Evidence map›Paper›PMID 27765037›Full record

ArticleBMC veterinary research2016

A method for extracting electronic patient record data from practice management software systems used in veterinary practice.

Julie S Jones-Diette, Marnie L Brennan, Malcolm Cobb, Hannah Doit, Rachel S Dean

Abstract readValidation Study
In one paragraph

Article in BMC veterinary research, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing 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

5 citing papers in PubMed.

  1. Article
  2. Article
  3. Review
  4. Review
  5. 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

5 authors.

Julie S Jones-DietteCentre for Evidence-based Veterinary Science, School of Veterinary Medicine & Science, University of Nottingham, Nottingham, LE12 5RD, UK.
Marnie L BrennanCentre for Evidence-based Veterinary Science, School of Veterinary Medicine & Science, University of Nottingham, Nottingham, LE12 5RD, UK.
Malcolm CobbDeputy Head of School, School of Veterinary Medicine & Science, University of Nottingham, Nottingham, LE12 5RD, UK.
Hannah DoitCentre for Evidence-based Veterinary Science, School of Veterinary Medicine & Science, University of Nottingham, Nottingham, LE12 5RD, UK.
Rachel S DeanCentre for Evidence-based Veterinary Science, School of Veterinary Medicine & Science, University of Nottingham, Nottingham, LE12 5RD, UK. Rachel.Dean@nottingham.ac.uk.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundData extracted from electronic patient records (EPRs) within practice management software systems are increasingly used in veterinary research. The use of real patient data gives the potential to generate research that can readily be applied to clinical practice. The use of veterinary EPRs for research in the United Kingdom is hindered by the number of different Practice Management System (PMS) providers used by practices, as obtaining and combining data from different systems electronically can be problematic. The use of extensible mark up language (XML) to extract clinical data for research would potentially resolve the compatibility issues between systems. The aim of this study was to establish and validate a method for the extraction of small animal patient records from a veterinary PMS that could potentially be used across multiple systems. An XML schema was designed to extract clinical information from EPRs. The schema was tested and validated in a test system, and was then tested in a real small animal practice where data was extracted for 16 weeks. A 10 % sample of the extracted records was then compared to paper copies provided by the practice.

resultsAll 21 fields encoded by the XML schema, from all of the records in the test system, were extracted with 100 % accuracy. Over the 18 week data collection period 4946 records, from 1279 patients, were extracted from the small animal practice. The 10 % printed records checked and compared with the XML extracted records demonstrated all required data was present. No unrequired, sensitive information e.g. costs or services/products or personal client information was extracted.

conclusionsThis is the first time a method for data extraction from EPRs in veterinary practice using an XML schema has been reported in the United Kingdom. This is an efficient and accurate way of extracting data which could be applied to all PMSs nationally and internationally.

Indexed as

Electronic Health RecordsSoftwareAnimalsPractice Management, VeterinaryUnited KingdomVeterinary MedicineAccuracyElectronic patient recordsExtensible mark-up language

Identifiers

PMID27765037
PMCPMC5073902

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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.