Agreement between veterinary patient data collected from different sources

Robinson, Natalie; Cobb, Malcolm; Dean, Rachel

doi:10.1016/j.tvjl.2015.04.023

Cited by 4 publications

(3 citation statements)

References 7 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The study applied a secondary use as a research resource to clinical data from primary-care veterinary practices. Although this offered benefits from reflecting all disorders recorded in the study dogs and that these diagnoses were made to primary care veterinary standards, it is also possible that the results underestimated conditions that were less likely to lead to veterinary presentation or to being formally recorded in the clinical records [ 66 ]. Normalisation of disorders within breed that are de facto an extreme conformation (e.g.…”

Section: Discussionmentioning

confidence: 99%

Is it now time to iron out the wrinkles? Health of Shar Pei dogs under primary veterinary care in the UK

O’Neill,

Engdahl,

Leach

et al. 2023

Canine Med Genet

View full text Add to dashboard Cite

Background The Shar Pei is a common dog breed with a distinctive appearance caused by hyaluronosis that has been linked with several health conditions. Anonymised primary-care veterinary clinical records were explored to extract data on the demography, common disorders and mortality of Shar Pei in the UK in 2013. Results The study population of 455,557 dogs included 1913 (0.42%) Shar Pei. The mean adult bodyweight was 22.26 kg. The most prevalent fine-level precision disorders were entropion (prevalence 17.88%, 95% CI: 16.16-19.59), otitis externa (16.36%, 95% CI: 14.70-18.02), ear disorders (6.69%, 95% CI: 5.57-7.81), aggression (5.23%, 95% CI: 4.23-6.22), and pyoderma (4.29%, 95% CI: 3.38-5.19). The most prevalent disorder groups were ophthalmologic (prevalence = 22.27%, 95% CI: 20.40-24.13), dermatological (21.01%, 95% CI: 19.19-22.84), aural (18.66%, 95% CI: 16.92-20.41), traumatic injury (7.53%, 95% CI: 6.35-8.71) and behavioural (7.21%, 95% CI: 6.05-8.37). The median longevity of 190 Shar Pei that died during the study period was 7.28 years (IQR 5.04-10.05, range 0.04-15.04). Of 184 deaths with a recorded method of death, 157 (85.33%) deaths involved euthanasia and 27 (14.67%) deaths were unassisted. Among 136 (71.58%) deaths with a recorded biomedical cause of death, the most common causes of death at group level precision were neoplasia (15.44%, 95% CI: 9.37-21.51), renal disorders (13.24%, 95% CI: 7.54-18.93), and behavioural disorders (11.03%, 95% CI: 5.76-16.29). Conclusions Almost one fifth of Shar Pei receive veterinary care each year for entropion, a condition linked strongly with the extreme conformation of thickened and folded skin and bristly hair that characterises the Shar Pei breed. Several other common disorders are also linked to hyaluronosis. Current UK legislation can help support efforts to avoid breeding or acquiring animals with extreme conformations and to promote adequate veterinary care for already-owned animals with extreme conformations.

show abstract

Section: Discussionmentioning

confidence: 99%

Is it now time to iron out the wrinkles? Health of Shar Pei dogs under primary veterinary care in the UK

O’Neill,

Engdahl,

Leach

et al. 2023

Canine Med Genet

View full text Add to dashboard Cite

show abstract

“…The recording of data within electronic medical records are not always accurate or consistent8 and it was evident when examining the case records that there was variation in clinical record keeping between practitioners. Additionally, there were differences in individual practitioner recording, particularly when there had been multiple cases attended in the same ‘out‐of‐hours’ period.…”

Section: Discussionmentioning

confidence: 99%

Retrospective case series to identify the most common conditions seen ‘out‐of‐hours’ by first‐opinion equine veterinary practitioners

et al. 2020

View full text Add to dashboard Cite

BackgroundThe study aim was to describe conditions seen ‘out-of-hours’ in equine practice.MethodsThis was a retrospective case series of first opinion ‘out-of-hours’ cases seen at two equine practices between 2011 and 2013. Data were retrieved on case presentation, diagnostic testing, treatment administered and outcome, and diseases categorised using a systems-based coding system. A hierarchical logistic regression, formulated using a generalised linear model, was used to identify clinical variables associated with a binary outcome of ‘critical’ cases (required hospitalisation or euthanasia or died).ResultsData from 2602 cases were analysed. The most common reasons for ‘out-of-hours’ visits were colic (35 per cent, n=923/2620), wounds (20 per cent, n=511/2620) and lameness (11 per cent, n=288/2,620). The majority of cases required a single treatment (58 per cent, n=1475/2550), 26 per cent (n=656/2550) needed multiple treatments and 13 per cent (n=339/2550) were euthanased. Eighteen per cent (n=480/2602) of cases had a critical outcome. Increased heart rate at primary presentation was associated with critical outcome in both practices (Practice A, OR 1.07 (95 per cent confidence interval 1.06 to 1.09), Practice B OR 1.08 (95 per cent confidence interval 1.07 to 1.09; p<0.001)).ConclusionColic, wounds and lameness were the most common equine ‘out-of-hours’ conditions; 13 per cent of cases were euthanased. Further research is required into out-of-hours euthanasia decision-making.

show abstract

“…Furthermore, research from the human health field has suggested the coding of clinical information is often too simplified to provide a rich and complex representation of both patient and disease needed for research (Jollis et al, 1993). It has been reported that there is often disagreement between the data in coded portions and free-text portions of the human medical record (Stein et al, 2000) and in the veterinary context (Robinson et al, 2015). These examples highlight some of the challenges involved with the use of routinely captured patient data for research (Benchimol et al, 2015).…”

Section: Introductionmentioning

confidence: 99%

Validation of text-mining and content analysis techniques using data collected from veterinary practice management software systems in the UK

Jones-Diette

Dean

Cobb

2019

Preventive Veterinary Medicine

Self Cite

View full text Add to dashboard Cite

Electronic patient records from practice management software systems have been used extensively in medicine for the investigation of clinical problems leading to the creation of decision support frameworks. To date, technologies that have been utilised for this purpose such as text mining and content analysis have not been employed significantly in veterinary medicine.The aim of this research was to pilot the use of content analysis and text-mining software for the synthesis and analysis of information extracted from veterinary electronic patient records. The purpose of the work was to be able to validate this approach for future employment across a number of practices for the purposes of practice based research. The approach utilised content analysis (Prosuite) and text mining (WordStat) software to aggregate the extracted text. Text mining tools such as Keyword in Context (KWIC) and Keyword Retrieval (KR) were employed to identify specific occurrences of data across the records. Two different datasets were interrogated, a bespoke test dataset that had been set up specifically for the purpose of the research, and a functioning veterinary clinic dataset that had been extracted from one veterinary practice.Across both datasets, the KWIC analysis was found to have a high level of accuracy with the search resulting in a sensitivity of between 85.3-100%, a specificity of between 99.1-99.7%, a positive predictive value between 93.5-95.8% and a negative predictive value between 97.7-100%. The KR search, based on machine learning, was utilised for the clinic-based dataset and was found to perform slightly better than the KWIC analysis.This study is the first to demonstrate the application of content analysis and text mining software for validation purposes across a number of different datasets for the purpose of search and recall of specific information across electronic patient records. This has not been demonstrated previously for small animal veterinary epidemiological research for the purposes of large scale analysis for practice-based research. Extension of this work to investigate more complex diseases across larger populations is required to fully explore the use of this approach in veterinary practice.

show abstract

Agreement between veterinary patient data collected from different sources

Cited by 4 publications

References 7 publications

Is it now time to iron out the wrinkles? Health of Shar Pei dogs under primary veterinary care in the UK

Is it now time to iron out the wrinkles? Health of Shar Pei dogs under primary veterinary care in the UK

Retrospective case series to identify the most common conditions seen ‘out‐of‐hours’ by first‐opinion equine veterinary practitioners

Validation of text-mining and content analysis techniques using data collected from veterinary practice management software systems in the UK

Contact Info

Product

Resources

About