Evidence map›Paper›PMID 18693826›Full record

ArticleAMIA ... Annual Symposium proceedings. AMIA Symposium2007

A modeling environment for patient portals.

Sean Duncavage, Janos Mathe, Jan Werner, Bradley A Malin, Akos Ledeczi, Janos Sztipanovits

Open access · greenAbstract read
In one paragraph

Article in AMIA ... Annual Symposium proceedings. AMIA Symposium, 2007. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
1.2field-weighted citation impact, top 11% of its field
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

3 citing papers in PubMed, 6 citations in OpenAlex.

  1. Article
  2. Review
  3. MyHealthAtVanderbilt: policies and procedures governing patient portal functionality.Journal of the American Medical Informatics Association : JAMIA · 2011
    Article
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

6 authors at 1 institution in 1 country.

Sean DuncavageDepartment of Electrical Engineering and Computer Science, School of Engineering, Vanderbilt University, Nashville, TN, USA.
Janos Mathe
Jan Werner
Bradley A Malin
Akos Ledeczi
Janos Sztipanovits
Vanderbilt University · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Clinical Information Systems (CIS) are complex environments that integrate information technologies, humans, and patient data. Given the sensitivity of patient data, federal regulations require health care providers to define privacy and security policies and to deploy enforcement technologies. The introduction of model-based design techniques, combined with the development of high-level modeling abstractions and analysis methods, provide a mechanism to investigate these concerns by conceptually simplifying CIS without sacrificing expressive power. This work introduces the Model-based Design Environment for Clinical Information Systems (MODECIS), which is a graphical design environment that assists CIS architects in formalizing systems and services. MODECIS leverages Service-Oriented Architectures to create realistic system models as abstractions. MODECIS enables the analysis of legacy architectures and the design and simulation of future CIS. We present the feasibility of MODECIS by modeling operations, such as user authentication, of MyHealth@Vanderbilt, a real world patient portal in use at Vanderbilt University Medical Center.

Indexed as

ConfidentialityUser-Computer InterfaceAccess to InformationComputer GraphicsHealth Insurance Portability and Accountability ActHumansInformation Storage and RetrievalInformation SystemsInternetMedical Records Systems, ComputerizedModels, OrganizationalSystems IntegrationUnited States

Identifiers

PMID18693826
PMCPMC2655806
OpenAlexW2104512195

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.