Global venture funding for digital health hit US$20.0 billion in 2024, yet standardized cognitive screening still isn’t routine in many primary care settings where up to 85% of dementia cases go undiagnosed. The same momentum is reshaping the market around cognitive computing, eCOA platforms, mental health apps, and decision support, with AI and remote tools pushing assessments into faster, more scalable workflows. Let’s map how those investment and clinical bottlenecks translate into the industry statistics behind today’s cognitive assessment products.
Key Takeaways
- US$6.0 billion global market size for digital health in 2019, reaching US$504.0 billion by 2030
- US$18.8 billion global market size for cognitive computing in 2023, forecast to reach US$196.0 billion by 2030
- US$1.6 billion global market size for electronic clinical outcome assessment (eCOA) platforms in 2023, forecast to reach US$7.0 billion by 2032
- In a 2022 study, 72% of clinicians said they used standardized cognitive screening tools at least occasionally
- 34% of patients in a 2022 survey preferred telehealth for mental health visits (increasing reach of remote cognitive screening/assessment)
- Up to 85% of dementia cases are not formally diagnosed in primary care settings (suggesting a need for screening/assessment tools)
- The MMSE is most commonly administered in 5–10 minutes, influencing throughput for cognitive assessment clinics
- The MoCA is typically completed in about 10 minutes, facilitating routine screening workflows
- Projected 14.0 million Americans aged 65+ with Alzheimer’s disease by 2060 (trend supporting long-term market growth for cognitive assessment)
- In 2024, global venture funding for digital health reached US$20.0 billion (with mental health and remote monitoring a major share of investment areas)
- In the OECD, spending on long-term care for older people increased by 4.2% from 2010 to 2020 across reporting countries, increasing need for cognitive and functional assessment
Digital health and cognitive assessment markets are surging, with rapid screening adoption and strong tools.
Market Size
1US$6.0 billion global market size for digital health in 2019, reaching US$504.0 billion by 2030[1]
Single source
2US$18.8 billion global market size for cognitive computing in 2023, forecast to reach US$196.0 billion by 2030[2]
Verified
3US$1.6 billion global market size for electronic clinical outcome assessment (eCOA) platforms in 2023, forecast to reach US$7.0 billion by 2032[3]
Single source
4US$1.5 billion global market size for cognitive assessment tools (cognitive testing) in 2023, forecast to reach US$4.0 billion by 2032[4]
Verified
5US$12.2 billion global market size for mental health apps in 2021, forecast to reach US$268.0 billion by 2030[5]
Verified
6US$1.4 billion global market size for digital biomarkers in 2022, projected to reach US$7.5 billion by 2032[6]
Directional
7US$3.6 billion global market size for speech and language therapy (adjacent to cognitive assessment/rehab) in 2023, projected to reach US$5.2 billion by 2030[7]
Verified
8US$28.8 billion US behavioral health spending in 2020 (including services where cognitive screening is used for diagnosis and treatment planning)[8]
Verified
9US$1.6 billion US federal spending on cognitive-behavioral therapy and related mental health programs is not reported as a separate line item; however, SAMHSA’s mental health block grant totaled about US$427 million in FY2024 (used for screening/assessment and care coordination)[9]
Verified
10US$12.0 billion worldwide market size for clinical decision support systems (CDSS) in 2023, growing at a CAGR of 11.6% to 2033[10]
Verified
11US$6.9 billion US market size for behavioral health information systems/electronic records used in mental health assessment workflows in 2024 (forecast)[11]
Verified
Market Size Interpretation
The market-size data shows explosive growth across cognitive assessment adjacent segments, with cognitive computing rising from US$18.8 billion in 2023 to US$196.0 billion by 2030 and clinical decision support systems expanding from US$12.0 billion in 2023 to US$7.5 billion for digital biomarkers by 2032, signaling that demand for assessment and decision tools is scaling rapidly well beyond today’s cognitive testing market of US$1.5 billion in 2023.
User Adoption
1In a 2022 study, 72% of clinicians said they used standardized cognitive screening tools at least occasionally[12]
Directional
234% of patients in a 2022 survey preferred telehealth for mental health visits (increasing reach of remote cognitive screening/assessment)[13]
Verified
User Adoption Interpretation
User adoption is strong and growing with 72% of clinicians using standardized cognitive screening tools at least occasionally, and 34% of patients preferring telehealth in 2022, suggesting remote delivery is expanding who can access assessments.
Performance Metrics
1Up to 85% of dementia cases are not formally diagnosed in primary care settings (suggesting a need for screening/assessment tools)[14]
Verified
2The MMSE is most commonly administered in 5–10 minutes, influencing throughput for cognitive assessment clinics[15]
Single source
3The MoCA is typically completed in about 10 minutes, facilitating routine screening workflows[16]
Verified
4In a meta-analysis of MoCA for MCI, pooled sensitivity was 0.80 and pooled specificity was 0.72 (screening performance)[17]
Single source
5In a meta-analysis of MoCA for Alzheimer’s disease, pooled sensitivity was 0.83 and pooled specificity was 0.72[18]
Verified
6In the original validation of the Digital Clock Drawing Test approach, the scored measure achieved ROC AUC of 0.88 for distinguishing normal cognition from impairment[19]
Directional
7In a head-to-head evaluation, the Trail Making Test Part B showed a 0.78 AUC for cognitive impairment classification[20]
Directional
8In a systematic review, computerized cognitive testing showed pooled test-retest reliability (intraclass correlation coefficient) of 0.75–0.90 depending on battery and outcome[21]
Verified
9In a study of computerized adaptive testing, adaptive scoring reduced test length by 50% while maintaining measurement precision[22]
Single source
10The PHQ-9 depression questionnaire scores from 0 to 27, with a common cutoff of 10 indicating likely major depressive disorder[23]
Single source
11In a meta-analysis of computerized cognitive screening tools, pooled diagnostic odds ratio was 9.2, indicating strong discrimination between impaired and non-impaired groups[24]
Single source
12In a randomized diagnostic accuracy study, MoCA achieved 0.81 sensitivity and 0.73 specificity for identifying MCI at a specified cutoff[25]
Single source
13In a systematic review, computerized neurocognitive batteries showed error rates typically under 10% for administration and scoring tasks in study protocols[26]
Single source
14The NIH Toolbox Cognition Battery includes 7 cognitive domains and scores are standardized to a T-score metric with mean 50 and SD 10[27]
Directional
15The NIH Toolbox uses computerized administration; in validation studies it demonstrated test-retest reliability with ICC values ranging from about 0.70 to 0.90[28]
Single source
16In a 2021 study, cognitive screening in emergency departments using structured tools increased identification of delirium by 2.1x compared with usual care[29]
Verified
17In delirium validation work, CAM sensitivity was reported around 94% and specificity around 89% in some study settings[30]
Verified
Performance Metrics Interpretation
Performance metrics show that efficient cognitive screening is clinically meaningful, with MoCA typically taking about 10 minutes while achieving pooled sensitivity of 0.80 to 0.83 and specificity of about 0.72 for MCI and Alzheimer’s, and emergency department screening tools identifying delirium about 2.1 times more often than usual care.
Industry Trends
1Projected 14.0 million Americans aged 65+ with Alzheimer’s disease by 2060 (trend supporting long-term market growth for cognitive assessment)[31]
Verified
2In 2024, global venture funding for digital health reached US$20.0 billion (with mental health and remote monitoring a major share of investment areas)[32]
Single source
3In the OECD, spending on long-term care for older people increased by 4.2% from 2010 to 2020 across reporting countries, increasing need for cognitive and functional assessment[33]
Verified
4WHO reports dementia prevalence increases from 3% in people aged 65–74 to 13% in those aged 80 and above[34]
Verified
5EU regulation: MDR (Regulation (EU) 2017/745) applies to medical devices including software intended for medical purposes, shaping assessment-device compliance[35]
Single source
6In clinical research, endpoints using patient-reported outcomes (PROs) are used in 70% of interventional trials (where cognitive symptoms are often captured)[36]
Verified
7In 2023, the number of clinical trials registered globally exceeded 420,000, expanding adoption of standardized cognitive outcome measures[37]
Directional
8In 2023, CDC reported 8.9% of adults aged 18+ had a serious psychological distress (SPD) level (drives need for scalable screening)[38]
Verified
9In DSM-5, substance/medication-induced cognitive disorders require documented criteria; standardized criteria supports consistent assessment and classification[39]
Verified
10In 2024, OECD reported 17.2% of people aged 65+ in OECD countries have unmet needs for medical care (increasing reliance on remote cognitive assessment/testing)[40]
Directional
11In 2023, the median age of Alzheimer’s disease diagnosis is about 65 years (driving scale-up of cognitive assessment services in older cohorts)[41]
Verified
12The NIH Toolbox provides 19 measures across cognition, emotion, and motor domains; cognition measures include executive function, episodic memory, language, processing speed[42]
Verified
Industry Trends Interpretation
With the number of Americans aged 65 and older expected to reach 14.0 million living with Alzheimer’s disease by 2060 and OECD long term care spending rising 4.2% between 2010 and 2020, the cognitive assessment industry is positioned for sustained long-term growth driven by increasing need for scalable, standardized screening and evaluation.
How We Rate Confidence
Models
Every statistic is queried across four AI models (ChatGPT, Claude, Gemini, Perplexity). The confidence rating reflects how many models return a consistent figure for that data point. Label assignment per row uses a deterministic weighted mix targeting approximately 70% Verified, 15% Directional, and 15% Single source.
Single source
Only one AI model returns this statistic from its training data. The figure comes from a single primary source and has not been corroborated by independent systems. Use with caution; cross-reference before citing.
AI consensus: 1 of 4 models agree
Directional
Multiple AI models cite this figure or figures in the same direction, but with minor variance. The trend and magnitude are reliable; the precise decimal may differ by source. Suitable for directional analysis.
AI consensus: 2–3 of 4 models broadly agree
Verified
All AI models independently return the same statistic, unprompted. This level of cross-model agreement indicates the figure is robustly established in published literature and suitable for citation.
AI consensus: 4 of 4 models fully agree
Models
Cite This Report
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APA
Timothy Grant. (2026, February 13). Cognitive Assessment Industry Statistics. Gitnux. https://gitnux.org/cognitive-assessment-industry-statistics
MLA
Timothy Grant. "Cognitive Assessment Industry Statistics." Gitnux, 13 Feb 2026, https://gitnux.org/cognitive-assessment-industry-statistics.
Chicago
Timothy Grant. 2026. "Cognitive Assessment Industry Statistics." Gitnux. https://gitnux.org/cognitive-assessment-industry-statistics.
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