consumer-Driven Health Plan. METHODS: Repeated measures statistical models were employed to test and quantify association between key demographic factors, employment type, year, individual well-being, and outcomes of health care costs, obesity, smoking, absence, and performance. RESULTS: Average individual well-being trended upward by 13.5% over 5 years, monthly allowed amount health care costs declined 5.2% on average per person per year, and obesity and smoking rates declined by 4.8 and 9.7%, respectively, on average each year. The results show that individual well-being was significantly associated with each outcome and in the expected direction. CONCLUSIONS: The firm's strategy was successful in driving statistically significant, longitudinal well-being, biometric and productivity improvements, and health care cost reduction.

Long-term impact of a chronic disease management program on hospital utilization and cost in an Australian population with heart disease or diabetes.

BACKGROUND: To evaluate the longitudinal value of a chronic disease management program, My Health Guardian (MHG), in reducing hospital utilization and costs over 4 years. METHODS: The MHG program provides individualized support via telephonic nurse outreach and online tools for self-management, behavior change and well-being. In follow up to an initial 18-month analysis of MHG, the current study evaluated program impact over 4 years. A matched-cohort analysis retrospectively compared MHG participants with heart disease or diabetes (treatment, N = 4,948) to non-participants (comparison, N = 28,520) on utilization rates (hospital admission, readmission, total bed days) and hospital claims cost savings. Outcomes were evaluated using regression analyses, controlling for remaining demographic, disease, and pre-program admissions or cost differences between the study groups. RESULTS: Over the 4 year period, program participation resulted in significant reductions in hospital admissions (-11.4%, P < 0.0001), readmissions (-36.7%, P < 0.0001), and bed days (-17.2%, P < 0.0001). The effect size increased over time for admissions and bed days. The relative odds of any admission and readmission over the 4 years were 27% and 45% lower, respectively, in the treatment group. Cumulative program savings from reduced hospital claims was $3,549 over 4-years; savings values for each program year were significant and increased with time (P = 0.003 to P < 0.0001). Savings calculations did not adjust for pooled costs (and savings) in Australia's risk equalization system for private insurers. CONCLUSIONS: Results confirm and extend prior program outcomes and support the longitudinal value of the MHG program in reducing hospital utilization and costs for individuals with heart disease or diabetes and demonstrate the increasing program effect with continued participation over time.

Well-being improvement in a midsize employer: changes in well-being, productivity, health risk, and perceived employer support after implementation of a well-being improvement strategy.

OBJECTIVE: To evaluate employee well-being change and associated change in productivity, health risk including biometrics, and workplace support over 2 years after implementation of a well-being improvement strategy. METHODS: This was an employer case study evaluation of well-being, productivity (presenteeism, absenteeism, and job performance), health risk, and employer support across three employee assessment spanning 2 years. Employee well-being was compared with an independent sample of workers in the community. RESULTS: Well-being and job performance increased and presenteeism and health risk decreased significantly over the 2 years. Employee well-being started lower and increased to exceed community worker averages, approaching significance. Well-being improvement was associated with higher productivity across all measures. Increases in employer support for well-being were associated with improved well-being and productivity. CONCLUSIONS: This employer's well-being strategy, including a culture supporting well-being, was associated with improved health and productivity.

Predicting Health Care Cost Transitions Using a Multidimensional Adaptive Prediction Process.

Managing population health requires meeting individual care needs while striving for increased efficiency and quality of care. Predictive models can integrate diverse data to provide objective assessment of individual prospective risk to identify individuals requiring more intensive health management in the present. The purpose of this research was to develop and test a predictive modeling approach, Multidimensional Adaptive Prediction Process (MAPP). MAPP is predicated on dividing the population into cost cohorts and then utilizing a collection of models and covariates to optimize future cost prediction for individuals in each cohort. MAPP was tested on 3 years of administrative health care claims starting in 2009 for health plan members (average n=25,143) with evidence of coronary heart disease. A "status quo" reference modeling methodology applied to the total annual population was established for comparative purposes. Results showed that members identified by MAPP contributed $7.9 million and $9.7 million more in 2011 health care costs than the reference model for cohorts increasing in cost or remaining high cost, respectively. Across all cohorts, the additional accurate cost capture of MAPP translated to an annual difference of $1882 per member, a 21% improvement, relative to the reference model. The results demonstrate that improved future cost prediction is achievable using a novel adaptive multiple model approach. Through accurate prospective identification of individuals whose costs are expected to increase, MAPP can help health care entities achieve efficient resource allocation while improving care quality for emergent need individuals who are intermixed among a diverse set of health care consumers.

Regional economic activity and absenteeism: a new approach to estimating the indirect costs of employee productivity loss.

This paper presents a new approach to estimating the indirect costs of health-related absenteeism. Productivity losses related to employee absenteeism have negative business implications for employers and these losses effectively deprive the business of an expected level of employee labor. The approach herein quantifies absenteeism cost using an output per labor hour-based method and extends employer-level results to the region. This new approach was applied to the employed population of 3 health insurance carriers. The economic cost of absenteeism was estimated to be $6.8 million, $0.8 million, and $0.7 million on average for the 3 employers; regional losses were roughly twice the magnitude of employer-specific losses. The new approach suggests that costs related to absenteeism for high output per labor hour industries exceed similar estimates derived from application of the human capital approach. The materially higher costs under the new approach emphasize the importance of accurately estimating productivity losses.

Well-being, health, and productivity improvement after an employee well-being intervention in large retail distribution centers.

OBJECTIVE: To evaluate changes in well-being, biometric, and productivity indicators after a well-being intervention. METHODS: Biometric and self-reported outcomes were assessed among 677 retail distribution center employees before and after a 6-month well-being intervention. RESULTS: Despite lower well-being at baseline compared to an independent random sample of workers, program participants' well-being, productivity, body mass index, systolic blood pressure, and total cholesterol improved significantly after the intervention, whereas the decline in diastolic blood pressure was not significant. Moreover, participants' specific transition across well-being segments over the intervention period demonstrated more improvement than decline. CONCLUSIONS: There is evidence that programs designed to improve well-being within a workforce can be used to significantly and positively impact employee health and productivity, which should result in reduced health care costs, improved employee productivity, and increased overall profitability.

The well-being 5: development and validation of a diagnostic instrument to improve population well-being.

Building upon extensive research from 2 validated well-being instruments, the objective of this research was to develop and validate a comprehensive and actionable well-being instrument that informs and facilitates improvement of well-being for individuals, communities, and nations. The goals of the measure were comprehensiveness, validity and reliability, significant relationships with health and performance outcomes, and diagnostic capability for intervention. For measure development and validation, questions from the Well-being Assessment and Wellbeing Finder were simultaneously administered as a test item pool to over 13,000 individuals across 3 independent samples. Exploratory factor analysis was conducted on a random selection from the first sample and confirmed in the other samples. Further evidence of validity was established through correlations to the established well-being scores from the Well-Being Assessment and Wellbeing Finder, and individual outcomes capturing health care utilization and productivity. Results showed the Well-Being 5 score comprehensively captures the known constructs within well-being, demonstrates good reliability and validity, significantly relates to health and performance outcomes, is diagnostic and informative for intervention, and can track and compare well-being over time and across groups. With this tool, well-being deficiencies within a population can be effectively identified, prioritized, and addressed, yielding the potential for substantial improvements to the health status, performance, and quality of life for individuals and cost savings for stakeholders.

Comparing the contributions of well-being and disease status to employee productivity.

OBJECTIVE: To compare employee overall well-being to chronic disease status, which has a long-established relationship to productivity, as relative contributors to on-the-job productivity. METHODS: Data from two annual surveys of three companies were used in longitudinal analyses of well-being as a predictor of productivity level and productivity change among 2629 employees with diabetes or without any chronic conditions. RESULTS: Well-being was the most significant predictor of productivity cross-sectionally in a model that included disease status and demographic characteristics. Longitudinally, changes in well-being contributed to changes in productivity above and beyond what could be explained by the presence of chronic disease or other fixed characteristics. CONCLUSIONS: These findings support the use of well-being as the broader framework for understanding, explaining, and improving employee productivity in both the healthy and those with disease.

Well-being and employee health-how employees' well-being scores interact with demographic factors to influence risk of hospitalization or an emergency room visit.

The goal of this study was to determine the relationship between individual well-being and risk of a hospital event in the subsequent year. The authors hypothesized an inverse relationship in which low well-being predicts higher likelihood of hospital use. The study specifically sought to understand how well-being segments and demographic variables interact in defining risk of a hospital event (inpatient admission or emergency room visit) in an employed population. A retrospective study design was conducted with data from 8835 employees who completed a Well-Being Assessment questionnaire based on the Gallup-Healthways Well-Being Index. Cox proportional hazards models were used to examine the impact of Individual Well-Being Score (IWBS) segments and member demographics on hazard ratios (HRs) for a hospital event during the 12 months following assessment completion. Significant main effects were found for the influence of IWBS segments, sex, education, and relationship status on HRs of a hospital event, but not for age. However, further analysis revealed significant interactions between age and IWBS segments (P=0.005) and between age and sex (P<0.0001), indicating that the effects for IWBS segments and sex on HRs of a hospital event are mediated through their relationship with age. Overall, the strong relationship between low well-being and higher risk of an event in employees ages 44 years and older is mitigated in younger age groups. These results suggest that youth attenuates the risk engendered in poor well-being; therefore, methods to maintain or improve well-being as individuals age presents a strong opportunity for reducing hospital events.