Trial reportBMJ quality & safety2014
Personalised physician learning intervention to improve hypertension and lipid control: randomised trial comparing two methods of physician profiling.
Trial report in BMJ quality & safety, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT00903071 (Personalized Physician Learning Intervention to Improve Hypertension Care), which is not on this map. Cited by 5 papers, 1 of them a synthesis that pooled it.
What it found
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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.
Personalized Physician Learning Intervention to Improve Hypertension Care
Who cites it
5 citing papers in PubMed, 1 synthesis or guideline pooled it, 6 citations in OpenAlex.
- The effect of computerized decision support systems on cardiovascular risk factors: a systematic review and meta-analysis.BMC medical informatics and decision making · 2019Pooled it
- Trial
- Digital Health Interventions to Enhance Prevention in Primary Care: Scoping Review.JMIR medical informatics · 2022Article
- Comparison of study samples recruited with virtual versus traditional recruitment methods.Contemporary clinical trials communications · 2020Review
- Provider- and Patient-Related Barriers to and Facilitators of Digital Health Technology Adoption for Hypertension Management: Scoping Review.JMIR cardio · 2019Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
12 authors at 3 institutions in 1 country.
Funding
Abstract
purposeTo assess the impact of personalised physician learning (PPL) interventions using simulated learning cases on control of hypertension and dyslipidaemia in primary care settings.
methodsA total of 132 primary care physicians, 4568 eligible patients with uncontrolled hypertension, and 15 392 eligible patients with uncontrolled dyslipidaemia were cluster-randomised to one of three conditions: (a) no intervention, (b) PPL-electronic medical record (EMR) intervention in which 12 PPL cases were assigned to each physician based on observed patterns of care in the EMR in the previous year, or (c) PPL-ASSESS intervention in which 12 PPL cases were assigned to each physician based on their performance on four standardised assessment cases. General and generalised linear mixed models were used to account for clustering and to model differences in patient outcomes in the study arms.
resultsAmong patients with uncontrolled hypertension at baseline, 49.1%, 46.6% and 47.3% (p=0.43) achieved blood pressure (BP) targets at follow-up. Among patients with uncontrolled dyslipidaemia at baseline, 37.5%, 37.3% and 38.1% (p=0.72) achieved low density lipoprotein cholesterol targets at follow-up in PPL-EMR, PPL-ASSESS and the control group, respectively. Although systolic (BP) (p<0.001) and lipid (p<0.001) values significantly improved during the study, the group-by-time interaction term showed no differential change in systolic BP values (p=0.51) or lipid values (p=0.61) among the three study arms. No difference in intervention effect was noted when comparing the PPL-EMR with the PPL-ASSESS intervention (p=0.47).
conclusionsThe two PPL interventions tested in this study did not lead to improved control of hypertension or dyslipidaemia in primary care clinics during a mean 14-month follow-up period. This null result may have been due in part to substantial overall improvement in BP and lipid control at the study sites during the study. TRIAL REGISTRATION NUMBER: NCT00903071.
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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 OpenQuestion graph.