End-of-life and palliative care provision to adults with congenital heart disease: mortality follow-back study using administrative data
Bibliographic record
Abstract
Abstract Background Although many adults with congenital heart disease (CHD) still die prematurely, end-of-life care for these patients receives limited attention. There are indications that current care provision at the end of life is burdensome, expensive, and not in line with patients' needs and preferences. We sought to analyse end-of-life care in adult CHD patients to determine whether health services need to be optimized. Purpose This study aimed to describe patterns of healthcare consumption of adults with CHD who died in the last year of life. Methods This retrospective mortality follow-back study used data of the BELgian COngenital heart disease Database combining Administrative and Clinical data (BELCODAC), including individually linked healthcare claims, death certificates and clinical data from adults with CHD in Flanders (Belgium). For this study, adults with CHD who died between 2007 and 2016 from any cause except sudden death, accident or violence, were selected for inclusion. Accidental, violent, and sudden deaths were identified based on causes of death and healthcare use in the last 3 months of life. Healthcare consumption was based on nomenclature codes derived from healthcare claims data. Results A total of 327 eligible patients (median age: 58 y; 54% women; 43% mild CHD; 45% moderate CHD; 11% complex CHD; 49% cardiovascular cause of death) were identified. During the last year of life, healthcare use increased substantially (Fig. 1). During the last month of life, 54% of patients were hospitalised, 55% visited the emergency department, and 15% were admitted to an intensive care unit at least once (Fig. 2). A total of 8% and 5% of patients underwent heart surgery or catherization in the last month of life, respectively. Furthermore, 70% of patients had at least one encounter with a general practitioner and 11% with a CHD specialist in the last month of life. Specialist palliative care was provided to 13% of patients in the last month of life. When looking at the subgroup of patients with CHD that died due to a cardiovascular cause, proportions of patients that were hospitalised or had visits at the emergency department or intensive care unit in the last month of life were similar (Fig. 2). However, these patients underwent more heart surgeries (11%) and catherizations (8%), had more encounters with CHD specialists (15%), and received remarkably less specialized palliative care (4%) in the last month of life. Conclusion Resource utilization increased substantially during the last year of life, resulting in high acute healthcare consumption in the last month of life. It is remarkable that only a minority of patients received palliative care, especially when looking at patients who died due to a cardiovascular cause. Our findings motivate the need to assess if and how end-of-life is planned for adults with CHD. Future studies using qualitative analyses and survey methodology are needed to optimize the management of end-of-life care. Funding Acknowledgement Type of funding sources: Public grant(s) – EU funding. Main funding source(s): Research Foundation Flanders, European Society of Cardiology, Koning Boudewijnstichting, National Foundation on Research in Pediatric Cardiology, Swedish Research Council for Health, Working Life and Welfare-FORTE
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".