Accelerating autism diagnosis using asynchronous telehealth technology

Authors

  • Uwe Reischl School of Public and Population Health, College of Health Sciences, Boise State University, Boise, Idaho, USA
  • Michael J. Morrier Department of Psychiatry and Behavioral Sciences, Emory Autism Center, Emory University School of Medicine, Atlanta, Georgia, USA https://orcid.org/0000-0002-9219-437X
  • Gwen E. Mitchell College of Education, Health and Human Sciences, Curriculum and Instruction, University of Idaho, Moscow, Idaho, USA
  • Ron Oberleitner Behavior Imaging Solutions, Boise, Idaho, USA

DOI:

https://doi.org/10.18203/2394-6040.ijcmph20230613

Keywords:

Autism assessment and diagnosis, Telehealth, Timesaving benefits

Abstract

Background: Early identification and treatment of autism can prevent additional behavioral problems later in a child’s life. Long wait lists and travel limitations can often make it difficult for parents to obtain timely evaluations. A new telehealth technology has been developed that can provide clinicians with the ability to remotely observe a child’s behavior at home and allows parents to communicate with the clinician directly. The objective of this study was to compare the length of time from referral to the completion of a child’s diagnostic evaluation using asynchronous telehealth (TH) and using the traditional in-person assessment method (IPA).

Methods: Three tertiary autism diagnostic centers in the United States conducted this study between 2016 and 2018. All three institutional review boards approved the research. Twenty-eight children were assigned to an IPA group and 29 children were assigned to a TH group. The IPA assessment was based on a standard in-person evaluation. Telehealth assessments used the naturalistic observation diagnostic assessment (NODA) system. Data were analyzed using SPSS. Required sample size was determined by power analysis.

Results: For the three diagnostic centers, the average time from referral to completion of an autism diagnosis with IPA was 115 days and 66 days with telehealth.

Conclusions: The NODA TH video-capture smartphone‐based technology offered a significant timesaving advantage for families seeking autism diagnostic services. The TH technology provided families located in remote areas with easier access to autism evaluations.

References

American Psychiatric Association. Diagnostic and statistical manual of mental disorders. 5th ed. American Psychiatric Association Publishing; 2013.

Office of disease prevention and health promotion. Fact sheet: Healthy People 2030. Available at: www.healthypeople.gov. Accessed on 1 January 2023.

Elder JH, Brasher S, Alexander B. Identifying the barriers to early diagnosis and treatment in underserved individuals with autism spectrum disorders (ASD) and their families: A qualitative study. Issue Mental Health Nurs. 2016;37(6):412-20.

d'Apice K, Latham RM, vonStumm S. A naturalistic home observational approach to children’s language, cognition, and behavior. Dev Psychol. 2019;55(7):1414-27.

Nazneen N, Rozga A, Smith CJ, Oberleitner R, Abowd GD, Arriaga RI. A novel system for supporting autism diagnosis using home videos: iterative development and evaluation of system design. JMIR Mhealth Uhealth. 2015;3(2):68.

Osterling J, Dawson G. Early recognition of children with autism: a study of first birthday home videotapes. J Autism Development Disord. 1994;24(3):247-57.

Ozonoff S, Iosif AM, Young GS, Hepburn S, Thompson M, Colombi C, et al. Onset patterns in autism: correspondence between home video and parent report. J Am Acad Child Adolescent Psychiat. 2011;50(8):796-806.

Baio J, Wiggins L, Christensen DL, Maenner MJ, Daniels J, Warren Z, et al. Prevalence of autism spectrum disorder among children aged 8 years-autism and developmental disabilities monitoring network, 11 sites, United States, 2014. MMWR Surveill Summar. 2018;67(6):1.

Tariq Q, Daniels J, Schwartz JN, Washington P, Kalantarian H, Wall DP. Mobile detection of autism through machine learning on home video: A development and prospective validation study. PLoS Med. 2018;15(11):1002705.

Jashar DT, Fein D, Berry LN. Parental perceptions of a comprehensive diagnostic evaluation for toddlers at risk for autism spectrum disorder. J Autism Dev Disord. 2016;49:1763-77.

Dunn LM, Dunn DM. Peabody Picture Vocabulary Test. 4th edition. Bloomington, MN: Pearson; 2007.

Mullen EM. Mullen Scales of Early Learning. Circle Pines, MN: American Guidance Service; 1995.

Kaufman AS, Kaufman NL. Kaufman Brief Intelligence Test. 2nd ed. Bloomington, MN: Pearson; 2004.

Lord C, Rutter M, DiLavore PC, Risi S, Gotham K, Bishop S. Autism diagnostic observation schedule. 2nd edition (ADOS-2). Torrance, CA: Western Psychological Services; 2012.

Rutter M, LeCouteur A, Lord C. Autism diagnostic interview-revised. Los Angeles, CA: Western Psychological Services; 2003.

Sparrow SS, Cicchetti VD, Balla AD. Vineland Adaptive Behavior Scales. 2nd ed. Circle Pines, MN: American Guidance Service; 2005.

Oberleitner R. Comparison of the remote NODA assessment method to the in-person gold standard assessment method for ASD. BI Techn Monogr. 2015.

Nazneen N, Matthews N, Smith CJ, Rozga A, Abowd GD, Oberleitner R, et al. Use of a novel imaging technology for Nazneen N. supporting in-home collection and sharing of behavior specimens for diagnostic assessment of children with autism. Georgia, Institute of Technology; 2015.

Reischl U, Oberleitner R. Telehealth technology supporting symptom management of children with autism. 5th International Conference on Applied Human Factors and Ergonomics. 2014

Smith CJ, Rozga A, Matthews N, Oberleitner R, Nazneen N, Abowd G. Supplemental material for investigating the accuracy of a novel telehealth diagnostic approach for autism spectrum disorder. Psychol Assess. 2017;29(3):245-52.

Zuckerman K, Lindly OJ, Chavez AE. Timeliness of autism spectrum disorder diagnosis and use of services among U.S. elementary school-aged children. Psychiatr Serv. 2017;68(1):33-40.

Terry M. Telemedicine and autism: researchers and clinicians are just starting to consider telemedicine applications for the diagnosis and treatment of autism. Telemed EHealth. 2009;15(5):416-9.

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Published

2023-02-28

How to Cite

Reischl, U., Morrier, M., Mitchell, G., & Oberleitner, R. (2023). Accelerating autism diagnosis using asynchronous telehealth technology. International Journal Of Community Medicine And Public Health, 10(3), 1000–1004. https://doi.org/10.18203/2394-6040.ijcmph20230613

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Section

Original Research Articles