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Assessing the validity of administrative health data for the identification of children and youth with autism spectrum disorder in Ontario / Jennifer D. BROOKS in Autism Research, 14-5 (May 2021)
[article]
Titre : Assessing the validity of administrative health data for the identification of children and youth with autism spectrum disorder in Ontario Type de document : Texte imprimé et/ou numérique Auteurs : Jennifer D. BROOKS, Auteur ; Jasleen ARNEJA, Auteur ; Longdi FU, Auteur ; Farah E. SAXENA, Auteur ; Karen TU, Auteur ; Virgiliu Bogdan PINZARU, Auteur ; Evdokia ANAGNOSTOU, Auteur ; Kirk NYLEN, Auteur ; Natasha R. SAUNDERS, Auteur ; Hong LU, Auteur ; John MCLAUGHLIN, Auteur ; Susan E. BRONSKILL, Auteur Article en page(s) : p.1037-1045 Langues : Anglais (eng) Mots-clés : Ontario administrative health data algorithm autism Index. décimale : PER Périodiques Résumé : Population-level identification of children and youth with ASD is essential for surveillance and planning for required services. The objective of this study was to develop and validate an algorithm for the identification of children and youth with ASD using administrative health data. In this retrospective validation study, we linked an electronic medical record (EMR)-based reference standard, consisting 10,000 individuals aged 1-24?years, including 112 confirmed ASD cases to Ontario administrative health data, for the testing of multiple case-finding algorithms. Sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), and corresponding 95% confidence intervals (CI) were calculated for each algorithm. The optimal algorithm was validated in three external cohorts representing family practice, education, and specialized clinical settings. The optimal algorithm included an ASD diagnostic code for a single hospital discharge or emergency department visit or outpatient surgery, or three ASD physician billing codes in 3?years. This algorithm's sensitivity was 50.0% (95%CI 40.7-88.7%), specificity 99.6% (99.4-99.7), PPV 56.6% (46.8-66.3), and NPV 99.4% (99.3-99.6). The results of this study illustrate limitations and need for cautious interpretation when using administrative health data alone for the identification of children and youth with ASD. LAY SUMMARY: We tested algorithms (set of rules) to identify young people with ASD using routinely collected administrative health data. Even the best algorithm misses more than half of those in Ontario with ASD. To understand this better, we tested how well the algorithm worked in different settings (family practice, education, and specialized clinics). The identification of individuals with ASD at a population level is essential for planning for support services and the allocation of resources. Autism Res 2021, 14: 1037-1045. © 2021 The Authors. Autism Research published by International Society for Autism Research published by Wiley Periodicals LLC. En ligne : http://dx.doi.org/10.1002/aur.2491 Permalink : https://www.cra-rhone-alpes.org/cid/opac_css/index.php?lvl=notice_display&id=444
in Autism Research > 14-5 (May 2021) . - p.1037-1045[article] Assessing the validity of administrative health data for the identification of children and youth with autism spectrum disorder in Ontario [Texte imprimé et/ou numérique] / Jennifer D. BROOKS, Auteur ; Jasleen ARNEJA, Auteur ; Longdi FU, Auteur ; Farah E. SAXENA, Auteur ; Karen TU, Auteur ; Virgiliu Bogdan PINZARU, Auteur ; Evdokia ANAGNOSTOU, Auteur ; Kirk NYLEN, Auteur ; Natasha R. SAUNDERS, Auteur ; Hong LU, Auteur ; John MCLAUGHLIN, Auteur ; Susan E. BRONSKILL, Auteur . - p.1037-1045.
Langues : Anglais (eng)
in Autism Research > 14-5 (May 2021) . - p.1037-1045
Mots-clés : Ontario administrative health data algorithm autism Index. décimale : PER Périodiques Résumé : Population-level identification of children and youth with ASD is essential for surveillance and planning for required services. The objective of this study was to develop and validate an algorithm for the identification of children and youth with ASD using administrative health data. In this retrospective validation study, we linked an electronic medical record (EMR)-based reference standard, consisting 10,000 individuals aged 1-24?years, including 112 confirmed ASD cases to Ontario administrative health data, for the testing of multiple case-finding algorithms. Sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), and corresponding 95% confidence intervals (CI) were calculated for each algorithm. The optimal algorithm was validated in three external cohorts representing family practice, education, and specialized clinical settings. The optimal algorithm included an ASD diagnostic code for a single hospital discharge or emergency department visit or outpatient surgery, or three ASD physician billing codes in 3?years. This algorithm's sensitivity was 50.0% (95%CI 40.7-88.7%), specificity 99.6% (99.4-99.7), PPV 56.6% (46.8-66.3), and NPV 99.4% (99.3-99.6). The results of this study illustrate limitations and need for cautious interpretation when using administrative health data alone for the identification of children and youth with ASD. LAY SUMMARY: We tested algorithms (set of rules) to identify young people with ASD using routinely collected administrative health data. Even the best algorithm misses more than half of those in Ontario with ASD. To understand this better, we tested how well the algorithm worked in different settings (family practice, education, and specialized clinics). The identification of individuals with ASD at a population level is essential for planning for support services and the allocation of resources. Autism Res 2021, 14: 1037-1045. © 2021 The Authors. Autism Research published by International Society for Autism Research published by Wiley Periodicals LLC. En ligne : http://dx.doi.org/10.1002/aur.2491 Permalink : https://www.cra-rhone-alpes.org/cid/opac_css/index.php?lvl=notice_display&id=444 Identifying Children and Youth With Autism Spectrum Disorder in Electronic Medical Records: Examining Health System Utilization and Comorbidities / Jennifer D. BROOKS in Autism Research, 14-2 (February 2021)
[article]
Titre : Identifying Children and Youth With Autism Spectrum Disorder in Electronic Medical Records: Examining Health System Utilization and Comorbidities Type de document : Texte imprimé et/ou numérique Auteurs : Jennifer D. BROOKS, Auteur ; Susan E. BRONSKILL, Auteur ; Longdi FU, Auteur ; Farah E. SAXENA, Auteur ; Jasleen ARNEJA, Auteur ; Virgiliu Bogdan PINZARU, Auteur ; Evdokia ANAGNOSTOU, Auteur ; Kirk NYLEN, Auteur ; John MCLAUGHLIN, Auteur ; Karen TU, Auteur Article en page(s) : p.400-410 Langues : Anglais (eng) Mots-clés : Asd algorithm autism comorbidity electronic medical record health system use Index. décimale : PER Périodiques Résumé : Autism spectrum disorder (ASD) is a neurodevelopmental disorder requiring significant health and educational resources for affected individuals. A reference standard for ASD was generated from an existing population-based cohort of 10,000 children and youth aged 1-24?years who were randomly selected for chart abstraction from 29,256 patients from 119 family physicians. We developed and validated an algorithm to identify children and youth with ASD within an electronic medical record system (N = 80,237, aged 1-24?years) in order to examine the prevalence of comorbidities and quantify health system utilization within the cohort. We identified 1,062 children and youth with ASD representing a prevalence of 1.32%. Compared to individuals without ASD, those with ASD had a higher prevalence of asthma, were more likely to visit a specialist, undergo surgery, and be hospitalized for psychiatric reasons. Children and youth with ASD in Ontario have complex health system needs, illustrated through a significant burden of comorbidities and increased health system utilization. LAY SUMMARY: Our paper generates population-based estimates of health system use by children and youth with ASD, who have a higher burden of comorbidities than the general population. We developed a case-finding algorithm and applied it in electronic medical records to create a cohort of children and youth with ASD, thereby generating an important resource to further study the health care needs of individuals with ASD. En ligne : http://dx.doi.org/10.1002/aur.2419 Permalink : https://www.cra-rhone-alpes.org/cid/opac_css/index.php?lvl=notice_display&id=441
in Autism Research > 14-2 (February 2021) . - p.400-410[article] Identifying Children and Youth With Autism Spectrum Disorder in Electronic Medical Records: Examining Health System Utilization and Comorbidities [Texte imprimé et/ou numérique] / Jennifer D. BROOKS, Auteur ; Susan E. BRONSKILL, Auteur ; Longdi FU, Auteur ; Farah E. SAXENA, Auteur ; Jasleen ARNEJA, Auteur ; Virgiliu Bogdan PINZARU, Auteur ; Evdokia ANAGNOSTOU, Auteur ; Kirk NYLEN, Auteur ; John MCLAUGHLIN, Auteur ; Karen TU, Auteur . - p.400-410.
Langues : Anglais (eng)
in Autism Research > 14-2 (February 2021) . - p.400-410
Mots-clés : Asd algorithm autism comorbidity electronic medical record health system use Index. décimale : PER Périodiques Résumé : Autism spectrum disorder (ASD) is a neurodevelopmental disorder requiring significant health and educational resources for affected individuals. A reference standard for ASD was generated from an existing population-based cohort of 10,000 children and youth aged 1-24?years who were randomly selected for chart abstraction from 29,256 patients from 119 family physicians. We developed and validated an algorithm to identify children and youth with ASD within an electronic medical record system (N = 80,237, aged 1-24?years) in order to examine the prevalence of comorbidities and quantify health system utilization within the cohort. We identified 1,062 children and youth with ASD representing a prevalence of 1.32%. Compared to individuals without ASD, those with ASD had a higher prevalence of asthma, were more likely to visit a specialist, undergo surgery, and be hospitalized for psychiatric reasons. Children and youth with ASD in Ontario have complex health system needs, illustrated through a significant burden of comorbidities and increased health system utilization. LAY SUMMARY: Our paper generates population-based estimates of health system use by children and youth with ASD, who have a higher burden of comorbidities than the general population. We developed a case-finding algorithm and applied it in electronic medical records to create a cohort of children and youth with ASD, thereby generating an important resource to further study the health care needs of individuals with ASD. En ligne : http://dx.doi.org/10.1002/aur.2419 Permalink : https://www.cra-rhone-alpes.org/cid/opac_css/index.php?lvl=notice_display&id=441 Brief Report: Two Day-Date Processing Methods in an Autistic Savant Calendar Calculator / Matteo DE MARCO in Journal of Autism and Developmental Disorders, 46-3 (March 2016)
[article]
Titre : Brief Report: Two Day-Date Processing Methods in an Autistic Savant Calendar Calculator Type de document : Texte imprimé et/ou numérique Auteurs : Matteo DE MARCO, Auteur ; Alessandro IAVARONE, Auteur ; Giovanna SANTORO, Auteur ; Sergio CARLOMAGNO, Auteur Article en page(s) : p.1096-1102 Langues : Anglais (eng) Mots-clés : Asperger Autism Calendrical calculation Memory Algorithm Index. décimale : PER Périodiques Résumé : Special ability in computing the day of week for given dates was observed in a 24 year-old male (FB) diagnosed with Asperger syndrome. FB performed almost flawlessly (98.2 %) both with past and future dates, over a span of 40 years. Response latency was slower as temporal remoteness of future dates increased. Within the future timespan, FB’s performance was consistent with the active use of calendar regularities. On the contrary, within the past timespan (for which no remoteness effect was seen), his performance was mainly linked to memory retrieval of personal events. The case presented here complements the existent literature on calendar calculators, as, for first time, two distinct day-date processing styles are described in the same individual. En ligne : http://dx.doi.org/10.1007/s10803-015-2626-z Permalink : https://www.cra-rhone-alpes.org/cid/opac_css/index.php?lvl=notice_display&id=282
in Journal of Autism and Developmental Disorders > 46-3 (March 2016) . - p.1096-1102[article] Brief Report: Two Day-Date Processing Methods in an Autistic Savant Calendar Calculator [Texte imprimé et/ou numérique] / Matteo DE MARCO, Auteur ; Alessandro IAVARONE, Auteur ; Giovanna SANTORO, Auteur ; Sergio CARLOMAGNO, Auteur . - p.1096-1102.
Langues : Anglais (eng)
in Journal of Autism and Developmental Disorders > 46-3 (March 2016) . - p.1096-1102
Mots-clés : Asperger Autism Calendrical calculation Memory Algorithm Index. décimale : PER Périodiques Résumé : Special ability in computing the day of week for given dates was observed in a 24 year-old male (FB) diagnosed with Asperger syndrome. FB performed almost flawlessly (98.2 %) both with past and future dates, over a span of 40 years. Response latency was slower as temporal remoteness of future dates increased. Within the future timespan, FB’s performance was consistent with the active use of calendar regularities. On the contrary, within the past timespan (for which no remoteness effect was seen), his performance was mainly linked to memory retrieval of personal events. The case presented here complements the existent literature on calendar calculators, as, for first time, two distinct day-date processing styles are described in the same individual. En ligne : http://dx.doi.org/10.1007/s10803-015-2626-z Permalink : https://www.cra-rhone-alpes.org/cid/opac_css/index.php?lvl=notice_display&id=282 Children with autism spectrum disorder produce more ambiguous and less socially meaningful facial expressions: an experimental study using random forest classifiers / Charline GROSSARD in Molecular Autism, 11 (2020)
[article]
Titre : Children with autism spectrum disorder produce more ambiguous and less socially meaningful facial expressions: an experimental study using random forest classifiers Type de document : Texte imprimé et/ou numérique Auteurs : Charline GROSSARD, Auteur ; Arnaud DAPOGNY, Auteur ; David COHEN, Auteur ; Sacha BERNHEIM, Auteur ; Estelle JUILLET, Auteur ; Fanny HAMEL, Auteur ; Stéphanie HUN, Auteur ; Jérémy BOURGEOIS, Auteur ; Hugues PELLERIN, Auteur ; Sylvie SERRET, Auteur ; Kevin BAILLY, Auteur ; Laurence CHABY, Auteur Article en page(s) : 5 p. Langues : Anglais (eng) Mots-clés : Algorithm Autism spectrum disorder Emotion Facial expressions Index. décimale : PER Périodiques Résumé : BACKGROUND: Computer vision combined with human annotation could offer a novel method for exploring facial expression (FE) dynamics in children with autism spectrum disorder (ASD). METHODS: We recruited 157 children with typical development (TD) and 36 children with ASD in Paris and Nice to perform two experimental tasks to produce FEs with emotional valence. FEs were explored by judging ratings and by random forest (RF) classifiers. To do so, we located a set of 49 facial landmarks in the task videos, we generated a set of geometric and appearance features and we used RF classifiers to explore how children with ASD differed from TD children when producing FEs. RESULTS: Using multivariate models including other factors known to predict FEs (age, gender, intellectual quotient, emotion subtype, cultural background), ratings from expert raters showed that children with ASD had more difficulty producing FEs than TD children. In addition, when we explored how RF classifiers performed, we found that classification tasks, except for those for sadness, were highly accurate and that RF classifiers needed more facial landmarks to achieve the best classification for children with ASD. Confusion matrices showed that when RF classifiers were tested in children with ASD, anger was often confounded with happiness. LIMITATIONS: The sample size of the group of children with ASD was lower than that of the group of TD children. By using several control calculations, we tried to compensate for this limitation. CONCLUSION: Children with ASD have more difficulty producing socially meaningful FEs. The computer vision methods we used to explore FE dynamics also highlight that the production of FEs in children with ASD carries more ambiguity. En ligne : http://dx.doi.org/10.1186/s13229-020-0312-2 Permalink : https://www.cra-rhone-alpes.org/cid/opac_css/index.php?lvl=notice_display&id=427
in Molecular Autism > 11 (2020) . - 5 p.[article] Children with autism spectrum disorder produce more ambiguous and less socially meaningful facial expressions: an experimental study using random forest classifiers [Texte imprimé et/ou numérique] / Charline GROSSARD, Auteur ; Arnaud DAPOGNY, Auteur ; David COHEN, Auteur ; Sacha BERNHEIM, Auteur ; Estelle JUILLET, Auteur ; Fanny HAMEL, Auteur ; Stéphanie HUN, Auteur ; Jérémy BOURGEOIS, Auteur ; Hugues PELLERIN, Auteur ; Sylvie SERRET, Auteur ; Kevin BAILLY, Auteur ; Laurence CHABY, Auteur . - 5 p.
Langues : Anglais (eng)
in Molecular Autism > 11 (2020) . - 5 p.
Mots-clés : Algorithm Autism spectrum disorder Emotion Facial expressions Index. décimale : PER Périodiques Résumé : BACKGROUND: Computer vision combined with human annotation could offer a novel method for exploring facial expression (FE) dynamics in children with autism spectrum disorder (ASD). METHODS: We recruited 157 children with typical development (TD) and 36 children with ASD in Paris and Nice to perform two experimental tasks to produce FEs with emotional valence. FEs were explored by judging ratings and by random forest (RF) classifiers. To do so, we located a set of 49 facial landmarks in the task videos, we generated a set of geometric and appearance features and we used RF classifiers to explore how children with ASD differed from TD children when producing FEs. RESULTS: Using multivariate models including other factors known to predict FEs (age, gender, intellectual quotient, emotion subtype, cultural background), ratings from expert raters showed that children with ASD had more difficulty producing FEs than TD children. In addition, when we explored how RF classifiers performed, we found that classification tasks, except for those for sadness, were highly accurate and that RF classifiers needed more facial landmarks to achieve the best classification for children with ASD. Confusion matrices showed that when RF classifiers were tested in children with ASD, anger was often confounded with happiness. LIMITATIONS: The sample size of the group of children with ASD was lower than that of the group of TD children. By using several control calculations, we tried to compensate for this limitation. CONCLUSION: Children with ASD have more difficulty producing socially meaningful FEs. The computer vision methods we used to explore FE dynamics also highlight that the production of FEs in children with ASD carries more ambiguity. En ligne : http://dx.doi.org/10.1186/s13229-020-0312-2 Permalink : https://www.cra-rhone-alpes.org/cid/opac_css/index.php?lvl=notice_display&id=427