| Literature DB >> 30339202 |
William Perry1,2,3, Laura Lacritz1,4, Tresa Roebuck-Spencer2,5, Cheryl Silver4,2, Robert L Denney1,6, John Meyers1, Charles E McConnel4, Neil Pliskin7, Deb Adler8, Christopher Alban9, Mark Bondi10, Michelle Braun11, Xavier Cagigas12, Morgan Daven13, Lisa Drozdick14, Norman L Foster15,16, Ula Hwang17,18,19,20, Laurie Ivey21, Grant Iverson1,22, Joel Kramer23, Melinda Lantz24, Lisa Latts25, Shari M Ling26, Ana Maria Lopez27,28,29,30, Michael Malone31,32, Lori Martin-Plank33, Katie Maslow34, Don Melady35,36,37, Melissa Messer38, Randi Most39, Margaret P Norris40, David Shafer14, Nina Silverberg41, Colin M Thomas42, Laura Thornhill43, Jean Tsai15,44, Nirav Vakharia45, Martin Waters46, Tamara Golden47.
Abstract
Entities:
Mesh:
Year: 2018 PMID: 30339202 PMCID: PMC6201735 DOI: 10.1093/arclin/acy052
Source DB: PubMed Journal: Arch Clin Neuropsychol ISSN: 0887-6177 Impact factor: 2.813
Differences between screening and diagnostic tools
| Cognitive screening measures | Diagnostic tests for dementia | |
|---|---|---|
| Purpose of test | Detect potential disease indicators | Establish presence or absence of a specific disease |
| Target population | Large number of individuals selected on the basis of demographic or clinical characteristics who are not previously diagnosed with the condition of interest | Symptomatic individuals, or those at high risk |
| Test characteristics | Simple, acceptable to patients and staff Inexpensive; the benefit must justify the cost of screening large numbers of individuals | May be invasive; precision of test weighted more than its patient acceptability May be expensive; cost is justified as necessary to establish diagnosis |
| Positive result threshold | Set to achieve high sensitivity (maximize potential positives) | Set to achieve high specificity (minimize false negatives) |
| Implication of positive result | Suspicion of disease; in combination with other risk factors provides reason for additional follow up | Provides definite diagnosis and thus prognosis and identification of appropriate management |
Key takeaway conclusions
There is a need to educate the public regarding the difference between |
It is important to emphasize that cognitive impairment screening is a measure of brain health, which needs to be monitored regularly in at-risk individuals to determine the fidelity of brain functioning. |
Cognitive impairment in older adults has multiple possible causes, including medical and psychiatric conditions, such as endocrine and metabolic conditions, chronic pain, depression, sleep disturbance, medication side-effects, delirium, and brain diseases causing dementia, with Alzheimer’s disease and MCI being the most common. |
Cognitive impairment is a clinically dominant comorbidity. Cognitive impairment is so serious that it overshadows the management of other health problems. It influences the effectiveness of doctor–patient communication, treatment adherence, the likelihood of medical follow-up, the selection of appropriate medications, and likely medication side effects. |
Cognitive evaluation to determine the causes and remediable factors contributing to impairment is necessary to guide appropriate choice of medications and management. |
Collaborative care models that include the expertise of specialists in the area of cognitive assessment (i.e., neuropsychologists, neurologists and geropsychiatrist) may be cost-effective and provide better quality care. In the emerging value over volume payment models, inclusion of cognitive specialists fits well into new team-based payment models that emphasize overall wellness. |
The EHR presents a great deal of promise for risk stratification modeling and for monitoring changes in cognitive screen performance over time. EHR automated tools for assessing and recording the results of individual’s cognition over time need to be developed. |
There is a need to increase awareness of identifying risk factors beyond medical data that include social, behavioral, and functional information. |
No one size fits all when assessing for cognitive impairment. It is important to recognize that the goals and means of cognitive assessment depend on the clinical setting and differ between the ED and the primary care environment. |
There is an important role that care managers or coordinators play in ensuring that people stay on a care pathway, and may also increase patient and caregiver satisfaction. |
There are deficiencies in health services in rural and economically disadvantaged America, resulting in a large gap in access to care and differences in resources such as care coordinators and cognitive specialists. |
Assessment of cognition must be done in a linguistically and culturally appropriate way to obtain meaningful results. |
There is a great need to increase advocacy regarding Medicare coverage and payment for a range of services and supports for beneficiaries with cognitive impairment (for example, including reimbursement for psychologists on interdisciplinary teams). |
Identified knowledge gaps
The need for research to determine whether “best practice” algorithms will guide risk stratification models and improve detection of cognitive impairment. |
Empirical determination of the best screening tools to use to assess cognitive impairment when taking in to consideration patient and provider acceptability, cost, time, sensitivity and specificity. |
How best to factor in language and cultural determinants when screening for cognitive impairment. |
How best to factor in a person’s age, intelligence, and education when interpreting screening and assessment results. |
What care models are most effective, time and cost efficient when conducting cognitive screening in the absence of clinical signs of cognitive disorder. |
How to consider repeated screening and the use of baseline data against which future assessments can be compared. |
What ways the EHR can best be leveraged to identify at risk individuals and document for all providers the cognitive health status of their patients. |
How best to utilize “smart technologies” and how to integrate these technologies with traditional medical data. |