Early Detection of Dementia and the Goal of Population-based Care

Abstract:

Early detection of dementia is the first step toward developing dementia-capable health and community care systems for people living with Alzheimer’s disease or related dementias, and their care partners. This article defines early detection and addresses dementia as a clinical condition causing decline in an individual's cognitive abilities that makes it harder to manage everyday life without help. The article also discusses the rationale for early detection, why it is not yet the standard of care, and how individuals, communities, healthcare providers, systems, and public health entities can contribute—individually and collectively—to achieving this important population goal.

Key Words:

dementia, early detection, Alzheimer’s disease, standard of care, healthcare, public health

Timely detection and accurate diagnosis of dementia are key elements of the national plan for Alzheimer’s Disease and Related Dementias. The BOLD Act—Building Our Largest Dementia infrastructure, passed in 2019—directs the Center for Disease Control and Prevention (CDC) to fund development of the public health infrastructure needed to realize nationwide improvements in dementia risk reduction, detection, and caregiver support (ASPE, 2021). This national investment, supported by decades of research by investigators across the scientific spectrum, deploys the tools of public health to advance understanding, influence policy and practice, and lighten the burden of dementia on the population as a whole.

The BOLD Public Health Center of Excellence on Early Detection of Dementia—one of three CDC-funded centers dedicated to dementia as a public health concern—supports efforts to improve dementia detection and care by collating and disseminating the best evidence on early detection methods, strategies for implementation in everyday settings, and improving clinical outcomes (CDC, 2022a). Below we summarize the state of dementia detection, the rationale for early detection, and challenges to successful implementation, as well as suggesting ways to close persistent gaps in knowledge and policy.

Defining Early Detection

What does early detection mean? It varies. Pharmaceutical companies working on disease-modifying biotherapeutics for Alzheimer’s Disease see early detection in terms of the very earliest phases of one specific disease confirmed with biomarker tests, before cognitive impairment is manifest or is just barely detectable.

Healthcare reformers might frame the answer in terms of shortening the delay between the first appearance of symptoms and a responsive clinical evaluation and care plan.

Dementia specialists typically see the goal as arriving at a specific causal diagnosis and a disease-focused treatment plan.

Family doctors might say early detection means recognition before dementia interferes with medical management or causes avoidable medical and psychosocial crises.

For community social service providers, it may mean identifying people who need long-term supportive services and support to alleviate family stress.

People living with dementia and those close to them may simply want to know what’s wrong, how to cope, and what to expect and plan for.

For purposes of this article, we define early detection as the systematic identification of individuals living with cognitive decline that is severe enough to interfere with everyday independence. This is the basic definition of dementia.

Dementia Detection: Current State

How well and how early do we now detect dementia? The best available evidence in the United States comes from federally funded, long-running research studies that use validated cognitive measures in carefully selected samples that aim to mirror the broader population. When research classification is matched with diagnosis in a clinical setting (e.g., through Medicare claims documenting medical care provided), most studies find that only about half of affected individuals have been diagnosed (Amjad et al., 2018; Luth & Prigerson, 2022; Qian et al., 2021), and that diagnosis is typically not “early”—it often occurs at moderate and severe stages, years after substantial cognitive decline has already had profound effects on an individual’s life and that of their care partners (de Vugt & Verhey, 2013). Many other studies support this basic conclusion.

Steps Toward Improving Early Detection: Three Approaches to Building Awareness

One approach to improving dementia detection has been to promote broad public understanding that brain health is important in overall health and that dementia is not a normal part of aging but is caused by brain disease and/or injury. The CDC’s Healthy Brain Initiative (CDC, 2022b) shares facts and tips via information campaigns and brings attention to the issue through telephone surveys conducted by state departments of health. Recent results published by the CDC show that fewer than half of people reporting cognitive concerns say they have talked about it with their doctor (CDC, 2022c).

A second approach teaches practicing clinicians to recognize dementia in their patients who may be at risk. Typical approaches use continuing medical education to teach clinicians about dementia and its causes, how to use standardized cognitive assessments, and how to implement best practices in dementia care. The 48 Geriatric Workforce Enhancement Programs funded by the Health Resources and Services Administration and a growing array of locally and nationally sponsored educational initiatives provide dementia training for clinicians.

A third approach works at the level of healthcare systems, bringing principles of geriatric care into everyday healthcare delivery. The “Age-Friendly Health System” (Institute for Healthcare Improvement, 2019) movement trains systems to implement brain health assessments (e.g., screening for dementia, delirium, and depression) as part of qualifying for national recognition by the Institute for Healthcare Improvement as an Age-Friendly System. Becoming age-friendly usually also means learning about and using dementia-relevant Medicare benefits.

Creating New Insurance Benefits

In 2011, the Centers for Medicare & Medicaid Services (CMS) introduced the Annual Wellness Visit (AWV), a new preventive health visit that reimburses providers to assess individuals’ health risks (including detecting any cognitive impairment) and create a proactive management plan. This way, CMS enables a voluntary dementia case-finding approach, but uptake by providers and healthcare systems is inconsistent (Ganguli et al., 2018) and—despite public awareness campaigns focused particularly on Alzheimer’s disease as the most common cause of dementia—there has been no clear demand from beneficiaries to spur adoption.

Findings are mixed as to whether the AWV has increased detection (Fowler et al., 2018; Lind et al., 2018) and no studies address the stage at which detection is occurring. CMS’ Cognitive Assessment and Care Plan visit, introduced in 2017, covers the next step in integrating recognized cognitive impairment into a multi-domain care plan. In the first year after its introduction, this benefit was used in fewer than 1% of eligible beneficiaries.(Li, Andy, & Mitchell, 2021)

Does Early Detection Matter?

Many families and clinicians think so. Individuals with early stage Alzheimer’s disease speak publicly about their struggles to get a diagnosis, and many families wish they had known earlier and been able to avoid the distress and conflict that can accompany undiagnosed dementia. (de Vugt & Verhey, 2013).

But can we measure the benefits in better outcomes for patients, lessened burden for families, or better decisions by clinicians? We don’t know. While it’s reasonable to assume that detecting the problem would lead to better care, rigorous evidence is lacking. The United States Preventive Services Task Force (USPSTF), an official body that provides influential evaluations of many healthcare practices, has three times, most recently in 2020, concluded that use of validated dementia screening tools can increase detection but evidence is insufficient to support screening of people with no existing indicator of impairment. (Owens et al., 2020).

At first, the USPSTF also found insufficient evidence for benefit from screening for depression—until multiple intervention trials showed clear benefit; the USPSTF now endorses depression screening if adequate treatment resources are provided (USPSTF, 2016) and it has recently approved screening for anxiety.

Why Diagnose Dementia?

There are three main reasons to detect and diagnose any medical condition: it leads to a treatment decision, affects an individual’s future health and longevity, or alleviates confusion and misunderstanding by explaining vexing signs and symptoms. All three reasons apply to dementia, and a fourth has emerged from studies of patterns of healthcare use: dementia increases the need for unplanned acute care, including emergency department visits and hospitalizations (Davydow et al., 2014; LaMantia et al., 2016; Ma et al., 2019), and increases the cost of care for older adults (Jutkowitz et al., 2017).

These statistics have not persuaded health system planners to adopt systematic dementia detection; doing so requires following up with thoughtful, personalized, sometimes complicated interventions that will change over time, do not easily fit healthcare work streams, and do not “pay their way” through existing reimbursement mechanisms.

What if the number of people eligible for detection efforts weren’t so large? Several ongoing research programs are testing the idea that selecting high risk groups (e.g., those of advanced age or who have poorly controlled diabetes, hypertension, or cardiovascular disease) could increase the efficiency of case finding by concentrating efforts on individuals who are more likely to be cognitively impaired. A systematic evidence review found that screening hospitalized patients with heart failure identified a group at high risk for hospital readmission (Kewcharoen et al., 2019).

If It’s the System, Change It!

Changing healthcare delivery is difficult, especially in large, complex systems when it means persuading leaders to change priorities, take on potential financial risk, mount new training programs, or restructure working relationships among individuals, communities, clinicians, health system planners, payers, and sometimes public health entities. “Carrots”—such as the dementia-relevant Medicare benefits described above—are insufficient to motivate big changes; “sticks”—such as penalties for falling short of certain quality goals—may be more potent, but reportable quality goals do not exist for dementia care outside of highly specialized practices, and even there, quality reporting is voluntary and its effect on patient outcomes has not been studied.

Smaller healthcare units or systems, especially when motivated by proprietary interests to experiment with new ways of delivering care, may achieve rapid and substantial improvements for even very complex patients, yet their inspiring stories are rarely accompanied by published data. Absent dramatic advances in treatment—as happened for hepatitis C with curative antiviral drugs—healthcare change takes a more circuitous path: prioritizing a new goal, building stakeholder buy-in, developing persuasive evidence, proposing (and often legislating) practice or policy solutions, establishing and reporting quality measures, and funding implementation of new care designs (Grol & Wensing, 2020).

For all the recent media attention on dementia, growing public awareness, and explosive growth in research, dementia care—including encouraging people to engage in brain-healthy behaviors, and dementia recognition and subsequent management—still largely relies upon the readiness of healthcare providers and systems, and in particular, on primary care as the only source of healthcare for most people in the United States.

Challenges for Primary Care

The need for thoughtful, personalized, and sometimes complicated interventions to improve dementia detection and care may inspire a sense of futility. Barriers to implementation may seem insurmountable, especially in primary care. Practitioners are inundated with clinical “best practice” alerts, mandatory quality measures, and productivity pressures to do more with relatively less reimbursement and fewer resources (Ancker et al., 2017). Too many spend precious evening and weekend time documenting the clinical work they’ve already done, and many flee from the latest practice alert when it pops up on their electronic medical record screen. Adding dementia detection to their list of “to-dos” might seem infeasible.

However, primary care practitioners do conduct thoughtful, personalized, and complicated interventions for other typical primary care conditions such as difficult-to-control hypertension, respiratory symptom diagnosis and management, or health-impairing personal behaviors. These interventions (among others) add tremendous value to our population’s health—primary care is the only healthcare discipline that is capable of doing so (Hughes, Cohen, and Phillips, 2022). So why can’t we add dementia detection and care to primary care’s successes? Why can’t dementia detection become a regular part of any routine clinical exam?

Health professionals, like the rest of us, engage in rituals. Despite the relentless call for “evidence-based practice” as a rational driver of clinical behavior, many preventive screenings that clinicians do lack compelling evidence. Imagine a visit to your doctor without having your blood pressure taken! Blood pressure measurement is, in fact, a “screen for hypertension.” If you have normal blood pressure, do you need to be “screened” every time? To make the most effective use of blood pressure tracking for health, perhaps three or four times a year is plenty for most people—but we have no evidence as to how often blood pressure should be measured. Blood sugar—a “screen for diabetes”—is part of nearly every routine blood test panel regardless of individual risk for diabetes, and providers conduct physical exams when no symptoms or signs are present, fearing they may miss an important condition. The physical exam too is a clinical ritual: visits may feel incomplete without one and patients expect at least some “laying on of hands.”

The COVID-19 pandemic altered this expectation out of necessity; we now know that much can be accomplished through virtual visits. Why can’t some of our routine, time-consuming activities with low single-visit yield be periodically replaced with brain health-related activities? What might such brain-focused activities look like?

Implementing Brain Health Care in Clinical Practice

Brain-focused care starts with a conversation. Managing blood pressure in midlife and earlier is about the brain—preventing strokes as well as heart attacks and kidney failure. Treating sleep apnea is about the brain—keeping the brain well oxygenated while sleeping. Managing diabetes is also about protecting the brain from harmful effects of metabolic and vascular disease. Stopping smoking and getting regular exercise are also about protecting the brain. This is the preventive side of brain health conversations; they can and should start much earlier than late life when concerns about dementia loom larger.

Moving Toward Population-based Dementia Detection

When symptoms and signs of cognitive impairment raise the possibility of dementia, the brain health conversation shifts toward detection and diagnosis, and it usually involves not only clinicians and patients, but also families. Dementia detection starts with asking the right questions in a sensitive manner that engenders trust, then knowing how to talk about the findings, propose meaningful next steps, and connect people to resources they can use and benefit from. Primary care practitioners already do this for many other healthcare conditions. But for dementia detection to become part of routine care, primary care practitioners need help.

Displaying brain health information prominently in primary care clinics—along with other health information—can help to mainstream awareness. Today’s healthcare technology offers several opportunities to capture clinicians’ attention: flagging patient demographic or clinical characteristics associated with higher risk, creating an electronic reminder, or adding a brain health placeholder to a structured electronic visit note. Electronic health record prompts to engage in dementia detection can be driven by a background computer algorithm that identifies patients at higher risk due to age, coexisting health conditions or other characteristics associated with greater probability of dementia. Such algorithms also could be directed toward individuals through electronic patient portals—encouraging them to bring up brain health with their clinician at their next visit. Whether directed toward clinicians, patients, or both, a case-finding approach can be an efficient and productive use of clinician time. The care most people with dementia need—when it’s detected early, at mild stages—is already in the domain of the primary care provider. But practitioners need to know what and how to do early detection, and then how to add some simple, relevant steps.

A Simple, Four-Step Approach for Primary Care

These steps include learning a few straightforward, encouraging statements and questions that introduce the subject (see Figure 1, above), knowing how to use and interpret a simple screening tool that most individuals readily accept (e.g., the Mini-Cog), following with a few brief questions that reveal changes in everyday function that depend upon cognition (see Figure 2, below) and/or use a simple validated functional inventory, (e.g., the Functional Activities Questionnaire), and being ready to explain the results in plain language. The combination of a simple, person-friendly detection strategy grounded in cognition and function sets the stage for additional steps in medical evaluation that can lead toward explaining the likely cause(s) of cognitive decline.

This simple approach is part of a “stigma-busting” strategy that helps remove the mystery surrounding dementia. Stigma is the elephant in the room. To combat it, dementia needs to be reframed as a condition that exists on a continuum of strengths and weaknesses in brain function—not as an all-or-nothing situation that deprives an individual of personhood and agency. These functions might be positively influenced through brain-healthy behaviors. Public health has an outsize role in supporting this reframing through public messaging, marketing strategies and “flooding” health and wellness conversations, much like what has been done for other conditions such as HIV, drug and alcohol abuse, and suicide.

Public health messaging will facilitate detection in the primary care space as patients and providers become more comfortable engaging in detection activities, in having these important conversations and understanding in concrete terms what having the condition means.

Dementia is demystified through use of plain language to explain the changes in brain structure and function that produce changes in how we think and act.

We know a lot about how to successfully detect and diagnose dementia, and how to care for affected individuals and those who love them. Changes in healthcare reimbursement policy could provide the necessary spark to improve detection and care. However, the solutions are likely to be largely local, and usually rely upon clinicians who will champion a change and get the backing of a supportive administration. Champions are individuals who express a commitment to achieving a specific change, have skills to facilitate it, and are respected by their peers as clinical leaders (Miech et al., 2018).

Identifying these champions and providing them with clear and easily accessible materials to support dementia detection and care strategies may lead to more widespread systemic change, especially when successful exemplars are identified and promoted through dissemination activities. The BOLD Public Health Center of Excellence on Early Detection of Dementia is committed to supporting clinical and public health champions working in any stage of a dementia detection program and identifying and disseminating their success.

Soo Borson, MD, is professor of Clinical Family Medicine at Keck USC School of Medicine and professor emerita of Psychiatry and Behavioral Sciences at University of Washington, and co-lead of the BOLD Center of Excellence on Early Detection of Dementia. She may be contacted at borson@usc.edu or soob@uw.edu. Joshua Chodosh, MD, MSHS, is director of the Division of Geriatric Medicine and Palliative Care, co-lead of the BOLD Center of Excellence on Early Detection of Dementia, and professor of Medicine and Population Health at the NYU Grossman School of Medicine. He may be contacted at joshua.chodosh@nyulangone.org.

Photo credit: MMD Creative/Shutterstock

References

Amjad, H., Roth, D. L., Sheehan, O. C., Lyketsos, C. G., Wolff, J. L., & Samus, Q. M. (2018). Underdiagnosis of Dementia: an Observational Study of Patterns in Diagnosis and Awareness in US Older Adults. Journal of General Internal Medicine, 33(7), 1131–8. https://doi.org/10.1007/s11606-018-4377-y

Ancker, J. S., Edwards, A., Nosal, S., Hauser, D., Mauer, E., & Kaushal, R. (2017). Effects of workload, work complexity, and repeated alerts on alert fatigue in a clinical decision support system. BMC Medical Informatics and Decision Making, 17(1), 36. https://doi.org/10.1186/s12911-017-0430-8

ASPE. (2021). National Plan to Address Alzheimer’s Disease: 2021 Update. https://bit.ly/3JOeAYw.

Centers for Disease Control and Prevention (CDC). (2022a). BOLD Public Health Centers of Excellence Recipients. www.cdc.gov/aging/funding/phc/index.html.

CDC. (2022b). Healthy Brain Initiative. www.cdc.gov/aging/healthybrain/.

CDC. (2022c). Subjective Cognitive Decline—A Public Health Issue. https://bit.ly/3z5ZCHr.

Davydow, D. S., Zivin, K., & Langa, K. M. (2014). Hospitalization, depression and dementia in community-dwelling older Americans: findings from the national health and aging trends study. General Hospital Psychiatry, 36(2), 135–41. https://doi.org/10.1016/j.genhosppsych.2013.11.008

de Vugt, M. E., & Verhey, F. R. (2013). The impact of early dementia diagnosis and intervention on informal caregivers. Progress in Neurobiology, 110, 54–62. https://doi.org/10.1016/j.pneurobio.2013.04.005

Fowler, N. R., Campbell, N. L., Pohl, G. M., Munsie, L. M., Kirson, N. Y., Desai, U., Trieschman, E. J., Meiselbach, M. K., Andrews, J. S., & Boustani, M. A. (2018). One-Year Effect of the Medicare Annual Wellness Visit on Detection of Cognitive Impairment: A Cohort Study. Journal of the American Geriatrics Society, 66(5), 969–75. https://doi.org/10.1111/jgs.15330

Ganguli, I., Souza, J., McWilliams, J. M., & Mehrotra, A. (2018). Practices Caring For the Underserved Are Less Likely to Adopt Medicare's Annual Wellness Visit. Health Affairs (Millwood), 37(2), 283–91. https://doi.org/10.1377/hlthaff.2017.1130

Grol, R., & Wensing, M. (2020). Effective Implementation of Change in Healthcare. In Improving Patient Care (pp. 45–71). https://doi.org/https://doi.org/10.1002/9781119488620.ch3

Hughes, L. S., Cohen, D. J., & Phillips, R. L., Jr. (2022). Strengthening Primary Care to Improve Health Outcomes in the US—Creating Oversight to Address Invisibility. JAMA Health Forum, 3(9), e222903. https://doi.org/10.1001/jamahealthforum.2022.2903

Institute for Healthcare Improvement. (2019). What Is an Age-Friendly Health System? https://bit.ly/3FtwkpK.

Jutkowitz, E., Kane, R. L., Gaugler, J. E., MacLehose, R. F., Dowd, B., & Kuntz, K. M. (2017). Societal and Family Lifetime Cost of Dementia: Implications for Policy. Journal of the American Geriatrics Society, 65(10), 2169–75. https://doi.org/10.1111/jgs.15043

Kewcharoen, J., Trongtorsak, A., Kanitsoraphan, C., Prasitlumkum, N., Mekritthikrai, R., Techorueangwiwat, C., Limpruttidham, N., & Rattanawong, P. (2019). Cognitive impairment and 30-day rehospitalization rate in patients with acute heart failure: A systematic review and meta-analysis. Indian Heart Journal, 71(1), 52–9. https://doi.org/10.1016/j.ihj.2018.12.006

LaMantia, M. A., Stump, T. E., Messina, F. C., Miller, D. K., & Callahan, C. M. (2016). Emergency Department Use Among Older Adults With Dementia. Alzheimer Disease and Associated Disorders, 30(1), 35–40. https://doi.org/10.1097/wad.0000000000000118

Li, J., Andy, C., & Mitchell, S. (2021). Use of Medicare’s New Reimbursement Codes for Cognitive Assessment and Care Planning, 2017-2018. JAMA Network Open, 4(9), e2125725-e2125725. https://doi.org/10.1001/jamanetworkopen.2021.25725

Lind, K. E., Hildreth, K., Lindrooth, R., Crane, L. A., Morrato, E., & Perraillon, M. C. (2018). Ethnoracial Disparities in Medicare Annual Wellness Visit Utilization: Evidence From a Nationally Representative Database. Medical Care, 56(9), 761–6. https://doi.org/10.1097/mlr.0000000000000962

Luth, E. A., & Prigerson, H. G. (2022). Socioeconomic status, race/ethnicity, and unexpected variation in dementia classification in longitudinal survey data. The Journals of Gerontology. Series B, Psychological Sciences and Social Sciences, gbac128. https://doi.org/10.1093/geronb/gbac128

Ma, C., Bao, S., Dull, P., Wu, B., & Yu, F. (2019). Hospital readmission in persons with dementia: A systematic review. International Journal of Geriatric Psychiatry, 34(8), 1170–84. https://doi.org/10.1002/gps.5140

Miech, E. J., Rattray, N. A., Flanagan, M. E., Damschroder, L., Schmid, A. A., & Damush, T. M. (2018). Inside help: An integrative review of champions in healthcare-related implementation. SAGE Open Medicine, 6, 2050312118773261. https://doi.org/10.1177/2050312118773261

Owens, D. K., Davidson, K. W., Krist, A. H., Barry, M. J., Cabana, M., Caughey, A. B., Doubeni, C. A., Epling, J. W., Jr., Kubik, M., Landefeld, C. S., Mangione, C. M., Pbert, L., Silverstein, M., Simon, M. A., Tseng, C. W., & Wong, J. B. (2020). Screening for Cognitive Impairment in Older Adults: US Preventive Services Task Force Recommendation Statement. Jama, 323(8), 757–63. https://doi.org/10.1001/jama.2020.0435

United States Preventive Services Taskforce. (2016). Screening for Depression in Adults. https://bit.ly/42z5R43

Qian, Y., Chen, X., Tang, D., Kelley, A. S., & Li, J. (2021). Prevalence of Memory-Related Diagnoses Among U.S. Older Adults With Early Symptoms of Cognitive Impairment. The Journals of Gerontology: Series A, Biological Sciences and Medical Sciences, 76(10), 1846–53. https://doi.org/10.1093/gerona/glab043