Evidence map›Paper›PMID 23569619›Full record

ArticleOnline journal of public health informatics2011

Evaluation of knowledge resources for public health reporting logic: Implications for knowledge authoring and management.

Catherine J Staes, Rita Altamore, Eungyoung Han, Susan Mottice, Deepthi Rajeev, Richard Bradshaw

Abstract read
In one paragraph

Article in Online journal of public health informatics, 2011. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
  2. 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.

Catherine J StaesDepartment of Biomedical Informatics, University of Utah, Salt Lake City, Utah.
Rita Altamore
Eungyoung Han
Susan Mottice
Deepthi Rajeev
Richard Bradshaw

Funding

UNIVERSITY OF UTAH MEDICAL INFORMATICS TRAININGT15LM007124 · NLM · UTAH STATE HIGHER EDUCATION SYSTEM--UNIVERSITY OF UTAH · PI Karen Louise Eilbeck · 1997 to 2026
$22.0M
NLM NIH HHS T15 LM007124PHITPO CDC HHS P01 HK000030PHITPO CDC HHS P01 HK000069
6 · The paper itself

Abstract

To control disease, laboratories and providers are required to report conditions to public health authorities. Reporting logic is defined in a variety of resources, but there is no single resource available for reporters to access the list of reportable events and computable reporting logic for any jurisdiction. In order to develop evidence-based requirements for authoring such knowledge, we evaluated reporting logic in the Council of State and Territorial Epidemiologist (CSTE) position statements to assess its readiness for automated systems and identify features that should be considered when designing an authoring interface; we evaluated codes in the Reportable Condition Mapping Tables (RCMT) relative to the nationally-defined reporting logic, and described the high level business processes and knowledge required to support laboratory-based public health reporting. We focused on logic for viral hepatitis. We found that CSTE tabular logic was unnecessarily complex (sufficient conditions superseded necessary and optional conditions) and was sometimes true for more than one reportable event: we uncovered major overlap in the logic between acute and chronic hepatitis B (52%), acute and Past and Present hepatitis C (90%). We found that the RCMT includes codes for all hepatitis criteria, but includes addition codes for tests not included in the criteria. The proportion of hepatitis variant-related codes included in RCMT that correspond to a criterion in the hepatitis-related position statements varied between hepatitis A (36%), acute hepatitis B (16%), chronic hepatitis B (64%), acute hepatitis C (96%), and past and present hepatitis C (96%). Public health epidemiologists have the need to communicate parameters other than just the name of a disease or organism that should be reported, such as the status and specimen sources. Existing knowledge resources should be integrated, harmonized and made computable. Our findings identified functionality that should be provided by future knowledge management systems to support epidemiologists as they communicate reporting rules for their jurisdiction.

Indexed as

Decision Support Systems, ClinicalDisease NotificationKnowledge BasesPublic Health Practice

Identifiers

PMID23569619
PMCPMC3615796

What OpenQuestion holds

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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.