Development of the Patient-Reported Indicator Surveys (PaRIS) conceptual framework to monitor and improve the performance of primary care for people living with chronic conditions.

BackgroundThe Organisation for Economic Co-operation and Development (OECD) Patient-Reported Indicator Surveys (PaRIS) initiative aims to support countries in improving care for people living with chronic conditions by collecting information on how people experience the quality and performance of primary and (generalist) ambulatory care services. This paper presents the development of the conceptual framework that underpins the rationale for and the instrumentation of the PaRIS survey. METHODS: The guidance of an international expert taskforce and the OECD Health Care Quality Indicators framework (2015) provided initial specifications for the framework. Relevant conceptual models and frameworks were then identified from searches in bibliographic databases (Medline, EMBASE and the Health Management Information Consortium). A draft framework was developed through narrative review. The final version was codeveloped following the participation of an international Patient advisory Panel, an international Technical Advisory Community and online international workshops with patient representatives. RESULTS: 85 conceptual models and frameworks were identified through searches. The final framework maps relationships between the following domains (and subdomains): patient-reported outcomes (symptoms, functioning, self-reported health status, health-related quality of life); patient-reported experiences of care (access, comprehensiveness, continuity, coordination, patient safety, person centeredness, self-management support, trust, overall perceived quality of care); health and care capabilities; health behaviours (physical activity, diet, tobacco and alcohol consumption), sociodemographic characteristics and self-reported chronic conditions; delivery system characteristics (clinic, main healthcare professional); health system, policy and context. DISCUSSION: The PaRIS conceptual framework has been developed through a systematic, accountable and inclusive process. It serves as the basis for the development of the indicators and survey instruments as well as for the generation of specific hypotheses to guide the analysis and interpretation of the findings.

Engaging primary care professionals in OECD's international PaRIS survey: a documentary analysis.

Healthcare professionals have first-hand experience with patients in clinical practice and the dynamics in the healthcare system, which can be of great value in the design, implementation, data analysis and dissemination of research study results. Primary care professionals are particularly important as they provide first contact, accessible, coordinated, comprehensive and continuous people-focused care. However, in-depth examination of the engagement of health professionals in health system research and planning activities-how professionals are engaged and how this varies across national contexts- is limited, particularly in international initiatives. There is a need to identify gaps in the planning of engagement activities to inform the design and successful implementation of future international efforts to improve the responsiveness of health systems to the changing needs of patients and professionals. The aim of this study was to explore how primary care professionals were engaged in the design and implementation plans of an international health policy study led by the Organisation for Economic Co-operation and Development (OECD). The OECD's international PaRIS survey measures and disseminates information on patient-reported outcome and experience measures (PROMs and PREMs) of people living with chronic conditions who are managed in primary care. A documentary analysis of 17 written national implementation plans (country roadmaps) was conducted between January and June 2023. Two reviewers independently performed the screening and data abstraction and resolved disagreements by discussion. We reported the intended target primary care professionals, phase of the study, channel of engagement, level of engagement, and purpose of engagement. All 17 countries aimed to engage primary care professionals in the execution plans for the international PaRIS survey. While organisations of primary care professionals, particularly of family doctors, were the most commonly targeted group, variation was found in the timing of engagement activities during the different phases of the study and in the level of engagement, ranging from co-development (half of the countries co-developed the survey together with primary care professionals) to one-off consultations with whom. International guidance facilitated the participation of primary care professionals. Continuous collaborative efforts at the international and national levels can foster a culture of engagement with primary care organisations and individual professionals and enhance meaningful engagement of primary care professionals.

Data analysis plan of the OECD PaRIS survey: leveraging a multi-level approach to analyse data collected from people living with chronic conditions and their primary care practices in 20 countries.

OBJECTIVE: In view of the increasing number of people with (multiple) chronic conditions, the Organisation for Economic Co-operation and Development (OECD) initiated the International Survey of People Living with Chronic Conditions (PaRIS survey), which aims to provide insight in patient-reported outcomes and experiences of chronic care provided by primary care practices to support policy development. The objective of this research note is to describe the structure of the data, collected in the PaRIS survey and how the data will be analysed in a multilevel approach for cross-country comparison. ANALYSIS PLAN: The data structure of the PaRIS survey represents three levels: countries/health systems, primary care practices and patients. Multilevel analysis is used because of its accuracy in estimating country-level outcomes, its flexibility in modelling relationships, and its opportunities in connecting to relevant policy questions. Country-level outcomes will be estimated to facilitate cross-country comparison and (future) within-country comparison over time. Characteristics of patients that potentially explain variation in patient-reported outcomes and experiences can be linked to primary care practice and country/health system characteristics. This makes it possible to address policy-relevant questions relating, e.g., to the impact of chronic care management on patients with a specific chronic condition.

Improving quality and patient safety in surgical care through standardisation and harmonisation of perioperative care (SAFEST project): A research protocol for a mixed methods study.

INTRODUCTION: Adverse events in health care affect 8% to 12% of patients admitted to hospitals in the European Union (EU), with surgical adverse events being the most common types reported. AIM: SAFEST project aims to enhance perioperative care quality and patient safety by establishing and implementing widely supported evidence-based perioperative patient safety practices to reduce surgical adverse events. METHODS: We will conduct a mixed-methods hybrid type III implementation study supporting the development and adoption of evidence-based practices through a Quality Improvement Learning Collaborative (QILC) in co-creation with stakeholders. The project will be conducted in 10 hospitals and related healthcare facilities of 5 European countries. We will assess the level of adherence to the standardised practices, as well as surgical complications incidence, patient-reported outcomes, contextual factors influencing the implementation of the patient safety practices, and sustainability. The project will consist of six components: 1) Development of patient safety standardised practices in perioperative care; 2) Guided self-evaluation of the standardised practices; 3) Identification of priorities and actions plans; 4) Implementation of a QILC strategy; 5) Evaluation of the strategy effectiveness; 6) Patient empowerment for patient safety. Sustainability of the project will be ensured by systematic assessment of sustainability factors and business plans. Towards the end of the project, a call for participation will be launched to allow other hospitals to conduct the self-evaluation of the standardized practices. DISCUSSION: The SAFEST project will promote patient safety standardized practices in the continuum of care for adult patients undergoing surgery. This project will result in a broad implementation of evidence-based practices for perioperative care, spanning from the care provided before hospital admission to post-operative recovery at home or outpatient facilities. Different implementation challenges will be faced in the application of the evidence-based practices, which will be mitigated by developing context-specific implementation strategies. Results will be disseminated in peer-reviewed publications and will be available in an online platform.

Recommendations on self-management interventions for adults living with obesity: COMPAR-EU project.

Self-management interventions (SMIs) may improve disease management in adults living with obesity. We formulated evidence-based recommendations for SMIs within the context of the COMPAR-EU project. The multidisciplinary panel selected critical outcomes based on the COMPAR-EU core outcome set and established decision thresholds for each outcome. Recommendations were informed by systematic reviews of effects, cost-effectiveness, and a contextual assessment. To assess the certainty of the evidence and formulate the recommendations, we used the GRADE approach guidance. Overall, SMIs were deemed to have a small impact, but the absence of harmful effects and potential cumulative benefits indicated a favourable balance of effects, despite low certainty. SMIs showed variations in structure, intensity, and resource utilisation, but overall are likely to be cost-effective. Adapting SMIs to local contexts would enhance equity, acceptability, and feasibility, considering patients' values, and availability of resources and teamwork. Consequently, the panel made conditional recommendations favouring SMIs over usual care. The rigorous and explicit recommendations demonstrated the effectiveness of SMIs for adults living with obesity. However, the gaps in the literature influenced the panel to make only conditional recommendations in favour of SMIs. Further research is needed to strengthen the evidence base and improve recommendations' certainty and applicability.

International cross-cultural development and field testing of the primary care practice questionnaire for the PaRIS survey (PaRIS-PCPQ).

BACKGROUND: The PaRIS survey, an initiative of the Organisation for Economic Co-operation and Development (OECD), aims to assess health systems performance in delivering primary care by measuring the care experiences and outcomes of people over 45 who used primary care services in the past six months. In addition, linked data from primary care practices are collected to analyse how the organisation of primary care practices and their care processes impact care experiences and outcomes. This article describes the development and validation of the primary care practice questionnaire for the PaRIS survey, the PaRIS-PCPQ. METHOD: The PaRIS-PCPQ was developed based on domains of primary care practice and professional characteristics included in the PaRIS conceptual framework. Questionnaire development was conducted in four phases: (1) a multi-step consensus-based development of the source questionnaire, (2) translation of the English source questionnaire into 17 languages, (3) cross-national cognitive testing with primary care professionals in participating countries, and (4) cross-national field-testing. RESULTS: 70 items were selected from 7 existing questionnaires on primary care characteristics, of which 49 were included in a first draft. Feedback from stakeholders resulted in a modified 34-item version (practice profile, care coordination, chronic care management, patient follow-up, and respondent characteristics) designed to be completed online by medical or non-medical staff working in a primary care practice. Cognitive testing led to changes in the source questionnaire as well as to country specific localisations. The resulting 32-item questionnaire was piloted in an online survey and field test. Data from 540 primary care practices from 17 countries were collected and analysed. Final revision resulted in a 34-item questionnaire. CONCLUSIONS: The cross-national development of a primary care practice questionnaire is challenging due to the differences in care delivery systems. Rigorous translation and cognitive testing as well as stakeholder engagement helped to overcome most challenges. The PaRIS-PCPQ will be used to assess how key characteristics of primary care practices relate to the care experiences and outcomes of people living with chronic conditions. As such, policymakers and care providers will be informed about the performance of primary care from the patient's perspective.

COMPAR-EU Recommendations on Self-Management Interventions in Type 2 Diabetes Mellitus.

Self-management interventions (SMIs) offer a promising approach to actively engage patients in the management of their chronic diseases. Within the scope of the COMPAR-EU project, our goal is to provide evidence-based recommendations for the utilisation and implementation of SMIs in the care of adult individuals with type 2 diabetes mellitus (T2DM). A multidisciplinary panel of experts, utilising a core outcome set (COS), identified critical outcomes and established effect thresholds for each outcome. The panel formulated recommendations using the Grading of Recommendations, Assessment, Development, and Evaluations (GRADE) approach, a transparent and rigorous framework for developing and presenting the best available evidence for the formulation of recommendations. All recommendations are based on systematic reviews (SR) of the effects and of values and preferences, a contextual analysis, and a cost-effectiveness analysis. The COMPAR-EU panel is in favour of using SMIs rather than usual care (UC) alone (conditional, very low certainty of the evidence). Furthermore, the panel specifically is in favour of using ten selected SMIs, rather than UC alone (conditional, low certainty of the evidence), mostly encompassing education, self-monitoring, and behavioural techniques. The panel acknowledges that, for most SMIs, moderate resource requirements exist, and cost-effectiveness analyses do not distinctly favour either the SMI or UC. Additionally, it recognises that SMIs are likely to enhance equity, deeming them acceptable and feasible for implementation.

Effectiveness and Cost-Effectiveness of Self-Management Interventions for Adults Living with Heart Failure to Improve Patient-Important Outcomes: An Evidence Map of Randomized Controlled Trials.

Self-management interventions (SMIs) may enhance heart failure (HF) outcomes and address challenges associated with disease management. This study aims to review randomized evidence and identify knowledge gaps in SMIs for adult HF patients. Within the COMPAR-EU project, from 2010 to 2018, we conducted searches in the databases MEDLINE, CINAHL, Embase, Cochrane, and PsycINFO. We performed a descriptive analysis using predefined categories and developed an evidence map of randomized controlled trials (RCTs). We found 282 RCTs examining SMIs for HF patients, comparing two to four interventions, primarily targeting individual patients (97%) globally (34 countries, only 31% from an European country). These interventions involved support techniques such as information sharing (95%) and self-monitoring (62%), often through a mix of in-person and remote sessions (43%). Commonly assessed outcomes included quality of life, hospital admissions, mortality, exercise capacity, and self-efficacy. Few studies have focused on lower socio-economic or minority groups. Nurses (68%) and physicians (30%) were the primary providers, and most studies were at low risk of bias in generating a random sequence for participant allocation; however, the reporting was noticeably unclear of methods used to conceal the allocation process. Our analysis has revealed prevalent support techniques and delivery methods while highlighting methodological challenges. These findings provide valuable insights for researchers, clinicians, and policymakers striving to optimize SMIs for individuals living with HF.

Contextual factors for the successful implementation of self-management interventions for chronic diseases: A qualitative review of reviews.

OBJECTIVES: To identify and describe the most relevant contextual factors (CFs) from the literature that influence the successful implementation of self-management interventions (SMIs) for patients living with type 2 diabetes mellitus, obesity, COPD and/or heart failure. METHODS: We conducted a qualitative review of reviews. Four databases were searched, 929 reviews were identified, 460 screened and 61 reviews met the inclusion criteria. CFs in this paper are categorized according to the Tailored Implementation for Chronic Diseases framework. RESULTS: A great variety of CFs was identified on several levels, across all four chronic diseases. Most CFs were on the level of the patient, the professional and the interaction level, while less CFs were obtained on the level of the intervention, organization, setting and national level. No differences in main themes of CFs across all four diseases were found. DISCUSSION: For the successful implementation of SMIs, it is crucial to take CFs on several levels into account simultaneously. Person-centered care, by tailoring SMIs to patients' needs and circumstances, may increase the successful uptake, application and implementation of SMIs in real-life practice. The next step will be to identify the most important CFs according to various stakeholders through a group consensus process.

Self-Management Interventions for Adults Living with Type II Diabetes to Improve Patient-Important Outcomes: An Evidence Map.

Self-management interventions (SMIs) may be promising in the treatment of Diabetes Mellitus Type 2 (T2DM). However, accurate comparisons of their relative effectiveness are challenging, partly due to a lack of clarity and detail regarding the intervention content being evaluated. This study summarizes intervention components and characteristics in randomized controlled trials (RCTs) related to T2DM using a taxonomy for SMIs as a framework and identifies components that are insufficiently incorporated into the design of the intervention or insufficiently reported. Following evidence mapping methodology, we searched MEDLINE, CINAHL, Embase, Cochrane, and PsycINFO from 2010 to 2018 for randomized controlled trials (RCTs) on SMIs for T2DM. We used the terms 'self-management', 'adult' and 'T2DM' for content. For data extraction, we used an online platform based on the taxonomy for SMIs. Two independent reviewers assessed eligible references; one reviewer extracted data, and a second checked accuracy. We identified 665 RCTs for SMIs (34% US, 21% Europe) including 164,437 (median 123, range 10-14,559) adults with T2DM. SMIs highly differed in design and content, and characteristics such as mode of delivery, intensity, location and providers involved were poorly described. The majority of interventions aimed to improve clinical outcomes like HbA1c (83%), weight (53%), lipid profile (45%) or blood pressure (42%); 27% (also) targeted quality of life. Improved knowledge, health literacy, patient activation or satisfaction with care were hardly used as outcomes (<16%). SMIs most often used education (98%), self-monitoring (56%), goal-setting (48%) and skills training (42%) to improve outcomes. Management of emotions (17%) and shared decision-making (5%) were almost never mentioned. Although diabetes is highly prevalent in some minority groups, in only 13% of the SMIs, these groups were included. Our findings highlight the large heterogeneity that exists in the design of SMIs for T2DM and the way studies are reported, making accurate comparisons of their relative effectiveness challenging. In addition, SMIs pay limited attention to outcomes other than clinical, despite the importance attached to these outcomes by patients. More standardized and streamlined research is needed to better understand the effectiveness and cost-effectiveness of SMIs of T2DM and benefit patient care.

Can peer effects explain prescribing appropriateness? a social network analysis.

BACKGROUND: Optimizing prescribing practices is important due to the substantial clinical and financial costs of polypharmacy and an increasingly aging population. Prior research shows the importance of social relationships in driving prescribing behaviour. Using social network analysis, we examine the relationship between a physician practices' connectedness to peers and their prescribing performance in two German regions. METHODS: We first mapped physician practice networks using links established between two practices that share 8 or more patients; we calculated network-level (density, average path length) and node-level measures (degree, betweenness, eigenvector). We defined prescribing performance as the total number of inappropriate medications prescribed or appropriate medications not prescribed (PIMs) to senior patients (over the age of 65) during the calendar year 2016. We used FORTA (Fit fOR The Aged) algorithm to classify medication appropriateness. Negative binomial regression models estimate the association between node-level measures and prescribing performance of physician practices controlling for patient comorbidity, provider specialization, percentage of seniors in practice, and region. We conducted two sensitivity analyses to test the robustness of our findings - i) limiting the network mapping to patients younger than 65; ii) limiting the network ties to practices that share more than 25 patients. RESULTS: We mapped two patient-sharing networks including 436 and 270 physician practices involving 28,508 and 20,935 patients and consisting of 217,126 and 154,274 claims in the two regions respectively. Regression analyses showed a practice's network connectedness as represented by degree, betweenness, and eigenvector centrality, is significantly negatively associated with prescribing performance (degree-bottom vs. top quartile aRR = 0.04, 95%CI: 0.035,0.045; betweenness-bottom vs. top quartile aRR = 0.063 95%CI: 0.052,0.077; eigenvector-bottom vs. top quartile aRR = 0.039, 95%CI: 0.034,0.044). CONCLUSIONS: Our study provides evidence that physician practice prescribing performance is associated with their peer connections and position within their network. We conclude that practices occupying strategic positions at the edge of networks with advantageous access to novel information are associated with better prescribing outcomes, whereas highly connected practices embedded in insulated information environments are associated with poor prescribing performance.

Identifying Factors to Facilitate the Implementation of Decision-Making Tools to Promote Self-Management of Chronic Diseases into Routine Healthcare Practice: A Qualitative Study.

This study, as part of the COMPAR-EU project, utilized a mixed-methods approach involving 37 individual, semi-structured interviews and one focus group with 7 participants to investigate the factors influencing the implementation and use of self-management interventions (SMIs) decision tools in clinical practice. The interviews and focus group discussions were guided by a tailored interview and focus group guideline developed based on the Tailored Implementation for Chronic Diseases (TICD) framework. The data were analyzed using a directed qualitative content analysis, with a deductive coding system based on the TICD framework and an inductive coding process. A rapid analysis technique was employed to summarize and synthesize the findings. The study identified five main dimensions and facilitators for implementation: decision tool factors, individual health professional factors, interaction factors, organizational factors, and social, political, and legal factors. The findings highlight the importance of structured implementation through SMI decision support tools, emphasizing the need to understand their benefits, secure organizational resources, and gain political support for sustainable implementation. Overall, this study employed a systematic approach, combining qualitative methods and comprehensive analysis, to gain insights into the factors influencing the implementation of SMIs' decision-support tools in clinical practice.

Patients' and informal caregivers' perspectives on self-management interventions for type 2 diabetes mellitus outcomes: a mixed-methods overview of 14 years of reviews.

BACKGROUND: Self-management interventions (SMIs) are core components of high-quality care in type 2 diabetes mellitus (T2DM). We aimed to identify and summarise the scientific evidence exploring the perspectives of patients with T2DM and their informal caregivers on outcomes of SMIs, and the key themes to enhance T2DM patient-centred care. METHODS: We conducted a mixed-methods overview of reviews. We searched MEDLINE, CINAHL and PsycINFO, up to June 2021 for systematic reviews (SRs) exploring the perspectives of adults with T2DM and their informal caregivers, regarding self-management. Two reviewers conducted independently study selection, data extraction and quality assessment. We estimated the degree of overlap across SRs. We performed a qualitative analysis using a thematic synthesis approach. RESULTS: We identified 54 SRs, corresponding to 939 studies, with a slight overlap. Most SRs (47/54, 87%) were considered high quality. We developed summaries for 22 outcomes and identified six overarching themes: (1) diabetic identity; (2) accessing healthcare; (3) experience of care; (4) engagement with self-management; (5) outcomes awareness; and (6) challenges adhering to self-management. We found important variability in how patients with T2DM and their informal caregivers value critical outcomes influenced by the disease progression and several contextual factors. CONCLUSIONS: Our findings represent what matters most to patients with T2DM and their informal caregivers regarding outcomes of SMIs. Our results can facilitate the development and evaluation of SMIs, and guide decision-making in diabetes care, including the formulation of decisions and recommendations.

Cooperation Improvement in an Integrated Healthcare Network: A Social Network Analysis.

Background: Cooperation is a core feature of integrated healthcare systems and an important link in their value-creating mechanism. The premise is that providers who cooperate can promote more efficient use of health services while improving health outcomes. We studied the performance of an integrated healthcare system in improving regional cooperation. Methods: Using claims data and social network analysis, we constructed the professional network from 2004 to 2017. Cooperation was studied by analyzing the evolution of network properties at network and physician practice (node) level. The impact of the integrated system was studied with a dynamic panel model that compared practices that participated in the integrated system versus nonparticipants. Results: The regional network evolved favourably towards cooperation. Network density increased 1.4% on average per year, while mean distance decreased 0.78%. At the same time, practices participating in the integrated system became more cooperative compared to other practices in the region: Degree (1.64e-03, p = 0.07), eigenvector (3.27e-03, p = 0.06) and betweenness (4.56e-03, p < 0.001) centrality increased more for participating practices. Discussion: Findings can be explained by the holistic approach to patients' care needs and coordination efforts of integrated healthcare. The paper provides a valuable design for performance assessment of professional cooperation. Highlights: Using claims data and social network analysis, we identify a regional cooperation network and conduct a panel analysis to measure the impact of an integrated care initiative on enhancing professional cooperation.Physician practices participating in the integrated system became more cooperative and improved their influence in the regional network more than non-participating practices.Integrated healthcare systems effectively incentivize cooperation through a holistic approach to patient care needs and coordination efforts.

Identifying most important contextual factors for the implementation of self-management interventions: A Delphi study.

OBJECTIVE: To reach consensus amongst stakeholders about the most important contextual factors (CFs) that may influence the successful implementation of (components of) self-management interventions (SMIs) for type 2 diabetes, obesity, COPD and heart failure. METHODS: Building on our literature review that identified 31 CFs on different levels we conducted a Delphi with 44 stakeholders to identify which of these CFs, or additional ones, contribute most to successful implementation of SMIs. The Delphi consisted of three rounds in which the CFs were scored, prioritized and discussed. RESULTS: The most important CFs overlapped to a great extent across components of SMIs and diseases. Overall, stakeholders identified 'HCP's ability to adapt the advice, communication or intervention to patients' situation and level of knowledge' as most important CF. CONCLUSION: CFs need to be taken into account when implementing promising SMIs. According to stakeholders, the most important CFs are patient-, HCP- or interaction related. 'Tailoring' was selected as the most crucial aspect for HCPs. PRACTICE IMPLICATIONS: Stakeholders can make informed decisions on the adoption of the most suitable SMIs in a given context. These CFs are available through a self-management platform. Suggestions to implement self-management behaviour and to close the research-to-practice gap are made.

Improving the evaluation of an integrated healthcare system using entropy balancing: Population health improvements in Gesundes Kinzigtal.

Background: Evidence of integrated healthcare networks' effect on population health is scarce. Moreover, current designs for evaluating such networks have shortcomings that can result in misleading conclusions. Our paper evaluates Gesundes Kinzigtal, a best-practice integrated healthcare network, using an innovative design that enlightens the discussion about health gains produced by integrated healthcare. Research question: What is the effect of Gesundes Kinzigtal on population health? Methods: We evaluated the effect of the integrated healthcare initiative by performing a quasi-experimental evaluation based on entropy balancing. Integrated network participants were compared to a control group and followed for five years. Claims data from 2004 to 2018 was used. Population health outcomes correspond to survival (Cox hazard ratio, Kaplan-Meier curve), mortality ratio, mean age at the time of death, and years of life lost or gained. Design validity was evaluated by assessing group balance at baseline. Finally, we compared our results to those obtained using a previously published design for evaluating integrated networks. Results: The treatment group was composed of 9083 network participants, compared to an equivalent control group, showing, respectively, a mortality ratio of 5.4% vs 7.5% (p < 0.05), mean age at the time of death of 80.1 vs 80.3 (p > 0.05) and a gain of 0.2 years of life per person for the treatment group (p > 0.05). The Cox hazard ratio (0.72; p < 0.05) and mean survival time (1784 vs 1768 days; p < 0.05) showed better survival for treated participants. Results using the previously published design were more favorable for the treatment group; however, the design excluded participants significantly associated with greater healthcare needs. Discussion: The integrated network had a favorable effect on participants' mortality and survival risk. Previous evaluations based on propensity score matching might overestimate the network's impact on population health by excluding participants with greater healthcare needs.

Big Data Analytics to Reduce Preventable Hospitalizations-Using Real-World Data to Predict Ambulatory Care-Sensitive Conditions.

The purpose of this study was to develop a prediction model to identify individuals and populations with a high risk of being hospitalized due to an ambulatory care-sensitive condition who might benefit from preventative actions or tailored treatment options to avoid subsequent hospital admission. A rate of 4.8% of all individuals observed had an ambulatory care-sensitive hospitalization in 2019 and 6389.3 hospital cases per 100,000 individuals could be observed. Based on real-world claims data, the predictive performance was compared between a machine learning model (Random Forest) and a statistical logistic regression model. One result was that both models achieve a generally comparable performance with c-values above 0.75, whereas the Random Forest model reached slightly higher c-values. The prediction models developed in this study reached c-values comparable to existing study results of prediction models for (avoidable) hospitalization from the literature. The prediction models were designed in such a way that they can support integrated care or public and population health interventions with little effort with an additional risk assessment tool in the case of availability of claims data. For the regions analyzed, the logistic regression revealed that switching to a higher age class or to a higher level of long-term care and unit from prior hospitalizations (all-cause and due to an ambulatory care-sensitive condition) increases the odds of having an ambulatory care-sensitive hospitalization in the upcoming year. This is also true for patients with prior diagnoses from the diagnosis groups of maternal disorders related to pregnancy, mental disorders due to alcohol/opioids, alcoholic liver disease and certain diseases of the circulatory system. Further model refinement activities and the integration of additional data, such as behavioral, social or environmental data would improve both model performance and the individual risk scores. The implementation of risk scores identifying populations potentially benefitting from public health and population health activities would be the next step to enable an evaluation of whether ambulatory care-sensitive hospitalizations can be prevented.

Self-management interventions for adults living with obesity to improve patient-relevant outcomes: An evidence map.

OBJECTIVES: To conduct an evidence map on self-management interventions and patient-relevant outcomes for adults living with overweight/obesity. METHODS: Following Arksey and O'Malley methodology, we searched in five electronical databases including randomized controlled trials (RCTs) on SMIs for overweight/obesity. We used the terms "self-management", "adult" and "obesity" for content. Two independent reviewers assessed eligible references; one reviewer extracted data, a second checked accuracy. RESULTS: We identified 497 RCTs (58% US, 20% Europe) including 99,741 (median 112, range 11-5145) adults living with overweight/obesity. Most research evaluated clinical outcomes (617, 55%) and behaviors adherence (255, 23%). Empowerment skills, quality of life and satisfaction were less targeted (8%, 7%, 0.2%, respectively). The most frequent techniques included sharing information (858, 99%), goal setting (619, 72%) and self-monitoring training (614, 71%), provided face-to-face (386, 45%) or in combination with remote techniques (256, 30%). Emotional management, social support and shared-decision were less frequent (18%, 26%, 4%). Socio-economic status, minorities or health literacy were seldom reported. CONCLUSION: There is a need of widening the scope of research by focusing on outcomes important to patients, assessing emotional/social/share-decision support, exploring remote techniques and including vulnerable populations.

Assessment of the Effectiveness, Socio-Economic Impact and Implementation of a Digital Solution for Patients with Advanced Chronic Diseases: The ADLIFE Study Protocol.

Due to population ageing and medical advances, people with advanced chronic diseases (ACD) live longer. Such patients are even more likely to face either temporary or permanent reduced functional reserve, which typically further increases their healthcare resource use and the burden of care on their caregiver(s). Accordingly, these patients and their caregiver(s) may benefit from integrated supportive care provided via digitally supported interventions. This approach may either maintain or improve their quality of life, increase their independence, and optimize the healthcare resource use from early stages. ADLIFE is an EU-funded project, aiming to improve the quality of life of older people with ACD by providing integrated personalized care via a digitally enabled toolbox. Indeed, the ADLIFE toolbox is a digital solution which provides patients, caregivers, and health professionals with digitally enabled, integrated, and personalized care, supporting clinical decisions, and encouraging independence and self-management. Here we present the protocol of the ADLIFE study, which is designed to provide robust scientific evidence on the assessment of the effectiveness, socio-economic, implementation, and technology acceptance aspects of the ADLIFE intervention compared to the current standard of care (SoC) when applied in real-life settings of seven different pilot sites across six countries. A quasi-experimental trial following a multicenter, non-randomized, non-concurrent, unblinded, and controlled design will be implemented. Patients in the intervention group will receive the ADLIFE intervention, while patients in the control group will receive SoC. The assessment of the ADLIFE intervention will be conducted using a mixed-methods approach.

The application of machine learning to predict high-cost patients: A performance-comparison of different models using healthcare claims data.

Our aim was to predict future high-cost patients with machine learning using healthcare claims data. We applied a random forest (RF), a gradient boosting machine (GBM), an artificial neural network (ANN) and a logistic regression (LR) to predict high-cost patients in the following year. Therefore, we exploited routinely collected sickness funds claims and cost data of the years 2016, 2017 and 2018. Various specifications of each algorithm were trained and cross-validated on training data (n = 20,984) with claims and cost data from 2016 and outcomes from 2017. The best performing specifications of each algorithm were selected based on validation dataset performance. For performance comparison, selected models were applied to unforeseen data with features of the year 2017 and outcomes of the year 2018 (n = 21,146). The RF was the best performing algorithm measured by the area under the receiver operating curve (AUC) with a value of 0.883 (95% confidence interval (CI): 0.872-0.893) on test data, followed by the GBM (AUC = 0.878; 95% CI: 0.867-0.889). The ANN (AUC = 0.846; 95% CI: 0.834-0.857) and LR (AUC = 0.839; 95% CI: 0.826-0.852) were significantly outperformed by the GBM and the RF. All ML algorithms and the LR performed ´good´ (i.e. 0.9 > AUC ≥ 0.8). We were able to develop machine learning models that predict high-cost patients with 'good' performance facilitating routinely collected sickness fund claims and cost data. We found that tree-based models performed best and outperformed the ANN and LR.