Using the electronic health record as an innovative approach to measure delirium in older hospitalized patients
Background: “Acute Care for Elders (ACE) Tracker” is an automated checklist generated by the electronic health record (EHR) and used to identify geriatric conditions among older hospitalized patients. Purpose: The aim of this study was to examine the validity of the EHR in detecting delirium. Method...
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ftaurorahc:oai:institutionalrepository.aah.org:geri-1011 2023-07-23T04:18:26+02:00 Using the electronic health record as an innovative approach to measure delirium in older hospitalized patients Khan, Ariba Simpson, Michelle R Singh, Maharaj Malone, Michael L Hook, Mary L 2014-07-01T07:00:00Z https://institutionalrepository.aah.org/geri/12 unknown Advocate Aurora Health Institutional Repository https://institutionalrepository.aah.org/geri/12 Geriatric Medicine delirium diagnosis electronic health record EHR Acute Care for Elders (ACE) Tracker Advocate Aurora Research Institute text 2014 ftaurorahc 2023-07-05T20:11:59Z Background: “Acute Care for Elders (ACE) Tracker” is an automated checklist generated by the electronic health record (EHR) and used to identify geriatric conditions among older hospitalized patients. Purpose: The aim of this study was to examine the validity of the EHR in detecting delirium. Methods: Hospitalized adults 65 years and older were included in this cross-sectional study. The researchers utilized “confusion assessment method” as the gold standard. “Delirium marker” on the ACE Tracker was defined as presence of any of the following: delirium symptoms (by nurse) or use of physical restraints or delirium treatment (quetiapine, haloperidol, olanzapine and risperdone). The performance of the delirium tool was evaluated using sensitivity, specificity, positive and negative predictive values, and likelihood ratios from simple 2 × 2 tables. Results: Ninety-two participants in three hospitals were included. Of these, 54% were female; mean age was 77 ± 8.8 years, mean length of hospitalization was 5.9 ± 5.1 days, and mean number of scheduled medications was 11.6 ± 4.3. Overall, 70% of individuals had a Morse score > 45; the mean ADL score was 10, and the mean Braden score was 17.3. Dementia was present in 10% of participants. Delirium symptoms were present in 5.4%, delirium treatment 11% and restraints 4.3%. The prevalence of delirium marker was 16% by EHR and 17% by researchers. The delirium marker had a sensitivity of 44%, specificity of 89%, positive predictive value of 47% and negative predictive value of 88%. The likelihood ratios for positive and negative tests were 4 and 0.6, respectively. Limitations: The researchers examined the patient only once. To ensure accurate assessment of fluctuation in status, the researchers interviewed the nurses and, if needed, the physician and family. There may have been a change in mental status between the time participant was assessed by the researchers and documentation of delirium by the EHR. Conclusion: The EHR is a useful tool to alert health care professionals ... Text Aurora Research Institute morse Aurora Health Care Digital Repository Morse ENVELOPE(130.167,130.167,-66.250,-66.250) Braden’ ENVELOPE(147.574,147.574,59.465,59.465) |
institution |
Open Polar |
collection |
Aurora Health Care Digital Repository |
op_collection_id |
ftaurorahc |
language |
unknown |
topic |
delirium diagnosis electronic health record EHR Acute Care for Elders (ACE) Tracker Advocate Aurora Research Institute |
spellingShingle |
delirium diagnosis electronic health record EHR Acute Care for Elders (ACE) Tracker Advocate Aurora Research Institute Khan, Ariba Simpson, Michelle R Singh, Maharaj Malone, Michael L Hook, Mary L Using the electronic health record as an innovative approach to measure delirium in older hospitalized patients |
topic_facet |
delirium diagnosis electronic health record EHR Acute Care for Elders (ACE) Tracker Advocate Aurora Research Institute |
description |
Background: “Acute Care for Elders (ACE) Tracker” is an automated checklist generated by the electronic health record (EHR) and used to identify geriatric conditions among older hospitalized patients. Purpose: The aim of this study was to examine the validity of the EHR in detecting delirium. Methods: Hospitalized adults 65 years and older were included in this cross-sectional study. The researchers utilized “confusion assessment method” as the gold standard. “Delirium marker” on the ACE Tracker was defined as presence of any of the following: delirium symptoms (by nurse) or use of physical restraints or delirium treatment (quetiapine, haloperidol, olanzapine and risperdone). The performance of the delirium tool was evaluated using sensitivity, specificity, positive and negative predictive values, and likelihood ratios from simple 2 × 2 tables. Results: Ninety-two participants in three hospitals were included. Of these, 54% were female; mean age was 77 ± 8.8 years, mean length of hospitalization was 5.9 ± 5.1 days, and mean number of scheduled medications was 11.6 ± 4.3. Overall, 70% of individuals had a Morse score > 45; the mean ADL score was 10, and the mean Braden score was 17.3. Dementia was present in 10% of participants. Delirium symptoms were present in 5.4%, delirium treatment 11% and restraints 4.3%. The prevalence of delirium marker was 16% by EHR and 17% by researchers. The delirium marker had a sensitivity of 44%, specificity of 89%, positive predictive value of 47% and negative predictive value of 88%. The likelihood ratios for positive and negative tests were 4 and 0.6, respectively. Limitations: The researchers examined the patient only once. To ensure accurate assessment of fluctuation in status, the researchers interviewed the nurses and, if needed, the physician and family. There may have been a change in mental status between the time participant was assessed by the researchers and documentation of delirium by the EHR. Conclusion: The EHR is a useful tool to alert health care professionals ... |
format |
Text |
author |
Khan, Ariba Simpson, Michelle R Singh, Maharaj Malone, Michael L Hook, Mary L |
author_facet |
Khan, Ariba Simpson, Michelle R Singh, Maharaj Malone, Michael L Hook, Mary L |
author_sort |
Khan, Ariba |
title |
Using the electronic health record as an innovative approach to measure delirium in older hospitalized patients |
title_short |
Using the electronic health record as an innovative approach to measure delirium in older hospitalized patients |
title_full |
Using the electronic health record as an innovative approach to measure delirium in older hospitalized patients |
title_fullStr |
Using the electronic health record as an innovative approach to measure delirium in older hospitalized patients |
title_full_unstemmed |
Using the electronic health record as an innovative approach to measure delirium in older hospitalized patients |
title_sort |
using the electronic health record as an innovative approach to measure delirium in older hospitalized patients |
publisher |
Advocate Aurora Health Institutional Repository |
publishDate |
2014 |
url |
https://institutionalrepository.aah.org/geri/12 |
long_lat |
ENVELOPE(130.167,130.167,-66.250,-66.250) ENVELOPE(147.574,147.574,59.465,59.465) |
geographic |
Morse Braden’ |
geographic_facet |
Morse Braden’ |
genre |
Aurora Research Institute morse |
genre_facet |
Aurora Research Institute morse |
op_source |
Geriatric Medicine |
op_relation |
https://institutionalrepository.aah.org/geri/12 |
_version_ |
1772180756311834624 |