Word search performance for diagnoses of equine surgical colics in free-text electronic patient records

Estberg, Leah; Case, James T.; Walters, Roy A.; Cardiff, Robert D.; Galuppo, Larry D.

doi:10.1016/s0167-5877(97)00075-5

Cited by 3 publications

(4 citation statements)

References 17 publications

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“…The ‘Independent Inquiry into Dog Breeding’ report cited primary-care practice electronic clinical data using standardised coding of diagnoses as the optimal data source for reliable prevalence estimation [ 7 ]. However, early attempts at large-scale electronic surveillance struggled to cope with the large volumes of clinical data collected [ 19 ] and initial veterinary PMSs did not enforce structured coding systems [ 97 ], although there is now evidence that practising veterinarians accept a clinical rationale for standardised data recording [ 98 , 99 ].…”

Section: Reviewmentioning

confidence: 99%

Approaches to canine health surveillance

O’Neill

Church

McGreevy

et al. 2014

Canine Genet Epidemiol

115

146

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Effective canine health surveillance systems can be used to monitor disease in the general population, prioritise disorders for strategic control and focus clinical research, and to evaluate the success of these measures. The key attributes for optimal data collection systems that support canine disease surveillance are representativeness of the general population, validity of disorder data and sustainability. Limitations in these areas present as selection bias, misclassification bias and discontinuation of the system respectively. Canine health data sources are reviewed to identify their strengths and weaknesses for supporting effective canine health surveillance. Insurance data benefit from large and well-defined denominator populations but are limited by selection bias relating to the clinical events claimed and animals covered. Veterinary referral clinical data offer good reliability for diagnoses but are limited by referral bias for the disorders and animals included. Primary-care practice data have the advantage of excellent representation of the general dog population and recording at the point of care by veterinary professionals but may encounter misclassification problems and technical difficulties related to management and analysis of large datasets. Questionnaire surveys offer speed and low cost but may suffer from low response rates, poor data validation, recall bias and ill-defined denominator population information. Canine health scheme data benefit from well-characterised disorder and animal data but reflect selection bias during the voluntary submissions process. Formal UK passive surveillance systems are limited by chronic under-reporting and selection bias. It is concluded that active collection systems using secondary health data provide the optimal resource for canine health surveillance.

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Section: Reviewmentioning

confidence: 99%

Approaches to canine health surveillance

O’Neill

Church

McGreevy

et al. 2014

Canine Genet Epidemiol

115

146

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“…It has been established that structured recording improves precision and recall. [10][11][12][13] Instead, our work is a demonstration of two possibilities for structured recording of detailed examination findings using SNOMED-CT.…”

Section: Discussionmentioning

confidence: 99%

“…Research has shown that information retrieval by free-text searching is inadequate. [10][11][12][13] Adequate retrieval and analysis of murmur descriptions requires that these findings be encoded using a semantic model rather than the current free-text entry system. Structured recording of murmur findings is complicated by the variety of characteristics that can be used to describe murmurs.…”

Section: Introductionmentioning

confidence: 99%

Development and Evaluation of Methods for Structured Recording of Heart Murmur Findings Using SNOMED-CT(R) Post-Coordination

Green

Wilcke

Abbott

et al. 2006

Journal of the American Medical Informatics Association

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“…However, from an epidemiologic standpoint, where complete retrieval of all cases with a given diagnosis may be required, iterative approaches to designing queries may be necessary. 4 On the other hand, since every word in the EMR is indexed, finding all spelling variations for any given word can generally be done quickly, and misspellings can potentially be recognized and retrospectively corrected throughout all records.…”

Section: Free-text Searching and Retrievalmentioning

confidence: 99%

Development of a complete electronic medical record in an academic institution

Hornof

Brentson²,

Self³

et al. 2001

javma

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I n veterinary medicine a complete electronic medical record (EMR) should contain all information (eg, demographic, financial, medical/surgical, diagnostic, and pharmaceutical) related to all visits of a patient as well as owner contact and billing information. It is clear that such a complete EMR and the ability to retrieve and use the information it contains in an integrated manner would provide operational economies, improve patient care, and enhance teaching. We embarked on a project to develop such a record in an academic institution. This article describes our approach and how the EMR is currently being used in academic medicine. Development of the Hospital Information SystemThe effort to develop a computerized patient record system for the veterinary medical teaching hospital (VMTH) began about 20 years ago but progressed with difficulty, largely because of a lack of human resources. The event that triggered the commitment of substantial resources toward development of the EMR was the need for the VMTH to become autonomous from the services of an outside accounting firm. The firm was unable to provide the level of detail and flexibility required for the fiscal management of the VMTH. The decision was made to hire programming staff to write a hospital information system (HIS) specifically designed to combine the objectives of clinical information management with those of hospital administration and patient billing in a single integrated system. The existing medical record system served as the foundation for this effort. The computing platform chosen was the Massachusetts General Hospital Utility Multiprogramming System (MUMPS), because it had a proven record of success in medical computing, provided a flexible programming environment and strong retrieval capabilities, and did not require a mainframe computer. 1,2 A decision was also made that the primary force guiding EMR development would be to meet the needs of the users it was designed to serve: the VMTH faculty, students, and staff.In the old accounting system all financial entries were made centrally in cashiering. At that time a copy of each completed procedure request was hand routed to cashiering, where it was manually posted. As an initial step toward facilitating diagnostic reporting, VMTH staff in the various services who already had responsibility for entering billing information onto the routing slips were assigned responsibility for entering that information directly into the HIS. This point-ofservice entry concept was adopted as an objective for development for all components of the EMR. Point-ofservice entry was defined as assigning responsibility for information entry to the individual closest to the source of the information. Software tools were designed that enabled these individuals to make the entries directly into the electronic record instead of the paper record. For example, admissions staff entered demographic information as they acquired information necessary to make an appointment, usually during a telephone conversation with t...

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Word search performance for diagnoses of equine surgical colics in free-text electronic patient records

Cited by 3 publications

References 17 publications

Approaches to canine health surveillance

Approaches to canine health surveillance

Development and Evaluation of Methods for Structured Recording of Heart Murmur Findings Using SNOMED-CT(R) Post-Coordination

Development of a complete electronic medical record in an academic institution

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