Development and efficacy of a computerized decision support system for osteoporosis management in the community.


Journal

Archives of osteoporosis
ISSN: 1862-3514
Titre abrégé: Arch Osteoporos
Pays: England
ID NLM: 101318988

Informations de publication

Date de publication:
26 02 2020
Historique:
received: 11 12 2019
accepted: 14 02 2020
entrez: 28 2 2020
pubmed: 28 2 2020
medline: 6 10 2020
Statut: epublish

Résumé

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. Measure the efficacy of an automated real-time alert which was developed to assist osteoporosis management in the community. 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. 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. A computerized decision support system can efficiently raise attention to many otherwise missed high-risk osteoporotic cases, particularly those after fractures.

Identifiants

pubmed: 32103347
doi: 10.1007/s11657-020-00718-3
pii: 10.1007/s11657-020-00718-3
doi:

Types de publication

Evaluation Study Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

27

Auteurs

Inbal Goldshtein (I)

Maccabitech institute for research and innovation, Maccabi Healthcare Services, Koyfman 4, Tel Aviv, Israel. goldst_in@mac.org.il.

Orna Shamai-Lubovitz (O)

Medical Informatics, Maccabi healthcare services, Tel Aviv-Yafo, Israel.

Michal Guindy (M)

Assuta Medical Centers, Tel Aviv-Yafo, Israel.

Varda Shalev (V)

Maccabitech institute for research and innovation, Maccabi Healthcare Services, Koyfman 4, Tel Aviv, Israel.
Sackler Faculty Of Medicine, Tel Aviv University, Tel Aviv-Yafo, Israel.

Gabriel Chodick (G)

Maccabitech institute for research and innovation, Maccabi Healthcare Services, Koyfman 4, Tel Aviv, Israel.
Sackler Faculty Of Medicine, Tel Aviv University, Tel Aviv-Yafo, Israel.

Uri Lerner (U)

Medical Informatics, Maccabi healthcare services, Tel Aviv-Yafo, Israel.

Vanessa Rouach (V)

Assuta Medical Centers, Tel Aviv-Yafo, Israel.

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