TY - JOUR
T1 - Using Artificial Intelligence to Reduce the Risk of Nonadherence in Patients on Anticoagulation Therapy
AU - Labovitz, Daniel L.
AU - Shafner, Laura
AU - Reyes Gil, Morayma
AU - Virmani, Deepti
AU - Hanina, Adam
N1 - Publisher Copyright:
© 2017 American Heart Association, Inc.
PY - 2017/5/1
Y1 - 2017/5/1
N2 - Background and Purpose - This study evaluated the use of an artificial intelligence platform on mobile devices in measuring and increasing medication adherence in stroke patients on anticoagulation therapy. The introduction of direct oral anticoagulants, while reducing the need for monitoring, have also placed pressure on patients to self-manage. Suboptimal adherence goes undetected as routine laboratory tests are not reliable indicators of adherence, placing patients at increased risk of stroke and bleeding. Methods - A randomized, parallel-group, 12-week study was conducted in adults (n=28) with recently diagnosed ischemic stroke receiving any anticoagulation. Patients were randomized to daily monitoring by the artificial intelligence platform (intervention) or to no daily monitoring (control). The artificial intelligence application visually identified the patient, the medication, and the confirmed ingestion. Adherence was measured by pill counts and plasma sampling in both groups. Results - For all patients (n=28), mean (SD) age was 57 years (13.2 years) and 53.6% were women. Mean (SD) cumulative adherence based on the artificial intelligence platform was 90.5% (7.5%). Plasma drug concentration levels indicated that adherence was 100% (15 of 15) and 50% (6 of 12) in the intervention and control groups, respectively. Conclusions - Patients, some with little experience using a smartphone, successfully used the technology and demonstrated a 50% improvement in adherence based on plasma drug concentration levels. For patients receiving direct oral anticoagulants, absolute improvement increased to 67%. Real-time monitoring has the potential to increase adherence and change behavior, particularly in patients on direct oral anticoagulant therapy.
AB - Background and Purpose - This study evaluated the use of an artificial intelligence platform on mobile devices in measuring and increasing medication adherence in stroke patients on anticoagulation therapy. The introduction of direct oral anticoagulants, while reducing the need for monitoring, have also placed pressure on patients to self-manage. Suboptimal adherence goes undetected as routine laboratory tests are not reliable indicators of adherence, placing patients at increased risk of stroke and bleeding. Methods - A randomized, parallel-group, 12-week study was conducted in adults (n=28) with recently diagnosed ischemic stroke receiving any anticoagulation. Patients were randomized to daily monitoring by the artificial intelligence platform (intervention) or to no daily monitoring (control). The artificial intelligence application visually identified the patient, the medication, and the confirmed ingestion. Adherence was measured by pill counts and plasma sampling in both groups. Results - For all patients (n=28), mean (SD) age was 57 years (13.2 years) and 53.6% were women. Mean (SD) cumulative adherence based on the artificial intelligence platform was 90.5% (7.5%). Plasma drug concentration levels indicated that adherence was 100% (15 of 15) and 50% (6 of 12) in the intervention and control groups, respectively. Conclusions - Patients, some with little experience using a smartphone, successfully used the technology and demonstrated a 50% improvement in adherence based on plasma drug concentration levels. For patients receiving direct oral anticoagulants, absolute improvement increased to 67%. Real-time monitoring has the potential to increase adherence and change behavior, particularly in patients on direct oral anticoagulant therapy.
KW - anticoagulants
KW - artificial intelligence
KW - patient compliance
KW - patient outcome assessment
KW - stroke
UR - http://www.scopus.com/inward/record.url?scp=85018673056&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85018673056&partnerID=8YFLogxK
U2 - 10.1161/STROKEAHA.116.016281
DO - 10.1161/STROKEAHA.116.016281
M3 - Article
C2 - 28386037
AN - SCOPUS:85018673056
SN - 0039-2499
VL - 48
SP - 1416
EP - 1419
JO - Stroke
JF - Stroke
IS - 5
ER -