Publication loaded menu close info list link CLOSE article Big data to analyze patterns of care and improve outcomes for children with cerebral palsy * navigate_before *BACK info *Details Details Cover Image ARTICLE Big data to analyze patterns of care and improve outcomes for children with cerebral palsy Felix Scholtes, Philippe Kolh format_quote CITE © 2021 Mac Keith Press https://doi.org/10.1111/dmcn.15027 Published inDevelopmental Medicine & Child Neurology PublisherJohn Wiley & Sons, Ltd ISSN0012-1622 eISSN1469-8749 Received25 July 2021 Accepted27 July 2021 Published14 October 2021 Volume63 Issue11 Pages1246 - 1246 * navigate_before *BACK list *Outline *OUTLINE sentiment_very_dissatisfied *This publication does not have an outline. * navigate_before *BACK perm_media *Materials *Materials o *FIGURES navigate_next <#figures-tab-pane> o *SUPPLEMENTS navigate_next <#supplementary-tab-pane> remove_from_queue *Figures cannot be displayed at the moment. image *Supplementary materials are not available for display. * navigate_before *BACK image *Figures * navigate_before *BACK perm_media *Supplements * navigate_before *BACK link *Links *Links o *REFERENCES navigate_next <#references-tab-pane> o *CITED BY navigate_next <#citations-tab-pane> o *RECOMMENDED navigate_next <#recommended-tab-pane> * navigate_before *BACK link *References * navigate_before *BACK format_quote *Cited by * navigate_before *BACK more_horiz *Recommended open_in_new View in Publisher's site format_size Alignment format_align_left format_align_justify Font Size remove add Hyphenation /close / Return to default styles Reading Flow swap_vert swap_horiz fullscreen fullscreen_exit remove_circle_outline add_circle_outline search *SEARCH search close group_add Copy Access more_horiz * print*Print document * *Offline reading * stop offline_pin *Save for offline reading *Saving for offline reading • 73.6 KB *Saved for offline reading *Remove *Removing from offline documents * library_books *View Offline documents * Login / Register get_app Big data to analyze patterns of care and improve outcomes forchildren with cerebral palsyFELIX SCHOLTES|PHILIPPE KOLHDepartment of Biomedical and Preclinical Sciences, University of Liege, Liege,Belgium.doi: 10.1111/dmcn.15027This commentary is on the original article by Kurowski et al. on pages1337–1343 of this issue.In their paper, Kurowski et al.1chose a particularly rele-vant example of complex clinical practice, as children withCP need variable, targeted, and adaptive care from multi-ple caregivers and in diverse settings.Based on a retrospective assessment of data made availablethrough electronic health records, 6369 children (mean age8y 2mo; range: 0–21y) were selected. Machine learning hier-archical clustering was used to determine clusters of care andthe ratio of in-person to care-coordination visits calculatedfor each specialty. Seven clusters of care were identified,including musculoskeletal and function, neurological, highfrequency and urgent care, procedural, comorbid diagnoses,developmental and behavioral, and primary care. Networkanalysis showed shared membership in several clusters. In-person to care-coordination visit ratio was 1:5 overall forhealth care encounters, implying that most interactions withcare teams occur outside of in-person visits.These results illustrate how health care data, whenentered into an electronic health record, are not only col-lected, but also structured and analyzed. Such an analysis isnot only beneficial for the patient through assessment ofhow care is provided for this particular individual, but alsoprovides substance for a more global assessment of caremodels and how, overall, health care is provided in practice.The described elucidation of the ‘breadth and depth’of the interaction of specific patient populations with thehealth care system can therefore lay the basis for stream-lining care. Although less common than other chronicdiseases, CP is particularly relevant for its complexityand its need for multidisciplinary care. Less complex butmore common chronic diseases, such as congestive heartfailure, diabetes mellitus, chronic obstructive pulmonarydisease, or dementia, would be accessible to the samekind of analyses, with potential impacts with a magnitudethat might at least equal the one reported for patientswith CP. Ideally, then, the broader and systematicchanges that could result from this approach would leadto benefits both for the individual patient, through morestructured interventions, and for the system, throughhigher efficiency.Furthermore, the authors are correct to point out thepotential benefits beyond measurable efficacy, for examplein terms of potential decrease in stressors like uncoordi-nated and urgent visits to emergency departments.1Although the population of children with CP may repre-sent the psychological distress associated with illness par-ticularly well, this relevant point, although not specificallyaddressed by the study, is indeed crucial in the care weprovide for any patient.With the cost of providing health care increasing atmore than the rate of gross domestic product in everyindustrialized country, smart systems are likely to play asignificant part in the future of health care. By more accu-rately predicting the demand for services, waste can bereduced and insurance can become more efficient.2How-ever, adequate management of big data implies a significantevolvement of the hospitals’ information systems, with astrong interaction between medical practitioners and engi-neers to avoid irrelevant clinical data being analyzed andproviding irrelevant results.REFERENCES1. Kurowski BG, Greve K, Bailes AF, et al. Electronichealth record and patterns of care for children with cere-bral palsy.Dev Med Child Neurol2021;63: 1337–43.2. Ricco J-B, Guetarni F, Kolh P. Learning from artificialintelligence and big data in health care.Eur J Vasc Endo-vasc Surg2020;59: 868–9.1246Developmental Medicine & Child Neurology2021, 63: 1242–1247 sort play_circle_filled play_circle_filled arrow_back *BACK chapter title here figure title here get_app All Materials (0) SHOW All materials 0 Figures 0 Tables 0 Videos 0 Audio files 0 Code snippets 0 Other files 0 fullscreen fullscreen_exit remove_circle_outline add_circle_outline play_circle_filled play_circle_filled arrow_back *BACK CLOSE figure title here get_app All Materials publication title here