Clinical low vision resource usage prediction

David Dilts, Joseph Khamalah, Ann Plotkin

Research output: Contribution to journalArticle

6 Citations (Scopus)

Abstract

In an era of increased demands and constrained budgets, it is necessary to make the best use of all available resources. This is difficult when specialized vision care, such as low vision clinical assessment, is involved because of the heterogeneity of the patient populations seen by such clinics Purpose. This research attempts to discover if these diverse patient populations can be identified and clustered into groups based upon similarity of clinical resources use. Specifically, the inquiry examines the potential for a low vision patient resource utilization classification scheme at the Low Vision Clinic (LVC) in the Centre for Sight Enhancement (CSE), University of Waterloo. Methods. From a sample of 99 patients consulting the LVC in a 3-month period, retrospective data collection involved abstracting and coding medical records containing information detailing each patient’s demographic, diagnostic, therapeutic, and resource utilization characteristics. Cluster analysis using Hartigan’s block clustering algorithm was then applied to the data. A replication study was completed using a sample of 99 patients visiting the LVC 1 year later. Results. Patients can be classified into five isoresource groups, hereby termed low vision patient re-source groups (LVPRGs). The clusters represent a re-source consistent and clinically coherent scheme for classifying low vision patients based upon resource requirements. As a measure of repeatability, the groups reemerged in the replication study. Conclusions. if the groupings demonstrate robustness in a field test, clustering algorithms in general, and LVPRGs in specific, may offer useful tools to enhance resource utilization in the LVC setting.

Original languageEnglish (US)
Pages (from-to)422-436
Number of pages15
JournalOptometry and Vision Science
Volume71
Issue number7
StatePublished - 1994
Externally publishedYes

Fingerprint

Low Vision
Cluster Analysis
Budgets
Population Characteristics
Medical Records
Demography

Keywords

  • Classification schemes
  • Low vision
  • Resource usage

ASJC Scopus subject areas

  • Ophthalmology
  • Optometry

Cite this

Dilts, D., Khamalah, J., & Plotkin, A. (1994). Clinical low vision resource usage prediction. Optometry and Vision Science, 71(7), 422-436.

Clinical low vision resource usage prediction. / Dilts, David; Khamalah, Joseph; Plotkin, Ann.

In: Optometry and Vision Science, Vol. 71, No. 7, 1994, p. 422-436.

Research output: Contribution to journalArticle

Dilts, D, Khamalah, J & Plotkin, A 1994, 'Clinical low vision resource usage prediction', Optometry and Vision Science, vol. 71, no. 7, pp. 422-436.
Dilts D, Khamalah J, Plotkin A. Clinical low vision resource usage prediction. Optometry and Vision Science. 1994;71(7):422-436.
Dilts, David ; Khamalah, Joseph ; Plotkin, Ann. / Clinical low vision resource usage prediction. In: Optometry and Vision Science. 1994 ; Vol. 71, No. 7. pp. 422-436.
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