 |
|
Impact of Vision Loss on Costs and Outcomes in Medicare Beneficiaries With Glaucoma
Thomas Bramley, PhD;
Patti Peeples, PhD;
John G. Walt, MBA;
Marta Juhasz, MSPH;
Jan E. Hansen, PhD
Arch Ophthalmol. 2008;126(6):849-856.
ABSTRACT
| |
Objective To assess the impact of vision loss severity on costs and health outcomes among Medicare beneficiaries with glaucoma.
Methods A retrospective cohort analysis was conducted using Medicare claims. Patients were stratified into 4 categories: no vision loss, moderate vision loss, severe vision loss, and blindness. Outcomes of interest were mean annual medical costs by category, component costs, and frequency of depression, falls and/or accidents, injury, femur fracture, and nursing home placement.
Results Multivariate regression analysis showed that patients with any degree of vision loss had 46.7% higher total costs compared with patients without vision loss. Mean total and component costs increased with onset and severity ($8157 for no vision loss to $18 670 for blindness). Patients with vision loss were significantly more likely to be placed in a nursing home (odds ratio = 2.18; 95% confidence interval, 2.06-2.31), develop depression (odds ratio = 1.63; 95% confidence interval, 1.54-1.73), fracture a femur (odds ratio = 1.67; 95% confidence interval, 1.53-2.83), or experience a fall or accident (odds ratio = 1.59; 95% confidence interval, 1.50-1.68) vs patients without vision loss.
Conclusions Vision loss in glaucoma is costly, and costs increase with severity. There is significantly increased risk of nursing home admission, depression, falls and/or accidents, injury, or femur fracture with vision loss compared with no vision loss.
INTRODUCTION
More than 3.3 million Americans had visual impairment or blindness in 2004; glaucoma, a chronic optic neuropathy, is a leading cause of vision impairment.1 Loss of vision is feared more than human immunodeficiency virus and AIDS, cancer, stroke,2 or death.3 Visual impairment increases risks of falls and accidents,4-5 hip fractures,6-13 injury,4, 14-17 motor vehicle crashes,4, 18-19 nursing home placement,5, 8, 20 and mortality.21-22 Moreover, inadequate vision is related to functional status decline23-27 and depression.28-32
The economic burden of all visual disorders to the United States was estimated at $35.4 billion, with a governmental budgetary impact of $13.7 billion (2005 US dollars).33 These estimates do not include costs of associated comorbidities (depression, traumatic injury) or eye-related well care and were not stratified by vision loss cause.
Because glaucoma is responsible for approximately 3 of every 4 cases of visual impairment and is predominantly a disease of the elderly,34 its cost impact is highly important to Medicare. Numerous glaucoma-specific burden of illness studies have been conducted.5, 35-38 However, some are limited by the patient population studied (eg, end-stage glaucoma only,37 non-Medicare patients36-37), method of glaucoma severity staging,35 and reliance on chart review methods35, 37 that measure prescribed—not consumed—resource use. Another study lacked visual loss severity stratification,37 and there is substantial evidence that costs and adverse consequences increase with visual impairment severity.5, 35-36,39-46 Each of these considerations limits the applicability and generalizability of results.
A retrospective claims analysis conducted by Javitt et al5 described an epidemiologically validated vision loss severity categorization using International Classification of Diseases, Ninth Revision, Clinical Modification (ICD-9-CM)47 codes for vision loss. An estimated $2.14 billion in non–eye-related medical care costs was attributed to blindness and vision loss in 2003, and 27% to 41% of excess vision loss costs were due to increased risk of depression, injury, skilled nursing facility use, and long-term care facility admission. The study, although important and methodologically sound, included Medicare beneficiaries aged 69 years or older with vision loss from any cause, used data spanning 1999 to 2003, and did not show costs by resource use category.
A more current estimate of total and component costs is needed to better understand the full economic implications of glaucoma-specific vision loss to Medicare and to determine the impact of these costs by severity. With the recent emphasis by Medicare on glaucoma awareness and disease progression,48-50 it is imperative to document the risk of associated adverse consequences (depression, injury, femur fracture, and nursing home admission) stratified by vision loss in a glaucoma population. Therefore, the objective of this research was to assess the impact of vision loss severity on costs and health outcomes among Medicare beneficiaries with glaucoma.
METHODS
DATA SOURCE
This retrospective cohort analysis was conducted with the frequently used51-52 and nationally representative Medicare 5% random sample, which contains covered inpatient and outpatient fee-for-service claims for beneficiaries aged 65 years or older. Data elements are derived from discharge records and contain unique identifier-linked medical claims and charges for inpatient hospitalization, physician visits, injectable medications, and services related to laboratory, skilled nursing facility, ambulatory surgery, home health, and hospice care in addition to mortality records. The study database was developed using a limited data set with masked patient identifiers, and materials were handled in compliance with the Health Insurance Portability and Accountability Act of 1996.
PATIENT SELECTION
Because the analytic file provided dates of service by quarter rather than specific day, inclusion criteria reflected quarter date stamping. Patients aged 65 years or older with a new diagnosis of glaucoma (index diagnosis, ICD-9-CM code 365.x) between the third quarter in 1999 and the fourth quarter in 2004 and with continuous Medicare enrollment in the 2 quarters prior to and 5 quarters after index diagnosis were selected, as this approximated 1 year of follow-up. Individuals with health maintenance organization enrollment or who died prior to the end of the minimally required 5-quarter follow-up period were excluded.
COHORT ASSIGNMENT
Patients were stratified into 4 mutually exclusive categories based on their worst degree of vision loss during follow-up using 57 ICD-9-CM codes previously described and validated by Javitt et al5: no vision loss, moderate vision loss (ICD-9-CM codes 369.6-369.9), severe vision loss (ICD-9-CM codes 369.1-369.4), and blindness (ICD-9-CM codes 369.0-369.08).
COST CATEGORIES
The direct medical cost analysis was from the Medicare perspective and included the amount reimbursed to the provider, excluding premiums, deductibles, and co-pays. Inpatient, outpatient, rehabilitation, physician visit, office-administered pharmaceutical, laboratory, skilled nursing facility care ( 100 days), hospice, and home health care costs were included. Because Medicare did not cover outpatient prescription drugs at the time of study conduct, these costs were excluded. Costs were adjusted for inflation using the medical care Consumer Price Index and are presented in 2007 US dollars.53
OUTCOMES ASSESSED
The primary cost outcome variable was the adjusted mean total annual health care costs in the postindex period by vision loss category. Component costs—inpatient, outpatient, emergency, physician, and other—were compared between cohorts. Other outcomes included incident depression, falls and/or accidents, injury, femur fracture, and nursing home placement (ie, admission to a skilled nursing facility or long-term care facility) and were based on ICD-9-CM codes (Table 1).
|
|
|
|
Table 1. International Classification of Diseases, Ninth Revision, Clinical Modification Codes to Define Adverse Events of Interest
|
|
|
Risk assessments for nursing home placement and depression were conducted on the population at risk at the time of index vision loss diagnosis; therefore, only patients who did not have the event of interest at that point were included. For falls or accidents, injury, and femur fracture, patients with prior events were not excluded.
COMORBIDITY ASSESSMENT
Comorbidities were assessed using the valid and reliable54-57 Charlson comorbidity score with Deyo modification.58-59 The calculated Deyo-Charlson Index score ranges from 0 to 29 with higher scores representing a higher burden of comorbidity, defined as the cumulative increased likelihood of 1-year mortality.
STATISTICAL ANALYSES
Univariate analyses of frequencies, medians, and means with standard deviations were performed to describe the study population. Statistical differences between vision loss cohorts were assessed using  2 tests of proportionality for categorical variables and analysis of variance for continuous variables.
Ordinary least squares regression models estimated and compared mean annual total and component health care costs between cohorts during the 5 quarters of follow-up from the index date. Five quarters approximated 1 year owing to the varying dates of initiation within the entry quarter. To produce the best fit, each model was adjusted for a subset of covariates found to be significantly associated with the costs. Covariates considered for analysis were age, sex, race, geographic region, presence of neurological disorders or inpatient claims in the preindex period, Deyo-Charlson Index score, sum of all existing diagnoses in the preindex period, and total costs in the preindex period. For patients with some degree of vision loss, the index date was reassigned as the date of first diagnostic evidence of the most severe vision loss. For those with no vision loss, the index date remained the first medical claim for glaucoma diagnosis. In the cost analyses, the mean overall cost per patient was first calculated for each group. When using statistical inference through modeling, cost variables were log transformed to adjust for the highly right-skewed distribution typical of cost data.60 The reference group for statistical comparison was beneficiaries with no evidence of vision loss during follow-up.
Separate stepwise parsimonious binary logistic regression models were derived to assess differences in the risk of experiencing each secondary outcome event, controlling for baseline covariates that may have impacted risk between those with vision loss and those with no vision loss. Odds ratios (ORs) of their occurrence and 95% confidence intervals (CIs) were derived. Baseline covariates considered were age, sex, race, geographic region, preindex comorbid diseases (dementia, Alzheimer disease, Parkinson disease, depression), Deyo-Charlson Index score, unique count of disease states beyond those considered in the Deyo-Charlson Index, and number of preindex inpatient claims. Variables that were significant at P < .05 were retained in the models. P values were considered significant when the 2-sided value was less than .05. All of the analyses were carried out using SAS version 9.1 statistical software (SAS Institute, Inc, Cary, North Carolina).
RESULTS
STUDY POPULATION AND PATIENT CHARACTERISTICS
A total of 365 345 Medicare beneficiaries with glaucoma met the inclusion criteria. Excluded were 50.2% (n = 183 423) owing to the following: death prior to the end of the 5-quarter follow-up period (n = 15 846); health maintenance organization enrollment (n = 22 904); or lack of continuous eligibility or complete data availability during the preindex and postindex periods (n = 144 673). Thus, 181 922 patients with glaucoma were categorized into vision loss cohorts: the majority (92.1%) as having no vision loss, 4.3% as having moderate vision loss, 1.9% as having severe vision loss, and 1.7% as blind. Table 2 shows patient characteristics of the study population.
|
|
|
|
Table 2. Patient Characteristics of 181922 Medicare Beneficiaries With Glaucoma by Vision Loss Cohort
|
|
|
HEALTH CARE COSTS
The simple mean total and component health care costs increased with onset and degree of vision loss, ranging from $8157 for no vision loss to $18 670 for blindness (Figure 1). Onset of moderate vision loss was associated with a $5005 increase in costs compared with those with glaucoma but no vision loss ($13 162 vs $8157, respectively). The cost for patients with severe vision loss was $7155 more than that for patients without any degree of vision loss, whereas the cost for blind patients was $10 513 higher than that for patients without vision loss.
|
|
|
|
Figure 1. Mean total and component annual health care costs per patient after index by vision loss cohort (n = 181 922). Total costs are not always equal to the sum of component costs because of rounding. Each component cost is rounded to the nearest integer, and the total cost is rounded to the nearest integer separately.
|
|
|
Results from the covariate-adjusted multivariate regression analysis showed that patients with any degree of vision loss had 46.7% higher total costs compared with patients without vision loss (P < .001) (Table 3).
|
|
|
|
Table 3. Results of Regression Modeling to Estimate Annual Costs
|
|
|
EVENT RISK
Frequency of events invariably increased with greater vision loss for all of the investigated events (Figure 2). In blind patients, 25.3% were placed in nursing homes, 17.0% had incident depression, 15.5% experienced a fall and/or accident, 16.9% sustained injury, and 7.0% fractured a femur. Conversely, in patients with no vision loss, no single event exceeded 7.8% in the total population.
|
|
|
|
Figure 2. Frequency of events by vision loss cohort.
|
|
|
Patients with vision loss were significantly more likely to be placed in a nursing home (OR = 2.18; 95% CI, 2.06-2.31) and to develop depression (OR = 1.63; 95% CI, 1.54-1.73) compared with patients with no vision loss. Additionally, they were 67.4% more likely to fracture a femur (OR = 1.67; 95% CI, 1.53-1.83) and 58.6% more likely to experience a fall or accident (OR = 1.59; 95% CI, 1.50-1.68) vs the reference group. In addition, there was a 33.4% higher risk of injury associated with vision loss (OR = 1.33; 95% CI, 1.27-1.41) compared with no vision loss. The odds of an individual with vision loss experiencing selected adverse events during the postindex period compared with patients with no vision loss, adjusted for all of the significant predictor variables, are shown in Table 4.
|
|
|
|
Table 4. Results of Logistic Modeling to Assess Risk of Events Associated With Vision Loss
|
|
|
COMMENT
The progressive nature of glaucoma and permanence of vision loss48 make it an important disease to properly manage with early intervention. Results from this study showed that as visual field limitations increased, resource consumption, adverse consequences, and intensity of care also increased. Medicare beneficiaries with glaucoma who experienced any degree of ICD-9-CM–coded vision loss had significantly higher covariate-adjusted total health care costs than patients without vision loss. Both total and component costs progressively increased with escalating severity of vision loss.
Most economic analyses within glaucoma evaluated costs associated with glaucoma severity rather than vision loss or patient-rated impairment. Javitt et al5 were the first to describe the vision loss categories used in our study, and their research estimated overall average annual non–eye-related costs in 2003 US dollars as $5954 to $7527 for no vision loss, $10 050 to $14 876 for moderate vision loss, $14 311 to $15 250 for severe vision loss, and $14 905 to $19 366 for blindness. In general, our average annual total (including eye-related care) costs were similar: $8157 for no vision loss; $13 162 for moderate vision loss; $15 312 for severe vision loss; and $18 670 for blindness (2007 US dollars). There are some important methodological differences between our study and the research by Javitt and colleagues. Of the patients in their study sample, 37% to 43% had a glaucoma diagnosis and 38% to 66% had macular degeneration compared with 100% of the patients with glaucoma in our study. Our analysis included all health care costs, whereas Javitt and colleagues segmented costs by eye-related and non–eye-related costs and also investigated incremental vision loss costs. We show mean costs from 1999 to 2005 for year 1 after diagnosis of initial vision loss or glaucoma (for the cohort with no vision loss); Javitt and colleagues derived annualized data during 4 years of follow-up with either stable or progressive vision loss (in 1999-2003).
Similar to our economic burden findings with vision loss severity, numerous studies have shown that glaucoma severity is associated with increased treatment costs.35-36,39-46 Lee et al35 found that patients with ocular hypertension or earliest-phase glaucoma had mean annual eye-related direct medical costs of $623 (2001 US dollars), rising to $2511 for those with end-stage disease (typically blindness), which were slightly higher than the eye-related costs in Medicare beneficiaries described by Javitt et al5 that excluded prescription drugs. Kobelt-Nguyen et al44 found that mean 2-year costs for glaucoma were $2188 (1995 US dollars) and increased with severity.
The primary driver of total cost was inpatient visits, increasing by severity (52.5%-69.4% of total costs). Physician visit costs ranged from 9.0% (blindness) to 23.1% (no vision loss) of total costs. Others42 have found that component costs for patients with open-angle glaucoma were dominated by procedures (45% of total costs) and physician visits (43%). As severity increased, physician visit costs decreased to 38% and procedure costs increased to 50%. Outpatient prescription medications were not included in our study because they were not covered by Medicare at the time of the study. The advent of Medicare Part D prescription drug coverage will likely increase the total cost estimate, and other studies36, 39-40 have estimated medication component costs to be dependent on disease severity41 and highly variable, ranging from 12%42 to 61%.35
The adjusted risk of nursing home placement was 2.18 times higher for patients with any vision loss compared with individuals with no vision loss, confirming results from other studies.5, 8, 20 Our results of a 33.4% increased risk of injury, 58.6% increased risk of falls and accidents, and 67.4% increased risk of femur fracture are also within the parameter risk estimates by other researchers.5, 8 Haymes et al4 found that compared with control subjects, patients with glaucoma had more than a 3-fold higher risk of falls in the previous year. Colón-Emeric et al13 found that glaucoma was significantly associated with hip fracture risk in ambulatory men (OR = 2.6; 95% CI, 1.0-6.2).
Studies show that approximately one-third of visually impaired older individuals report clinically significant depressive symptoms,28-30,61-63 and rates are significantly higher than those in the healthy population of similar age and are similar to or greater than those in other medically ill elderly individuals.28-32 Our analysis found a 63.0% increased risk of depression diagnosis, similar to the depression risk increases of 40% to 80% found by Javitt et al.5 Numerous other studies found links between vision loss and depression, family dysfunction, and marital problems28-32 and between depression and physical functioning.64
Several limitations should be considered when interpreting the results of this study. The data source was administrative claims and the design was retrospective; thus, causality cannot be ascribed. Although numerous other studies have shown similar trends with costs and adverse consequences, the possibility cannot be ruled out that factors other than visual loss severity were responsible for differences in outcomes.
The Medicare 5% analytic sample did not include outpatient medications or long-term care and may limit generalizability of the results to the non-Medicare population, to elderly individuals who do not receive their primary health care through Medicare, or to the post–Medicare Part D period. However, the Medicare 5% analytic database is a representative reflection of those individuals aged 65 years or older with glaucoma who receive medical care through Medicare coverage. Moreover, median glaucoma-associated costs have been shown to be similar for patients younger than 65 years compared with patients aged 65 years or older.36
Derived costs represented first-year postdiagnosis total health care cost, reflecting a snapshot in time rather than longitudinal costs, and were not specifically attributed to vision loss. Year 1 costs have been shown to be both lower35 and higher36-37,39 in patients with glaucoma compared with post–year 1 costs. Severity-associated costs may have been due to other diseases coexisting with visual loss deterioration, and differences in outcomes may have been affected if cohorts were not equally balanced with respect to these factors. To moderate this effect, the multivariate cost and risk statistical analyses controlled for age, sex, preindex health care utilization, and other confounders.
The ICD-9-CM codes were used for both glaucoma diagnosis and vision loss, and they are subject to the limitations in coding variance and projection of administrative claims data to larger populations.65-66 The ICD-9-CM code 365.0 may be used for patients with ocular hypertension or glaucoma suspects, and these patients typically have a much lower risk of current or future vision loss. As such, the cohort with no vision loss may not exclusively contain patients with confirmed glaucoma who have no vision loss, thus the estimated costs and risks for this category may be conservative. Although the vision loss categories used in our study have previously been described and validated against epidemiologic studies34 by Javitt et al,5 the possibility remains that the codes were not accurate reflections of either the presence of vision loss or vision loss gradations. Further, the severity categorizations are susceptible to individual clinician judgment, which introduces a degree of interrater reliability and variance.
CONCLUSIONS
The risk of blindness or significant, permanent loss of visual field in glaucoma is costly, and the total direct medical and component costs increase with vision loss severity. There is a significant increase in the risk of major adverse consequences such as nursing home admission, depression, falls and accidents, injury, or femur fracture with any degree of vision loss compared with no vision loss.
AUTHOR INFORMATION
Correspondence: Thomas Bramley, PhD, Xcenda, 1528 Preston St, Salt Lake City, UT 84108 (thomas.bramley{at}xcenda.com).
Submitted for Publication: August 23, 2007; final revision received December 20, 2007; accepted January 3, 2008.
Financial Disclosure: None reported.
Author Contributions: Dr Bramley had full access to all of the data in the study and takes responsibility for the integrity of the data and the accuracy of the data analysis.
Funding/Support: This work was supported by Allergan, Inc.
Additional Contributions: Elizabeth Davis, PhD, contributed to the development of the manuscript, and Laurie Kozbelt, MA, contributed to the preparation of the manuscript.
Author Affiliations: Xcenda, Salt Lake City, Utah (Dr Bramley); Xcenda, Palm Harbor, Florida (Drs Peeples and Juhasz); and Allergan, Inc, Irvine, California (Mr Walt and Dr Hansen).
REFERENCES
| |
1. Resnikoff S, Pascolini D, Etya’ale D; et al. Global data on visual impairment in the year 2002. Bull World Health Organ. 2004;82(11):844-851.
ISI
| PUBMED
2. Vision 2007 Survey AFB: Americans fear impact of vision loss more than cancer. Vision Monday. May 21, 2007;21:06. http://www.visionmonday.com/articles/details.asp?ID=16808. Accessed May 31, 2007.3. Lions Clubs International Foundation. US adults with diabetes fear blindness or vision loss more than premature death: many respondents in international diabetes survey worried about quality of life. http://www.lionsclubs.org/EN/content/news_news_release58.stm. Accessed May 29, 2007.4. Haymes SA, LeBlanc RP, Nicolela MT, Chiasson LA, Chauhan BC. Risk of falls and motor vehicle collisions in glaucoma. Invest Ophthalmol Vis Sci. 2007;48(3):1149-1155.
FREE FULL TEXT
5. Javitt JC, Zhou Z, Willke RJ. Association between vision loss and higher medical care costs in Medicare beneficiaries: costs are greater for those with progressive vision loss. Ophthalmology. 2007;114(2):238-245.
FULL TEXT
|
ISI
| PUBMED
6. Cummings SR, Nevitt MC, Browner WS; et al, Study of Osteoporotic Fractures Research Group. Risk factors for hip fracture in white women. N Engl J Med. 1995;332(12):767-773.
FREE FULL TEXT
7. Felson DT, Anderson JJ, Hannan MT, Milton RC, Wilson PW, Kiel DP. Impaired vision and hip fracture: the Framingham Study. J Am Geriatr Soc. 1989;37(6):495-500.
ISI
| PUBMED
8. Klein BE, Moss SE, Klein R, Lee KE, Cruickshanks KJ. Associations of visual function with physical outcomes and limitations 5 years later in an older population: the Beaver Dam eye study. Ophthalmology. 2003;110(4):644-650.
FULL TEXT
|
ISI
| PUBMED
9. Chan KM, Pang WS, Ee CH, Ding YY, Choo P. Epidemiology of falls among the elderly community dwellers in Singapore. Singapore Med J. 1997;38(10):427-431.
PUBMED
10. Nevitt MC, Cummings SR, Kidd S, Black D. Risk factors for recurrent nonsyncopal falls: a prospective study. JAMA. 1989;261(18):2663-2668.
FREE FULL TEXT
11. Lord SR, Ward JA, Williams P, Anstey KJ. Physiological factors associated with falls in older community-dwelling women. J Am Geriatr Soc. 1994;42(10):1110-1117.
ISI
| PUBMED
12. Ivers RQ, Cumming RG, Mitchell P, Attebo K. Visual impairment and falls in older adults: the Blue Mountains Eye Study. J Am Geriatr Soc. 1998;46(1):58-64.
ISI
| PUBMED
13. Colón-Emeric CS, Biggs DP, Schenck AP, Lyles KW. Risk factors for hip fracture in skilled nursing facilities: who should be evaluated? Osteoporos Int. 2003;14(6):484-489.
FULL TEXT
|
ISI
| PUBMED
14. Szlyk JP, Mahler CL, Seiple W, Edward DP, Wilensky JT. Driving performance of glaucoma patients correlates with peripheral visual field loss. J Glaucoma. 2005;14(2):145-150.
FULL TEXT
|
ISI
| PUBMED
15. Sims RV, McGwin G Jr, Allman RM, Ball K, Owsley C. Exploratory study of incident vehicle crashes among older drivers. J Gerontol A Biol Sci Med Sci. 2000;55(1):M22-M27.
ISI
| PUBMED
16. Owsley C, McGwin G Jr, Ball K. Vision impairment, eye disease, and injurious motor vehicle crashes in the elderly. Ophthalmic Epidemiol. 1998;5(2):101-113.
FULL TEXT
| PUBMED
17. Owsley C, Stalvey BT, Wells J, Sloane ME, McGwin G Jr. Visual risk factors for crash involvement in older drivers with cataract. Arch Ophthalmol. 2001;119(6):881-887.
FREE FULL TEXT
18. Owsley C, McGwin G Jr. Vision impairment and driving. Surv Ophthalmol. 1999;43(6):535-550.
FULL TEXT
|
ISI
| PUBMED
19. Wood JM. Aging, driving and vision. Clin Exp Optom. 2002;85(4):214-220.
PUBMED
20. Wang JJ, Mitchell P, Cumming RG, Smith W. Visual impairment and nursing home placement in older Australians: the Blue Mountains Eye Study. Ophthalmic Epidemiol. 2003;10(1):3-13.
FULL TEXT
|
ISI
| PUBMED
21. Pedula KL, Coleman AL, Hillier TA; et al, Study of Osteoporotic Fractures Research Group. Visual acuity, contrast sensitivity, and mortality in older women: study of osteoporotic fractures. J Am Geriatr Soc. 2006;54(12):1871-1877.
FULL TEXT
|
ISI
| PUBMED
22. Freeman EE, Egleston BL, West SK, Bandeen-Roche K, Rubin G. Visual acuity change and mortality in older adults. Invest Ophthalmol Vis Sci. 2005;46(11):4040-4045.
FREE FULL TEXT
23. Bess FH, Lichtenstein MJ, Logan SA, Burger MC, Nelson E. Hearing impairment as a determinant of function in the elderly. J Am Geriatr Soc. 1989;37(2):123-128.
ISI
| PUBMED
24. Rudberg MA, Furner SE, Dunn JE, Cassel CK. The relationship of visual and hearing impairments to disability: an analysis using the longitudinal study of aging. J Gerontol. 1993;48(6):M261-M265.
ABSTRACT
25. West SK, Munoz B, Rubin GS; et al. Function and visual impairment in a population-based study of older adults: the SEE project: Salisbury Eye Evaluation. Invest Ophthalmol Vis Sci. 1997;38(1):72-82.
FREE FULL TEXT
26. Salive ME, Guralnik J, Glynn RJ, Christen W, Wallace RB, Ostfeld AM. Association of visual impairment with mobility and physical function. J Am Geriatr Soc. 1994;42(3):287-292.
ISI
| PUBMED
27. Rubin GS, Bandeen-Roche K, Huang GH; et al. The association of multiple visual impairments with self-reported visual disability: SEE project. Invest Ophthalmol Vis Sci. 2001;42(1):64-72.
FREE FULL TEXT
28. Brody BL, Gamst AC, Williams RA; et al. Depression, visual acuity, comorbidity, and disability associated with age-related macular degeneration. Ophthalmology. 2001;108(10):1893-1900.
FULL TEXT
|
ISI
| PUBMED
29. Rovner BW, Casten RJ. Activity loss and depression in age-related macular degeneration. Am J Geriatr Psychiatry. 2002;10(3):305-310.
FULL TEXT
|
ISI
| PUBMED
30. Rovner BW, Casten RJ, Tasman WS. Effect of depression on vision function in age-related macular degeneration. Arch Ophthalmol. 2002;120(8):1041-1044.
FREE FULL TEXT
31. Bernbaum M, Albert SG, Duckro PN, Merkel W. Personal and family stress in individuals with diabetes and vision loss. J Clin Psychol. 1993;49(5):670-677.
ISI
| PUBMED
32. Bernbaum M, Albert SG, Duckro PN. Psychosocial profiles in patients with visual impairment due to diabetic retinopathy. Diabetes Care. 1988;11(7):551-557.
ABSTRACT
33. Rein DB, Zhang P, Wirth KE; et al. The economic burden of major adult visual disorders in the United States. Arch Ophthalmol. 2006;124(12):1754-1760.
FREE FULL TEXT
34. Friedman DS, Wolfs RC, O’Colmain BJ; et al, Eye Diseases Prevalence Research Group. Prevalence of open-angle glaucoma among adults in the United States. Arch Ophthalmol. 2004;122(4):532-538.
FREE FULL TEXT
35. Lee PP, Walt JG, Doyle JJ; et al. A multicenter, retrospective pilot study of resource use and costs associated with severity of disease in glaucoma. Arch Ophthalmol. 2006;124(1):12-19.
FREE FULL TEXT
36. Lee PP, Levin LA, Walt JG; et al. Cost of patients with primary open-angle glaucoma: a retrospective study of commercial insurance claims data. Ophthalmology. 2007;114(7):1241-1247.
FULL TEXT
|
ISI
| PUBMED
37. Gieser DK, Tracy Williams R, O’Connell W; et al. Costs and utilization of end-stage glaucoma patients receiving visual rehabilitation care: a US multisite retrospective study. J Glaucoma. 2006;15(5):419-425.
FULL TEXT
|
ISI
| PUBMED
38. Ellwein LB, Urato CJ. Use of eye care and associated charges among the Medicare population: 1991-1998. Arch Ophthalmol. 2002;120(6):804-811.
FREE FULL TEXT
39. Iskedjian M, Walker J, Vicente C; et al. Cost of glaucoma in Canada: analyses based on visual field and physician's assessment. J Glaucoma. 2003;12(6):456-462.
FULL TEXT
|
ISI
| PUBMED
40. Oostenbrink JB, Rutten-van Mölken MP, Sluyter-Opdenoordt TS. Resource use and costs of patients with glaucoma or ocular hypertension: a one-year study based on retrospective chart review in the Netherlands. J Glaucoma. 2001;10(3):184-191.
FULL TEXT
|
ISI
| PUBMED
41. Traverso CE, Walt JG, Kelly SP; et al. Direct costs of glaucoma and severity of disease: a multinational long term study of resource utilization in Europe. Br J Ophthalmol. 2005;89(10):1245-1249.
FREE FULL TEXT
42. Vicente C, Walker J, Buys Y, Einarson TR, Covert D, Iskedjian M. Association between mean intraocular pressure, disease stability and cost of treating glaucoma in Canada. Curr Med Res Opin. 2004;20(8):1245-1251.
FULL TEXT
|
ISI
| PUBMED
43. Wang JC, Chew PT. What is the direct cost of treatment of acute primary angle closure glaucoma? the Singapore model. Clin Experiment Ophthalmol. 2004;32(6):578-583.
FULL TEXT
|
ISI
| PUBMED
44. Kobelt-Nguyen G, Gerdtham UG, Alm A. Costs of treating primary open-angle glaucoma and ocular hypertension: a retrospective, observational two-year chart review of newly diagnosed patients in Sweden and the United States. J Glaucoma. 1998;7(2):95-104.
ISI
| PUBMED
45. Kobelt G, Jönsson L, Gerdtham U, Krieglstein GK. Direct costs of glaucoma management following initiation of medical therapy: a simulation model based on an observational study of glaucoma treatment in Germany. Graefes Arch Clin Exp Ophthalmol. 1998;236(11):811-821.
FULL TEXT
|
ISI
| PUBMED
46. Oostenbrink JB, Rutten-van Mölken MP, Opdenoordt TS. The treatment of newly diagnosed patients with glaucoma or with ocular hypertension in The Netherlands: an observational study of costs and initial treatment success based on retrospective chart review. Doc Ophthalmol. 1999;98(3):285-299.
FULL TEXT
|
ISI
| PUBMED
47. American Medical Association. International Classification of Diseases, 9th Revision, Clinical Modification. Vol 1-2. Chicago, IL: American Medical Association; 2001.48. American Academy of Ophthalmology. Primary open-angle glaucoma suspect preferred practice pattern. http://www.aao.org/education/library/ppp/poags_new.cfm. Accessed September 28, 2006.49. Centers for Medicare and Medicaid Services. Medicare coverage of skilled nursing facility care. http://www.medicare.gov/publications/pubs/pdf/snf.pdf. Accessed May 25, 2007.50. Centers for Medicare and Medicaid Services. January is National Glaucoma Awareness Month. http://www.medicarenhic.com/whats_new/current/glaucomamonth_0107.htm. Accessed May 30, 2007.51. Lave JR, Pashos CL, Anderson GF; et al. Costing medical care: using Medicare administrative data. Med Care. 1994;32(7)(suppl):JS77-JS89.
ISI
| PUBMED
52. Brandeis J, Pashos CL, Henning JM, Litwin MS. A nationwide charge comparison of the principal treatments for early stage prostate carcinoma. Cancer. 2000;89(8):1792-1799.
FULL TEXT
|
ISI
| PUBMED
53. Bureau of Labor Statistics, US Department of Labor. Annual change in the Consumer Price Index for all urban consumers, medical care, 1996-2005. http://stats.bls.gov/opub/ted/2006/jun/wk3/art02.txt. Accessed May 28, 2007.54. Bernardini J, Callen S, Fried L, Piraino B. Inter-rater reliability and annual rescoring of the Charlson comorbidity index. Adv Perit Dial. 2004;20:125-127.
PUBMED
55. Roos LL, Sharp SM, Cohen MM. Comparing clinical information with claims data: some similarities and differences. J Clin Epidemiol. 1991;44(9):881-888.
FULL TEXT
|
ISI
| PUBMED
56. Roos LL, Sharp SM, Cohen MM, Wajda A. Risk adjustment in claims-based research: the search for efficient approaches. J Clin Epidemiol. 1989;42(12):1193-1206.
FULL TEXT
|
ISI
| PUBMED
57. O'Connor GT, Plume SK, Olmstead EM; et al, Northern New England Cardiovascular Disease Study Group. A regional prospective study of in-hospital mortality associated with coronary artery bypass grafting. JAMA. 1991;266(6):803-809.
FREE FULL TEXT
58. Deyo RA, Cherkin DC, Ciol MA. Adapting a clinical comorbidity index for use with ICD-9-CM administrative databases. J Clin Epidemiol. 1992;45(6):613-619.
FULL TEXT
|
ISI
| PUBMED
59. Charlson ME, Pompei P, Ales KL, MacKenzie CR. A new method of classifying prognostic comorbidity in longitudinal studies: development and validation. J Chronic Dis. 1987;40(5):373-383.
FULL TEXT
|
ISI
| PUBMED
60. Dodd S, Bassi A, Bodger K, Williamson P. A comparison of multivariable regression models to analyze cost data. J Eval Clin Pract. 2006;12(1):76-86.
FULL TEXT
|
ISI
| PUBMED
61. Horowitz A, Reinhardt JP, Boerner K, Travis LA. The influence of health, social support quality, and rehabilitation on depression among disabled elders. Aging Ment Health. 2003;7(5):342-350.
FULL TEXT
|
ISI
| PUBMED
62. Reinhardt JP. Effects of positive and negative support received and provided on adaptation to chronic physical impairment. Appl Dev Sci. 2001;5(2):76-85.
FULL TEXT
63. Rovner BW, Zisselman PM, Schmuely-Dulitzki Y. Depression and disability in older people with impaired vision: a follow-up study. J Am Geriatr Soc. 1996;44(2):181-184.
ISI
| PUBMED
64. Zeiss AM, Lewinsohn PM, Rohde P, Seeley JR. Relationship of physical disease and functional impairment to depression in older people. Psychol Aging. 1996;11(4):572-581.
FULL TEXT
|
ISI
| PUBMED
65. Coleman AL, Morgenstern H. Use of insurance claims databases to evaluate the outcomes of ophthalmic surgery. Surv Ophthalmol. 1997;42(3):271-278.
FULL TEXT
|
ISI
| PUBMED
66. Mitchell JB, Bubolz T, Paul JE; et al. Using Medicare claims for outcomes research. Med Care. 1994;32(7)(suppl):JS38-JS51.
FULL TEXT
|
ISI
| PUBMED
SECTION EDITOR: PAUL P. LEE, MD
 CiteULike  Connotea  Del.icio.us  Digg  Reddit  Technorati  Twitter
What's this?
|
