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Cost Variation in Diabetes Care across Dutch Care Groups?

ABSTRACT: OBJECTIVE:The introduction of bundled payment for diabetes care in the Netherlands led to the origination of care groups. This study explored to what extent variation in health care costs per patient can be attributed to the performance of care groups. Furthermore, the commonly applied simple mean aggregation was compared with the more advanced generalized linear mixed model (GLMM) to benchmark health care costs per patient between care groups. DATA SOURCE:Dutch 2009 nationwide insurance claims data of diabetes type 2 patients (104,544 patients, 50 care groups). STUDY DESIGN:Both a simple mean aggregation and a GLMM approach was applied to rank care groups, using two different health care costs variables: total treatment health care costs and diabetes-specific specialist care costs per diabetes patient. PRINCIPAL FINDINGS:Care groups varied slightly in the first and mainly in the second indicator. Care group variation was not explained by composition. Although the ranking methods were correlated, some care groups' rank positions differed, with consequences on the top-10 and the low-10 positions. CONCLUSIONS:Differences between care groups exist when an appropriate indicator and a sophisticated aggregation technique is used. Currently applied benchmarking may have unfair consequences for some care groups.

SUBMITTER: Mohnen SM

PROVIDER: S-EPMC5264018 | biostudies-literature | 2017 Feb

REPOSITORIES: biostudies-literature

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Cost Variation in Diabetes Care across Dutch Care Groups?

Mohnen Sigrid M SM Molema Claudia C CC Steenbeek Wouter W van den Berg Michael J MJ de Bruin Simone R SR Baan Caroline A CA Struijs Jeroen N JN

Health services research 20160321 1

<h4>Objective</h4>The introduction of bundled payment for diabetes care in the Netherlands led to the origination of care groups. This study explored to what extent variation in health care costs per patient can be attributed to the performance of care groups. Furthermore, the commonly applied simple mean aggregation was compared with the more advanced generalized linear mixed model (GLMM) to benchmark health care costs per patient between care groups.<h4>Data source</h4>Dutch 2009 nationwide in ...[more]

PMID: 26997514

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Project description:BackgroundIn recent years, most Dutch general practitioners started working under the umbrella of diabetes care groups, responsible for the organisation and coordination of diabetes care. The quality management of these new organisations receives growing interest, although its association with quality of diabetes care is yet unclear. The best way to measure quality management is unknown and it has not yet been studied at the level of outpatient clinics or care groups. We aimed to assess quality management of type 2 diabetes care in care groups and outpatient clinics.ResultsQuality management was measured with online questionnaires, containing six domains (see below). They were divided into 28 subdomains, with 59 (care groups) and 57 (outpatient clinics) questions respectively. The mean score of the domains reflects the overall score (0-100%) of an organisation. Two quality managers of all Dutch care groups and outpatient clinics were invited to fill out the questionnaire.Sixty care groups (response rate 61.9%) showed a mean score of 59.6% (CI 57.1-62.1%). The average score in 52 outpatient clinics (response rate 50.0%) was 61.9% (CI 57.5-66.8%).Mean scores on the six domains for care groups and outpatient clinics respectively were: 'organisation of care' 71.9% (CI 68.8-74.9%), 76.8% (CI 72.8-80.7%); 'multidisciplinary teamwork' 67.1% (CI 62.4-71.9%), 71.5% (CI 65.3-77.8%); 'patient centeredness' 46.7% (CI 42.6-50.7%), 62.5% (CI 57.7-67.2%); 'performance management' 63.3% (CI 61.2-65.3%), 50.9% (CI 44.2-57.5%); 'quality improvement policy' 52.6% (CI 49.2-56.1%), 50.9% (CI 44.6-57.3%); and 'management strategies' 56.0% (CI 51.4-60.7%), 59.0% (CI 52.8-65.2%). On subdomains, care groups scored highest on 'care program' (83.3%) and 'measured outcomes' (98.3%) and lowest on 'patient safety' (15.1%) and 'patient involvement' (17.7%). Outpatient clinics scored high on the presence of a 'diabetic foot team' (81.6%) and the support in 'self-management' (81.0%) and low on 'patient involvement' (26.8%) and 'inspection of medical file' (28.0%).ConclusionsThis nationwide assessment reveals that the level of quality management in diabetes care varies between several subdomains in both diabetes care groups and outpatient clinics.

Project description:BackgroundWorldwide, the organisation of diabetes care is changing. As a result general practices and diabetes teams in hospitals are becoming part of new organisations in which multidisciplinary care programs are implemented. In the Netherlands, 97 diabetes care groups and 104 outpatient clinics are working with a diabetes care program. Both types of organisations aim to improve the quality of diabetes care. Therefore, it is essential to understand the comprehensive elements needed for optimal quality management at organisational level. This study aims to assess the current level of diabetes quality management in both care groups and outpatient clinics and its improvement after providing feedback on their quality management system and tailored support.Methods/designThis study is a before-after study with a one-year follow-up comparing the levels of quality management before and after an intervention to improve diabetes quality management. To assess the status of quality management, online questionnaires were developed based on current literature. They consist of six domains: organisation of care, multidisciplinary teamwork, patient centeredness, performance management, quality improvement policy and management strategies. Based on the questionnaires, respondents will receive feedback on their score in a radar diagram and an elucidating table. They will also be granted access to an online toolbox with instruments that proved to be effective in quality of care improvement and with practical examples. If requested, personal support in implementing these tools will be available. After one year quality management will be measured again using the same questionnaire.DiscussionThis study will reveal a nationwide picture of quality management in diabetes care groups and outpatient clinics in the Netherlands and evaluate the effect of offering tailored support. The operationalisation of quality management on organisational level may be of interest for other countries as well.

Project description:AimsThe COVID-19 pandemic impacted diabetes care by reducing diabetes outpatient visits and diabetes-related screening due to allocation of healthcare resources. Yet the impact of COVID-19 on diabetes outpatients has not been extensively evaluated. This study aimed to assess the effect of the COVID-19 pandemic on diagnostics and intermediate outcomes of outpatient diabetes care pre- and during COVID.MethodsThis observational cohort study included 8,442 diabetes patients in the Dutch Pediatric and Adult Registry of Diabetes (DPARD) visiting diabetes outpatient clinics in 2019 and 2021. A mixed-effects regression analysis was used to examine differences in target achievement of HbA1c, BMI, blood pressure, LDL-cholesterol, eGFR, and the difference in mean HbA1c between 2019 and 2020 among n = 1,426 outpatients who visited in both years. Analyses were adjusted for age, sex, and BMI.ResultsA 22.7% (21.6-23.8%, p < 0.001) decline in outpatient volume was observed during the pandemic (2020). BMI, lipid spectrum, kidney function, and HbA1c were assessed less frequently in 2020 than in 2019. In 2020, compared to 2019, the median HbA1c level increased by 2.2% (1.0 mmol/mol, p = 0.035) and the percentages of patients with known HbA1C meeting targets below 10, 8, 7% (86, 64, and 53 mmol/mol) decreased by 0.5%, 1.7% and 1.4%, respectively. Target blood pressure ≤ 130/80 mmHg was achieved more often in 2020 (15.0% versus 18.3%, p = 0.018), while HbA1c ≤ 86 mmol/mol was achieved less (89.3% versus 87.1%, p = 0.001), among diabetes outpatients seen in both 2019 and 2020. In patients visiting both years, HbA1c was 2.3% (1.9 mmol/l, 95% CI 1.2-2.5, p < 0.001) lower during the pandemic than in the prepandemic (2019).ConclusionsThe COVID pandemic was associated with a marked reduction in patient volume in diabetes outpatient care among five hospitals. Among patients who received outpatient care both before and during the pandemic period, HbA1c control and blood pressure control enhanced during the pandemic. Re-evaluation of current diabetes outpatient care organization is warranted to ensure optimal diabetes care in future times.

Project description:BackgroundAlthough evidence is accumulating that lifestyle modification may be cost-effective in patients with prediabetes, information is limited on the cost-effectiveness of interventions implemented in public health and primary health care settings. Evidence from well-conducted pragmatic trials is needed to gain insight into the realistic cost-effectiveness of diabetes prevention interventions in real-world settings. The aim of this study is to assess the cost-effectiveness of the SLIMMER lifestyle intervention targeted at patients at high risk of developing type 2 diabetes compared with usual health care in a primary care setting in the Netherlands.MethodsThree hundred and sixteen high-risk subjects were randomly assigned to the SLIMMER lifestyle intervention or to usual health care. Costs and outcome assessments were performed at the end of the intervention (12 months) and six months thereafter (18 months). Costs were assessed from a societal perspective. Patients completed questionnaires to assess health care utilisation, participant out-of-pocket costs, and productivity losses. Quality Adjusted Life Years (QALY) were calculated based on the SF-36 questionnaire. Cost-effectiveness planes and acceptability curves were generated using bootstrap analyses.ResultsThe cost-effectiveness analysis showed that the incremental costs of the SLIMMER lifestyle intervention were €547 and that the incremental effect was 0.02 QALY, resulting in an incremental cost-effectiveness ratio (ICER) of €28,094/QALY. When cost-effectiveness was calculated from a health care perspective, the ICER decreased to €13,605/QALY, with a moderate probability of being cost-effective (56% at a willingness to pay, WTP, of €20,000/QALY and 81% at a WTP of €80,000/QALY).ConclusionsThe SLIMMER lifestyle intervention to prevent type 2 diabetes had a low to moderate probability of being cost-effective, depending on the perspective taken.Trial registrationThe SLIMMER study is retrospectively registered with ClinicalTrials.gov (Identifier NCT02094911) since March 19, 2014.

Project description:BackgroundWithin the Dutch health care system the focus is shifting from a disease oriented approach to a more population based approach. Since every inhabitant in the Netherlands is registered with one general practice, this offers a unique possibility to perform Population Health Management analyses based on general practitioners' (GP) registries. The Johns Hopkins Adjusted Clinical Groups (ACG) System is an internationally used method for predictive population analyses. The model categorizes individuals based on their complete health profile, taking into account age, gender, diagnoses and medication. However, the ACG system was developed with non-Dutch data. Consequently, for wider implementation in Dutch general practice, the system needs to be validated in the Dutch healthcare setting. In this paper we show the results of the first use of the ACG system on Dutch GP data. The aim of this study is to explore how well the ACG system can distinguish between different levels of GP healthcare utilization.MethodsTo reach our aim, two variables of the ACG System, the Aggregated Diagnosis Groups (ADG) and the mutually exclusive ACG categories were explored. The population for this pilot analysis consisted of 23,618 persons listed with five participating general practices within one region in the Netherlands. ACG analyses were performed based on historical Electronic Health Records data from 2014 consisting of primary care diagnoses and pharmaceutical data. Logistic regression models were estimated and AUC's were calculated to explore the diagnostic value of the models including ACGs and ADGs separately with GP healthcare utilization as the dependent variable. The dependent variable was categorized using four different cut-off points: zero, one, two and three visits per year.ResultsThe ACG and ADG models performed as well as models using International Classification of Primary Care chapters, regarding the association with GP utilization. AUC values were between 0.79 and 0.85. These models performed better than the base model (age and gender only) which showed AUC values between 0.64 and 0.71.ConclusionThe results of this study show that the ACG system is a useful tool to stratify Dutch primary care populations with GP healthcare utilization as the outcome variable.

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Cost Variation in Diabetes Care across Dutch Care Groups?

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Cost Variation in Diabetes Care across Dutch Care Groups?

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