October 2013
Volume 54, Issue 10
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Glaucoma  |   October 2013
Patient-Related and System-Related Barriers to Glaucoma Follow-up in a County Hospital Population
Author Affiliations & Notes
  • Bradford W. Lee
    Department of Ophthalmology, Stanford University School of Medicine, Stanford, California
  • Yohko Murakami
    Department of Ophthalmology, Stanford University School of Medicine, Stanford, California
  • Martin T. Duncan
    Department of Ophthalmology, Stanford University School of Medicine, Stanford, California
  • Andrew A. Kao
    Department of Ophthalmology, University of California, San Francisco, San Francisco, California
  • Jehn-Yu Huang
    Department of Ophthalmology, University of California, San Francisco, San Francisco, California
  • Shan Lin
    Department of Ophthalmology, University of California, San Francisco, San Francisco, California
  • Kuldev Singh
    Department of Ophthalmology, Stanford University School of Medicine, Stanford, California
  • Correspondence: Shan Lin, University of California, San Francisco, 10 Koret Way, Room K-325, San Francisco, CA 94143-0730;LinS@vision.ucsf.edu
Investigative Ophthalmology & Visual Science October 2013, Vol.54, 6542-6548. doi:10.1167/iovs.13-12108
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      Bradford W. Lee, Yohko Murakami, Martin T. Duncan, Andrew A. Kao, Jehn-Yu Huang, Shan Lin, Kuldev Singh; Patient-Related and System-Related Barriers to Glaucoma Follow-up in a County Hospital Population. Invest. Ophthalmol. Vis. Sci. 2013;54(10):6542-6548. doi: 10.1167/iovs.13-12108.

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Abstract

Purpose.: To identify the barriers to glaucoma follow-up and to assess how ethnicity influences the effect of such barriers among patients in a county hospital population.

Methods.: This cross-sectional study included 152 patients, 76 with poor clinic follow-up and 76 with good clinic follow-up, who were recruited at the San Francisco General Hospital glaucoma clinic as part of a case-control study. All subjects were required to be established patients with glaucoma initially seen and diagnosed in the clinic at least 1 year before enrollment. An oral questionnaire pertaining to the barriers to follow-up for glaucoma, as well as patient ethnicity, was administered to all participating subjects. The main outcome measure was the prevalence of significant barriers to follow-up, both overall and stratified by ethnicity.

Results.: The most prevalent barriers to follow-up included long clinic waiting times (75%), appointment scheduling difficulties (38%), the effect of other medical or physical comorbidities (29%), and difficulties related to medical interpretation (23%). While several barriers were cited as being important across different ethnicities, Latinos and Asian–Pacific Islanders were particularly affected by difficulties related to medical interpretation (P = 0.0001) and long waiting times in the clinic (P = 0.048).

Conclusions.: Understanding patient-reported barriers to glaucoma follow-up and their variation based on ethnicity may give providers insight as to why patients do not adhere to follow-up recommendations. Strategies to improve follow-up may include reduced clinic wait times, simplified appointment scheduling, and provision of appropriate education and counseling regardless of the patient's native language and ethnicity.

Introduction
Glaucoma is a leading cause of blindness in the United States and globally, 1,2 with a US prevalence that is expected to increase more than 50% between 2000 and 2020 in large part due to an aging population. 3 Prospective randomized clinical trials have validated the efficacy of medications and surgical interventions to lower IOP and slow glaucomatous vision loss. 4 9 However, the lack of an ideal surgical procedure, as well as problems with adherence to medication use and clinical follow-up, makes glaucoma care a challenge both in developing and developed countries. 
Numerous studies 10 15 have demonstrated poor patient adherence to glaucoma medication regimens, but relatively little is known about the problem of poor clinic follow-up among existing patients with glaucoma. Kosoko et al. 16 anecdotally reported several primary reasons for poor follow-up in an inner-city glaucoma clinic in Baltimore, Maryland, including the costs of glaucoma care, the perception that this disease was “not serious enough,” and dissatisfaction with waiting times. Lee et al., 17 in a study at the Aravind Eye Care System in South India, found that the most prevalent patient-reported barriers to glaucoma follow-up were the patients' belief that they had no problem with their eyes, the lack of an escort to assist patients in attending the clinic, and inability to be absent from work responsibilities. 
There is considerable interest in the glaucoma community on how glaucoma affects populations of different races. Several large epidemiologic studies 18 21 have clearly demonstrated that race influences glaucoma prevalence, with African Americans and Latinos being at particularly high risk of having the disease. However, less is known about how race and ethnicity affect glaucoma care within a multiethnic population. The report by the Institute of Medicine of the National Academies on racial and ethnic disparities in health care suggests that several minority groups receive poor-quality health care compared with nonminorities residing in the United States; furthermore, minority groups may face a range of complex barriers relating to access to care, language, provider bias, or other patient-level or health care system factors. 22 No studies, to our knowledge, have examined the barriers to glaucoma follow-up in a multiethnic population and the ways such barriers may differentially affect specific ethnic groups. 
Regular follow-up in the clinic is generally considered important in maximizing the likelihood of visual preservation in those with glaucoma. Glaucomatous disease varies tremendously between individuals with regard to severity and rate of progression, and regular follow-up allows the practitioner to adjust therapy based on the disease course. A greater understanding of the barriers to follow-up from the patient's perspective would allow eye care providers to develop targeted strategies to eliminate obstacles to clinic follow-up. This study aimed to identify the most significant barriers to follow-up in a multiethnic population of patients with glaucoma attending an urban county hospital clinic in the United States. 
Methods
This cross-sectional study included 76 patients having glaucoma with poor clinic follow-up and 76 patients having glaucoma with good clinic follow-up who were recruited during a 6-month period in 2008–2009 as part of a case-control study at the San Francisco General Hospital (SFGH) glaucoma clinic. The clinic is situated at an urban publicly owned county hospital that provides comprehensive health care services and acts as a safety net for San Francisco's poor, uninsured, homeless, and immigrant populations. The clinic is staffed by resident and attending physicians from the University of California, San Francisco. 
All subjects were classified either as cases (those with poor follow-up) or controls (those with good follow-up). This classification was based on adherence to follow-up regimens generally recommended for patients at the SFGH depending primarily on disease severity and control (Table 1). For all subjects, glaucoma follow-up visits at the SFGH during the period 12 to 18 months before the commencement of the study were ascertained from documentation in their medical records. Subjects deemed to have good follow-up were those who attended follow-up visits within a certain maximum interval between visits as advised by their ophthalmologist. Disease severity for each subject was assessed by a senior glaucoma specialist (J-YH, SL) according to the American Academy of Ophthalmology Preferred Practice Pattern guidelines for primary open-angle glaucoma 23 and was based on the subject's most recent ophthalmological examination, including optic nerve and visual field characteristics. 
Table 1
 
Criteria for Classifying Cases and Controls Based on Follow-up During the 12 to 18 Months Preceding the Study*
Table 1
 
Criteria for Classifying Cases and Controls Based on Follow-up During the 12 to 18 Months Preceding the Study*
Variable Glaucoma Disease Severity
Mild Moderate Severe
Follow-up recommendations‡ Every 5–6 mo (approximately 2 visits per year) Every 4–5 mo (approximately 3 visits per year) Every 3–4 mo (approximately 4 visits per year)
Good follow-up (controls) ≥2 Visits per year, with 5–6 mo maximum intervals between visits ≥3 Visits per year, with 4–5 mo maximum intervals between visits ≥3 Visits per year, with 3–4 mo maximum intervals between visits
Poor follow-up (cases) ≤1 Visit per year or extended interval between visits ≤2 Visits per year or extended interval between visits ≤2 Visits per year or extended interval between visits
Subject eligibility criteria included the following: (1) establishment of care at the SFGH glaucoma clinic at least 1 year before study commencement as ascertained by review of the medical record, (2) age 40 years or older, and (3) a diagnosis of primary open-angle glaucoma, angle-closure glaucoma, normal tension glaucoma, pigmentary and/or exfoliative glaucoma, or ocular hypertension. All eligible patients attending follow-up visits in the glaucoma clinic were approached regarding enrollment in the study whenever a member of the multilingual research team (BWL, YM, MTD, AAK) was available to conduct oral questionnaires. 
After obtaining informed consent, subjects were asked whether they were proficient in English. The standardized questionnaires were administered orally in the subject's preferred language (English, Spanish, Mandarin, Cantonese, Vietnamese, or Tagalog) by a member of the multilingual research team. Data were collected on race and ethnicity, as well as on other factors such as transportation to the clinic, monetary cost of medications and follow-up clinic visits, medication use, knowledge about glaucoma, and perceptions regarding the difficulty and importance of attending glaucoma follow-up examinations. All subjects were then asked specifically whether any of 16 potential barriers posed “significant barriers” to attending glaucoma follow-up during the past year. They were also asked to cite any additional barriers, as well as the single most important barrier, where applicable. 
Before formal commencement of the study, a pilot study was conducted with 14 patients meeting the eligibility criteria to validate the questionnaire, develop coding classifications, and test the questionnaire's feasibility and acceptability. The study protocol was approved by the institutional review boards of the collaborating institutions (the Stanford University School of Medicine, the SFGH, and the University of California, San Francisco). This research project adhered to the tenets of the Declaration of Helsinki and maintained Health Insurance Portability and Accountability Act of 1996 compliance at all times. 
Statistical analysis was performed using a commercially available software package (SPSS 18.0; SPSS, Chicago, IL). The prevalence of various barriers to follow-up was calculated for the aggregate study population and was also stratified by race as part of a prospectively planned analysis. The χ2 test was used to determine whether certain barriers disproportionately affected specific ethnic groups. 
Results
Demographic characteristics of patients with inconsistent follow-up (cases) and consistent follow-up (controls) are summarized in Table 2. Of 170 patients recruited for the study, 14 were involved in the pilot study, and four declined to participate, citing time constraints. The remaining 152 subjects completed the oral questionnaire and were included in the final analysis according to the case-control protocol. Latino subjects represented the largest racial/ethnic subgroup, followed by Asian–Pacific Islanders (APIs), blacks, and whites. The mean age and severity of glaucoma did not differ substantially across ethnicities within the study. There was, however, a preponderance of men comprising the white subject group, while approximately two-thirds of black, Latino, and API subjects were female. All white and black subjects were proficient in English, whereas roughly 60% to 80% of Latino and API subjects reported a lack of proficiency in English and thus required the assistance of a foreign language medical interpreter. Black race was associated with poor follow-up on univariate analysis (P = 0.04), as has been previously reported by Murakami et al. 24  
Table 2
 
Demographic Characteristics of the Study Population
Table 2
 
Demographic Characteristics of the Study Population
Variable Overall, n = 152 Cases, n = 76 Controls, n = 76 P Value*
Age, y
 Mean (SD) 64.5 (9.1) 64.3 (9.5) 64.8 (8.8) 0.47
 Group, n (%)
  40–49 8 (5.3) 4 (5.3) 4 (5.3)
  50–59 34 (22.4) 19 (25.0) 15 (19.7)
  60–69 69 (45.4) 36 (47.3) 33 (43.4)
  70–79 33 (21.7) 12 (15.8) 21 (27.6)
  ≥80 8 (5.3) 5 (6.6) 3 (3.9)
Sex, n (%) 0.24
 Female 96 (63.2) 44 (57.9) 52 (68.4)
 Male 56 (36.8) 32 (42.1) 24 (31.6)
Race/ethnicity, n (%)
 White 19 (12.5) 6 (7.9) 13 (17.1) Reference
 Black 34 (22.4) 21 (27.6) 13 (17.1) OR, 3.50 (95% CI, 1.07–11.5), P = 0.04
 Asian–Pacific Islander 41 (27.0) 18 (23.7) 24 (31.6) OR, 1.63 (95% CI, 0.52–5.10), P = 0.41
 Latino 57 (37.5) 31 (40.8) 26 (34.2) OR, 2.58 (95% CI, 0.86–7.75), P = 0.09
English proficiency, n (%) 0.87
 Yes 80 (52.6) 39 (51.3) 41 (53.9)
 No 72 (47.4) 37 (48.7) 35 (46.1)
Primary language, n (%) 0.62
 English 53 (34.9) 29 (38.2) 24 (31.6)
 Spanish 54 (35.5) 29 (38.2) 25 (32.9)
 Mandarin/Cantonese 24 (15.8) 10 (13.2) 14 (18.4)
 Tagalog 13 (8.6) 5 (6.6) 8 (10.5)
 Other 8 (5.3) 3 (3.9) 5 (6.6)
Level of education, n (%) 0.93
 College and beyond 48 (31.6) 25 (32.9) 23 (30.3)
 Secondary school 40 (26.3) 18 (23.7) 22 (28.9)
 Grade school or less 64 (42.1) 33 (43.4) 31 (40.8)
Disease severity, n (%) 0.24
 Mild 61 (40.1) 25 (32.9) 36 (47.3)
 Moderate 33 (21.7) 18 (23.7) 15 (19.7)
 Severe 58 (38.2) 33 (43.4) 25 (32.9)
Outside service utilization, n (%) 0.25
 Seen only at SFGH for glaucoma-related care 139 (91.4) 67 (88.2) 72 (94.7)
 Seen outside of SFGH 13 (8.6) 9 (11.8) 4 (5.3)
Employment status, n (%) 0.86
 Not employed/retired 111 (73.0) 55 (72.4) 56 (73.7)
 Employed 41 (27.0) 21 (27.6) 20 (26.3)
Health insurance status, n (%) 0.18
 Government coverage (Medicare, MediCal,  San Francisco Health Plan) 143 (94.1) 69 (90.8) 74 (97.4)
 Private 7 (4.6) 5 (6.6) 2 (2.6)
 None 2 (1.3) 2 (2.6) 0
Among the 152 subjects in the study, 132 (87%) reported having at least one significant barrier to follow-up. Patient-reported barriers to follow-up are shown in Figure 1. The most prevalent barriers were long waiting times in the clinic (75%), appointment scheduling difficulties (38%), the effect of other medical or physical conditions (29%), and difficulties related to medical interpretation (23%). Subjects reported waiting an average of 2.3 hours when attending the clinic for glaucoma follow-up examinations. Appointment scheduling difficulties included delayed appointment availability, rescheduling of confirmed appointments by clinic staff, and inability to communicate with schedulers because of the subject's lack of English proficiency. The medical and physical conditions found to be the most prominent barriers to follow-up were those limiting mobility, including joint disease. Our definition of “difficulties related to interpretation” applied only to subjects utilizing foreign language medical interpreters, and these difficulties included additional waiting times for interpreters to arrive in the clinic and a sense that the interpreter-assisted physician-patient discussions still resulted in inadequate comprehension of their condition, treatment, and prognosis. 
Figure 1
 
Patient-reported barriers to follow-up in an urban county hospital population in San Francisco.
Figure 1
 
Patient-reported barriers to follow-up in an urban county hospital population in San Francisco.
Figure 1 also shows the single barrier deemed most important by those study subjects citing at least one significant barrier to follow-up. Long waiting times in the clinic (27%), other medical or physical conditions (15%), difficulties related to interpretation (14%), and appointment scheduling difficulties (13%) were reported to be the most important barriers. 
Because all subjects were recruited as part of a related case-control study, univariate and multivariate logistic regression analyses were performed for each potential barrier to follow-up in an effort to determine whether a particular barrier was independently predictive of good versus poor follow-up. None of the barriers were found to be statistically significant in predicting poor versus good follow-up in this particular analysis. 
Data on the barriers to follow-up were analyzed by race and ethnicity as part of a prospectively planned subgroup analysis (Fig. 2). Responses were remarkably similar across different ethnic groups with regard to which barrier was considered most important. All ethnicities reported long waiting times among their most important barriers to follow-up, with three out of four ethnic groups citing this factor as being most important. The exception was in the Latino group, among whom difficulties relating to interpretation ranked as the most important barrier to follow-up. Difficulties with interpretation were also reported to be important in the API group, ranking second only to waiting times, but were not ranked within the top three for the white and black groups, undoubtedly because subjects in the latter groups were more commonly fluent in English than those in the Latino and API groups. 
Figure 2
 
Most important barrier to follow-up by race in an urban county hospital population in San Francisco.
Figure 2
 
Most important barrier to follow-up by race in an urban county hospital population in San Francisco.
Table 3 summarizes all reported barriers to follow-up among the four ethnic groups. The problem of long waiting times in the clinic and difficulties related to interpretation varied significantly among different ethnic groups. While the data suggested that cost of care may be a more important barrier for the API group relative to the other groups, this finding did not achieve statistical significance in our study population. 
Table 3
 
All Reported Barriers to Follow-up Based on Ethnicity
Table 3
 
All Reported Barriers to Follow-up Based on Ethnicity
Barrier Subjects Reporting Specific Barrier, n (%) χ2 Statistic P Value*
White, n = 19 Black, n = 34 Latino, n = 57 API, n = 41
Long waiting times in clinic 13 (68.4) 20 (58.8) 48 (84.2) 32 (78.0) 7.93 0.048
Appointment scheduling difficulties 10 (52.6) 11 (32.4) 24 (42.1) 13 (31.7) 3.26 0.353
Other medical or physical conditions 7 (36.8) 8 (23.5) 20 (35.1) 8 (19.5) 3.90 0.272
Difficulties related to interpretation 0 1 (2.9) 21 (36.8) 13 (31.7) 21.20 0.0001
Forgot appointment 3 (15.8) 8 (23.5) 8 (14.0) 5 (12.2) 2.05 0.562
Financial costs 2 (10.5) 1 (2.9) 6 (10.5) 9 (22.0) 6.68 0.083
Unable to leave work responsibilities 0 2 (5.9) 9 (15.8) 6 (14.6) 5.03 0.169
Lack of escort 2 (10.5) 4 (11.8) 3 (5.3) 6 (14.6) 2.54 0.469
Other serious personal matters 2 (10.5) 2 (5.9) 3 (5.3) 1 (2.4) 1.73 0.631
Other incidental obligations 0 1 (2.9) 4 (7.0) 3 (7.3) 2.11 0.550
Security concerns when coming to clinic 0 0 4 (7.0) 2 (4.9) 3.67 0.300
Lost wages 0 0 2 (3.5) 3 (7.3) 3.88 0.275
“My eyes were okay at the time” 0 3 (8.8) 2 (3.5) 0 5.29 0.152
Unaware of the importance of regular follow-up 0 3 (8.8) 2 (3.5) 0 5.29 0.152
Discussion
The field of glaucoma research has devoted much attention to demonstrating the efficacy of various medical, laser, and surgical interventions that lower IOP and can slow glaucomatous visual loss. Glaucoma medication noncompliance has likewise been the subject of intensive investigation given the assumed importance of administering prescribed therapy to slow disease progression. In contrast, there has been a dearth of research regarding the problem of poor patient adherence to recommended glaucoma follow-up, an issue that is undoubtedly important in providing quality glaucoma care for individuals and populations. Without proper glaucoma follow-up, providers cannot monitor treatment efficacy and adverse effects, create individualized therapeutic regimens, or offer continual counseling and education to patients about their disease. Predictors of poor follow-up in our study population are reported separately 24 and can assist the clinician in predicting which patients may be at risk of nonadherence with glaucoma follow-up. The present analysis focused on better understanding the barriers to follow-up from the patient's perspective, a necessary step in facilitating adherence to follow-up. 
The Los Angeles Latino Eye Study 25 27 reported on eye care utilization patterns among a southern California Latino population in which subjects were identified via population-based eye screenings and subsequently sought formal care per health care provider recommendations. In contrast, our multiethnic study population was identified in an urban glaucoma clinic and then assessed with regard to adherence to recommended clinic follow-up. In our study, the four most significant barriers to follow-up, assessed both in terms of overall prevalence and by the single most important barrier to follow-up, were the following: (1) long waiting times in the clinic, (2) appointment scheduling difficulties, (3) other medical or physical conditions, and (4) difficulties related to interpretation. Among these top four, the first three were universally problematic across all ethnic groups. 
Waiting time was found to be the single most important barrier to follow-up, and among those reporting this as a significant barrier, the average reported waiting time was 2.3 hours (range, 1–6 hours). These waiting times were patient reported and were not confirmed by the research team. The estimates, however, were confirmed to be reasonable when clinic staff were informally interviewed regarding this matter during the course of the study. One contributing factor to long waiting times may have been an overabundance of patients with glaucoma relative to glaucoma physicians, a problem that is widespread across the United States and particularly worse in medically underserved areas and in developing countries. Other factors that prolong waiting times include the frequent need to use interpreters for patients lacking English proficiency and the fact that certain patients may need to be evaluated by both a resident and an attending ophthalmologist. 
Difficulty with appointment scheduling was the second most commonly cited reason for poor follow-up, with limiting factors ranging from a lack of availability of follow-up appointments at the recommended interval to inability of the patient to communicate with appointment schedulers who lacked proficiency in the language spoken by the patient. Strategies to mitigate the latter problem might include hiring appointment schedulers with basic proficiency in the most commonly spoken languages among patients in the clinic and using interpreter services for patient scheduling when needed. 
Medical and physical conditions posed a significant barrier to follow-up for many subjects, with the most common causes being lower extremity joint pain, limited mobility, and poor vision. A previous report from India by Lee et al. 17 similarly revealed that patients viewed their other nonocular medical and physical comorbidities as important barriers to follow-up for glaucoma but that this effect was diminished by the custom of having family members accompany patients to the clinic. 
Difficulties related to interpretation differentially affected Latino and API subjects, who viewed this as the single most and second most important barriers to follow-up, respectively. English proficiency, surprisingly, was not found to correlate with the likelihood of keeping scheduled appointments, which concurred with the results of another study 28 assessing follow-up for breast abnormalities in minority, low-income patients in Los Angeles. These findings are consistent with the possibility that patients lacking English proficiency, while able to attend follow-up appointments, are perhaps affected with regard to the quality of care received if difficulties with interpretation result in unanswered questions about glaucomatous disease, its prognosis, or the rationale behind attending regular follow-up examinations. Each of these hypotheses warrants further study. 
One limitation of this study was that the study population was drawn from a very specific practice environment (an urban, county, university-affiliated teaching hospital). There are particular limitations and constraints imposed by this practice environment; thus, our findings may not be generalizable to other glaucoma populations. The study also had a somewhat modest sample size, especially for the subgroup analysis that partitioned the study population into racial subgroups. The study was not powered to specifically address the question of differential barriers by race. Thus, while the sample size was adequate to assess our primary study goal of determining the barriers to follow-up, caution must be used in attempting to generalize our findings regarding race to other populations. Further confirmatory studies are needed that are specifically powered to address this question. 
To process the ramifications of this study's findings from a health system perspective, one must consider which barriers are system related and thus modifiable at the clinic and hospital levels versus those which are patient related, with the latter being less amenable to intervention by practitioners delivering health care. Of the four most significant barriers to follow-up, three (long waiting times in the clinic, appointment scheduling difficulties, and difficulties related to interpretation) are indeed system related, whereas only one (other medical or physical conditions) is patient related. Health care providers in medically underserved settings may ascribe poor glaucoma follow-up primarily to patient-related barriers, but the results of our study suggest that patients may find system-related barriers to be of paramount importance. 
Every eye care provider operates in a unique practice environment with regard to physical resources, staff, and patient population. While one must thus exert caution in generalizing this study's conclusions to other urban multiethnic glaucoma practices, our findings suggest that providers should at least consider, if not systematically seek to understand, the patient-related and system-related barriers to follow-up experienced by patients. Although individual barriers to follow-up did not ultimately predict who did and did not follow up as advised, these barriers certainly have implications in terms of quality and equitability of care provided. Our study underscores how different barriers to follow-up may be borne disproportionately by certain ethnic groups. Future studies are needed to assist in developing interventions that can reduce system-related barriers to follow-up, ensure equitable glaucoma care delivery regardless of language or ethnicity, and ultimately determine whether reducing patient-reported barriers translates into improved clinical follow-up and outcomes. 
Acknowledgments
Supported by the Stanford University Medical Scholars Research Program (BWL, YM). 
Disclosure: B.W. Lee, None; Y. Murakami, None; M.T. Duncan, None; A.A. Kao, None; J.-Y. Huang, None; S. Lin, None; K. Singh, None 
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Figure 1
 
Patient-reported barriers to follow-up in an urban county hospital population in San Francisco.
Figure 1
 
Patient-reported barriers to follow-up in an urban county hospital population in San Francisco.
Figure 2
 
Most important barrier to follow-up by race in an urban county hospital population in San Francisco.
Figure 2
 
Most important barrier to follow-up by race in an urban county hospital population in San Francisco.
Table 1
 
Criteria for Classifying Cases and Controls Based on Follow-up During the 12 to 18 Months Preceding the Study*
Table 1
 
Criteria for Classifying Cases and Controls Based on Follow-up During the 12 to 18 Months Preceding the Study*
Variable Glaucoma Disease Severity
Mild Moderate Severe
Follow-up recommendations‡ Every 5–6 mo (approximately 2 visits per year) Every 4–5 mo (approximately 3 visits per year) Every 3–4 mo (approximately 4 visits per year)
Good follow-up (controls) ≥2 Visits per year, with 5–6 mo maximum intervals between visits ≥3 Visits per year, with 4–5 mo maximum intervals between visits ≥3 Visits per year, with 3–4 mo maximum intervals between visits
Poor follow-up (cases) ≤1 Visit per year or extended interval between visits ≤2 Visits per year or extended interval between visits ≤2 Visits per year or extended interval between visits
Table 2
 
Demographic Characteristics of the Study Population
Table 2
 
Demographic Characteristics of the Study Population
Variable Overall, n = 152 Cases, n = 76 Controls, n = 76 P Value*
Age, y
 Mean (SD) 64.5 (9.1) 64.3 (9.5) 64.8 (8.8) 0.47
 Group, n (%)
  40–49 8 (5.3) 4 (5.3) 4 (5.3)
  50–59 34 (22.4) 19 (25.0) 15 (19.7)
  60–69 69 (45.4) 36 (47.3) 33 (43.4)
  70–79 33 (21.7) 12 (15.8) 21 (27.6)
  ≥80 8 (5.3) 5 (6.6) 3 (3.9)
Sex, n (%) 0.24
 Female 96 (63.2) 44 (57.9) 52 (68.4)
 Male 56 (36.8) 32 (42.1) 24 (31.6)
Race/ethnicity, n (%)
 White 19 (12.5) 6 (7.9) 13 (17.1) Reference
 Black 34 (22.4) 21 (27.6) 13 (17.1) OR, 3.50 (95% CI, 1.07–11.5), P = 0.04
 Asian–Pacific Islander 41 (27.0) 18 (23.7) 24 (31.6) OR, 1.63 (95% CI, 0.52–5.10), P = 0.41
 Latino 57 (37.5) 31 (40.8) 26 (34.2) OR, 2.58 (95% CI, 0.86–7.75), P = 0.09
English proficiency, n (%) 0.87
 Yes 80 (52.6) 39 (51.3) 41 (53.9)
 No 72 (47.4) 37 (48.7) 35 (46.1)
Primary language, n (%) 0.62
 English 53 (34.9) 29 (38.2) 24 (31.6)
 Spanish 54 (35.5) 29 (38.2) 25 (32.9)
 Mandarin/Cantonese 24 (15.8) 10 (13.2) 14 (18.4)
 Tagalog 13 (8.6) 5 (6.6) 8 (10.5)
 Other 8 (5.3) 3 (3.9) 5 (6.6)
Level of education, n (%) 0.93
 College and beyond 48 (31.6) 25 (32.9) 23 (30.3)
 Secondary school 40 (26.3) 18 (23.7) 22 (28.9)
 Grade school or less 64 (42.1) 33 (43.4) 31 (40.8)
Disease severity, n (%) 0.24
 Mild 61 (40.1) 25 (32.9) 36 (47.3)
 Moderate 33 (21.7) 18 (23.7) 15 (19.7)
 Severe 58 (38.2) 33 (43.4) 25 (32.9)
Outside service utilization, n (%) 0.25
 Seen only at SFGH for glaucoma-related care 139 (91.4) 67 (88.2) 72 (94.7)
 Seen outside of SFGH 13 (8.6) 9 (11.8) 4 (5.3)
Employment status, n (%) 0.86
 Not employed/retired 111 (73.0) 55 (72.4) 56 (73.7)
 Employed 41 (27.0) 21 (27.6) 20 (26.3)
Health insurance status, n (%) 0.18
 Government coverage (Medicare, MediCal,  San Francisco Health Plan) 143 (94.1) 69 (90.8) 74 (97.4)
 Private 7 (4.6) 5 (6.6) 2 (2.6)
 None 2 (1.3) 2 (2.6) 0
Table 3
 
All Reported Barriers to Follow-up Based on Ethnicity
Table 3
 
All Reported Barriers to Follow-up Based on Ethnicity
Barrier Subjects Reporting Specific Barrier, n (%) χ2 Statistic P Value*
White, n = 19 Black, n = 34 Latino, n = 57 API, n = 41
Long waiting times in clinic 13 (68.4) 20 (58.8) 48 (84.2) 32 (78.0) 7.93 0.048
Appointment scheduling difficulties 10 (52.6) 11 (32.4) 24 (42.1) 13 (31.7) 3.26 0.353
Other medical or physical conditions 7 (36.8) 8 (23.5) 20 (35.1) 8 (19.5) 3.90 0.272
Difficulties related to interpretation 0 1 (2.9) 21 (36.8) 13 (31.7) 21.20 0.0001
Forgot appointment 3 (15.8) 8 (23.5) 8 (14.0) 5 (12.2) 2.05 0.562
Financial costs 2 (10.5) 1 (2.9) 6 (10.5) 9 (22.0) 6.68 0.083
Unable to leave work responsibilities 0 2 (5.9) 9 (15.8) 6 (14.6) 5.03 0.169
Lack of escort 2 (10.5) 4 (11.8) 3 (5.3) 6 (14.6) 2.54 0.469
Other serious personal matters 2 (10.5) 2 (5.9) 3 (5.3) 1 (2.4) 1.73 0.631
Other incidental obligations 0 1 (2.9) 4 (7.0) 3 (7.3) 2.11 0.550
Security concerns when coming to clinic 0 0 4 (7.0) 2 (4.9) 3.67 0.300
Lost wages 0 0 2 (3.5) 3 (7.3) 3.88 0.275
“My eyes were okay at the time” 0 3 (8.8) 2 (3.5) 0 5.29 0.152
Unaware of the importance of regular follow-up 0 3 (8.8) 2 (3.5) 0 5.29 0.152
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