Trial reportJournal of general internal medicine2015
Randomized trial of a health IT tool to support between-visit-based laboratory monitoring for chronic disease medication prescriptions.
Trial report in Journal of general internal medicine, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers, 3 of them syntheses that pooled it.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
4 citing papers in PubMed, 3 syntheses or guidelines pooled it.
- Digital patient safety interventions in primary care: a systematic review and meta-analysis.BMC medicine · 2026Pooled it
- Digital tracking, provider decision support systems, and targeted client communication via mobile devices to improve primary health care.The Cochrane database of systematic reviews · 2025Pooled it
- Using an Integrated Framework to Investigate the Facilitators and Barriers of Health Information Technology Implementation in Noncommunicable Disease Management: Systematic Review.Journal of medical Internet research · 2022Pooled it
- Digital Health Interventions to Enhance Prevention in Primary Care: Scoping Review.JMIR medical informatics · 2022Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
7 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundLack of timely medication intensification and inadequate medication safety monitoring are two prevalent and potentially modifiable barriers to effective and safe chronic care. Innovative applications of health information technology tools may help support chronic disease management.
objectiveTo examine the clinical impact of a novel health IT tool designed to facilitate between-visit ordering and tracking of future laboratory testing. DESIGN AND
participantsClinical trial randomized at the provider level (n = 44 primary care physicians); patient-level outcomes among 3,655 primary care patients prescribed 5,454 oral medicines for hyperlipidemia, diabetes, and/or hypertension management over a 12-month period. MAIN MEASURES: Time from prescription to corresponding follow-up laboratory testing; proportion of follow-up time that patients achieved corresponding risk factor control (A1c, LDL); adverse event laboratory monitoring 4 weeks after medicine prescription. KEY
resultsPatients whose physicians were allocated to the intervention (n = 1,143) had earlier LDL laboratory assessment compared to similar patients (n = 703) of control physicians [adjusted hazard ratio (aHR): 1.15 (1.01-1.32), p = 0.04]. Among patients with elevated LDL (486 intervention, 324 control), there was decreased time to LDL goal in the intervention group [aHR 1.26 (0.99-1.62)]. However, overall there were no significant differences between study arms in time spent at LDL or HbA1c goal. Follow-up safety monitoring (e.g., creatinine, potassium, or transaminases) was relatively infrequent (ranging from 7 % to 29 % at 4 weeks) and not statistically different between arms. Intervention physicians indicated that lack of reimbursement for non-visit-based care was a barrier to use of the tool.
conclusionsA health IT tool to support between-visit laboratory monitoring improved the LDL testing interval but not LDL or HbA1c control, and it did not alter safety monitoring. Adoption of innovative tools to support physicians in non-visit-based chronic disease management may be limited by current visit-based financial and productivity incentives.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.