- Email: [email protected]
ELECTRONIC MEDICAL RECORD (EMR) PREDICTORS OF UNDIAGNOSED DEMENTIA
P1040
P3-253
Poster Presentations: Tuesday, July 18, 2017
2.2%, p¼0.0013). Thirteen percent (n¼764) of all patients recruited (n¼5,887) were administered the ADAS-Cog to diagnose or monitor their disease. These patients were more likely to have a family history of AD (38.5% vs. 27.1%, p<0.0001), require both professional and non-professional caregiving (27.0% vs. 22.1%, p¼0.0004) and be diagnosed by a neurologist (56.9% vs. 45.1%, p<0.0001). Conclusions: Use of the ADAS-cog is rare in the real world and is mostly used by neurologist, physicians attending or delivering care at memory clinics, and physicians participating in clinical trials. Patients appear more likely to have been administered the ADAS-Cog if they had more risk factors for AD, more severe symptoms, needed specialist care, or had caregiver requirements. Our data suggests that attempts to associate clinical meaningfulness to the ADAS-Cog are severely hampered by low rates of real world clinical use.
REAL WORLD ADMINISTRATION OF THE ALZHEIMER’S DISEASE ASSESSMENT SCALE-COGNITIVE
Christopher M. Black1, Craig W. Ritchie2, Robert Wood3, Rezaul Karim Khandker1, Eddie Jones3, Baishali M. Ambegaonkar1, 1Merck & Co., Inc., Kenilworth, NJ, USA; 2University of Edinburgh, Edinburgh, United Kingdom; 3 Adelphi Real World, Macclesfield, United Kingdom. Contact e-mail: [email protected] Background: The Alzheimer’s disease assessment scale-cognitive (ADAS-Cog) is the preferred efficacy measure in Alzheimer’s disease (AD) clinical trials but is rarely used in real-world practice ADAS-cog data generated in the real-world could be used to facilitate a better understanding of the clinical and economic meaningfulness of ADAS-cog changes observed during trials. The objective of this analysis was to estimate the frequency of ADAS-cog use in the real-world and describe the characteristics of administering physicians and their patients. Methods: Data were taken from the 2015/16 Adelphi RealWorld Dementia Disease Specific Programme, a cross-sectional survey of physicians, and their patients with cognitive impairment (CI) in the UK, France, Italy, Germany, Spain, Canada and the US. Physicians completed interviews about their clinical knowledge and practice setting and also completed record forms, containing patient demographics, clinical characteristics, diagnosis and tests/scales performed to aid diagnosis. Results: While 71% (n¼534) of all physicians surveyed (n¼757) were aware of the ADAS-Cog, only 40% (n¼211) used the ADAS-Cog in clinical practice with varying levels of frequency: 9.5% very often, 22.4% often, 52.4% occasionally and 15.7% rarely. Physicians who administered the ADAS-Cog were more likely to be neurologists (48.8% vs. 37.6%, p¼0.0410), deliver care at memory clinics (50.5% vs. 25.5%, p<0.0001), or were currently involved in CI/dementia clinical trials (10.6% vs.
Risk factors/Comorbidities Cerebrovascular disease Congestive heart failure Diabetes Depression Traumatic brain injury Healthcare Utilization 1 emergency department visit 1 hospitalization 1 visit for accident/injury 1 “no show”
P3-254
WITHDRAWN
P3-255
ELECTRONIC MEDICAL RECORD (EMR) PREDICTORS OF UNDIAGNOSED DEMENTIA
Sei J. Lee1, Eric B. Larson2, Sascha Dublin3, Rod L. Walker3, Zachary Marcum4, Deborah E. Barnes1, 1University of California San Francisco/San Francisco VA Medical Center, San Francisco, CA, USA; 2Group Health Research Institute/Kaiser Permanente Washington Health Research Institute, Seattle, WA, USA; 3 Group Health Research Institute, Seattle, WA, USA; 4 University of Washington, Seattle, WA, USA. Contact e-mail: [email protected] Background: Patients with undiagnosed dementia are more likely than those with a diagnosis to require emergency care for comorbid conditions and to engage in risky behaviors such as driving. Efficient strategies to identify patients with undiagnosed dementia are needed. Our goal was to determine whether information in the electronic medical record (EMR) can be used to detect patients with undiagnosed dementia. Methods: We used data from Adult Changes in Thought (ACT), a prospective cohort study within Group Health (GH), an integrated healthcare delivery system. ACT enrolls non-demented community-dwelling GH members aged 65+ and performs in-person biennial assessments to identify incident dementia. The GH EMR includes data on diagnoses, procedures, utilization, vital signs, pharmacy, laboratory results and clinical notes. We categorized ACT participants with incident
Diagnosed Dementia (N¼544)
Undiagnosed Dementia (N¼436)
No Dementia (N¼1308)
Age-adjusted p-value (undiagnosed vs. no dementia)
35% 28% 15% 38% 14%
22% 28% 20% 25% 8%
10% 13% 13% 14% 3%
<0.001 0.004 <0.001 <0.001 0.003
53% 46% 25% 53%
48% 31% 14% 43%
25% 21% 6% 29%
<0.001 0.02 0.006 <0.001
Poster Presentations: Tuesday, July 18, 2017
dementia as having “diagnosed dementia” if the GH EMR contained a dementia diagnosis or dementia-related medication dispensing prior to the date of dementia detection in ACT (the index date) and as having “undiagnosed dementia” if none of these elements were present. Each “undiagnosed dementia” case was matched with three randomly selected ACT participants who did not develop dementia. Characteristics of “undiagnosed” and “no dementia” patients were compared using age-adjusted conditional logistic regression. Results: 44% of dementia patients were undiagnosed. Undiagnosed dementia patients were more likely than no dementia patients to have dementia risk factors and comorbidities including cerebrovascular disease (22% vs. 10%, p<0.001), diabetes (20% vs. 13%, p<0.001), congestive heart failure (28% vs. 13%, p¼0.004), depression (25% vs. 14%, p<0.001) and traumatic brain injury (8% vs. 3%, p¼0.003). In addition, they were more likely to have had at least one emergency department visit (48% vs. 25%, p<0.001), hospitalization (31% vs. 21%, p¼0.024), or visit for an injury (14% vs. 6%, p¼0.006), and to “no-show” for a scheduled ambulatory visit (43% vs. 29%, p<0.001) in the previous two years. Conclusions: The EMR includes many elements that could be used to identify patients likely to have undiagnosed dementia. Additional studies are needed to develop an optimal predictive model and ultimately to investigate whether identifying and screening these patients could improve clinical outcomes and quality of life. P3-256
THE PREVALENCE, CAUSES AND CONSEQUENCES OF UNDIAGNOSED DEMENTIA IN ENGLAND: A RECORD LINKAGE STUDY OF THE COGNITIVE FUNCTION AND AGEING STUDY II
Clare Aldus1, Carol Brayne2, Fiona Matthews3, Antony Arthur1, Tom Dening4, Chris Fox1, Louise Robinson5, Blossom C. M. Stephan5, George M. Savva1, 1University of East Anglia, Norwich, United Kingdom; 2 University of Cambridge, Cambridge, United Kingdom; 3Newcastle University, Newcastle, United Kingdom; 4University of Nottingham, Nottingham, United Kingdom; 5Newcastle University, Newcastle upon Tyne, United Kingdom. Contact e-mail: [email protected] Background: It is acknowledged that, whatever criteria are used, a substantial proportion of people with dementia remain undiagnosed. This may vary according to diagnostic methods, the services available and clinical and community perceptions of the value of diagnosis. Research that can examine the characteristics of those who are known to services in relation to an independent and objective assessment of dementia is rare. Here we describe diagnostic status of a population representative cohort of people with dementia, and estimate the prevalence, predictors and outcomes of undiagnosed dementia in England. Methods: The Cognitive Function and Ageing Study II (CFAS II) recruited 7500 people aged 65 years from three areas of England (2008-11). Baseline and two year follow-up assessments included a cognitive battery, personal interview and an informant interview. For each participant study dementia status, previously validated against DSM-III-R, was established. Primary care records from 598 participants with consent for health service data linkage were sought including 447 people with dementia and a stratified subsample of those without (n¼151). Dementia diagnoses, cognitive complaints and referrals to specialist services were extracted. Linking study diagnoses and CFAS II assessments with the records held in primary care enables estimation of: (i) the true relation-
P1041
ship between those receiving a formal health service diagnosis and those receiving a study diagnosis; (ii) social and clinical predictors of becoming diagnosed; and, (iii) outcomes among the diagnosed and non-diagnosed populations. We hypothesise that these groups will vary in social circumstances, signs and symptoms, comorbidities and service use outcomes. Results: To date primary care records from 472 patients have been collected. We will present the prevalence of diagnosis among groups stratified by dementia severity, and the proportion of those with no diagnosis but with a record of help seeking or referral to secondary services. We will compare the characteristics and service use history of diagnosed and undiagnosed people with dementia. Conclusions: Epidemiological studies including objective validated dementia diagnoses provide a unique opportunity to estimate the extent and predictors of heath service use among people with dementia. This is important to understanding dementia in populations and improving diagnostic and support services. P3-257
DECODING VARIABILITY IN AGE-ATSYMPTOMATIC-ONSET BETWEEN PARENTS AND CHILDREN WITH SPORADIC ALZHEIMER DISEASE DEMENTIA
Gregory S. Day1,2, Carlos Cruchaga3,4, Thomas Wingo5, John C. Morris3,6, 1 Knight Alzheimer Disease Research Center, St. Louis, MO, USA; 2 Washington University in St. Louis, St. Louis, MO, USA; 3Washington University School of Medicine, St. Louis, MO, USA; 4Knight Alzheimer Disease Center, Saint Louis, MO, USA; 5Emory University, Atlanta, GA, USA; 6Knight Alzheimer’s Disease Research Center, St. Louis, MO, USA. Contact e-mail: [email protected] Background: Adult children of demented individuals harbor an increased risk of developing AD dementia, with ages-at-symptomatic-onset (AAO) that may differ from those of their affected parent(s). Factors responsible for differences in AAO within families remain unknown. We hypothesized that participant-specific factors may account for a proportion of this variability. Methods: The prevalence of putative dementia risk factors was determined in 482 participants with symptomatic AD dementia and a reported parental history of dementia. All participants were enrolled within Knight Alzheimer Disease Research Center longitudinal studies of memory and aging between August 1979 and February 2016. For each participant, the difference between the (reported) parental AAO, and the (observed) participant AAO was determined, and used to stratify participants. “Early” participants manifested with AD dementia >10 years before parental AAO (n¼79), while “late” participants were diagnosed >10 years after parental AAO (n¼73). The prevalence of putative dementia risk factors were compared across groups, including female gender; years of education; race; body mass index; and past or present history of cardiovascular disease, hypertension, hypercholesterolemia, diabetes, depression, traumatic brain injury, and tobacco and/or alcohol abuse. APOEallele status was also considered, given its recognized association with dementia risk. Results: Participants were diagnosed with AD dementia, on average, 6.1610.9 years earlier than their parent(s) (p<0.001). Maternal history of dementia was most common, reported amongst 74% of participants (p<0.001). Both parents were affected in 7% of cases. Despite differences in frequency, the pattern of inheritance did not account for the earlier-than-expected AAO in participants (p¼0.6). Likewise, although putative risk factors were commonly represented in our sample, no single
P3-253
Poster Presentations: Tuesday, July 18, 2017
2.2%, p¼0.0013). Thirteen percent (n¼764) of all patients recruited (n¼5,887) were administered the ADAS-Cog to diagnose or monitor their disease. These patients were more likely to have a family history of AD (38.5% vs. 27.1%, p<0.0001), require both professional and non-professional caregiving (27.0% vs. 22.1%, p¼0.0004) and be diagnosed by a neurologist (56.9% vs. 45.1%, p<0.0001). Conclusions: Use of the ADAS-cog is rare in the real world and is mostly used by neurologist, physicians attending or delivering care at memory clinics, and physicians participating in clinical trials. Patients appear more likely to have been administered the ADAS-Cog if they had more risk factors for AD, more severe symptoms, needed specialist care, or had caregiver requirements. Our data suggests that attempts to associate clinical meaningfulness to the ADAS-Cog are severely hampered by low rates of real world clinical use.
REAL WORLD ADMINISTRATION OF THE ALZHEIMER’S DISEASE ASSESSMENT SCALE-COGNITIVE
Christopher M. Black1, Craig W. Ritchie2, Robert Wood3, Rezaul Karim Khandker1, Eddie Jones3, Baishali M. Ambegaonkar1, 1Merck & Co., Inc., Kenilworth, NJ, USA; 2University of Edinburgh, Edinburgh, United Kingdom; 3 Adelphi Real World, Macclesfield, United Kingdom. Contact e-mail: [email protected] Background: The Alzheimer’s disease assessment scale-cognitive (ADAS-Cog) is the preferred efficacy measure in Alzheimer’s disease (AD) clinical trials but is rarely used in real-world practice ADAS-cog data generated in the real-world could be used to facilitate a better understanding of the clinical and economic meaningfulness of ADAS-cog changes observed during trials. The objective of this analysis was to estimate the frequency of ADAS-cog use in the real-world and describe the characteristics of administering physicians and their patients. Methods: Data were taken from the 2015/16 Adelphi RealWorld Dementia Disease Specific Programme, a cross-sectional survey of physicians, and their patients with cognitive impairment (CI) in the UK, France, Italy, Germany, Spain, Canada and the US. Physicians completed interviews about their clinical knowledge and practice setting and also completed record forms, containing patient demographics, clinical characteristics, diagnosis and tests/scales performed to aid diagnosis. Results: While 71% (n¼534) of all physicians surveyed (n¼757) were aware of the ADAS-Cog, only 40% (n¼211) used the ADAS-Cog in clinical practice with varying levels of frequency: 9.5% very often, 22.4% often, 52.4% occasionally and 15.7% rarely. Physicians who administered the ADAS-Cog were more likely to be neurologists (48.8% vs. 37.6%, p¼0.0410), deliver care at memory clinics (50.5% vs. 25.5%, p<0.0001), or were currently involved in CI/dementia clinical trials (10.6% vs.
Risk factors/Comorbidities Cerebrovascular disease Congestive heart failure Diabetes Depression Traumatic brain injury Healthcare Utilization 1 emergency department visit 1 hospitalization 1 visit for accident/injury 1 “no show”
P3-254
WITHDRAWN
P3-255
ELECTRONIC MEDICAL RECORD (EMR) PREDICTORS OF UNDIAGNOSED DEMENTIA
Sei J. Lee1, Eric B. Larson2, Sascha Dublin3, Rod L. Walker3, Zachary Marcum4, Deborah E. Barnes1, 1University of California San Francisco/San Francisco VA Medical Center, San Francisco, CA, USA; 2Group Health Research Institute/Kaiser Permanente Washington Health Research Institute, Seattle, WA, USA; 3 Group Health Research Institute, Seattle, WA, USA; 4 University of Washington, Seattle, WA, USA. Contact e-mail: [email protected] Background: Patients with undiagnosed dementia are more likely than those with a diagnosis to require emergency care for comorbid conditions and to engage in risky behaviors such as driving. Efficient strategies to identify patients with undiagnosed dementia are needed. Our goal was to determine whether information in the electronic medical record (EMR) can be used to detect patients with undiagnosed dementia. Methods: We used data from Adult Changes in Thought (ACT), a prospective cohort study within Group Health (GH), an integrated healthcare delivery system. ACT enrolls non-demented community-dwelling GH members aged 65+ and performs in-person biennial assessments to identify incident dementia. The GH EMR includes data on diagnoses, procedures, utilization, vital signs, pharmacy, laboratory results and clinical notes. We categorized ACT participants with incident
Diagnosed Dementia (N¼544)
Undiagnosed Dementia (N¼436)
No Dementia (N¼1308)
Age-adjusted p-value (undiagnosed vs. no dementia)
35% 28% 15% 38% 14%
22% 28% 20% 25% 8%
10% 13% 13% 14% 3%
<0.001 0.004 <0.001 <0.001 0.003
53% 46% 25% 53%
48% 31% 14% 43%
25% 21% 6% 29%
<0.001 0.02 0.006 <0.001
Poster Presentations: Tuesday, July 18, 2017
dementia as having “diagnosed dementia” if the GH EMR contained a dementia diagnosis or dementia-related medication dispensing prior to the date of dementia detection in ACT (the index date) and as having “undiagnosed dementia” if none of these elements were present. Each “undiagnosed dementia” case was matched with three randomly selected ACT participants who did not develop dementia. Characteristics of “undiagnosed” and “no dementia” patients were compared using age-adjusted conditional logistic regression. Results: 44% of dementia patients were undiagnosed. Undiagnosed dementia patients were more likely than no dementia patients to have dementia risk factors and comorbidities including cerebrovascular disease (22% vs. 10%, p<0.001), diabetes (20% vs. 13%, p<0.001), congestive heart failure (28% vs. 13%, p¼0.004), depression (25% vs. 14%, p<0.001) and traumatic brain injury (8% vs. 3%, p¼0.003). In addition, they were more likely to have had at least one emergency department visit (48% vs. 25%, p<0.001), hospitalization (31% vs. 21%, p¼0.024), or visit for an injury (14% vs. 6%, p¼0.006), and to “no-show” for a scheduled ambulatory visit (43% vs. 29%, p<0.001) in the previous two years. Conclusions: The EMR includes many elements that could be used to identify patients likely to have undiagnosed dementia. Additional studies are needed to develop an optimal predictive model and ultimately to investigate whether identifying and screening these patients could improve clinical outcomes and quality of life. P3-256
THE PREVALENCE, CAUSES AND CONSEQUENCES OF UNDIAGNOSED DEMENTIA IN ENGLAND: A RECORD LINKAGE STUDY OF THE COGNITIVE FUNCTION AND AGEING STUDY II
Clare Aldus1, Carol Brayne2, Fiona Matthews3, Antony Arthur1, Tom Dening4, Chris Fox1, Louise Robinson5, Blossom C. M. Stephan5, George M. Savva1, 1University of East Anglia, Norwich, United Kingdom; 2 University of Cambridge, Cambridge, United Kingdom; 3Newcastle University, Newcastle, United Kingdom; 4University of Nottingham, Nottingham, United Kingdom; 5Newcastle University, Newcastle upon Tyne, United Kingdom. Contact e-mail: [email protected] Background: It is acknowledged that, whatever criteria are used, a substantial proportion of people with dementia remain undiagnosed. This may vary according to diagnostic methods, the services available and clinical and community perceptions of the value of diagnosis. Research that can examine the characteristics of those who are known to services in relation to an independent and objective assessment of dementia is rare. Here we describe diagnostic status of a population representative cohort of people with dementia, and estimate the prevalence, predictors and outcomes of undiagnosed dementia in England. Methods: The Cognitive Function and Ageing Study II (CFAS II) recruited 7500 people aged 65 years from three areas of England (2008-11). Baseline and two year follow-up assessments included a cognitive battery, personal interview and an informant interview. For each participant study dementia status, previously validated against DSM-III-R, was established. Primary care records from 598 participants with consent for health service data linkage were sought including 447 people with dementia and a stratified subsample of those without (n¼151). Dementia diagnoses, cognitive complaints and referrals to specialist services were extracted. Linking study diagnoses and CFAS II assessments with the records held in primary care enables estimation of: (i) the true relation-
P1041
ship between those receiving a formal health service diagnosis and those receiving a study diagnosis; (ii) social and clinical predictors of becoming diagnosed; and, (iii) outcomes among the diagnosed and non-diagnosed populations. We hypothesise that these groups will vary in social circumstances, signs and symptoms, comorbidities and service use outcomes. Results: To date primary care records from 472 patients have been collected. We will present the prevalence of diagnosis among groups stratified by dementia severity, and the proportion of those with no diagnosis but with a record of help seeking or referral to secondary services. We will compare the characteristics and service use history of diagnosed and undiagnosed people with dementia. Conclusions: Epidemiological studies including objective validated dementia diagnoses provide a unique opportunity to estimate the extent and predictors of heath service use among people with dementia. This is important to understanding dementia in populations and improving diagnostic and support services. P3-257
DECODING VARIABILITY IN AGE-ATSYMPTOMATIC-ONSET BETWEEN PARENTS AND CHILDREN WITH SPORADIC ALZHEIMER DISEASE DEMENTIA
Gregory S. Day1,2, Carlos Cruchaga3,4, Thomas Wingo5, John C. Morris3,6, 1 Knight Alzheimer Disease Research Center, St. Louis, MO, USA; 2 Washington University in St. Louis, St. Louis, MO, USA; 3Washington University School of Medicine, St. Louis, MO, USA; 4Knight Alzheimer Disease Center, Saint Louis, MO, USA; 5Emory University, Atlanta, GA, USA; 6Knight Alzheimer’s Disease Research Center, St. Louis, MO, USA. Contact e-mail: [email protected] Background: Adult children of demented individuals harbor an increased risk of developing AD dementia, with ages-at-symptomatic-onset (AAO) that may differ from those of their affected parent(s). Factors responsible for differences in AAO within families remain unknown. We hypothesized that participant-specific factors may account for a proportion of this variability. Methods: The prevalence of putative dementia risk factors was determined in 482 participants with symptomatic AD dementia and a reported parental history of dementia. All participants were enrolled within Knight Alzheimer Disease Research Center longitudinal studies of memory and aging between August 1979 and February 2016. For each participant, the difference between the (reported) parental AAO, and the (observed) participant AAO was determined, and used to stratify participants. “Early” participants manifested with AD dementia >10 years before parental AAO (n¼79), while “late” participants were diagnosed >10 years after parental AAO (n¼73). The prevalence of putative dementia risk factors were compared across groups, including female gender; years of education; race; body mass index; and past or present history of cardiovascular disease, hypertension, hypercholesterolemia, diabetes, depression, traumatic brain injury, and tobacco and/or alcohol abuse. APOEallele status was also considered, given its recognized association with dementia risk. Results: Participants were diagnosed with AD dementia, on average, 6.1610.9 years earlier than their parent(s) (p<0.001). Maternal history of dementia was most common, reported amongst 74% of participants (p<0.001). Both parents were affected in 7% of cases. Despite differences in frequency, the pattern of inheritance did not account for the earlier-than-expected AAO in participants (p¼0.6). Likewise, although putative risk factors were commonly represented in our sample, no single