ArticleProceedings. AMIA Symposium2002
Correlating web usage of health information with patient medical data.
Article in Proceedings. AMIA Symposium, 2002. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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
2 citing papers in PubMed, 2 citations in OpenAlex.
- Learning Clinical Workflows to Identify Subgroups of Heart Failure Patients.AMIA ... Annual Symposium proceedings. AMIA Symposium · 2016Article
- Learning relational policies from electronic health record access logs.Journal of biomedical informatics · 2011Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
1 author at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The number of online websites providing health-related information to the general public increases daily. Yet, it is relatively unknown as to how individuals in the general population access information with respect to their own medical status. In this study, clickstream data from an online health information website is analyzed with respect to the user's health insurance claims. The relationships are assessed through the construction and study of intersecting sets of ICD-9 codes in visited web pages and claims made. Results demonstrate that approximately 15% of patients use health information on the web in exact agreement with their medical status. In addition, almost 40 codes were found to be indicative of temporal aspects in user behavior with respect to physician visits.
Indexed as
Identifiers
12463871PMC2244241W137540605What OpenQuestion holds
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 OpenQuestion graph.