Modelling the balance of care: Impact of an evidence-informed policy on a mental health ecosystem

Major efforts worldwide have been made to provide balanced Mental Health (MH) care. Any integrated MH ecosystem includes hospital and community-based care, highlighting the role of outpatient care in reducing relapses and readmissions. This study aimed (i) to identify potential expert-based causal relationships between inpatient and outpatient care variables, (ii) to assess them by using statistical procedures, and finally (iii) to assess the potential impact of a specific policy enhancing the MH care balance on real ecosystem performance. Causal relationships (Bayesian network) between inpatient and outpatient care variables were defined by expert knowledge and confirmed by using multivariate linear regression (generalized least squares). Based on the Bayesian network and regression results, a decision support system that combines data envelopment analysis, Monte Carlo simulation and fuzzy inference was used to assess the potential impact of the designed policy. As expected, there were strong statistical relationships between outpatient and inpatient care variables, which preliminarily confirmed their potential and a priori causal nature. The global impact of the proposed policy on the ecosystem was positive in terms of efficiency assessment, stability and entropy. To the best of our knowledge, this is the first study that formalized expert-based causal relationships between inpatient and outpatient care variables. These relationships, structured by a Bayesian network, can be used for designing evidence-informed policies trying to balance MH care provision. By integrating causal models and statistical analysis, decision support systems are useful tools to support evidence-informed planning and decision making, as they allow us to predict the potential impact of specific policies on the ecosystem prior to its real application, reducing the risk and considering the population’s needs and scientific findings.

Food Insecurity and Healthcare Utilization in Indonesia: Evidence from Indonesian National Household Surveys

Treatment for sicknesses in healthcare is a crucial determinant to improve health. In Indonesia, the unmet need for healthcare is common for people in the lower economic group. This study aims to examine how food insecurity affects outpatient care using the indicators of food insecurity to highlight individuals with high health risks and experiencing problems with limited resources. The data used in this study consisted of 159,236 individuals representing different age ranges from the 2017 National Socio-Economic Survey (SUSENAS) and the 2018 Village Potential Census (PODES). Data were analyzed using ivprobit to address bias due to the endogeneity in the food insecurity variables. The results indicate that a higher food insecurity score will increase the chances of not accessing modern healthcare for outpatient care when sick. Several variables like sex, types of residence, number of household members living together, access to healthcare, health insurance, social protection, and illness characteristic were also found to influence individual behavior in not utilizing modern healthcare for outpatient care. This study suggests that policymakers should pay attention to the utilization of modern healthcare, especially for outpatient care in groups experiencing food insecurity.

Pro-inflammatory diet, frailty and sarcopenia: a study with older people in outpatient care

Objectives: To analyze the relationship between the Dietary Inflammatory Index (DII), sarcopenia, and frailty syndrome in older people. Methods: A cross-sectional, non-probabilistic study was carried out with 135 older people, attended by a general outpatient clinic. The older people were classified in relation to sarcopenia according to the European Working Group on Sarcopenia in Older People. The frailty classification was made through self-referred questions. The calculation of the DII was made using the iOS application IF RATING®. Association analysis was performed using multiple logistic regression. Results: Of the 135 older people evaluated, 17.78% were classified as sarcopenic and 47.41% as frail. No association was observed between the most inflammatory DII and sarcopenia. Regarding frailty syndrome, older people with a more inflammatory DII were more likely to be frail (OR=3.64; 95%CI=1.24-10.70). Discussion: These results could stimulate actions to promote an anti-inflammatory diet, with a view to preventing frailty in older people.

Pain Control: Normalization of the BPCQ Questionnaire on a Group of Patients Diagnosed with Malignant Cancer

The purpose of this article is to examine the applicability of the Beliefs about Pain Control Questionnaire (BPCQ) among cancer patients and develop norms that allow differentiation of patients with diagnosed cancer in terms of beliefs about pain control. Normalization aims to establish the value of test results in the study population. The study involved 1187 patients diagnosed with cancer in outpatient care Maria Sklodowska-Curie Cancer Center and Institute of Oncology, in Warsaw. The applied tool was the Beliefs about Pain Control Questionnaire developed by S. Skevington. The results are most strongly differentiated in each dimension of pain control by education, income, and professional status. Sten norms were developed to determine the level of beliefs about pain control in low, average, and high categories. The BPCQ assessment applies to cancer patients, and the assessment of the location of pain control in patients will allow for the identification of patients whose standard therapy should be supplemented with psychotherapeutic support.

A new model to deliver scheduled outpatient care

Here we describe an integrated model for scheduled care (the ‘cluster clinic’). Following a pilot in April 2018, cluster clinics were established across Aberdeen City from April 2019 but not the area surrounding Aberdeen (ie, Aberdeenshire). There were 2360 referrals in 2017/2018 (pre-cluster clinic), and 2615 in 2019/2020 (post-Aberdeen City cluster clinics). The proportions of referrals from City practices seen pre-cluster and post-cluster were 72% and 56%, respectively, and from Shire practices the corresponding proportions were 70% and 65%. The cluster clinic received positive feedback from parents and referring clinicians and was not associated with increased ‘missed diagnoses’ compared with business as usual clinic. The cluster clinic model is a realistic and effective method to deliver integrated scheduled care for children.