Creating the BELgian COngenital heart disease database combining administrative and clinical data (BELCODAC) : rationale, design and methodology

Background: Congenital heart disease (CHD) entails a broad spectrum of malformations with various degrees of severity and prognosis. Consequently, new and specific healthcare needs are emerging, requiring responsive healthcare provision. Research on this matter is predominantly performed on population-based databases, to inform clinicians, researchers and policy-makers on health outcomes and economic burden of CHD. Most databases contain data either from administrative sources or from clinical systems. We describe the methodological design of the BELgian COngenital Heart Disease Database combining Administrative and Clinical data (BELCODAC), to investigate patients with CHD. Methods: Data on clinical characteristics from three university hospitals in Belgium (Leuven, Ghent and Brussels) were merged with mortality and socio-economic data from the official Belgian statistical office (StatBel), and with healthcare use data from the InterMutualistic Agency, an overarching national organization that collects data from the seven sickness funds for all Belgian citizens. Over 60 variables with multiple entries over time are included in the database. Results: BELCODAC contains data on 18,510 patients, of which 8926 patients (48%) have a mild, 7490 (41%) a moderately complex and 2094 (11%) a complex anatomical heart defect. The most prevalent diagnosis is Ventricular Septal Defect in 3879 patients (21%), followed by Atrial Septal Defect in 2565 patients (14%). Conclusions: BELCODAC comprises longitudinal data on patients with CHD in Belgium. This will help build evidence-based provision of care to the changing CHD population

Palliative care for solid transplant candidates and recipients: protocol for a scoping review of the literature

Palliative care for solid transplant candidates and recipients: protocol for a scoping review of the literatur

Mental health in adult congenital heart disease

Mental health issues are common in individuals with congenital heart disease (CHD), stemming from various factors such as traumatic experiences, existential questions, and genetic predisposition. This article provides an overview of the literature on mental disorders and mental health in adults with CHD (ACHD) and presents new data on mental health as a predictor of quality of life (QoL). Empirical data show that disorders such as depression, anxiety, bipolar disorder, psychosis, Attention Deficit Hyperactivity Disorder (ADHD), and autism spectrum disorders occur more often in people with CHD than in healthy counterparts (Graphical abstract). Further, mental health is a strong predictor of QoL. Therefore, psychological interventions should be integrated into CHD care to enhance mental health and QoL of afflicted patients

The Temperature Feature of ChatGPT: Modifying Creativity for Clinical Research

More clinicians and researchers are exploring uses for large language model chatbots, such as ChatGPT, for research, dissemination, and educational purposes. Therefore, it becomes increasingly relevant to consider the full potential of this tool, including the special features that are currently available through the application programming interface. One of these features is a variable called temperature, which changes the degree to which randomness is involved in the model’s generated output. This is of particular interest to clinicians and researchers. By lowering this variable, one can generate more consistent outputs; by increasing it, one can receive more creative responses. For clinicians and researchers who are exploring these tools for a variety of tasks, the ability to tailor outputs to be less creative may be beneficial for work that demands consistency. Additionally, access to more creative text generation may enable scientific authors to describe their research in more general language and potentially connect with a broader public through social media. In this viewpoint, we present the temperature feature, discuss potential uses, and provide some examples

Illness identity: capturing the influence of illness on the person’s sense of self

status: Published onlin

Illness identity as predictor of healthcare use in adults with congenital heart disease

Background: To facilitate optimal care for patients with congenital heart disease (CHD), it is important to know which factors contribute to their healthcare use. Clinical and psychological characteristics, such as depressive symptoms, illness perceptions and personality, have been found to predict healthcare use. However, a relatively new concept, illness identity, which assesses the degree to which CHD is integrated into one's identity, has not yet been investigated in relation with healthcare use. Purpose: To examine the predictive value of illness identity on healthcare use in adults with CHD. Methods: In a longitudinal cohort study, 216 adults (mean age=38 years; 50% men) were selected from the database of congenital cardiology in one large-volume university hospital. The self-reported Illness Identity Questionnaire was used to assess the 4 illness identity dimensions: engulfment, rejection, acceptance, and enrichment on baseline. After 1 year, self-reported healthcare use for the CHD or other reasons over the past 6 months was administered: hospitalisations; visits to general practitioners (GP); visits to medical specialists; and emergency department visits. Binary and multinomial logistic regression analyses were conducted, adjusting for age, sex and disease complexity. Results: The more the heart disease dominates one's identity (i.e., engulfment), the more likely this person was to be hospitalised (OR=3.41; 95% CI=1.48–7.87), to have multiple visits at the GP (OR=2.31; 95% CI=1.25–4.25), and to have one (OR=1.98; 95% CI=1.16–3.36) or multiple visits (OR=3.99; 95% CI=2.01–7.92) at the medical specialist, all related to their CHD. They also had multiple visits at the specialist not related to their CHD (OR=1.95; 95% CI=1.07–3.57). Rejection, acceptance and enrichment did not predict healthcare use. Conclusion: When adjusted for age, sex and disease complexity, engulfment predicts healthcare use related to CHD in the upcoming year. Future research should investigate the unique contribution of illness identity in terms of preventing inappropriate healthcare use.status: publishe

Illness identity: a novel predictor for healthcare use in adults with congenital heart disease.

Background: To optimize healthcare use of adults with congenital heart disease (CHD), all important predictors of healthcare utilization should be identified. Clinical and psychological characteristics (e.g., age and depression) have been found to be associated with healthcare use. However, the concept of illness identity, which assesses the degree to which CHD is integrated into one’s identity, has not yet been investigated in association with healthcare use. Hence, the purpose of the study is to examine the predictive value of illness identity for healthcare use. Methods and Results: In this ambispective analytical observational cohort study, 216 adults with CHD were included. The self-reported Illness Identity Questionnaire was used to assess illness identity states: engulfment, rejection, acceptance, and enrichment. After one year, self-reported healthcare use for CHD or other reasons over the past 6 months was assessed including hospitalizations; visits to general practitioner; visits to medical specialists; and emergency room visits. Binary logistic and negative binomial regression analyses were conducted, adjusting for age, sex, disease complexity, and depressive and anxious symptoms. The more profound the heart defect dominated one’s identity (i.e., engulfment), the more likely this person was to be hospitalized (OR=3.76;95%CI=1.43-9.86), to visit a medical specialist (OR=2.32;95%CI=1.35-4.00) or a general practitioner (OR=1.78;95%CI=1.01-3.17), because of their heart defect. Conclusions: Illness identity, more specifically engulfment, has a unique predictive value for the occurrence of healthcare encounters. This association deserves further investigation, in which the directionality of effects and the contribution of illness identity in terms of preventing inappropriate healthcare use should be determined.status: publishe

Patient and treatment characteristics associated with patient activation in patients undergoing hemodialysis: a cross-sectional study

Abstract Background Patient activation is associated with better outcomes and lower costs. Although the concept is widely investigated, little attention was given to patient activation and its predictors in patients undergoing hemodialysis. Hence, we aimed to investigate the level of patient activation and aimed to determine patient- and treatment-related predictors of activation in patients undergoing hemodialysis. Methods This cross-sectional observational study recruited patients undergoing hemodialysis in three Flemish hospitals. Participants were questioned about patient characteristics (i.e., age, sex, education, employment, children, social support, leisure-time, living condition, and care at home), treatment- and health-related characteristics (i.e., hospital, time since first dialysis, transplantation, self-reported health (EQ-VAS) and depressive symptoms (PHQ-2)), and patient activation (PAM-13). Univariate and multiple linear regression analyses with dummy variables were conducted to investigate the associations between the independent variables and patient activation. Results The average patient activation-score was 51. Of 192 patients, 44% patients did not believe they had an important role regarding their health. Multiple linear regression showed that older patients, who reported being in bad health, treated in a particular hospital, without leisure-time activities, and living in a residential care home, had lower patient activation. These variables explained 31% of the variance in patient activation. Based on literature, we found that activation of patients on hemodialysis is low, compared to that of other chronic patient groups. Conclusion It could be useful to implement patient activation monitoring, since the level of activation is low in patients undergoing hemodialysis. Older patients, who reported being in bad health, treated in a particular hospital, without leisure-time activities, living in a residential care home, are at higher risk for lower activation