Evidence map›Paper›PMID 29888081›Full record

ArticleAMIA Joint Summits on Translational Science proceedings. AMIA Joint Summits on Translational Science2018

CHCi - A Dynamic Data Platform for Clinical Data Capture and Use.

Danny T Y Wu, Kai Zheng, David J Bradley

Abstract read
In one paragraph

Article in AMIA Joint Summits on Translational Science proceedings. AMIA Joint Summits on Translational Science, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from 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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors.

Danny T Y WuSchool of Information, University of Michigan, Ann Arbor, MI.
Kai ZhengDepartment of Health Management and Policy, University of Michigan, Ann Arbor, MI.
David J BradleyDivision of Pediatric Cardiology, University of Michigan, Ann Arbor, MI.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

All academic medical centers have a strong desire to maximize the value of their clinical data for secondary use purposes such as quality improvement (QI) and research. However, this need has not been adequately fulfilled due in part to the fact that the data capture functions in current electronic health record systems predominantly focus on clinical documentation and billing, lacking the flexibility to allow the collection of additional data elements critical to QI or research. To address this gap, we designed and developed a dynamic data platform to support clinicians' varied needs for recording additional data about their patients outside of direct patient care (e.g. classifying patient conditions based on the inclusion criteria of a research-oriented patient registry). In this paper, we describe the design considerations of this platform such as data models, query functions, coding and controlled vocabulary, user interface design, access control, and data interoperability. In developing the platform, we partnered with the frontline clinicians in an academic congenital heart canter, and adopted the agile software development approach with numerous rounds of evaluation and iterative refinement. Since 2013, this platform has been successfully used to meet the dynamic QI and research data needs of clinicians in the congenital heart center. Future work includes improving the efficiency and effectiveness of the platform and incorporating cutting-edge data interoperability standards.

Identifiers

PMID29888081
PMCPMC5961796

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

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.