The objective is to develop a pragmatic framework, based on value-based healthcare principles, to monitor health outcomes per unit costs on an institutional level. Subsequently, we investigated the association between health outcomes and healthcare utilisation costs.

This is a retrospective cohort study.

A teaching hospital in Rotterdam, The Netherlands.

The study was performed in two use cases. The bariatric population contained 856 patients of which 639 were diagnosed with morbid obesity body mass index (BMI)

The quality cost indicator (QCI) was the primary measures and was defined as

QCI = (resulting outcome * 100)/average total costs (per thousand Euros)

where average total costs entail all healthcare utilisation costs with regard to the treatment of the primary diagnosis and follow-up care. Resulting outcome is the number of patients achieving textbook outcome (passing all health outcome indicators) divided by the total number of patients included in the care path.

The breast cancer and bariatric population had the highest resulting outcome values in 2020 Q4, 0.93 and 0.73, respectively. The average total costs of the bariatric population remained stable (avg, 8833.55, min 8494.32, max 9164.26). The breast cancer population showed higher variance in costs (avg, 12 735.31 min 12 188.83, max 13 695.58). QCI values of both populations showed similar variance (0.3 and 0.8). Failing health outcome indicators was significantly related to higher hospital-based costs of care in both populations (p

The QCI framework is effective for monitoring changes in average total costs and relevant health outcomes on an institutional level. Health outcomes are associated with hospital-based costs of care.

The aim of this study was to investigate risk factors for cognitive impairment (CI) and explore the relationship between obesity and cognition in hospitalised middle-aged patients with type 2 diabetes (T2DM).

Subjects were divided into normal cognitive function (NCF) (n=320) and CI (n=204) groups based on the results of the Montreal Cognitive Assessment (MoCA) and Mini-Mental State Examination (MMSE). The risk factors for CI were determined by logistic regression analysis and generalised linear modelling. The associations between obesity parameters (body mass index (BMI) and waist circumference (WC)) and cognitive ability were studied with the use of linear regression analysis, piecewise regression modelling and interaction analysis. The receiver operating characteristic curve analysis was used to examine the diagnostic value of influencing factors for cc

The prevalence of CI was 38.9% in hospitalised middle-aged T2DM patients (median age, 58 years). Age, WC, hypoglycaemic episode within past 3 months and cerebrovascular disease (CVD) were identified as independent risk factors for CI, while the independent protective factors were education, diabetic dietary pattern, overweight and obesity. BMI was a protective factor for the MoCA score within a certain range, whereas WC was a risk factor for the MMSE and MoCA scores. The area under the curve for the combination of BMI and WC was 0.754 (p

Age, education, diabetic dietary pattern, WC, overweight, obesity, hypoglycaemic episode in 3 months and CVD may be potential influencing factors for the occurrence of CI in hospitalised middle-aged population with T2DM. The combination of BMI and WC may represent a good predictor for early screening of CI in this population. Nevertheless, more relevant prospective studies are still needed.