Harvesting the wisdom of the crowd: using online ratings to explore care experiences in regions.

Regional population health management (PHM) initiatives need an understanding of regional patient experiences to improve their services. Websites that gather patient ratings have become common and could be a helpful tool in this effort. Therefore, this study explores whether unsolicited online ratings can provide insight into (differences in) patient's experiences at a (regional) population level

Are low-value care measures up to the task? A systematic review of the literature

Background Reducing low-value care is a core component of healthcare reforms in many Western countries. A comprehensive and sound set of low-value care measures is needed in order to monitor low-value care use in general and in provider-payer contracts. Our objective was to review the scientific literature on low-value care measurement, aiming to assess the scope and quality of current measures. Methods A systematic review was performed for the period 2010–2015. We assessed the scope of low-value care recommendations and measures by categorizing them according to the Classification of Health Care Functions. Additionally, we assessed the quality of the measures by 1) analysing their development process and the level of evidence underlying the measures, and 2) analysing the evidence regarding the validity of a selected subset of the measures. Results Our search yielded 292 potentially relevant articles. After screening, we selected 23 articles eligible for review. We obtained 115 low-value care measures, of which 87 were concentrated in the cure sector, 25 in prevention and 3 in long-term care. No measures were found in rehabilitative care and health promotion. We found 62 measures from articles that translated low-value care recommendations into measures, while 53 measures were previously developed by institutions as the National Quality Forum. Three measures were assigned the highest level of evidence, as they were underpinned by both guidelines and literature evidence. Our search yielded no information on coding/criterion validity and construct validity for the included measures. Despite this, most measures were already used in practice. Conclusion This systematic review provides insight into the current state of low-value care measures. It shows that more attention is needed for the evidential underpinning and quality of these measures. Clear information about the level of evidence and validity helps to identify measures that truly represent low-value care and are sufficiently qualified to fulfil their aims through quality monitoring and in innovative payer-provider contracts. This will contribute to creating and maintaining the support of providers, payers, policy makers and citizens, who are all aiming to improve value in health care

Comparing the Health of Populations: Methods to Evaluate and Tailor Population Management Initiatives in the Netherlands

Health care no longer focuses solely on patients and increasingly emphasizes regions and their populations. Strategies, such as population management (PM) initiatives, aim to improve population health and well-being by redesigning health care and community services. Hence, insight into population health is needed to tailor interventions and evaluate their effects. This study aims to assess whether population health differs between initiatives and to what extent demographic, personal, and lifestyle factors affect these differences. A population health survey that included the Short Form 12 version 2 (SF12, physical and mental health status), Patient Activation Measure 13 (PAM13), and demographic, personal, and lifestyle factors was administered in 9 Dutch PM initiatives. Potential confounders were determined by comparing these factors between PM initiatives using analyses of variance and chi-square tests. The influence of these potential confounders on the health outcomes was studied using multivariate linear regression. Age, education, origin, employment, body mass index, and smoking were identified as potential confounders for differences found between the 9 PM initiatives. Each had a noteworthy influence on all of the instruments' scores. Not all health differences between PM initiatives were explained, as the SF12 outcomes still differed between PM initiatives once corrected. For the PAM13, the differences were no longer significant. Demographic and lifestyle factors should be included in the evaluation of PM initiatives and population health differences found can be used to tailor initiatives. Other factors beyond health care (eg, air quality) should be considered to further refine the tailoring and evaluation of PM initiatives

How to Measure Population Health: An Exploration Toward an Integration of Valid and Reliable Instruments This study was presented as a poster presentation at the International Conference on Integrated Care 2017, held May 8-10, 2017 in Dublin, Ireland.

Population health management initiatives are introduced to transform health and community services by implementing interventions that combine various services and address the continuum of health and well-being of populations. Insight is required into a population's health to evaluate implementation of these initiatives. This study aims to determine the performance of commonly used instruments for measuring a population's experienced health and explores the assessed concepts of population health. Survey-based Short Form 12, version 2 (SF12, health status), Patient Activation Measure 13 (PAM13), and Kessler 10 (K10, psychological distress) data of 3120 respondents was used. Floor/ceiling effects were studied using descriptive statistics. Validity was assessed using factor and discriminant analyses, and reliability was assessed using Cronbach . Finally, to study covered concepts, exploratory factor analyses (EFAs) were conducted, which included additional surveyed characteristics. The SF12 and PAM13 sum scores showed acceptable averages and distributions, while results of the K10 indicated a floor effect. SF12 and K10 measured their expected constructs, while PAM13 did not. The EFA of PAM13 displayed 1 instead of the expected 4 constructs. Reliability was good for all instruments ( 0.89-0.93). The overall EFA identified 4 concepts: mental, physical ability, lifestyle, and self-management. SF12 and PAM13, combined with lifestyle characteristics, are shown to provide insightful information to measure the physical, mental, lifestyle, and self-management concepts of population health. Future research should include additional instruments that cover new aspects introduced by recent definitions of health

Which Triple Aim related measures are being used to evaluate population management initiatives? An international comparative analysis

Introduction Population management (PM) initiatives are introduced in order to create sustainable health care systems. These initiatives should focus on the continuum of health and well-being of a population by introducing interventions that integrate various services. To be successful they should pursue the Triple Aim, i.e. simultaneously improve population health and quality of care while reducing costs per capita. This study explores how PM initiatives measure the Triple Aim in practice. Method An exploratory search was combined with expert consultations to identify relevant PM initiatives. These were analyzed based on general characteristics, utilized measures and related selection criteria. Results In total 865 measures were used by 20 PM initiatives. All quality of care domains were included by at least 11 PM initiatives, while most domains of population health and costs were included by less than 7 PM initiatives. Although their goals showed substantial overlap, the measures applied showed few similarities between PM initiatives and were predominantly selected based on local priority areas and data availability. Conclusion Most PM initiatives do not measure the full scope of the Triple Aim. Additionally, variety between measures limits comparability between PM initiatives. Consensus on the coverage of Triple Aim domains and a set of standardized measures could further both the inclusion of the various domains as well as the comparability between PM initiatives. Keywords: Population management, Triple Aim, Population health, Quality of care, Costs, Measure