ReviewYearbook of medical informatics2014
Reuse of clinical data.
Review in Yearbook of medical informatics, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 24 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
24 citing papers in PubMed.
- Contribution of Open Access Databases to Intensive Care Medicine Research: Scoping Review.Journal of medical Internet research · 2025Article
- Transforming Primary Care Data Into the Observational Medical Outcomes Partnership Common Data Model: Development and Usability Study.JMIR medical informatics · 2024Article
- Data Lake, Data Warehouse, Datamart, and Feature Store: Their Contributions to the Complete Data Reuse Pipeline.JMIR medical informatics · 2024Article
- Standardized Description of the Feature Extraction Process to Transform Raw Data Into Meaningful Information for Enhancing Data Reuse: Consensus Study.JMIR medical informatics · 2022Article
- Transformation and Evaluation of the MIMIC Database in the OMOP Common Data Model: Development and Usability Study.JMIR medical informatics · 2021Article
- Leveraging National Claims and Hospital Big Data: Cohort Study on a Statin-Drug Interaction Use Case.JMIR medical informatics · 2021Article
- The Secondary Use of Data to Support Medication Safety in the Hospital Setting: A Systematic Review and Narrative Synthesis.Pharmacy (Basel, Switzerland) · 2021Review
- What Oncologists Want: Identifying Challenges and Preferences on Diagnosis Data Entry to Reduce EHR-Induced Burden and Improve Clinical Data Quality.JCO clinical cancer informatics · 2021Article
- A method for interoperable knowledge-based data quality assessment.BMC medical informatics and decision making · 2021Article
- Developing a Data Quality Standard Primer for Cardiovascular Risk Assessment from Electronic Health Record Data Using the DataGauge Process.AMIA ... Annual Symposium proceedings. AMIA Symposium · 2021Article
- Is the survival of patients treated with ipilimumab affected by antibiotics? An analysis of 1585 patients from the French National hospital discharge summary database (PMSI).Oncoimmunology · 2020Article
- Workflow Differences Affect Data Accuracy in Oncologic EHRs: A First Step Toward Detangling the Diagnosis Data Babel.JCO clinical cancer informatics · 2020Article
- Catch Me if You Can: Acute Events Hidden in Structured Chronic Disease Diagnosis Descriptions Show Detectable Recording Patterns in EHR.AMIA ... Annual Symposium proceedings. AMIA Symposium · 2020Article
- A tale of three subspecialties: Diagnosis recording patterns are internally consistent but Specialty-Dependent.JAMIA open · 2019Article
- DataGauge: A Practical Process for Systematically Designing and Implementing Quality Assessments of Repurposed Clinical Data.EGEMS (Washington, DC) · 2019Article
- Access to Routinely Collected Clinical Data for Research: A Process Implemented at an Academic Medical Center.Clinical and translational science · 2019Article
- Lost in Translation: Diagnosis Records Show More Inaccuracies After Biopsy in Oncology Care EHRs.AMIA Joint Summits on Translational Science proceedings. AMIA Joint Summits on Translational Science · 2019Article
- Biopsy Records Do Not Reduce Diagnosis Variability in Cancer Patient EHRs: Are We More Uncertain After Knowing?AMIA Joint Summits on Translational Science proceedings. AMIA Joint Summits on Translational Science · 2018Article
- Update on Data Reuse in Health Care.Yearbook of medical informatics · 2017Review
- Clinical Data Reuse or Secondary Use: Current Status and Potential Future Progress.Yearbook of medical informatics · 2017Review
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.
Funding
No grant is acknowledged in the PubMed record.
Abstract
objectivesTo provide an overview of the benefits of clinical data collected as a by-product of the care process, the potential problems with large aggregations of these data, the policy frameworks that have been formulated, and the major challenges in the coming years.
methodsThis report summarizes some of the major observations from AMIA and IMIA conferences held on this admittedly broad topic from 2006 through 2013. This report also includes many unsupported opinions of the author.
resultsThe benefits of aggregating larger and larger sets of routinely collected clinical data are well documented and of great societal benefit. These large data sets will probably never answer all possible clinical questions for methodological reasons. Non-traditional sources of health data that are patient-sources will pose new data science challenges.
conclusionsIf we ever hope to have tools that can rapidly provide evidence for daily practice of medicine we need a science of health data perhaps modeled after the science of astronomy.
Indexed as
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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 OpenQuestion graph.