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Caring Technologies Inc.

Address

106 N. 6th St., Suite 200
BOISE, ID, 83702-5980
USA

UEI: FK25QH6D6VN3

Number of Employees: 20

HUBZone Owned: No

Woman Owned: Yes

Socially and Economically Disadvantaged: No

SBIR/STTR Involvement

Year of first award: 2012

Phase I Awards

Phase II Awards

166.67%

Conversion Rate

$1,144,906

Phase I Dollars

$9,417,255

Phase II Dollars

$10,562,161

Total Awarded

Awards

Up to 10 of the most recent awards are being displayed. To view all of this company's awards, visit the Award Data search page.

Transforming Hospitalizations of Autistic Adolescents via a Novel ABA Telehealth Platform

Amount: $2,374,538 Topic: 104

PROJECT SUMMARY There is an increasing trend for children with ASD with primary behavioral challenges to be hospitalized in medical facilities because accessible behavioral support resources are not available in local communities. Unfortunately, most community-based hospitals are not well equipped to meet optimal behavioral care with families consequently experiencing prolonged/protracted hospitalizations where behaviors may not be adequately treated and could potentially worsen. Further, the specific inability to adequately respond to challenging behaviors may limit the ability of children to be accepted into step-down facilities or return home safely and contribute to extremely stressful aspects of care. Prolonged hospitalizations also result in significant negative financial return for hospitals (un/under-reimbursement). In prior work, deploying a specialized brief Applied Behavioral Analysis (ABA) assessment and intervention explicitly designed for use during hospitalizations demonstrated improvements in challenging behaviors, decreases in restraint and staffing, and high levels of family satisfaction. Unfortunately, community access to this type of intervention is extremely limited by geographic location and provider availability. Appropriate telehealth and digital health systems that can facilitate tele-mediated support may hold great potential for increasing the availability of such care to children, families, and the providers and hospitals responsible for their care. While many technologies for real- time video conferencing are available (e.g. zoom), in order to be able to accurately support understanding of precursors and the context of key behaviors technologies capable of supporting intelligent surveillance, data- flagging, and efficient communication of key behaviors across human support teams (both expert and non- expert) over substantial periods of time (including when experts are not present) are needed to enable meaningful telemediated ABA service. The current project creates and tests the potential clinical value of an innovative telehealth platform to facilitate appropriate, efficacious ABA tele-assessment and intervention for adolescents with ASD displaying challenging behaviors during hospitalizations and post-discharge transition. In the first phase of this work, we propose co-design of the novel system with key stakeholders and feasibility testing to demonstrate both technical capacity and potential clinical value. In the second phase of this work, we hone the systems commercial value and conduct a rigorous trial to demonstrate clinical utility and financial return for children, families, systems of care, and payers.

SBIR

Phase II

2024

HHS

NIH

i-Corp -Transforming Hospitalizations of Autistic Adolescents via a Novel ABA Telehealth Platform

Amount: $795,782 Topic: 104

The I-Corps curriculum provides real-world, hands-on, immersive learning about what it takes to successfully translate promising technologies into products or services that will benefit society. At the beginning of the training program, all I-Corps team members are required to attend an evening reception plus an intensive, 3-day Kick-Off Workshop (exact location to be announced).

SBIR

Phase I

2023

HHS

NIH

Combining Autism Telehealth and Screening Technologies for Earlier Diagnostic Assessments

Amount: $2,804,961 Topic: 102

Summary: This Phase IIb grant application describes a plan for demonstrating significant improvement of identifying ASD subjects at a very young age and facilitating diagnostic assessments for autism earlier via a proven telehealth service. The plan includes partnering with a private company (CHADIS) that has a substantial client base of referring pediatricians already using their technology to screen toddlers for autism. We have a novel telehealth system for remote autism diagnostic assessment called NODA™. We can add innovations including a Realtime Telemedicine module, and integration with the widely-used CHADIS™ system to provide a state-of-the-art telehealth system for pediatricians to refer at-risk young children electronically for a remote diagnostic assessment with a specialty diagnostic clinic earlier than conventional methods. This novel system will be shown to benefit subjects by providing equivalent services in a shorter time period compared to existing procedures and may also improve the current shortage of early diagnosis by qualified trained autism diagnostic clinicians. The proposed studies include enrollment of subjects in several major clinical centers and in commercial settings. If shown to be successful, the new system we call NODA Enhanced™ will benefit need for intervention services for ASD subjects at an earlier age, and regardless if families can access diagnostic assessments in person. Commercially, the combining of NODA with the widely used CHADIS system will substantially raise the opportunities for a commercially successful product.

SBIR

Phase II

2020

HHS

NIH

Deep Learning to Transform Clinician Autism Diagnostic Assessments and More

Amount: $149,124 Topic: 103

NODA Telehealth system improves access to an autism diagnostic assessment by guiding families to share video clips of their child at homeso diagnostic clinicians can directly observe andtagvideo of any atypical behaviorand if warrantedrender a diagnosisThis system is evidence based and has been commercializedwith several published studies to discuss the benefitsWe now propose to improve this service by developing a DeepmachineLearning capability in a software product calledNODA DL Classifierto help clinicians more quickly identify and better quantify typical and atypical behaviors on videos they receive from familiesIf successfulthis NODA DL feature within the NODA system will have a profound impact in the time to reach a firm diagnosisand then the capability could be used subsequently to effectively monitor treatment progress of individuals diagnosed with autismIn this projectwe will determine how much DL improves the diagnostic processIn Phase Iwe will test our use previously generated datasets to qualify and quantify potential benefitsIn Phase IIwe will conduct a clinical study to document time savings and other clinical benefitsOur proposed NODA DL innovation represents a large step change in identification and then the care for ASD individualsnot an incremental oneIt will lead to a significant improvement in both health outcomes and in reduced time required by clinicians or psychologists for office visits and for analyzing video dataThis reduced time can be translated into reduced costsWe anticipate that significant commercial benefits will result from the use of our innovative computer methodologies The proposed computerized Deep LearningDLfunction within our current NODA Telehealth System will have a profound impact in saving time to reach a firm diagnosis of individuals with ASDplus provide other important benefits

SBIR

Phase I

2018

HHS

NIH

Deep Learning to Transform Clinician Autism Diagnostic Assessments and More

Amount: $1,040,663 Topic: 103

SBIR

Phase II

2018

HHS

NIH

Accelerating the diagnosis of autism spectrum disorder in rural Idaho via evidence based Smartphone technology

Amount: $982,790 Topic: 102

DESCRIPTION provided by applicant A disparity exists between rural and urban suburban children with suspected ASD in the time interval between first identification of a possible problem and a firm diagnosis This project will investigate the effect of a recently developed and validated remote diagnostic method leveraging an evidence based Smartphone Telehealth service called NODA tm for autism spectrum disorder ASD on reducing the time between the age of first parent concern and the age at first diagnosis from a qualified professional The reduction of this time interval is critical to allow families to fully benefit from an early intensve behavioral intervention EIBI program This application of technology can be particularly advantageous for families who live in rural regions throughout the United States because they may face additional barriers to obtaining an accurate diagnosis which is necessary before commencing appropriate treatment services PUBLIC HEALTH RELEVANCE We propose reducing or eliminating disparity in time for diagnosis of Autism Spectrum Disorder in children using our innovative NODA telehealth system

SBIR

Phase II

2016

HHS

NIH

Accelerating the diagnosis of autism spectrum disorder in rural Idaho via evidence-based Smartphone technology

Amount: $200,000 Topic: NIBIB

SBIR

Phase I

2015

HHS

NIH

Intelligent Data Capture and Assessment Technology for Developmental Disabilities

Amount: $2,214,303 Topic: NIMH

DESCRIPTION (provided by applicant): This proposed SBIR Phase II renewal will leverage the technical expertise of academic collaborators at Georgia Institute of Technology and ongoing relationships forged with behavioral health professionals to introduce key technical innovations to our existing Behavior Imaging(R) telehealth system, and evaluate the enhanced system in two clinical assessment settings relevant to Autism Spectrum Disorders. These technical innovations will significantly improve ease of deployment and clinical utility of our system, resulting in a far more commercially viable product. The specific aims of the proposed project are: (1) To introduce hardware and software modifications to Behavior Capture, with simplified video capture on commodity smartphones and novel interactive features, including tags for target behaviors and the ability to flag examples of appropriate recordings; (2) To improve clinicians' experience with our online Behavior Connect telehealth system through the design of modules that optimize their workflow and reduce the need for training, and (3) To conduct two clinical studies to demonstrate how the technology innovations impact clinical decision-making. The first of these studies will be conducted in collaboration with the Southwest Autism Research and Resource Center (SARRC) in Arizona, and will evaluate the use of the technology to streamline the process of diagnosis for autism using videos recorded by parents in the home. The second study will be conducted in collaboration with the Marcus Autism Center in Georgia, and will evaluate the use of the technology for assessment of severity and function of problem behavior, again, based on caregiver captured video of child behavior in the home. Caring Technologies (now Behavior Imaging Solutions) successfully executed its Phase I and II research studies to partially develop and evaluate the research efficacy of its Behavior Imaging(R) telehealth technology to facilitate data collection and remote consultation/supervision for special educators and clinicians treating autism and other behavior disorders in classrooms. The company subsequently successfully launched its Behavior Imaging(R) consultation platform, and without institutional investment, generated 900K in revenue in 2010 for the technology's use primarily for (1) capturing and tracking the progress of special needs students, and (2) remotely supervising the delivery of in-home behavioral treatment. We anticipate that the proposed enhanced system, once validated in the clinical studies described in this proposal, will be adopted widely by the autism research and clinical community, and will significantly improve access to care among children with autism and developmental disabilities, as well as their families. PUBLIC HEALTH RELEVANCE: We intend to significantly enhance our existing telehealth system with hardware/software innovations and to validate its clinical performance for two important autism use cases. Enhancements based upon user feedback of our existing system will result in a far wider commercially acceptable product than we now have.

SBIR

Phase II

2012

HHS

NIH