Sarah V Slade1, Christopher J Davey1,2, Darren Shickle1. 1. Academic Unit of Public Health, University of Leeds, Leeds, UK. 2. Bradford School of Optometry and Vision Science, University of Bradford, Bradford, UK.
Abstract
PURPOSE: The purpose of this paper is to investigate the potential of using primary care optometry data to support ophthalmic public health, research and policy making. METHODS: Suppliers of optometric electronic patient record systems (EPRs) were interviewed to gather information about the data present in commercial software programmes and the feasibility of data extraction. Researchers were presented with a list of metrics that might be included in an optometric practice dataset via a survey circulated by email to 102 researchers known to have an interest in eye health. Respondents rated the importance of each metric for research. A further survey presented the list of metrics to 2000 randomly selected members of the College of Optometrists. The optometrists were asked to specify how likely they were to enter information about each metric in a routine sight test consultation. They were also asked if data were entered as free text, menus or a combination of these. RESULTS: Current EPRs allowed the input of data relating to the metrics of interest. Most data entry was free text. There was a good match between high priority metrics for research and those commonly recorded in optometric practice. CONCLUSIONS: Although there were plenty of electronic data in optometric practice, this was highly variable and often not in an easily analysed format. To facilitate analysis of the evidence for public health purposes a UK based minimum dataset containing standardised clinical information is recommended. Further research would be required to develop suitable coding for the individual metrics included. The dataset would need to capture information from all sectors of the population to ensure effective planning of any future interventions.
PURPOSE: The purpose of this paper is to investigate the potential of using primary care optometry data to support ophthalmic public health, research and policy making. METHODS: Suppliers of optometric electronic patient record systems (EPRs) were interviewed to gather information about the data present in commercial software programmes and the feasibility of data extraction. Researchers were presented with a list of metrics that might be included in an optometric practice dataset via a survey circulated by email to 102 researchers known to have an interest in eye health. Respondents rated the importance of each metric for research. A further survey presented the list of metrics to 2000 randomly selected members of the College of Optometrists. The optometrists were asked to specify how likely they were to enter information about each metric in a routine sight test consultation. They were also asked if data were entered as free text, menus or a combination of these. RESULTS: Current EPRs allowed the input of data relating to the metrics of interest. Most data entry was free text. There was a good match between high priority metrics for research and those commonly recorded in optometric practice. CONCLUSIONS: Although there were plenty of electronic data in optometric practice, this was highly variable and often not in an easily analysed format. To facilitate analysis of the evidence for public health purposes a UK based minimum dataset containing standardised clinical information is recommended. Further research would be required to develop suitable coding for the individual metrics included. The dataset would need to capture information from all sectors of the population to ensure effective planning of any future interventions.
Authors: Kam Chun Ho; Dian Rahardjo; Fiona Stapleton; Louise Wiles; Peter D Hibbert; Andrew J R White; Andrew Hayen; Isabelle Jalbert Journal: BMJ Open Date: 2019-03-04 Impact factor: 2.692
Authors: Kam Chun Ho; Fiona Stapleton; Louise Wiles; Peter Hibbert; Sally Alkhawajah; Andrew White; Isabelle Jalbert Journal: BMC Health Serv Res Date: 2019-09-06 Impact factor: 2.655