Hanneke W. Drewes

Background: Working toward a healthy living environment requires organizations from different policy domains and nongovernment partners involved in public health and the living environment to collaborate across sectors. The aim of this study is to understand how this cross-sector collaboration for a healthy living environment can be achieved. Methods: The realist evaluation approach was used to investigate what strategies can be used in which contexts to achieve cross-sector collaboration. The “Collaborative Adaptive Health Networks” framework was used as a theoretical framework. Seventeen partners of three Dutch projects collaborating for a healthy living environment in different regions were interviewed about their experiences during the initiating phase of their projects. Results: Seven themes for achieving cross-sector collaboration were identified, namely creating a feeling of equivalence, building trust, bridging different perspectives, providing clarity regarding roles and tasks, creating commitment, creating active engagement, and understanding whom to engage and when. For each theme, the strategies that were used, and why, were specified. Conclusion: This study provides new insights in how cross-sector collaboration for a healthy living environment can be achieved in different contexts. Whether the start of a cross-sectoral collaboration is successful is largely influenced by the choice of leadership and the interorganizational relations.

Background: Community engagement is increasingly seen as key to improving healthcare systems and to increasing communities’ involvement in the shaping of their own communities. This paper describes how ‘community engagement’ (CE) is understood and being operationalised in the Dutch healthcare system by investigating the CE approaches being implemented in six different regions and by examining engaged citizens’ and professionals’ experiences of those CE approaches. Methods: For this realist study, interviews and focus groups were held with citizens (16) and professionals (42) involved in CE approaches in the six regions. Additionally, CE-related activities were observed to supplement interview data. Results: This study shows that citizens and professionals defined and experienced CE differently and that they differed in who they felt had ownership of CE. The CE approaches implemented in community-led initiatives and organisationally-led initiatives varied accordingly. Furthermore, both citizens and professionals were searching for meaningful ways for citizens to have more control over healthcare in their own communities. Conclusion: CE can be improved by, first of all, developing a shared and overarching vision of what CE should look like, establishing clear roles and remits for organisations and communities, and taking active measures to ensure CE is more inclusive and representative of harder-to-reach groups. At the same time, to help ensure such shared visions do not further entrench power imbalances between citizens and professionals, professionals require training in successful CE approaches.

Background: Regional population management (PM) health initiatives require insight into experienced quality of care at the regional level. Unsolicited online provider ratings have shown potential for this use. This study explored the addition of comments accompanying unsolicited online ratings to regional analyses. Objective: The goal was to create additional insight for each PM initiative as well as overall comparisons between these initiatives by attempting to determine the reasoning and rationale behind a rating. Methods: The Dutch Zorgkaart database provided the unsolicited ratings from 2008 to 2017 for the analyses. All ratings included both quantitative ratings as well as qualitative text comments. Nine PM regions were used to aggregate ratings geographically. Sentiment analyses were performed by categorizing ratings into negative, neutral, and positive ratings. Per category, as well as per PM initiative, word frequencies (ie, unigrams and bigrams) were explored. Machine learning—naïve Bayes and random forest models—was applied to identify the most important predictors for rating overall sentiment and for identifying PM initiatives. Results: A total of 449,263 unsolicited ratings were available in the Zorgkaart database: 303,930 positive ratings, 97,739 neutral ratings, and 47,592 negative ratings. Bigrams illustrated that feeling like not being “taken seriously” was the dominant bigram in negative ratings, while bigrams in positive ratings were mostly related to listening, explaining, and perceived knowledge. Comparing bigrams between PM initiatives showed a lot of overlap but several differences were identified. Machine learning was able to predict sentiments of comments but was unable to distinguish between specific PM initiatives. Conclusions: Adding information from text comments that accompany online ratings to regional evaluations provides insight for PM initiatives into the underlying reasons for ratings. Text comments provide useful overarching information for health care policy makers but due to a lot of overlap, they add little region-specific information. Specific outliers for some PM initiatives are insightful.

Background: Within Population Health Management (PHM) initiatives, stakeholders from various sectors apply PHM strategies, via which services are reorganised and integrated in order to improve population health and quality of care while reducing cost growth. This study unravelled how stakeholders’ expectations and prior experiences influenced stakeholders intended PHM strategies. Methods: This study used realist principles. Nine Dutch PHM initiatives participated. Seventy stakeholders (mainly executive level) from seven different stakeholder groups (healthcare insurers, hospitals, primary care groups, municipalities, patient representative organisations, regional businesses and program managers of the PHM initiatives) were interviewed. Associations between expectations, prior experiences and intended strategies of the various stakeholder groups were identified through analyses of the interviews. Results: Stakeholders’ expectations, their underlying explanations and intended strategies could be categorized into four themes: 1. Regional collaboration; 2. Governance structures and stakeholder roles; 3. Regional learning environments, and 4. Financial and regulative conditions. Stakeholders agreed on the long-term expectations of PHM development. Differences in short- and middle-term expectations, and prior experiences were identified between stakeholder groups and within the stakeholder group healthcare insurers. These differences influenced stakeholders’ intended strategies. For instance, healthcare insurers that intended to stay close to the business of care had encountered barriers in pushing PHM e.g. lack of data insight, and expected that staying in control of the purchasing process was the best way to achieve value for money. Healthcare insurers that were more keen to invest in experiments with data-technology, new forms of payment and accountability had encountered positive experiences in establishing regional responsibility and expected this to be a strong driver for establishing improvements in regional health and a vital and economic competitive region. Conclusion: This is the first study that revealed insight into the differences and similarities between stakeholder groups’ expectations, experiences and intended strategies. These insights can be used to improve the pivotal cooperation within and between stakeholder groups for PHM.

Population health perspectives increasingly focus on people's perception of resilience, ability to adapt and self-manage. The goal of this study is to determine whether the MijnKwaliteitVanLeven.nl ("MyQualityOfLife.nl") survey is a valid and reliable instrument for assessing the broader health perspectives at population level. 19,809 entries of the MyQualityOfLife.nl survey were used. To assess face validity, Huber's six dimensions of positive health were used as a framework for expert feedback. A confirmative factor analyses was done using the expert's item clustering, followed by data-driven explorative factor analyses and reliability tests. Experts distributed 74 of the 118 items over all six dimensions of positive health. The confirmatory factor analysis model based on expert classification was not confirmed. The subsequent exploratory factor analysis excluded most items based on factor loading and suggested two factors; 'quality of life' and 'daily functioning', both showing excellent reliability. The MyQualityOfLife.nl survey can assess the broader concept of health in a population as well as 'quality of life' and 'daily functioning'. However, the survey can currently not evaluate several of the positive health dimensions separately. Further research is needed to determine whether this is due to the instrument or the positive health dimensions.

BACKGROUND Regional population management (PM) health initiatives require insight into experienced quality of care at the regional level. Unsolicited online provider ratings have shown potential for this use. This study explored the addition of comments accompanying unsolicited online ratings to regional analyses. OBJECTIVE The goal was to create additional insight for each PM initiative as well as overall comparisons between these initiatives by attempting to determine the reasoning and rationale behind a rating. METHODS The Dutch Zorgkaart database provided the unsolicited ratings from 2008 to 2017 for the analyses. All ratings included both quantitative ratings as well as qualitative text comments. Nine PM regions were used to aggregate ratings geographically. Sentiment analyses were performed by categorizing ratings into negative, neutral, and positive ratings. Per category, as well as per PM initiative, word frequencies (ie, unigrams and bigrams) were explored. Machine learning—naïve Bayes and random forest models—was applied to identify the most important predictors for rating overall sentiment and for identifying PM initiatives. RESULTS A total of 449,263 unsolicited ratings were available in the Zorgkaart database: 303,930 positive ratings, 97,739 neutral ratings, and 47,592 negative ratings. Bigrams illustrated that feeling like not being “taken seriously” was the dominant bigram in negative ratings, while bigrams in positive ratings were mostly related to listening, explaining, and perceived knowledge. Comparing bigrams between PM initiatives showed a lot of overlap but several differences were identified. Machine learning was able to predict sentiments of comments but was unable to distinguish between specific PM initiatives. CONCLUSIONS Adding information from text comments that accompany online ratings to regional evaluations provides insight for PM initiatives into the underlying reasons for ratings. Text comments provide useful overarching information for health care policy makers but due to a lot of overlap, they add little region-specific information. Specific outliers for some PM initiatives are insightful.

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. Unsolicited online ratings from the Dutch website Zorgkaart Nederland (year = 2008–2017) were used. Patients rated their care providers on six dimensions from 1 to 10 and these ratings were geographically aggregated based on nine PHM regions. Distributions were explored between regions. Multilevel analyses per provider category, which produced Intraclass Correlation Coefficients (ICC), were performed to determine clustering of ratings of providers located within regions. If ratings were clustered, then this would indicate that differences found between regions could be attributed to regional characteristics (e.g. demographics or regional policy). In the nine regions, 70,889 ratings covering 4100 care providers were available. Overall, average regional scores (range = 8.3–8.6) showed significant albeit small differences. Multilevel analyses indicated little clustering between unsolicited provider ratings within regions, as the regional level ICCs were low (ICC pioneer site < 0.01). At the provider level, all ICCs were above 0.11, which showed that ratings were clustered. Unsolicited online provider-based ratings are able to discern (small) differences between regions, similar to solicited data. However, these differences could not be attributed to the regional level, making unsolicited ratings not useful for overall regional policy evaluations. At the provider level, ratings can be used by regions to identify under-performing providers within their regions.

Community engagement is increasingly seen as crucial to achieving high quality, efficient and collaborative care. However, organisations are still searching for the best and most effective ways to engage citizens in the shaping of health and care services. This review highlights the barriers and enablers for engaging communities in the planning, designing, governing, and/or delivering of health and care services on the macro or meso level. It provides policymakers and professionals with evidence-based guiding principles to implement their own effective community engagement (CE) strategies. A Rapid Realist Review was conducted to investigate how interventions interact with contexts and mechanisms to influence the effectiveness of CE. A local reference panel, consisting of health and care professionals and experts, assisted in the development of the research questions and search strategy. The panel’s input helped to refine the review’s findings. A systematic search of the peer-reviewed literature was conducted. Eight action-oriented guiding principles were identified: An especially important thread throughout the CE literature is the influence of power imbalances and organisations’ willingness, or not, to address such imbalances. The literature suggests that ‘meaningful participation’ of citizens can only be achieved if organisational processes are adapted to ensure that they are inclusive, accessible and supportive of citizens.