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Record W2972296841 · doi:10.1111/jgs.16158

Monetizing the MoCA: What Now?

2019· editorial· en· W2972296841 on OpenAlexaboutno aff
Soo Borson, Mandi Sehgal, Joshua Chodosh

Bibliographic record

VenueJournal of the American Geriatrics Society · 2019
Typeeditorial
Languageen
FieldMedicine
TopicDementia and Cognitive Impairment Research
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineGerontology

Abstract

fetched live from OpenAlex

In late June 2019, we learned that the Montreal Cognitive Assessment (MoCA) would become proprietary in September. Users must be trained and certified for a fee of $125 and recertify every 2 years. Colleagues, especially those who experienced the privatization of the Mini-Mental State Examination (MMSE) in 2000,1 have registered a range of reactions from resignation to anger and disgust. With its catchy name, visual appeal, and free download, the MoCA is the preferred cognitive mini-battery for use in clinical care, training, and research, and it has found its way into a number of electronic medical record platforms. Ziad Nasreddine, the MoCA's author and copyright holder, has created a company (MoCA Test Inc; www.mocatest.org) to manage certification, licensing, administration, scoring, and communication. Under the new requirements and subject to uncertain future iterations, users must register a unique profile, obtain consent, and enter selected patient data and test responses through an online portal for centralized scoring.2 In recent e-mail exchanges, Nasreddine told us that his goals are to create an international database that may be shared with researchers and sold to commercial or other entities, and to support further development of the MoCA by user fees and other funding. We assume that patients will have to consent to the use of their clinically acquired data and that proxy consent will be needed when consent capacity is in question. These issues will discourage clinicians from routinely assessing cognition and create substantial inconvenience and potential legal challenges for healthcare systems choosing to retain access to the MoCA. We do not ask patients to "consent" to having their blood pressure or blood glucose measured. We should not have to do so for the basic cognitive assessment that is essential for effective patient care planning. The full implications of the change in access to the MoCA are unknown. It is not yet clear how data acquired as part of ongoing or new federally funded research will be handled; the existing contract governing its inclusion in the Uniform Data Set, used by all US Alzheimer's Disease Research Centers, is valid until 2025 (personal communication, Walter Kukull, director of the National Alzheimer's Coordinating Center [NACC]). The two major user groups most immediately affected are clinicians and educators, but healthcare systems will also feel the pain. Low identification of cognitive impairment in clinical practice has been tagged as a healthcare quality problem in every country studied, and routine use of cognitive screening tools can partially fix that. In 2011, introduction of the Centers for Medicaid & Medicare Services (CMS) Medicare Annual Wellness Visit (AWV) included cognitive impairment among the health risks that must be considered when individualizing prevention plans for older people.3, 4 Some healthcare systems embedded cognitive screening tools with searchable scores into their AWV documentation process, and in 2017, the introduction of the Cognitive Impairment Assessment and Care Plan code by CMS provided a new payment vehicle to encourage linking detection of cognitive impairment to comprehensive assessment and management. This new benefit reflects an important policy advance; we should be promoting its implementation. These two key benefits, combined with transition and chronic care management, provide a suite of payment tools that could positively transform dementia care in the United States. To the extent that healthcare systems have embraced the goal of standardizing cognitive assessment, the loss of a popular screening tool could throw this hard-won progress into disarray. We think the anticipated disruption offers an important opportunity to reexamine the value we place on cognitive tests and our growing reliance on them. The standardized tests we use today derive from a cognitive taxonomy that has evolved with, and partly as a result of, advances in clinical neuroscience. These tools serve several important purposes. In research, they allow for longitudinal assessment of change and comparison of different clinical or treatment groups and serve as key outcomes in studying the benefits and harms of interventions. In clinical geriatric care and training, they simplify assessment of certain mental functions that are vulnerable to aging and disease effects, create a common descriptive language, help identify individuals who may need specialized management, and track changes over time. Easy-to-use validated instruments encourage assessment of problems invisible or neglected in routine care that, if detected, can benefit from clinical intervention: cognitive impairment, fall risk, and depression are prime examples. As physicians, we like measures that yield a neat numerical value—and we are now often called on to provide a specific test score (usually MMSE or MoCA) as evidence in determination of decisional capacity, eligibility for long-term care benefits or other essential services, or exemption from citizenship examination (although this practice should be questioned). The impact of privatizing the MoCA on clinician education could be far reaching. Medical educators have adopted it as their cognitive assessment tool of choice, and innumerable residents, fellows, and practicing physicians throughout the United States and Canada have been trained to use it. Countless hours have been spent developing didactic materials, simulation exercises, and observed structured clinical exams for this purpose. However, one could argue that any screening tool that requires so much effort to get right in routine use should be considered, at the very least, provisional, a work in progress rather than a gold standard. Nasreddine has publicly acknowledged a worrisome degree of variability in test performance5 as one reason for his decision to require certification. Should we accede to the new requirements, or find or develop other assessment tools that accomplish what we expected MMSE and then MoCA to do? A number of such tools are already freely available, among them the Mini-Cog,6 a brief screen designed to detect dementia in generalist settings but more sensitive to mild cognitive impairment (MCI) when paired with an established functional impairment screen,7 and three mini-batteries: the Kokmen Short Test of Mental Status (STMS)8; the Rowland Universal Dementia Assessment Scale (RUDAS),9 and the St. Louis Mental Status Exam.10 The STMS11 and the RUDAS12 perform at least as well as the MoCA in detecting MCI, the primary cognitive target for which the MoCA was developed. It bears repeating that all screening tests, including the MoCA, have strengths and weaknesses, and none yield a diagnosis. It is also important to keep in mind that the value of a test lies not only in its intrinsic characteristics but (perhaps more importantly) in its fitness for the purpose it is meant to serve and the people with whom it will be used. To acquaint trainees and practicing clinicians with the importance of cognition in the lives and healthcare of their patients, it makes sense to teach about everyday cognition, an aspect not measured by the MoCA or other popular screening tests. Everyday cognition includes such functions as prospective memory (remembering to remember, critical in adhering to home treatment and getting to the doctor); understanding the basics of one's health problems and evaluating changes should they occur; thinking about one's possible future states and accepting help when needed; and maintaining relationships with others who matter and are, or will be, called on to help provide care. One example of a standardized approach to assessing practical cognition is the Clinical Dementia Rating, or CDR,13 now known as the CDR Dementia Staging Instrument. This tool was initially developed for staging Alzheimer's disease and has been updated to include items particular to frontotemporal lobar degeneration (the NACC FTLD Behavior & Language Domains, CDR plus NACC FTLD). It combines cognitive with behavioral and functional domains to classify individuals on a spectrum of impairment from none to severely demented. Although it requires extensive training and user certification, no fee is currently required. A derivative of the original CDR, the Dementia Severity Rating Scale,14 can be completed by an independent historian (eg, a family care partner) and performs well in multiple applications.15 Where do we go from here? Clinicians, academic institutions, and healthcare systems could, of course, choose to pay for training to use the MoCA. The process might improve reliability, as argued by its author (mocatest.org). The MoCA is, after all, a difficult test to give and score properly with heterogeneous patient populations in ordinary clinical settings where time and experience are at a premium. But what about the requirements to register as a user, obtain patient (and perhaps proxy) consent for each use, and share clinical data with a commercial entity? Although not unlawful, such a requirement feels vaguely exploitative. It creates, by design, a MoCA registry that can be used in ways that those who contribute to it have no rights to challenge or critique and from which there is no guarantee of benefit. Moreover, might such a required consent process undermine the comfort and trust we seek to establish when conducting a sensitive inquiry that is already potentially threatening to the patients we seek to help? Our major research and public health organizations, professional associations, and many health systems now recognize the urgent need to address the care of cognitively impaired older people as a population health imperative. We call on them to take on the problem of cognitive assessment in a new way. The field needs a multifaceted tool designed for ease of use across healthcare settings, relevant to everyday cognition and function, unbiased in application with diverse populations, and guaranteed availability at no cost. Large increases in National Institutes of Health (NIH) funding for research on Alzheimer's disease and related dementias, now at $2.34 billion for FY 2019, can surely accommodate this effort. The 2020 NIH National Research Summit on Care, Services, and Supports for Persons with Dementia and Their Caregivers provides the perfect opportunity to launch a collaborative commitment to development of new tools, and it would signify a much needed national investment in improving healthcare for our aging population. We thank Barak Gaster, MD, and Ziad Nasreddine, MD, for their comments, and other expert colleagues who provided valuable feedback but have chosen to remain anonymous. None declared. Concept, initial and final drafting, and revisions: Borson. Drafting and revision: Sehgal and Chodosh. No sponsor.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.022
metaresearch head score (Gemma)0.068
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Editorial · Consensus signal: none
Teacher disagreement score0.054
Threshold uncertainty score0.180

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0220.068
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0020.002
Science and technology studies0.0040.006
Scholarly communication0.0110.024
Open science0.0040.004
Research integrity0.0100.016
Insufficient payload (model declined to judge)0.0540.033

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.009
GPT teacher head0.304
Teacher spread0.295 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreEditorial

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

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Citations18
Published2019
Admission routes1
Has abstractyes

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