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Digital Health Technologies: Diagnostic Applications

Policy Number: MP-750

Latest Review Date: July 2023

Category: DME

POLICY:

Prescription digital health technologies for diagnostic application that have received clearance for marketing by the U.S. Food and Drug Administration as a diagnostic aid for autism spectrum disorder are considered investigational.

DESCRIPTION OF PROCEDURE OR SERVICE:

Digital health technologies is a broad term that includes categories such as mobile health, health information technology, wearable devices, telehealth and telemedicine, and personalized medicine. These technologies span a wide range of uses, from applications in general wellness to applications as a medical device, and include technologies intended for use as a medical product, in a medical product, as companion diagnostics, or as an adjunct to other medical products (devices, drugs, and biologics). The scope of this review includes only those digital technologies that are intended to be used for diagnostic application (detecting the presence or absence of a condition, the risk of developing a condition in the future, or treatment response [beneficial or adverse]) and meet the following 3 criterion- 1) Must meet the definition of "Software as a medical device" which states that software is intended to be used for a medical purpose, without being part of a hardware medical device or software that stores or transmits medical information. 2) Must have received marketing clearance or approval by the U.S. Food and Drug Administration either through the de novo premarket process or 510(k) process or pre-market approval and 3) Must be prescribed by a healthcare provider.

Autism Spectrum Disorder

Autism spectrum disorder (ASD) is a biologically based neurodevelopmental disorder characterized by persistent deficits in social communication and social interaction and restricted, repetitive patterns of behavior, interests, and activities. ASD can range from mild social impairment to severely impaired functioning; as many as half of individuals with autism are non-verbal and have symptoms that may include debilitating intellectual disabilities, inability to change routines, and severe sensory reactions. The American Psychiatric Association’s Diagnostic and Statistical Manual, Fifth Edition (DSM-5) provides standardized criteria to help diagnose ASD.

Diagnosis of ASD in the United States generally occurs in two steps: developmental screening followed by comprehensive diagnostic evaluation if screened positive. American Academy of Pediatrics (AAP) recommends general developmental screening at 9, 18 and 30 months of age and ASD specific screening at 18 and 24 months of age. Diagnosis and treatment in the first few years of life can have a strong impact on functioning as it allows for treatment during a key window of developmental plasticity. However, early diagnosis in the US remains an unmet need even though studies have demonstrated a temporal trend of decreasing mean ages at diagnosis over time. According to a 2020 study by Autism and Developmental Disabilities Monitoring (ADDM) Network, an active surveillance system that provides estimates of ASD in the US, reported median age of earliest known ASD diagnosis ranged from 36 months in California to 63 months in Minnesota.

Scope of Review

Software has become an important part of product development and is integrated widely into digital platforms that serve both medical and non-medical purposes. Three broad categories of software use in medical device are

  1. Software used in the manufacture or maintenance of a medical device (example software that monitors x-ray tube performance to anticipate the need for replacement),
  2. Software that is integral to a medical device or software in a medical device (example software used to "drive or control" the motors and the pumping of medication in an infusion pump)
  3. Software, which on its own is a medical device referred to as "Software as a Medical Device" (SaMD) (example, software that can track the size of a mole over time and determine the risk of melanoma)

The International Medical Device Regulators Forum, a consortium of medical device regulators from around the world led by the U.S. Food and Drug Administration (FDA) defines SaMD as "software that is intended to be used for one or more medical purposes that perform those purposes without being part of a hardware medical device". Such software was previously referred to by industry, international regulators, and health care providers as "standalone software," "medical device software," and/or "health software," and can sometimes be confused with other types of software.

The scope of this review includes only those digital technologies that are intended to be used for diagnostic application (detecting presence or absence of a condition, the risk of developing a condition in the future, or treatment response [beneficial or adverse]) and meet the following 3 criterion-

  1. Must meet the definition of "Software as a medical device" which states that software is intended to be used for a medical purpose, without being part of a hardware medical device or software that stores or transmits medical information.
  2. Must have received marketing clearance or approval by the U.S. Food and Drug Administration either through the de novo premarket process or 510(k) process or pre-market approval and
  3. Must be prescribed by a healthcare provider.

BCBSA Evaluation Framework for Digital Health Technologies

SaMDs, as defined by FDA, are subject to the same evaluation standards as other devices; the Blue Cross and Blue Shield Association Technology Evaluation Criterion are as follows:

  1. The technology must have final approval from the appropriate governmental regulatory bodies.
  2. The scientific evidence must permit conclusions concerning the effect of the technology on health outcomes.
  3. The technology must improve the net health outcome.a
  4. The technology must be as beneficial as any established alternatives.
  5. The improvement must be attainable outside the investigational settings.b

a The technology must assure protection of sensitive patient health information as per the requirements of the Health Insurance Portability and Accountability Act of 1996 (HIPAA)

b The technology must demonstrate usability in a real-world setting

Other regulatory authorities such as the United Kingdom's National Institute for Health and Care Excellence (NICE) have proposed standards to evaluate SaMD.

KEY POINTS:

This evidence review was created in April 2022 with a search of the PubMed database. The most recent literature update was performed through May 10, 2023.

Summary of Evidence:

For individuals who are in the age range of 18 to 72 months and in whom there is a suspicion of autism spectrum disorder (ASD) by a parent, caregiver, or healthcare provider and who receive Canvas Dx, the evidence includes a single, double-blind, multicenter, prospective, comparator cohort study of clinical validity. Relevant outcomes are test validity, change in disease status, functional outcomes, and quality of life. The study compared Canvas Dx output to diagnostic agreement by 2 or more independent specialists in a cohort of 18 to 72-month-olds with developmental delay concerns. The majority of study participants (68% or 290/425) were classified as “indeterminates” by Canvas DX. For the 32% of participants who received a determinate output (ASD positive or negative), sensitivity was 98.4% (95% CI, 91.6% to 100%), specificity was78.9% (95% CI, 67.6% to 87.7%), positive predictive value (PPV) was 80.8% (95% CI, 70.3% to 88.8%) and negative predictive value (NPV) was 98.3% (95% CI, 90.6% to100%). A major limitation in study relevance is the lack of clarity on how the test fits into the current pathway and the appropriate referral process subsequent to testing. It is unclear if Canvas Dx is a "rule-out" or "rule-in" test or perhaps both. Major limitations in the design and conduct of the study included missing data and lack of generalizability. The estimated dropout rate was 40%. Authors reported that COVID-19 control measures led to changes in study visit schedules, missed visits, patient discontinuations, and site closures (9 out of 14 sites). No clear description of reasons for discrepancy in the number of clinical sites (30 proposed sites versus 14 actual sites), characteristics of missing observations, or sensitivity analyses of missing data assumptions were provided. Issues related to the generalizability of the study findings were also noted. Data on participants stratified by enrollment sites/states and origin of primary concern for developmental delay (whether it was patient/caregiver or healthcare professional) was not reported. Other limitations include differences that may occur between the testing environments of a structured clinical trial setting versus the home setting and lack of data on usability outside a clinical trial. More clarity on these issues is needed to understand generalizability of this study. Evidence for the Canvas Dx has not directly demonstrated that the test is clinically useful, and a chain of evidence cannot be constructed to support its utility. The evidence is insufficient to determine that the technology results in an improvement in the net health outcome.

Practice Guidelines and Position Statements

American Academy of Pediatrics

The American Academy of Pediatrics (AAP) guidelines recommend ASD-specific universal screening in all children at ages 18 and 24 months in addition to developmental surveillance and monitoring. Toddlers and children should be referred for diagnostic evaluation when increased risk for developmental disorders (including ASD) is identified through screening and/or surveillance. Children should be referred for intervention for all identified developmental delays at the time of identification and not wait for an ASD diagnostic evaluation to take place. The AAP does not approve nor endorse any specific tool for screening purposes. The AAP has published a toolkit that provides a list of links to tools for developmental surveillance and screening for use at the discretion of the health care professional.

The American Academy of Child and Adolescent Psychiatry

The American Academy of Child and Adolescent Psychiatry recommends that the developmental assessment of young children and the psychiatric assessment of all children should routinely include questions about ASD symptomatology.

The UK National Screening Committee

The UK National Screening Committee does not recommend systematic population screening for ASD because:

  • There is not currently a test that is good enough for screening the general population
  • It is not known if screening would improve long term outcomes for children with autism
  • There is not an established approach to screening which is acceptable to parents

These recommendations were based on a summary of evidence published in 2012. The next review is estimated to be completed in 2022.

U.S. Preventive Services Task Force Recommendations

The U.S. Preventive Services Task Force (USPSTF) published recommendations for ASD in young children in 2016. The USPSTF concludes that the current evidence is insufficient to assess the balance of benefits and harms of screening for ASD in young children (children 18 to 30 months of age) for whom no concerns of ASD have been raised by their parents or a clinician.

KEY WORDS:

Canvas DX, Coagnoa App

APPROVED BY GOVERNING BODIES:

Digital health technologies that meet the current scope of review are shown in Table 1.

Table 1. Digital Health Technology for Diagnostic Applications

Application

Manufacturer

FDA Cleared Indication

Description

FDA Product Code

FDA Marketing Clearance

Year

Canvas DX (formerly known as Coagnoa App)

Cognoa

"Canvas Dx is intended for use by healthcare providers as an aid in the diagnosis of Autism Spectrum Disorder (ASD) for patients ages 18 months through 72 months who are at risk for developmental delay based on concerns of a parent, caregiver, or healthcare provider. The device is not intended for use as a stand-alone diagnostic device but as an adjunct to the diagnostic process. The device is for prescription use only (Rx only)."

Artificial intelligence app for use by health care providers as an adjunct in the diagnosis of autism spectrum disorder for patients ages 18 to 72 months. Canvas DX includes 3 questionnaires: parent/caregiver, a video analyst, and a health care provider, with an algorithm that synthesizes the 3 inputs for use by the primary care provider.

QPF

DEN200069

2021

FDA: U.S. Food and Drug Administration;

BENEFIT APPLICATION:

Coverage is subject to member’s specific benefits.  Group-specific policy will supersede this policy when applicable.

ITS: Home Policy provisions apply

FEP contracts: Special benefit consideration may apply.  Refer to member’s benefit plan.  

CURRENT CODING: 

There is no specific CPT or HCPCS coding for these devices.

E1399

Durable medical equipment, miscellaneous

REFERENCES:

  1. Abbas H, Garberson F, Liu-Mayo S, et al. Multi-modular AI Approach to Streamline Autism Diagnosis in Young Children. Sci Rep. Mar 19 2020; 10(1): 5014.
  2. American Psychiatric Association. Diagnostic and Statistical Manual of Mental Disorders (DSM-5), 5th ed. Washington, DC: American Psychiatric Association; 2013
  3. Autism Spectrum Disorder: Links to Commonly Used Screening Instruments and Tools (AAP Toolkits). American Academy of Pediatrics. Available at https://publications.aap.org/toolkits/pages/asd-screening-tools
  4. Berument SK, Rutter M, Lord C, et al. Autism screening questionnaire: diagnostic validity. Br J Psychiatry. Nov 1999; 175: 444-51.
  5. Canvas Dx Website. Accessed on April 25, 2022. Available at https://canvasdx.com/
  6. Canvas HCP User Guide. Available at https://cognoa-production-cms.s3.amazonaws.com/documents/LBL-001_ASD+Dx+-+HCP+Portal+IFU_Rev.+L.pdf
  7. Chandler S, Charman T, Baird G, et al. Validation of the social communication questionnaire in a population cohort of children with autism spectrum disorders. J Am Acad Child Adolesc Psychiatry. Oct 2007; 46(10): 1324-1332.
  8. Dawson G, Bernier R. A quarter century of progress on the early detection and treatment of autism spectrum disorder. Dev Psychopathol. Nov 2013; 25(4 Pt 2): 1455-72.
  9. Dawson G, Rogers S, Munson J, et al. Randomized, controlled trial of an intervention for toddlers with autism: the Early Start Denver Model. Pediatrics. Jan 2010; 125(1): e17-23.
  10. DuBay M, Watson LR, Mendez LI, et al. Psychometric Comparison of the English and Spanish Western-Hemisphere Versions of the Modified Checklist for Autism in Toddlers-Revised. J Dev Behav Pediatr. Dec 01 2021; 42(9): 717-725.
  11. Dumont-Mathieu T, Fein D. Screening for autism in young children: The Modified Checklist for Autism in Toddlers (M-CHAT) and other measures. Ment Retard Dev Disabil Res Rev. 2005; 11(3): 253-62.
  12. Eaves LC, Wingert H, Ho HH. Screening for autism: agreement with diagnosis. Autism. May 2006; 10(3): 229-42.
  13. Hertz-Picciotto I, Delwiche L. The rise in autism and the role of age at diagnosis. Epidemiology. Jan 2009; 20(1): 84-90.
  14. Hyman SL, Levy SE, Myers SM, et al. Identification, Evaluation, and Management of Children With Autism Spectrum Disorder. Pediatrics. Jan 2020; 145(1).
  15. International Medical Device Regulators Forum. Software as a Medical Device (SaMD): Key Definitions. 2013. http://www.imdrf.org/docs/imdrf/final/technical/imdrf-tech-131209-samd-key-definitions-140901.pdf. 
  16. Kleinman JM, Ventola PE, Pandey J, et al. Diagnostic stability in very young children with autism spectrum disorders. J Autism Dev Disord. Apr 2008; 38(4): 606-15.
  17. Leigh JP, Grosse SD, Cassady D, et al. Spending by California's Department of Developmental Services for Persons with Autism across Demographic and Expenditure Categories. PLoS One. 2016; 11(3): e0151970.
  18. Lipkin PH, Macias MM, Norwood KW, et al. Promoting Optimal Development: Identifying Infants and Young Children With Developmental Disorders Through Developmental Surveillance and Screening. Pediatrics. Jan 2020; 145(1).
  19. Maenner MJ, Shaw KA, Bakian AV, et al. Prevalence and Characteristics of Autism Spectrum Disorder Among Children Aged 8 Years - Autism and Developmental Disabilities Monitoring Network, 11 Sites, United States, 2018. MMWR Surveill Summ. Dec 03 2021; 70(11): 1-16.
  20. Megerian JT, Dey S, Melmed RD, et al. Evaluation of an artificial intelligence-based medical device for diagnosis of autism spectrum disorder. NPJ Digit Med. May 05 2022; 5(1): 57.
  21. National Institute for Health and Care Excellence (NICE). Evidence standards framework for digital health technologies. 2021. nice.org.uk/corporate/ecd7/chapter/section-a-evidence-for-effectiveness-standards. 
  22. Pierce K, Gazestani V, Bacon E, et al. Get SET Early to Identify and Treatment Refer Autism Spectrum Disorder at 1 Year and Discover Factors That Influence Early Diagnosis. J Pediatr. Sep 2021; 236: 179-188.
  23. Randall M, Egberts KJ, Samtani A, et al. Diagnostic tests for autism spectrum disorder (ASD) in preschool children. Cochrane Database Syst Rev. Jul 24 2018; 7: CD009044.
  24. Robins DL, Casagrande K, Barton M, et al. Validation of the modified checklist for Autism in toddlers, revised with follow-up (M-CHAT-R/F). Pediatrics. Jan 2014; 133(1): 37-45.
  25. Robins DL, Dumont-Mathieu TM. Early screening for autism spectrum disorders: update on the modified checklist for autism in toddlers and other measures. J Dev Behav Pediatr. Apr 2006; 27(2 Suppl): S111-9.
  26. Salisbury LA, Nyce JD, Hannum CD, et al. Sensitivity and Specificity of 2 Autism Screeners Among Referred Children Between 16 and 48 Months of Age. J Dev Behav Pediatr. Apr 2018; 39(3): 254-258.
  27. Siu AL, Bibbins-Domingo K, Grossman DC, et al. Screening for Autism Spectrum Disorder in Young Children: US Preventive Services Task Force Recommendation Statement. JAMA. Feb 16 2016; 315(7): 691-6.
  28. Stone WL, Coonrod EE, Ousley OY. Brief report: screening tool for autism in two-year-olds (STAT): development and preliminary data. J Autism Dev Disord. Dec 2000; 30(6): 607-12.
  29. Stone WL, Coonrod EE, Turner LM, et al. Psychometric properties of the STAT for early autism screening. J Autism Dev Disord. Dec 2004; 34(6): 691-701.
  30. Stone WL, McMahon CR, Henderson LM. Use of the Screening Tool for Autism in Two-Year-Olds (STAT) for children under 24 months: an exploratory study. Autism. Sep 2008; 12(5): 557-73.
  31. UK National Screening Committee. Child screening programme. Autism. Accessed on April 27, 2022 Available at https://view-health-screening-recommendations.service.gov.uk/autism/
  32. Volkmar F, Siegel M, Woodbury-Smith M, et al. Practice parameter for the assessment and treatment of children and adolescents with autism spectrum disorder. J Am Acad Child Adolesc Psychiatry. Feb 2014; 53(2): 237-57.
  33. Wetherby AM, Brosnan-Maddox S, Peace V, et al. Validation of the Infant-Toddler Checklist as a broadband screener for autism spectrum disorders from 9 to 24 months of age. Autism. Sep 2008; 12(5): 487-511.
  34. Zwaigenbaum L, Bauman ML, Choueiri R, et al. Early Intervention for Children With Autism Spectrum Disorder Under 3 Years of Age: Recommendations for Practice and Research. Pediatrics. Oct 2015; 136 Suppl 1: S60-81.
  35. Zwaigenbaum L, Bryson S, Lord C, et al. Clinical assessment and management of toddlers with suspected autism spectrum disorder: insights from studies of high-risk infants. Pediatrics. May 2009; 123(5): 1383-91.

POLICY HISTORY:

Medical Policy Panel, July 2022

Medical Policy Group, August 2022 (6): New Medical Policy. DRAFT comment period through September 15, 2022.

Medical Policy Panel, July 2023

Medical Policy Group, July 2023 (6): Updates to Key Points, Benefit Application and References.

This medical policy is not an authorization, certification, explanation of benefits, or a contract. Eligibility and benefits are determined on a case-by-case basis according to the terms of the member’s plan in effect as of the date services are rendered. All medical policies are based on (i) research of current medical literature and (ii) review of common medical practices in the treatment and diagnosis of disease as of the date hereof. Physicians and other providers are solely responsible for all aspects of medical care and treatment, including the type, quality, and levels of care and treatment.

This policy is intended to be used for adjudication of claims (including pre-admission certification, pre-determinations, and pre-procedure review) in Blue Cross and Blue Shield’s administration of plan contracts.

The plan does not approve or deny procedures, services, testing, or equipment for our members. Our decisions concern coverage only. The decision of whether or not to have a certain test, treatment or procedure is one made between the physician and his/her patient. The plan administers benefits based on the member’s contract and corporate medical policies. Physicians should always exercise their best medical judgment in providing the care they feel is most appropriate for their patients. Needed care should not be delayed or refused because of a coverage determination.

As a general rule, benefits are payable under health plans only in cases of medical necessity and only if services or supplies are not investigational, provided the customer group contracts have such coverage.

The following Association Technology Evaluation Criteria must be met for a service/supply to be considered for coverage:

1. The technology must have final approval from the appropriate government regulatory bodies;

2. The scientific evidence must permit conclusions concerning the effect of the technology on health outcomes;

3. The technology must improve the net health outcome;

4. The technology must be as beneficial as any established alternatives;

5. The improvement must be attainable outside the investigational setting.

 

Medical Necessity means that health care services (e.g., procedures, treatments, supplies, devices, equipment, facilities or drugs) that a physician, exercising prudent clinical judgment, would provide to a patient for the purpose of preventing, evaluating, diagnosing or treating an illness, injury or disease or its symptoms, and that are:

1. In accordance with generally accepted standards of medical practice; and

2. Clinically appropriate in terms of type, frequency, extent, site and duration and considered effective for the patient’s illness, injury or disease; and

3. Not primarily for the convenience of the patient, physician or other health care provider; and

4. Not more costly than an alternative service or sequence of services at least as likely to produce equivalent therapeutic or diagnostic results as to the diagnosis or treatment of that patient’s illness, injury or disease.