Identifying client characteristics to predict homecare use more accurately: a Delphi-study involving nurses and homecare purchasing specialists.

BACKGROUND: Case-mix based prospective payment of homecare is being implemented in several countries to work towards more efficient and client-centred homecare. However, existing models can only explain a limited part of variance in homecare use, due to their reliance on health- and function-related client data. It is unclear which predictors could improve predictive power of existing case-mix models. The aim of this study was therefore to identify relevant predictors of homecare use by utilizing the expertise of district nurses and health insurers. METHODS: We conducted a two-round Delphi-study according to the RAND/UCLA Appropriateness Method. In the first round, participants assessed the relevance of eleven client characteristics that are commonly included in existing case-mix models for predicting homecare use, using a 9-Point Likert scale. Furthermore, participants were also allowed to suggest missing characteristics that they considered relevant. These items were grouped and a selection of the most relevant items was made. In the second round, after an expert panel meeting, participants re-assessed relevance of pre-existing characteristics that were assessed uncertain and of eleven suggested client characteristics. In both rounds, median and inter-quartile ranges were calculated to determine relevance. RESULTS: Twenty-two participants (16 district nurses and 6 insurers) suggested 53 unique client characteristics (grouped from 142 characteristics initially). In the second round, relevance of the client characteristics was assessed by 12 nurses and 5 health insurers. Of a total of 22 characteristics, 10 client characteristics were assessed as being relevant and 12 as uncertain. None was found irrelevant for predicting homecare use. Most of the client characteristics from the category 'Daily functioning' were assessed as uncertain. Client characteristics in other categories - i.e. 'Physical health status', 'Mental health status and behaviour', 'Health literacy', 'Social environment and network', and 'Other' - were more frequently considered relevant. CONCLUSION: According to district nurses and health insurers, homecare use could be predicted better by including other more holistic predictors in case-mix classification, such as on mental functioning and social network. The challenge remains, however, to operationalize the new characteristics and keep stakeholders on board when developing and implementing case-mix classification for homecare prospective payment.

First Things First: How to Elicit the Initial Program Theory for a Realist Evaluation of Complex Integrated Care Programs.

Policy Points Realist evaluation (RE) is an emerging and promising research approach for evaluating integrated care, addressing what works, how, for whom, and in what circumstances. The rich philosophical foundation of RE, critical realism, can help to systematically unravel an integrated care program's initial theory prior to implementation, as a first step within RE. RE can be considered a robust methodological asset in integrated care research by facilitating a deeper level of insight into program functioning than traditional forms of evaluation do and by shaping a realist-informed monitoring and evaluation process. CONTEXT: The complexity of integrated care and the need for transferable evaluation insights ask for a suitable evaluation paradigm. Realist evaluation (RE), underpinned by the philosophy of critical realism, is a theory-driven approach that addresses what works, how, for whom, and in what circumstances. The current study illustrates the process needed for RE's first step: eliciting the initial program theory (IPT). The TARGET program, a Dutch primary care initiative to facilitate more integrated care for chronically ill patients, i.e., care that is efficient, tailored, and holistic,  was taken as a real-world case. METHODS: An RE approach informed the phased IPT elicitation: (1) identifying an abstract theory framework; (2) formulating the preliminary IPT, building on the abstract theory and informed by previous scientific studies that underpin TARGET; and (3) refining the preliminary IPT, informed by RE expert interviews (n = 7). An RE heuristic tool, specifying the interplay between intervention-context-actors-mechanisms-outcomes (ICAMO) and retroductive reasoning, was applied to synthesize the underlying theory of individual TARGET components into TARGET's IPT. FINDINGS: Separate but related IPTs were identified for the two main types of actors involved in TARGET: primary care professionals (PCPs) and patients. For both actors, two sorts of mechanisms are assumed to be activated by TARGET, which-via instrumental outcomes-contribute to long-term quadruple aim targets. The first is confidence to enhance PCPs' person-centered conversational skills and to increase patients' active engagement in TARGET. The second is mutual trust, between PCPs and patients and between PCPs and their network partners. A supportive context is assumed crucial for activating these mechanisms-for example, sufficient resources to invest in integrated care. CONCLUSIONS: Although the IPT elicitation process is time intensive and requires a mind shift, it facilitates a deeper insight into program functioning than accommodated by the prevailing experimental designs in integrated care. Furthermore, the design of a realist-informed evaluation process can be informed by the IPT.

The Patient Centered Assessment Method (PCAM) for Action-Based Biopsychosocial Evaluation of Patient Needs: Validation and Perceived Value of the Dutch Translation.

The Patient Centered Assessment Method (PCAM) is an action-based tool that supports professionals to engage in a biopsychosocial assessment with patients and measure their needs. It is a promising tool for person-centered care. As the Netherlands lacks such a tool, a Dutch version was developed. Furthermore, we aimed to contribute to the relatively limited insights into the psychometric properties and value of the tool when used as part of a needs assessment in primary care. Confirmatory factor analysis was used to study construct validity and Cronbach's alpha was computed to assess reliability. Furthermore, we interviewed 15 primary care professionals who used the PCAM. It was confirmed that each PCAM domain measures a separate construct, informed by the biopsychosocial model. The tool showed adequate reliability (Cronbach's alpha = 0.83). Despite face validity concerns, the tool was mainly valued for measurement of patient needs and to facilitate action planning. Criticism of the PCAM pertained to a limited focus on the patient perspective, which is one of the crucial aspects of person-centered care. These rich, mixed-method insights can help to improve the value of the PCAM, as one of the few multifunctional tools to support professionals in holistic assessments.

Person-centred and efficient care delivery for high-need, high-cost patients: primary care professionals' experiences.

BACKGROUND: High-need, high-cost (HNHC) patients, who typically have complex and long-term care demands, contribute considerably to the high work pressure of primary care professionals (PCPs). To improve patient as well as provider experiences, it is crucial to take into account the PCPs' perspective in designing health care strategies for HNHC patients. Therefore, this study aimed to create insight into PCPs' experienced barriers and possible solutions with regards to person-centred, efficient care delivery to HNHC patients. METHODS: We conducted a qualitative study using focus group interviews with PCPs at a Dutch primary care group. A semi-structured interview guide was developed for the interviews. Qualitative content analysis was employed deductively by means of a categorisation matrix. The matrix was based on the components retrieved from the SELFIE framework for integrated care for multi-morbidity. RESULTS: Forty-two PCPs participated in five focus group interviews. Discussed barriers and solutions were related to the core of the SELFIE framework (i.e. the individual and environment), and particularly four of the six health system components in the framework: service delivery, leadership & governance, workforce, and technologies & medical products. Many discussed barriers revolved around the complex biopsychosocial needs of HNHC patients: PCPs reported a lack of time (service delivery), insufficiently skilled PCPs (workforce), and inefficient patient information retrieval and sharing (technologies & medical products) as barriers to adequately meet the biopsychosocial needs of HNHC patients. CONCLUSIONS: This qualitative study suggests that primary care is currently insufficiently equipped to accommodate the complex biopsychosocial needs of HNHC patients. Therefore, it is firstly important to strengthen primary care internally, taking into account the experienced lack of time, the insufficient number of equipped PCPs and lack of inter-professional information retrieval and sharing. Secondly, PCPs should be supported in cooperating and communicating more efficiently with health services outside primary care to adequately deliver person-centred, efficient care. As a prerequisite, it is crucial to direct policy efforts at the design of a strong system of social and community services. In terms of future research, it is important to assess the feasibility and effects of re-designing primary care based on the provided recommendations.

Relevant patient characteristics for guiding tailored integrated diabetes primary care: a systematic review.

AimTo identify which patient-related effect modifiers influence the outcomes of integrated care programs for type 2 diabetes in primary care. BACKGROUND: Integrated care is a widespread management strategy for the treatment of type 2 diabetes. However, most integrated care programs are not tailored to patients' needs, preferences and abilities. There is increasing consensus that such a patient-centered approach could improve the management of type 2 diabetes. Thus far, it remains unclear which patient-related effect modifiers should guide such an approach. METHODS: PubMed, CINAHL and EMBASE were searched for empirical studies published after 1998. A systematic literature review was conducted according to the PRISMA guidelines.FindingsIn total, 23 out of 1015 studies were included. A total of 21 studies measured the effects of integrated diabetes care programs on hemoglobin A1c (HbA1c) and three on low-density lipoprotein cholesterol, systolic blood pressure and health-care utilization. In total, 49 patient characteristics were assessed as potential effect modifiers with HbA1c as an outcome, of which 46 were person or health-related and only three were context-related. Younger age, insulin therapy and longer disease duration were associated with higher HbA1c levels in cross-sectional and longitudinal studies. Higher baseline HbA1c was associated with higher HbA1c at follow-up in longitudinal studies. Information on context- and person-related characteristics was limited, but is necessary to help identify the care needs of individual patients and implement an effective integrated type 2 diabetes tailored care program.

Estimating community health needs against a Triple Aim background: What can we learn from current predictive risk models?

INTRODUCTION: To support providers and commissioners in accurately assessing their local populations' health needs, this study produces an overview of Dutch predictive risk models for health care, focusing specifically on the type, combination and relevance of included determinants for achieving the Triple Aim (improved health, better care experience, and lower costs). METHODS: We conducted a mixed-methods study combining document analyses, interviews and a Delphi study. Predictive risk models were identified based on a web search and expert input. Participating in the study were Dutch experts in predictive risk modelling (interviews; n=11) and experts in healthcare delivery, insurance and/or funding methodology (Delphi panel; n=15). RESULTS: Ten predictive risk models were analysed, comprising 17 unique determinants. Twelve were considered relevant by experts for estimating community health needs. Although some compositional similarities were identified between models, the combination and operationalisation of determinants varied considerably. CONCLUSIONS: Existing predictive risk models provide a good starting point, but optimally balancing resources and targeting interventions on the community level will likely require a more holistic approach to health needs assessment. Development of additional determinants, such as measures of people's lifestyle and social network, may require policies pushing the integration of routine data from different (healthcare) sources.