Use of electronic patient data storage for evaluating and setting the risk category of late effects in childhood cancer survivors

Abstract

Background: Many of the late effects of cancer treatment in childhood may occur even decades after the treatment, and only a minority of the survivors remain as healthy as their peers. Providing appropriate long-term care for childhood cancer survivors after transition to primary health care is a challenge. Both survivors and primary care providers need information on potential late effects. The lack of a systematic late effect follow-up plan may lead to excessive use of health care services or delayed intervention. While manual compilation of individual follow-up plans is time consuming for experienced clinicians, electronic algorithms may be feasible. Procedure: In Finland, international guidelines for determining the risk of late effects have been implemented. Nationally, Turku University Hospital was asked with developing an automatized system for calculating the risk of late effects, based on electronic patient records saved in the hospital data lake. An electronic algorithm that uses details from exposure-based health screening guidelines published by the Children's Oncology Group was created. The results were compared with those manually extracted by an experienced clinician. Results: Significant concordance between the manual and algorithm-based risk classification was found. A total of 355 patients received a classification using the algorithm, and 325 of those matched with the manual categorization, producing a Cohen's coefficient of 0.91 (95% confidence interval 0.88-0.95). Conclusion: Automated algorithms can be used to categorize childhood cancer survivors efficiently and reliably into late effect risk groups. This further enables automatized compilation of appropriate individual late effect follow-up plan for all survivors. K E Y W O R D S algorithm, childhood cancer survivor, electronic tool, late effect, long-term follow up 1 INTRODUCTION Childhood cancer survivors (CCSs) with late effects comprise a significant new patient group in the health care system, and the num-Abbreviations: CCS, childhood cancer survivor; CED, cyclophosphamide equivalent doses; CRP, C-reactive protein; HSCT, hematopoietic stem cell transplantation; ICD, International Classification of Diseases ber of CCSs is constantly increasing. The current overall survival rate for childhood malignancies is approximately 80%. 1,2 However, studies show that virtually all survivors develop at least one chronic health condition by the age of 45 years. 3-5 In many countries, individualized follow-up plans for CCSs are still not implemented. However, many patients could benefit from anticipatory guidance regarding health promotion and disease prevention aimed at minimizing the risk of

A software tool to support follow-up care in a French childhood cancer cohort: construction and feasibility

“…Nevertheless, the availability of a LTFU care, a personalized treatment summary, and a survivorship care plan for every childhood and young adult former patient is still not equal throughout Europe [ 28 ]. A number of digital tools have been described and developed across Europe in response to this challenge, including SurPass (an Italian initiative now available in 6 European countries) [ 23 ], and the Scandinavian tool (currently available in 2 countries) [ 29 ]. While some of these tools focus on quality of life digital tools [ 30 ], others develop lifestyle modules for preventive care [ 4 ].…”

Surveillance for radiation‐related late effects in childhood cancer survivors: The impact of using volumetric dosimetry

“…Approaches have been developed to automate the extraction of this information, facilitating the creation of patient-specific guides. 26 Such care plans have been shown to enhance survivors' understanding of their follow-up needs 27 and create a crucial reference for future care providers. 28 Use of VD to determine late effects surveillance aligns with the goal to improve patient knowledge of their own health state while taking advantage of available technology and personalized medicine.…”

“…Comprehensive treatment profiles personalized for each patient, often referred to as survivorship care plans, 25 allow for integration of this data, and can be compiled by the specific treating providers at the end of therapy. Approaches have been developed to automate the extraction of this information, facilitating the creation of patient‐specific guides 26 . Such care plans have been shown to enhance survivors' understanding of their follow‐up needs 27 and create a crucial reference for future care providers 28 .…”