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Record W4322757050 · doi:10.2196/42350

The Health Care Utilization and Medical Costs in Long-Term Follow-Up of Children Diagnosed With Leukemia, Solid Tumor, or Brain Tumor: Population-Based Study Using the National Health Insurance Claims Data

2023· article· en· W4322757050 on OpenAlexvenueno aff
James S Miser, Ben‐Chang Shia, Yi‐Wei Kao, Yen‐Lin Liu, Shih-Yen Chen, Wan‐Ling Ho

Bibliographic record

VenueJMIR Public Health and Surveillance · 2023
Typearticle
Languageen
FieldMedicine
TopicChildhood Cancer Survivors' Quality of Life
Canadian institutionsnot available
FundersNational Taiwan UniversityTaipei Medical UniversityFu Jen Catholic UniversityMinistry of Education, IndiaNational Taiwan University HospitalShin Kong Wu Ho-Su Memorial Hospital
KeywordsMedicinePopulationCancerHealth careFamily medicinePediatricsGerontologyEnvironmental healthDemographyInternal medicine

Abstract

fetched live from OpenAlex

BACKGROUND: Childhood cancer survivors are at a high risk of medical consequences of their disease and treatment. There is growing information about the long-term health issues of childhood cancer survivors; however, there are very few studies describing the health care utilization and costs for this unique population. Understanding their utilization of health care services and costs will provide the basis for developing strategies to better serve these individuals and potentially reduce the cost. OBJECTIVE: This study aims to determine the utilization of health services and costs for long-term survivors of childhood cancer in Taiwan. METHODS: This is a nationwide, population-based, retrospective case-control study. We analyzed the claims data of the National Health Insurance that covers 99% of the Taiwanese population of 25.68 million. A total of 33,105 children had survived for at least 5 years after the first appearance of a diagnostic code of cancer or a benign brain tumor before the age of 18 years from 2000 to 2010 with follow-up to 2015. An age- and gender-matched control group of 64,754 individuals with no cancer was randomly selected for comparison. Utilization was compared between the cancer and no cancer groups by χ2 test. The annual medical expense was compared by the Mann-Whitney U test and Kruskal-Wallis rank-sum test. RESULTS: At a median follow-up of 7 years, childhood cancer survivors utilized a significantly higher proportion of medical center, regional hospital, inpatient, and emergency services in contrast to no cancer individuals: 57.92% (19,174/33,105) versus 44.51% (28,825/64,754), 90.66% (30,014/33,105) versus 85.70% (55,493/64,754), 27.19% (9000/33,105) versus 20.31% (13,152/64,754), and 65.26% (21,604/33,105) versus 59.36% (38,441/64,754), respectively (all P<.001). The annual total expense (median, interquartile range) of childhood cancer survivors was significantly higher than that of the comparison group (US $285.56, US $161.78-US $535.80 per year vs US $203.90, US $118.98-US $347.55 per year; P<.001). Survivors with female gender, diagnosis before the age of 3 years, and diagnosis of brain cancer or a benign brain tumor had significantly higher annual outpatient expenses (all P<.001). Moreover, the analysis of outpatient medication costs showed that hormonal and neurological medications comprised the 2 largest costs in brain cancer and benign brain tumor survivors. CONCLUSIONS: Survivors of childhood cancer and a benign brain tumor had higher utilization of advanced health resources and higher costs of care. The design of the initial treatment plan minimizing long-term consequences, early intervention strategies, and survivorship programs have the potential to mitigate costs of late effects due to childhood cancer and its treatment.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.013
Threshold uncertainty score0.026

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0020.002
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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.

Opus teacher head0.080
GPT teacher head0.410
Teacher spread0.330 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations10
Published2023
Admission routes1
Has abstractyes

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