Disentangling Population Health Management Initiatives in Diabetes Care: A Scoping Review.

Introduction: Population Health Management (PHM) focusses on keeping the whole population as healthy as possible. As such, it could be a promising approach for long-term health improvement in type 2 diabetes. This scoping review aimed to examine the extent to which and how PHM is used in the care for people with type 2 diabetes. Methods: PubMed, Web of Science, and Embase were searched between January 2000 and September 2021 for papers on self-reported PHM initiatives for type 2 diabetes. Eligible initiatives were described using the analytical framework for PHM. Results: In total, 25 studies regarding 18 PHM initiatives for type 2 diabetes populations were included. There is considerable variation in whether and how the PHM steps are operationalized in existing PHM initiatives. Population identification, impact evaluation, and quality improvement processes were generally part of the PHM initiatives. Triple Aim assessment and risk stratification actions were scarce or explained in little detail. Moreover, cross-sector integration is key in PHM but scarce in practice. Conclusion: Operationalization of PHM in practice is limited compared to the PHM steps described in the analytical framework. Extended risk stratification and integration efforts would contribute to whole-person care and further health improvements within the population.

Evaluation of Healthcare Utilisation and Expenditures in Persons with Type 2 Diabetes Undergoing Bariatric-Metabolic Surgery.

PURPOSE: Changes in healthcare utilisation and expenditures after bariatric-metabolic surgery (BMS) for people with type 2 diabetes mellitus (T2DM) are unclear. We used the Dutch national all-payer claims database (APCD) to evaluate utilisation and expenditures in people with T2DM who underwent BMS. METHODS: In this cohort study, patients with T2DM who had BMS in 2016 were identified in the APCD. This group was matched 1:2 to a control group with T2DM who did not undergo BMS based on age, gender and healthcare expenditures. Data on healthcare expenditures and utilisation were collected for 2013-2019. RESULTS: In total, 1751 patients were included in the surgery group and 3502 in the control group. After BMS, total median expenditures in the surgery group stabilised (€ 3156 to € 3120) and increased in the control group (€ 3174 to € 3434). Total pharmaceutical expenditures decreased 28% in the surgery group (€957 to €494) and increased 55% in the control group (€605 to €936). In the surgery group, 67.1% did not use medication for T2DM in 2019 compared to 13.3% in the control group. Healthcare use for microvascular complications increased in the control group, but not in the surgery group. CONCLUSION: BMS in people with T2DM stabilises healthcare expenditures and decreases medication use and care use for microvascular complications. In contrast, healthcare use and expenditures in T2DM patients who do not undergo surgery gradually increase over time. Due to the progressive nature of T2DM, it is expected that these differences will become larger in the long-term.

Supporting professionals to implement integrated, person-centered care for people with chronic conditions: the TARGET pilot study.

OBJECTIVE: The TARGET program for integrated, person-centered care for people with chronic conditions offers primary care (PC) professionals a set of tools and trainings to actively engage in population segmentation and person-centered needs assessments (PCNAs). A pilot study was conducted to gain insight into the program's feasibility and acceptability, and identify preconditions for successful implementation. DESIGN AND SETTING: Seven Dutch PC practices participated in a half-year pilot study starting in August 2020. We performed a review of the population segmentation tool, observed four training sessions and 15 PCNAs, and interviewed 15 professionals and 12 patients. RESULTS: Regarding feasibility and acceptability, we found that the tools and trainings provided professionals with skills to use the segmentation tool and take a more coaching role in the well-appreciated PCNAs. Concerning implementation preconditions, we found that team commitment and network connections need improvement, although work pleasure increased and professionals generally wanted the program to continue. CONCLUSIONS: While the content of the TARGET program is supported by its users, the implementation process, for instance team commitment to the program, needs more attention in future upscaling efforts.

Key PointsTo implement integrated care in practice, primary care professionals (PCPs) need concrete tools, skills and confidence.PCPs consider the tools and trainings of the TARGET program as feasible and acceptable to organize integrated careTARGET's success depends on commitment from professionals to its implementation and the strength of ties with professionals in other domains.Based on qualitative insights, TARGET improves work pleasure and patient experience, but it takes time to decrease work pressure effectively.

Preferred Conversation Topics with Respect to Treatment Decisions Among Individuals with Type 2 Diabetes.

Purpose: Greater knowledge of individuals' needs and preferences can enhance shared decision-making, which is associated with improved quality of decisions and increased satisfaction. This study aimed to identify and prioritize the attributes (ie conversation topics) that individuals with type 2 diabetes find it most important to discuss with their healthcare provider regarding treatment decisions. Patients and Methods: First, small group interviews were organized with adults with type 2 diabetes (N=8) treated in primary care to identify the attributes that they find important to discuss regarding treatment decisions. A five-step nominal group technique was applied during the interviews. An object best-worst scaling (BWS) survey was subsequently distributed to individuals with self-reported diabetes participating in the Dutch Health Care Consumer Panel of the Netherlands Institute for Health Services Research (N=600) to determine the relative importance score (RIS) of the identified attributes. A higher RIS indicates a higher level of perceived importance. Subgroup and latent class analyses were performed to explore whether individuals' demographic and disease characteristics influenced their attribute preferences. Results: A total of 21 attributes were identified during three small group interviews with individuals with type 2 diabetes. Respondents in the BWS survey (N=285) viewed "quality of life" (RIS=11.97), "clinical outcomes" (RIS=10.40), "long-term diabetes complications" (RIS=9.83) and "short-term adverse medication" (RIS=7.72) as the most important in the decision-making process for the treatment of type 2 diabetes. Some differences in attribute preferences were identified according to demographic and disease characteristics. Conclusion: In general, individuals with type 2 diabetes not only want to discuss the biological effects of treatments, but also the impact of treatment on their quality of life. Healthcare providers should be aware that attributes are viewed differently by different individuals. This emphasizes the need for tailor-made healthcare decisions, which means eliciting and responding to individual preferences in the decision-making process.

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.

In the Eye of the Storm: A Quantitative and Qualitative Account of the Impact of the COVID-19 Pandemic on Dutch Home Healthcare.

The COVID-19 pandemic has severely affected healthcare delivery across the world. However, little is known about COVID-19's impact on home healthcare (HHC) services. Our study aimed to: (1) describe the changes in volume and intensity of HHC services and the crisis management policies implemented; (2) understand the responses and the experiences of HHC staff and clients. We conducted an explanatory sequential mixed methods study. First, retrospective client data (N = 43,495) from four Dutch HHC organizations was analyzed. Second, four focus group interviews were conducted for the strategic, tactical, operational, and client levels of the four HHC organizations. Our results showed that both the supply of and demand for Dutch HHC decreased considerably, especially during the first wave (March-June 2020). This was due to factors such as fear of infection, anticipation of a high demand for COVID-19-related care from the hospital sector, and lack of personal protective equipment. The top-down management style initially applied made way for a more bottom-up approach in the second wave (July 2020-January 2021). Experiences vary between levels and waves. HHC organizations need more responsive protocols to prevent such radical scaling-back of HHC in future crises, and interventions to help HHC professionals cope with crisis situations.

Delineating the Type 2 Diabetes Population in the Netherlands Using an All-Payer Claims Database: Specialist Care, Medication Utilization and Expenditures 2016-2018.

OBJECTIVES: The aim of this study was to describe the healthcare utilization and expenditures related to medical specialist care and medication of the entire type 2 diabetes population in the Netherlands in detail. METHODS: For this retrospective, observational study, we used an all-payer claims database. Comprehensive data on specialist care and medication utilization and expenditures of the type 2 diabetes population (n = 900,522 in 2018) were obtained and analyzed descriptively. Data were analyzed across medical specialties and for various types of diabetes medication (or glucose-lowering drugs [GLDs]) and other medication. RESULTS: Specialist care utilization was diverse: different medical specialties were visited by a considerable fraction of the type 2 diabetes population. Total expenditures on specialist care were €2498 million in 2018 (i.e., 10.6% of the national specialist care expenditures). In total, 97.8% of patients used other medication (not GLDs) and 81.8% used GLDs; 25.6% of medication expenditures were for GLDs. For both specialist care and medication, mean expenditures per treated patient were higher than median expenditures, indicating a skewed distribution of spending. CONCLUSION: Use of and expenditures on specialist care and medication of the type 2 diabetes population is diverse. These heterogeneous healthcare use patterns are likely caused by the presence of comorbidities. Additionally, we found that a small fraction of the population is responsible for a large share of the expenditures. A shift towards more patient-centered care could lead to health improvements and a reduction in overall costs, subsequently promoting the sustainability of healthcare systems.

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.

Identifying and delineating the type 2 diabetes population in the Netherlands using an all-payer claims database: characteristics, healthcare utilisation and expenditures.

OBJECTIVES: We aimed to identify and delineate the Dutch type 2 diabetes population and the distribution of healthcare utilisation and expenditures across the health system from 2016 to 2018 using an all-payer claims database. DESIGN: Retrospective observational cohort study based on an all-payer claims database of the Dutch population. SETTING: The Netherlands. PARTICIPANTS: The whole Dutch type 2 diabetes population (n=900 522 in 2018), determined based on bundled payment codes for integrated diabetes care and medication use indicating type 2 diabetes. OUTCOME MEASURES: Annual prevalence of type 2 diabetes, comorbidities and characteristics of the type 2 diabetes population, as well as the distribution of healthcare utilisation and expenditures were analysed descriptively. RESULTS: In 2018, 900 522 people (6.5% of adults) were identified as having type 2 diabetes. The most common comorbidity in the population was heart disease (12.1%). Additionally, 16.2% and 5.6% of patients received specialised care for microvascular and macrovascular diabetes-related complications, respectively. Most patients with type 2 diabetes received pharmaceutical care (99.1%), medical specialist care (97.0%) and general practitioner consultations (90.5%). In total, €8173 million, 9.4% of total healthcare expenditures, was reimbursed for the type 2 diabetes population. Medical specialist care accounted for the largest share of spending (38.1%), followed by district nursing (12.4%), and pharmaceutical care (11.5%). CONCLUSIONS: All-payer claims databases can be used to delineate healthcare use: this insight can inform health policy and practice and, thereby, support better decisions to promote long-term sustainability of healthcare systems. The healthcare utilisation of the Dutch type 2 diabetes population is distributed across the health system and utilisation of medical specialist care is high. This is likely to be due to presence of concurrent morbidities and complications. Therefore, a shift from a disease-specific approach to a person-centred and integrated care approach could be beneficial in the treatment of type 2 diabetes.

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.

Nurse-sensitive outcomes in district nursing care: A Delphi study.

OBJECTIVES: To determine nurse-sensitive outcomes in district nursing care for community-living older people. Nurse-sensitive outcomes are defined as patient outcomes that are relevant based on nurses' scope and domain of practice and that are influenced by nursing inputs and interventions. DESIGN: A Delphi study following the RAND/UCLA Appropriateness Method with two rounds of data collection. SETTING: District nursing care in the community care setting in the Netherlands. PARTICIPANTS: Experts with current or recent clinical experience as district nurses as well as expertise in research, teaching, practice, or policy in the area of district nursing. MAIN OUTCOME MEASURES: Experts assessed potential nurse-sensitive outcomes for their sensitivity to nursing care by scoring the relevance of each outcome and the ability of the outcome to be influenced by nursing care (influenceability). The relevance and influenceability of each outcome were scored on a nine-point Likert scale. A group median of 7 to 9 indicated that the outcome was assessed as relevant and/or influenceable. To measure agreement among experts, the disagreement index was used, with a score of <1 indicating agreement. RESULTS: In Delphi round two, 11 experts assessed 46 outcomes. In total, 26 outcomes (56.5%) were assessed as nurse-sensitive. The nurse-sensitive outcomes with the highest median scores for both relevance and influenceability were the patient's autonomy, the patient's ability to make decisions regarding the provision of care, the patient's satisfaction with delivered district nursing care, the quality of dying and death, and the compliance of the patient with needed care. CONCLUSIONS: This study determined 26 nurse-sensitive outcomes for district nursing care for community-living older people based on the collective opinion of experts in district nursing care. This insight could guide the development of quality indicators for district nursing care. Further research is needed to operationalise the outcomes and to determine which outcomes are relevant for specific subgroups.

Using machine learning to assess the predictive potential of standardized nursing data for home healthcare case-mix classification.

BACKGROUND: The Netherlands is currently investigating the feasibility of moving from fee-for-service to prospective payments for home healthcare, which would require a suitable case-mix system. In 2017, health insurers mandated a preliminary case-mix system as a first step towards generating information on client differences in relation to care use. Home healthcare providers have also increasingly adopted standardized nursing terminology (SNT) as part of their electronic health records (EHRs), providing novel data for predictive modelling. OBJECTIVE: To explore the predictive potential of SNT data for improvement of the existing preliminary Dutch case-mix classification for home healthcare utilization. METHODS: We extracted client-level data from the EHRs of a large home healthcare provider, including data from the existing Dutch case-mix system, SNT data (specifically, NANDA-I) and the hours of home healthcare provided. We evaluated the predictive accuracy of the case-mix system and the SNT data separately, and combined, using the machine learning algorithm Random Forest. RESULTS: The case-mix system had a predictive performance of 22.4% cross-validated R-squared and 6.2% cross-validated Cumming's Prediction Measure (CPM). Adding SNT data led to a substantial relative improvement in predicting home healthcare hours, yielding 32.1% R-squared and 15.4% CPM. DISCUSSION: The existing preliminary Dutch case-mix system distinguishes client needs to some degree, but not sufficiently. The results indicate that routinely collected SNT data contain sufficient additional predictive value to warrant further research for use in case-mix system design.

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.

A systematic review of case-mix models for home health care payment: Making sense of variation.

BACKGROUND: Case-mix based payment of health care services offers potential to contain expenditure growth and simultaneously support needs-based care provision. However, limited evidence exists on its application in home health care (HHC). Therefore, this study aimed to synthesize available international literature on existing case-mix models for HHC payment. METHODS: We performed a systematic review of scientific literature, supplemented with grey literature. We searched for literature using six scientific databases, reference lists, expert consultation, and targeted websites. Data on study design, case-mix model attributes, and conclusions were extracted narratively. RESULTS: Of 3303 references found, 22 scientific studies and 27 grey documents met eligibility criteria. Eight case-mix models for HHC were identified, from the US, Canada, New Zealand, Australia, and Germany. Three countries have implemented a case-mix model as part of a HHC payment system. Different combinations of in total 127 unique case-mix predictors are included across models to predict HHC use. Case-mix models also differ in targeted services, operationalization, and outcome measures and predictive power. CONCLUSIONS: Case-mix based payment is not yet widely used within HHC. Multiple varieties were found between HHC case-mix models, and no one best form of a model seems to exist. Even though varieties are partly inevitable due to country-specific contexts, developing a shared vision in case-mix model attributes would be key to achieving efficient, needs-based HHC.

Identifying subgroups of high-need, high-cost, chronically ill patients in primary care: A latent class analysis.

INTRODUCTION: Segmentation of the high-need, high-cost (HNHC) population is required for reorganizing care to accommodate person-centered, integrated care delivery. Therefore, we aimed to identify and characterize relevant subgroups of the HNHC population in primary care by using demographic, biomedical, and socioeconomic patient characteristics. METHODS: This was a retrospective cohort study within a Dutch primary care group, with a follow-up period from September 1, 2014 to August 31, 2017. Chronically ill patients were included in the HNHC population if they belonged to the top 10% of care utilizers and/or suffered from multimorbidity and had an above-average care utilization. In a latent class analysis, forty-one patient characteristics were initially used as potential indicators of heterogeneity in HNHC patients' needs. RESULTS: Patient data from 12 602 HNHC patients was used. A 4-class model was considered statistically and clinically superior. The classes were named according to the characteristics that were most dominantly present and distinctive between the classes (i.e. mainly age, household position, and source of income). Class 1 ('older adults living with partner') included 39.3% of patients, class 2 ('older adults living alone') included 25.5% of patients, class 3 ('middle-aged, employed adults with family') included 23.3% of patients, and class 4 ('middle-aged adults with social welfare dependency') included 11.9% of patients. Diabetes was the most common condition in all classes; the second most prevalent condition differed between osteoarthritis in class 1 (21.7%) and 2 (23.8%), asthma in class 3 (25.3%), and mood disorders in class 4 (23.1%). Furthermore, while general practitioner (GP) care utilization increased during the follow-up period in the classes of older adults, it remained relatively stable in the middle-aged classes. CONCLUSIONS: Although the HNHC population is heterogeneous, distinct subgroups with relatively homogeneous patterns of mainly demographic and socioeconomic characteristics can be identified. This calls for tailoring care and increased attention for social determinants of health.

Patients' perspective on self-management: type 2 diabetes in daily life.

BACKGROUND: The number of type 2 diabetes mellitus (T2DM) patients and related treatment costs are rapidly increasing. Consequentially, more cost-effective and efficient strategies for the treatment of T2DM are needed. One such strategy is improving patients' self-management. As patients are more and more expected to self-manage their disease, it is important to provide them with suitable self-management support. This way, success of self-management will increase and complications and related costs of T2DM can be reduced. Currently, self-management support is developed mainly from the perspective of health professionals and caregivers, rather than patients. This research focused on gaining a better understanding of patients' perspectives on self-management and support. METHODS: Semi-structured interviews, preceded by preparatory assignments, were conducted with ten patients with T2DM treated in Dutch primary care. RESULTS: We found that patients experience 'active' self-management when recently diagnosed. As time progresses and no problems occur, patients do not experience their disease-related behaviour as self-management. Diabetes has 'just' become part of their daily life, now including new routines taking diabetes into account. CONCLUSIONS: With this knowledge, support solutions can be designed and implemented that better fit the needs, preferences and abilities of patients with T2DM.

Relevant patient characteristics for estimating healthcare needs according to healthcare providers and people with type 2 diabetes: a Delphi survey.

BACKGROUND: Recently, there has been growing interest in providing more tailored, patient-centered care for the treatment of type 2 diabetes mellitus (T2DM). Yet it remains unclear which patient characteristics should be determined to guide such an approach. Therefore, the opinions of healthcare providers (HCP) and people with T2DM about relevant patient characteristics for estimating healthcare needs of people with T2DM were assessed and compared. METHODS: Two separate online Delphi studies were conducted according to the RAND-UCLA Appropriateness Method: one with HCPs (n = 22) from Dutch primary and secondary care and one with people with T2DM treated in Dutch primary care (n = 46). The relevance of patient characteristics for estimating healthcare needs, defined as the number of yearly consultations, was assessed on a 5-point Likert scale. Characteristics with a median of 4 or 5 and an interquartile range ≤ 1.5 were considered relevant with consensus. Participants were also asked to select the top 5 of most relevant patient characteristics. To determine the overall top 5, the mean relative importance score of each characteristic was calculated. RESULTS: In two Delphi rounds, 28 and 15 patient characteristics were rated by HCPs and people with T2DM, respectively. Both HCPs and people with T2DM found health-related characteristics relevant for estimating healthcare needs of people with T2DM. However, HCPs preferred to estimate healthcare needs using person- and context-related characteristics. They ranked self-efficacy as the most relevant estimator. In contrast, people with T2DM were more in favor of health-related characteristics and ranked HbA1c as the most relevant estimator. CONCLUSIONS: The findings show that there is discrepancy in opinions on relevant patient characteristics for estimating healthcare needs between HCPs and people with T2DM. To achieve more tailored, patient-centered care, it is important that both groups agree on the topics to be discussed during patient consultations.

Which client characteristics predict home-care needs? Results of a survey study among Dutch home-care nurses.

Fee-for-service, funding care on an hourly rate basis, creates an incentive for home-care providers to deliver high amounts of care. Under casemix funding, in contrast, clients are allocated-based on their characteristics-to homogenous, hierarchical groups, which are subsequently funded to promote more effective and efficient care. The first step in developing a casemix model is to understand which client characteristics are potential predictors of home-care needs. Nurses working in home care (i.e. home-care nurses) have a good insight into clients' home-care needs. This study was conducted in co-operation with the Dutch Nurses' Association and the Dutch Healthcare Authority. Based on international literature, 35 client characteristics were identified as potential predictors of home-care needs. In an online survey (May, 2017), Dutch home-care nurses were asked to score these characteristics on relevance, using a 9-point Likert scale. They were subsequently asked to identify the top five client characteristics. Data were analysed using descriptive statistics. The survey was completed by 1,007 home-care nurses. Consensus on relevance was achieved for 15 client characteristics, with "terminal phase" being scored most relevant, and "sex" being scored as the least relevant. Relevance of the remaining 20 characteristics was uncertain. Additionally, based on the ranking, "ADL functioning" was ranked as most relevant. According to home-care nurses, both biomedical and psychosocial client characteristics need to be taken into account when predicting home-care needs. Collaboration between clinical practice, policy development, and science is necessary to realise a funding model, to work towards the Triple Aim (improved health, better care experience, and lower costs).

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.

A risk score including body mass index, glycated haemoglobin and triglycerides predicts future glycaemic control in people with type 2 diabetes.

AIM: To identify, predict and validate distinct glycaemic trajectories among patients with newly diagnosed type 2 diabetes treated in primary care, as a first step towards more effective patient-centred care. METHODS: We conducted a retrospective study in two cohorts, using routinely collected individual patient data from primary care practices obtained from two large Dutch diabetes patient registries. Participants included adult patients newly diagnosed with type 2 diabetes between January 2006 and December 2014 (development cohort, n = 10 528; validation cohort, n = 3777). Latent growth mixture modelling identified distinct glycaemic 5-year trajectories. Machine learning models were built to predict the trajectories using easily obtainable patient characteristics in daily clinical practice. RESULTS: Three different glycaemic trajectories were identified: (1) stable, adequate glycaemic control (76.5% of patients); (2) improved glycaemic control (21.3% of patients); and (3) deteriorated glycaemic control (2.2% of patients). Similar trajectories could be discerned in the validation cohort. Body mass index and glycated haemoglobin and triglyceride levels were the most important predictors of trajectory membership. The predictive model, trained on the development cohort, had a receiver-operating characteristic area under the curve of 0.96 in the validation cohort, indicating excellent accuracy. CONCLUSIONS: The developed model can effectively explain heterogeneity in future glycaemic response of patients with type 2 diabetes. It can therefore be used in clinical practice as a quick and easy tool to provide tailored diabetes care.