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Expected and diagnosed rates of mild cognitive impairment and dementia in the U.S. Medicare population: observational analysis
Open accessAbstract
Background: With the emergence of disease-modifying Alzheimer’s treatments, timely detection of early-stage disease is more important than ever, as the treatment will not be indicated for later stages. Contemporary population-level data for detection rates of mild cognitive impairment (MCI), the stage at which treatment would ideally start, are lacking, and detection rates for dementia are only available for subsets of the Medicare population. We sought to compare documented diagnosis rates of MCI and dementia in the full Medicare population with expected rates based on a predictive model. Methods: We performed an observational analysis of Medicare beneficiaries aged 65 and older with a near-continuous enrollment over a 3-year observation window or until death using 100% of the Medicare fee-for-service or Medicare Advantage Plans beneficiaries from 2015 to 2019. Actual diagnoses for MCI and dementia were derived from ICD-10 codes documented in those data. We used the 2000–2016 data of the Health and Retirement Study to develop a prediction model for expected diagnoses for the included population. The ratios between actually diagnosed cases of MCI and dementia over number of cases expected, the observed over expected ratio, reflects the detection rate. Results: Although detection rates for MCI cases increased from 2015 to 2019 (0.062 to 0.079), the results mean that 7.4 of 8 million (92%) expected MCI cases remained undiagnosed. The detection rate for MCI was 0.039 and 0.048 in Black and Hispanic beneficiaries, respectively, compared with 0.098 in non-Hispanic White beneficiaries. Individuals dually eligible for Medicare and Medicaid had lower estimated detection rates than their Medicare-only counterparts for MCI (0.056 vs 0.085). Dementia was diagnosed more frequently than expected (1.086 to 1.104) from 2015 to 2019, mostly in non-Hispanic White beneficiaries (1.367) compared with 0.696 in Black beneficiaries and 0.758 in Hispanic beneficiaries. Conclusions: These results highlight the need to increase the overall detection rates of MCI and of dementia particularly in socioeconomically disadvantaged groups.
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“suggesting there may be as many as 8 million people with undiagnosed MCI”
From 2024 Alzheimer's disease facts and figures (2024) · cites this paper as [696]
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“A recent study of Medicare beneficiaries found that only about 8% of expected mild cognitive impairment (MCI) cases are diagnosed on average, suggesting there may be as many as 8 million people with undiagnosed MCI”
From 2024 Alzheimer's disease facts and figures (2024) · cites this paper as [696]
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Cites
Lecanemab in early Alzheimer's disease
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“These missed and delayed diagnoses have long taken away from patients and families the opportunity to adopt lifestyle changes to reduce the speed of decline [4], start symptomatic medication treatment, and consider measures to increase physical and financial safety and security [5].”
BackgroundDonanemab in Early Symptomatic Alzheimer Disease: The TRAILBLAZER-ALZ 2 Randomized Clinical Trial
Sims, J. R., Zimmer, J. A., Evans, C. D., Lu, M., Ardayfio, P., Sparks, J., Wessels, A. M., Shcherbinin, S., Wang, H., Monkul Nery, E. S., et al. (2023) · JAMA · doi:10.1001/jama.2023.13239 · Cited by 2,932
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“In other words, there may be around 10 million Americans with undiagnosed MCI, and around half of them would have the AD pathology [24].”
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“This dementia detection rate is much higher than the 38% reported by a meta-analysis of US-based studies prior to 2007 [29] and the July 2022 estimate of 62% from the National Health Service in England [30], but close to a 2.”
ResultTimely Diagnosis for Alzheimer’s Disease: A Literature Review on Benefits and Challenges
Dubois, B., Padovani, A., Scheltens, P., Rossi, A., & Dell’Agnello, G. (2015) · Journal of Alzheimer s Disease · doi:10.3233/jad-150692 · Cited by 565 · cited 1×
“These missed and delayed diagnoses have long taken away from patients and families the opportunity to adopt lifestyle changes to reduce the speed of decline [4], start symptomatic medication treatment, and consider measures to increase physical and financial safety and security [5].”
BackgroundManly, J. J., Jones, R. N., Langa, K. M., Ryan, L. H., Levine, D. A., McCammon, R., Heeringa, S. G., & Weir, D. (2022) · JAMA Neurology · doi:10.1001/jamaneurol.2022.3543 · Cited by 560
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“Predictors included sex, age groups (50–54, 55–59, 60–64, 65–69, 70–74, 75–79, 80–84, and ≥ 85 years), race and ethnicity (non-Hispanic [NH] White, Black, Hispanic, and others), dual eligibility status (individuals covered by both Medicare and Medicaid), and a linear trend for year to account for the secular decline i…”
BackgroundThe accuracy of medicare claims data in identifying Alzheimer's disease
Taylor, D. H., Fillenbaum, G. G., & Ezell, M. E. (2002) · Journal of Clinical Epidemiology · doi:10.1016/s0895-4356(02)00452-3 · Cited by 256
Improving identification of cognitive impairment in primary care
Soo Borson, B., Scanlan, J. M., Watanabe, J. M., Tu, S.-P., & Lessig, M. C. (2006) · International Journal of Geriatric Psychiatry · doi:10.1002/gps.1470 · Cited by 254 · cited 1×
“[25] reported that primary care physicians correctly identified just 6% of MCI cases in a small sample of 371 patients.”
BackgroundDementia Diagnosis Disparities by Race and Ethnicity
Lin, P.-J., Daly, A. T., Olchanski, N., Cohen, J. T., Neumann, P. J., Faul, J. D., Fillit, H. M., & Freund, K. M. (2021) · Medical Care · doi:10.1097/mlr.0000000000001577 · Cited by 239
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“However, socioeconomically disadvantaged populations have much lower dementia detection rates in spite of their greater disease burden [31] and higher rates of risk factors [32], which mirrors the results published by others, who compared HRS data to diagnoses in Medicare claims.”
ResultRacial disparities and temporal trends in dementia misdiagnosis risk in the United States
Gianattasio, K. Z., Prather, C., Glymour, M. M., Ciarleglio, A., & Power, M. C. (2019) · Alzheimer's & Dementia: Translational Research & Clinical Interventions · doi:10.1016/j.trci.2019.11.008 · Cited by 168
Validation of Claims Algorithms to Identify Alzheimer’s Disease and Related Dementias
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“Similarly, the classification algorithm based on claims data may have misclassified some individuals [40].”
MethodSavva, G. M., & Arthur, A. J. (2015) · Age and Ageing · doi:10.1093/ageing/afv020 · Cited by 138 · cited 2×
“[8] estimated that the rates of self-reported MCI diagnosis were 11.”
BackgroundMethodGorina, Y., & Kramarow, E. A. (2011) · Health Services Research · doi:10.1111/j.1475-6773.2011.01277.x · Cited by 137 · cited 7×
“Calculation of diagnosed prevalence in claims data To identify persons diagnosed with dementia, we modified the algorithm published by the CCW [18] based on a recent study by Festa et al.”
MethodInfluentialEvaluation of Medicare Claims Data as a Tool to Identify Dementia
Lee, E., Gatz, M., Tseng, C.-C., Schneider, L. S., Pawluczyk, S., Wu, A. H., & Deapen, D. (2019) · Journal of Alzheimer s Disease · doi:10.3233/jad-181005 · Cited by 104 · cited 1×
“[10] for the 2007 to 2012 period of the same data.”
BackgroundJacobson, M., Thunell, J. A., & Zissimopoulos, J. (2020) · Health Affairs · doi:10.1377/hlthaff.2019.01795 · Cited by 77 · cited 1×
“The Medicare Annual Wellness Visit, which requires a cognitive assessment, might increase detection rates, but uptake remains limited, and a recent study reported that cognitive state was formally assessed in less than onethird of visits [28].”
BackgroundMattke, S., Cho, S. K., Bittner, T., Hlávka, J. P., & Hanson, M. (2020) · Alzheimer s & Dementia Diagnosis Assessment & Disease Monitoring · doi:10.1002/dad2.12081 · Cited by 73
Self-citationMattke, S., Batie, D., Chodosh, J., Felten, K. M., Flaherty, E., Fowler, N. R., Kobylarz, F. A., O’Brien, K., Paulsen, R., Pohnert, A. M., et al. (2023) · Alzheimer s & Dementia · doi:10.1002/alz.13051 · Cited by 73
Self-citationSex, Race, and Age Differences in Prevalence of Dementia in Medicare Claims and Survey Data
Zhu, Y., Chen, Y., Crimmins, E. M., & Zissimopoulos, J. (2020) · The Journals of Gerontology Series B · doi:10.1093/geronb/gbaa083 · Cited by 72 · cited 4×
“expected rates To estimate the underlying prevalence of MCI and dementia based on cognitive assessments, we used HRS data from 2000 to 2016 [11].”
MethodResultInfluentialAducanumab: Appropriate use recommendations
Cummings, J., & Salloway, S. (2022) · Alzheimer's & Dementia · doi:10.1002/alz.12444 · Cited by 65
Do general practitioners recognize mild cognitive impairment in their patients?
Kaduszkiewicz, H., Zimmermann, T. P., van den Bussche, H., Bachmann, C., Wiese, B., Bickel, H., Mösch, E., Romberg, H.-P., Jessen, F., Cvetanovska, G., et al. (2010) · The journal of nutrition health & aging · doi:10.1007/s12603-010-0038-5 · Cited by 59 · cited 1×
“A similar study in Germany found that only 11 to 12% of MCI cases were detected by primary care physicians [26].”
White, L. L. Y., Ingraham, B. C., Larson, E. B., Fishman, P. A., Park, S., & Coe, N. B. (2021) · Journal of General Internal Medicine · doi:10.1007/s11606-021-07169-7 · Cited by 50 · cited 1×
“[7] used data from the Health and Retirement Study (HRS), a nationally representative survey of older US adults that contains cognitive assessments, to estimate that 11.”
MethodPlan switching among Medicare Advantage beneficiaries with Alzheimer's disease and other dementias
Meyers, D. J., Rahman, M., Rivera‐Hernandez, M., Trivedi, A. N., & Mor, V. (2021) · Alzheimer s & Dementia Translational Research & Clinical Interventions · doi:10.1002/trc2.12150 · Cited by 39
Diagnosed prevalence of Alzheimer's disease and related dementias in Medicare Advantage plans
Jutkowitz, E., Bynum, J., Mitchell, S. L., Cocoros, N. M., Shapira, O., Haynes, K., Nair, V. P., McMahill‐Walraven, C. N., Platt, R. G., & McCarthy, E. P. (2020) · Alzheimer s & Dementia Diagnosis Assessment & Disease Monitoring · doi:10.1002/dad2.12048 · Cited by 29 · cited 1×
“[12] found considerably lower dementia diagnosis rates of 5.”
BackgroundSubstantial Growth In Medicare Advantage And Implications For Reform
Trish, E. E., Valdez, S., Ginsburg, P. Β., Randall, S., & Lieberman, S. M. (2023) · Health Affairs · doi:10.1377/hlthaff.2022.00668 · Cited by 24 · cited 2×
“We did not account for switching between FFS and Medicare Advantage within an observation window, as switching rates tend to be low, between 1 and 6% [16, 17].”
BackgroundNicholas, L. H. (2013) · Forum for Health Economics & Policy · doi:10.1515/fhep-2012-0037 · Cited by 20 · cited 1×
“However, those studies commonly use older data and/ or are limited to subsets of either the Medicare FFS population or members of Medicare Advantage Plans, which is important as the decision to enroll in a Medicare Advantage Plan is not random [13, 14].”
BackgroundEvaluating The Accuracy Of Medicare Risk Adjustment For Alzheimer’s Disease And Related Dementias
Festa, N., Price, M., Weiss, M., Moura, L. M. V. R., Benson, N. M., Zafar, S. F., Blacker, D., Normand, S. T., Newhouse, J. P., & Hsu, J. (2022) · Health Affairs · doi:10.1377/hlthaff.2022.00185 · Cited by 19 · cited 1×
“, [19] which found that noncognitive and unspecific codes in the CCW algorithm, as well as diagnoses made during a single inpatient or skilled nursing facility episode, were likely to be false positives.”
BackgroundThoits, T., Dutkiewicz, A., Raguckas, S., Lawrence, M., Parker, J., Keeley, J., Andersen, N. J., VanDyken, M., & Hatfield-Eldred, M. (2018) · American Journal of Alzheimer s Disease & Other Dementias® · doi:10.1177/1533317518758785 · Cited by 17 · cited 1×
“[3] found that about 79% of randomly selected patients newly diagnosed at a memory clinic had moderate or severe dementia.”
BackgroundCho, S. M. (2022) · The American Journal of Managed Care · doi:10.37765/ajmc.2022.88868 · Cited by 17 · cited 1×
“Such observed to expected (O/E) ratios are frequently used in quality measurement [22].”
BackgroundMirel, L. B., Wheatcroft, G., Parker, J. D., & Makuc, D. M. (2012) · PubMed · Cited by 14
Beneficiary Switching Between Traditional Medicare and Medicare Advantage Between 2016 and 2020
Unuigbe, A., Cintina, I., & Koenig, L. (2022) · JAMA Health Forum · doi:10.1001/jamahealthforum.2022.4896 · Cited by 13 · cited 2×
“We did not account for switching between FFS and Medicare Advantage within an observation window, as switching rates tend to be low, between 1 and 6% [16, 17].”
BackgroundDetection of Undiagnosed Disease in Medicare Beneficiaries After a Clinical Home Visit
Han, D., Wilks, A., & Mattke, S. (2016) · Population Health Management · doi:10.1089/pop.2015.0187 · Cited by 4 · cited 1×
“It is somewhat unexpected that members of Medicare Advantage Plans have lower detection rates than those in Medicare FFS, because Medicare Advantage Plans commonly include clinical home visits that lead to the detection of undiagnosed disease [35], and a dementia diagnosis is part of the risk adjustment scheme that se…”
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Sorted by citations
2024 Alzheimer's disease facts and figures
(2024) · Alzheimer's & Dementia · doi:10.1002/alz.13809 · Cited by 2,536
Recommendations for clinical implementation of blood‐based biomarkers for Alzheimer's disease
Mielke, M. M., Anderson, M., Ashford, J. W., Jeromin, A., Lin, P., Rosen, A. C., Tyrone, J., VandeVrede, L. A., Willis, D. R., Hansson, O., et al. (2024) · Alzheimer s & Dementia · doi:10.1002/alz.14184 · Cited by 130
Self-citationAlzheimer's disease outlook: controversies and future directions
Frisoni, G. B., Aho, E., Brayne, C., Ciccarelli, O., Dubois, B., Fox, N. C., Frederiksen, K. S., Gabay, C., Garibotto, V., Hofmarcher, T., et al. (2025) · The Lancet · doi:10.1016/s0140-6736(25)01389-3 · Cited by 116
Liu, Y., Jun, H., Becker, A., Wallick, C., & Mattke, S. (2024) · The Journal of Prevention of Alzheimer's Disease · doi:10.14283/jpad.2023.131 · Cited by 105
“Additional details of the predictive model can be found elsewhere (21).”
BackgroundSelf-citationConsiderations for widespread implementation of blood‐based biomarkers of Alzheimer's disease
Mielke, M. M., Anderson, M., Ashford, J. W., Jeromin, A., Lin, P., Rosen, A. C., Tyrone, J., VandeVrede, L. A., Willis, D. R., Hansson, O., et al. (2024) · Alzheimer s & Dementia · doi:10.1002/alz.14150 · Cited by 47
“10,11 Misdiagnosis, especially common in the early stages when symptoms are subtle, often leads to delays in care or inappropriate treatment.”
Self-citation
Metadata
- Authors
- Mattke, S., Jun, H., Chen, E., Liu, Y., Becker, A., & Wallick, C.
- Affiliations
- University of Southern California (US)
- Harvard University (US)
- Roche (United States) (US)
- Corresponding author
- Mattke, Soeren
- Venue
- Alzheimer's Research & Therapy
- Published
- 2023-07-22
- Volume
- 15
- Issue
- 1
- Pages
- 128-128
- ISSN
- 1758-9193 (ISSN-L)
- PMC
- PMC10362635
- OpenAlex
- W4385075320
- Cited by
- 106
- References
- 38
- Citations by year
- 2026: 32 · 2025: 39 · 2024: 32 · 2023: 3
- FWCI
- 21.59
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Locations
- Alzheimer s Research & Therapy (publishedVersion, cc-by)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
- Funders
- Genentech, Inc., a member of the Roche Group
- Topics
- Health Sciences › Medicine › Psychiatry and Mental health › Dementia and Cognitive Impairment Research
- Health Sciences › Medicine › Oncology › Cancer-related cognitive impairment studies
- Life Sciences › Neuroscience › Cellular and Molecular Neuroscience › Alzheimer's disease research and treatments
- Keywords
- mild cognitive impairment, dementia, detection rate, underdiagnosis, Medicare beneficiaries, older adults, racial and ethnic disparities, prediction model, ICD-10 diagnoses
- MeSH terms
- Aged, Alzheimer Disease, Medicare, Humans, United States, Cognitive Dysfunction
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