Abstract
Purpose: :
To identify and compare perceived causes of loss of vision (LOV) in glaucoma patients receiving current medical care, and to identify potential actions to minimize this outcome through use of patient, family member, and eye-care provider focus groups.
Methods: :
A total of 26 glaucoma-specific focus groups were conducted at three collaborating teaching university ophthalmology centers to collect information directly from participants regarding specific perceived factors involved in LOV in glaucoma patients and interventions that could reduce LOV. Three types of focus groups included: patients with glaucoma, family members of patients, and eye-care providers. Transcripts from all focus group sessions were reviewed, and content analysis was performed to determine frequencies of response categories within a specific focus group type and for response comparison between different focus group types.
Results: :
Eye-care providers reported the greatest number of specific response categories for causes of LOV (11), and reported non-compliance with greatest frequency (31%), followed by cost of care (15%) and delayed/missed diagnosis (15%). This group also suggested the greatest number of potential interventions that could reduce LOV (13), with tighter follow-up as the most common (23%). Patients provided nine response types for perceived causes of LOV, and most frequently reported non-compliance (37%), and that they were unsure of the causes (13%). Patients offered four categories of potential actions to decrease LOV, with emphasis on improving patient education (38%). Family members reported the fewest response types for LOV (4), and most commonly reported they were unsure of causes (49%), followed by cost of care (25%). This group also provided the fewest suggested actions to reduce LOV, and recommended increasing family member education/involvement with greatest frequency (42%).
Conclusions: :
Use of focus groups provided multiple perspectives in identification of causes of LOV and suggestions for potential interventions to reduce LOV. Although eye-care providers reported the greatest number of response categories both for causes of LOV and potential interventions, patients supplied unique perspective on causes of LOV not identified by the other groups, for example change of eye-care providers. Information gained from understanding factors in LOV may be implemented in developing tools to optimize delivery of glaucoma care and patient outcome in the clinical setting.
Keywords: clinical (human) or epidemiologic studies: health care delivery/economics/manpower • clinical (human) or epidemiologic studies: outcomes/complications