A strategy for statistical Master Person Index linking.

M K Martin, I P Shevchenko, L L Reed-Fourquet, J T Lynch

Abstract read

In one paragraph

Article in Proceedings. AMIA Symposium, 1999. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it

0cells of the map it votes in

1citing 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

1 citing paper in PubMed.

Connecticut RxData project.Proceedings. AMIA Symposium · 2002
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

4 authors.

M K MartinConnecticut Healthcare Research and Education Foundation, Wallingford, USA.

I P Shevchenko

L L Reed-Fourquet

J T Lynch

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

A linking program used by Connecticut Healthcare Information Management and Exchange to maintain the Master Person Index for its large, state-wide patient data repository is being stretched beyond its limits by the growing size and complexity of the database. This paper presents the early work into developing a second-generation linking program. Like the original program, the new linker will use a unique multi-step process to allow effective linking of data from a large number of dissimilar data sources. The new linker will use parallel multi-processing to allow improved performance and scalability. These changes will also make possible more sophisticated statistical methods of defining link confidence. The system is implemented using a scalable collection of inexpensive, PC based systems running the Linux operating system, a freely available database engine, and the Java programming language.

Indexed as

Abstracting and IndexingConnecticutDatabases as TopicHumansMedical Record LinkageMedical Records Systems, Computerized

Identifiers

PMID10566482

PMCPMC2232665

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.