TY - JOUR
T1 - Development and efficacy of a computerized decision support system for osteoporosis management in the community
AU - Goldshtein, Inbal
AU - Shamai-Lubovitz, Orna
AU - Guindy, Michal
AU - Shalev, Varda
AU - Chodick, Gabriel
AU - Lerner, Uri
AU - Rouach, Vanessa
N1 - Publisher Copyright:
© 2020, International Osteoporosis Foundation and National Osteoporosis Foundation.
PY - 2020/12/1
Y1 - 2020/12/1
N2 - Summary: Computerized alerts for primary care physicians, provided during visits of patients who met treatment guidelines based on their electronic medical records, are an efficient method to raise awareness to many otherwise missed cases, especially after fracture. Purpose: Measure the efficacy of an automated real-time alert which was developed to assist osteoporosis management in the community. Methods: The study population included treatment naïve patients with T-score ≤ − 2.5 or hip or vertebral fracture in a 2 million member Israeli health fund. On each ambulatory visit to a primary care physician or endocrinologist, a pop-up screen reminded the caregiver to consider treatment initiation. A follow-up “smart-set” screen conveniently gathered links to common actions (namely, (a) issue first line therapy prescription, (b) referral to nutritionist consultation, (c) laboratory tests relevant for osteoporosis, and (d) printing an information page for the patient). Time till treatment initiation was compared between the 3 years prior to and following the intervention. Results: Within 2 years since alert activation, a total of n = 21,070 cases were alerted, 52% of which were long standing cases: untreated for over 6 months since the event. During this period, a total of 30% initiated treatment purchases. As compared with the 3 years prior to the intervention, time till treatment initiation decreased following the intervention with HR = 1.05, 1.94, 1.29 (p values = 0.020, < 0.001, 0.005) for T-score, hip, and vertebral cases respectively. Initiation rates within 6 months increased from 52.0 to 59.8%, from 12.3 to 27.7%, and from 17.4 to 27.1% among T-score, hip, and vertebral cases, respectively (p value < 0.001). Male sex, nursing home residence, having diabetes or a cardiovascular disease and age younger than 60 or older than 80 were associated with lower treatment rates. Conclusions: A computerized decision support system can efficiently raise attention to many otherwise missed high-risk osteoporotic cases, particularly those after fractures.
AB - Summary: Computerized alerts for primary care physicians, provided during visits of patients who met treatment guidelines based on their electronic medical records, are an efficient method to raise awareness to many otherwise missed cases, especially after fracture. Purpose: Measure the efficacy of an automated real-time alert which was developed to assist osteoporosis management in the community. Methods: The study population included treatment naïve patients with T-score ≤ − 2.5 or hip or vertebral fracture in a 2 million member Israeli health fund. On each ambulatory visit to a primary care physician or endocrinologist, a pop-up screen reminded the caregiver to consider treatment initiation. A follow-up “smart-set” screen conveniently gathered links to common actions (namely, (a) issue first line therapy prescription, (b) referral to nutritionist consultation, (c) laboratory tests relevant for osteoporosis, and (d) printing an information page for the patient). Time till treatment initiation was compared between the 3 years prior to and following the intervention. Results: Within 2 years since alert activation, a total of n = 21,070 cases were alerted, 52% of which were long standing cases: untreated for over 6 months since the event. During this period, a total of 30% initiated treatment purchases. As compared with the 3 years prior to the intervention, time till treatment initiation decreased following the intervention with HR = 1.05, 1.94, 1.29 (p values = 0.020, < 0.001, 0.005) for T-score, hip, and vertebral cases respectively. Initiation rates within 6 months increased from 52.0 to 59.8%, from 12.3 to 27.7%, and from 17.4 to 27.1% among T-score, hip, and vertebral cases, respectively (p value < 0.001). Male sex, nursing home residence, having diabetes or a cardiovascular disease and age younger than 60 or older than 80 were associated with lower treatment rates. Conclusions: A computerized decision support system can efficiently raise attention to many otherwise missed high-risk osteoporotic cases, particularly those after fractures.
KW - Alert
KW - Osteoporosis
UR - http://www.scopus.com/inward/record.url?scp=85080057594&partnerID=8YFLogxK
U2 - 10.1007/s11657-020-00718-3
DO - 10.1007/s11657-020-00718-3
M3 - Article
C2 - 32103347
AN - SCOPUS:85080057594
SN - 1862-3522
VL - 15
JO - Archives of Osteoporosis
JF - Archives of Osteoporosis
IS - 1
M1 - 27
ER -