A retrospective study on the impact of comorbid depression or anxiety on healthcare resource use and costs among diabetic neuropathy patients
© Boulanger et al; licensee BioMed Central Ltd. 2009
Received: 08 December 2008
Accepted: 30 June 2009
Published: 30 June 2009
Diabetic neuropathy (DN) is a common complication of diabetes that has significant economic burden, especially for patients with comorbid depression or anxiety. This study examines and quantifies factors associated with healthcare costs among patients diagnosed with diabetic neuropathy (DN) with or without a comorbid diagnosis of depression or anxiety (DA) using retrospective administrative claims data. No study has examined the differences in economic outcomes depending on the presence of comorbid DA disorders.
Over-age-18 individuals with 1+ diagnosis of DN in 2005 were selected. The first observed DN claim was considered the "index date." All individuals had a 12-month pre-index and follow-up period. For both under-age-65 commercially insured and over-age-65 individuals with employer-sponsored Medicare supplemental insurance, we constructed 2 subgroups for individuals with DA (DN-DA) or without (DN-only). Patients' clinical characteristics over pre-index period were compared. Multivariate regressions were performed to assess whether DN-DA patients had higher utilization of healthcare resources and costs than DN-only patients, controlling for demographic and clinical characteristics.
We identified 16,831 DN-only and 1,699 DN-DA patients in the Medicare supplemental cohort, as well as 17,205 and 3,105 in the commercially insured. DN-DA patients had higher prevalence of diabetes-related comorbidities for cardiovascular disease, cerebrovascular/peripheral vascular disease, nephropathy, obesity, and hypoglycemic events than DN-only patients (all p < 0.05). Controlling for differences in demographic and clinical characteristics, DN-DA patients had $9,235 (p < 0.05) higher total healthcare costs than patients with DN-only among those with Medicare supplemental coverage ($26,718 vs. $17,483), and $10,389 (p < 0.05) more total costs among commercially insured ($29,775 vs. $19,386). Factors associated with increased costs included insurance type, geographical region, diabetes-related comorbidities, and insulin therapy.
These findings indicate that the healthcare costs were significantly higher for DN patients with depression or anxiety relative to those without such comorbid disorders.
Diabetes mellitus is a chronic condition that has been estimated to affect over 20 million people or 7% of the total population in the U.S. in 2005 . Diabetic neuropathy (DN) is a common complication of diabetes, in which nerves are damaged as a result of hyperglycemia. Painful DN manifests itself as an electric, burning, or shooting sensation; however patients with DN can also be asymptomatic. Risk factors for DN include hyperglycemia, hyperlipidemia, high blood pressure, obesity, age of at least 40 years, and having diabetes for at least 25 years [2–4].
The economic burden of symptomatic and non-symptomatic DN is significant. The total annual direct costs of DN and its complications in the U.S. were $4.6–13.7 billion in 2001 . Patients with DN had significantly higher total medical costs than individuals with diabetes but no DN . It has been shown that more than one quarter of total direct costs for diabetes in the U.S. can be attributed to DN . The indirect costs of DN, including missed days of work and decreased productivity, are a considerable component of total costs . Recent research suggests that DN symptoms cause workers to lose approximately $3.65 billion per year in health-related lost productivity .
Compared to the general U.S. population, diabetic patients are twice as likely to be diagnosed with depression . Prior studies have estimated that 28% of DN patients have depression and 35% have moderate to severe anxiety [9, 10], and a more recent multi-center study reported that 59% of DN patients had either condition . The healthcare resource utilization and associated treatment costs for patients with diabetes comorbid with DN or depression are much higher than those without . However, little has been done to examine resource utilization and costs among DN patients, and no study has examined the differences in these outcomes depending on the presence of comorbid depression or anxiety disorders.
The aim of this study is to fill this gap by employing a retrospective cohort design using a large US administrative claims database to examine and quantify the economic impact of comorbid depression or anxiety disorders on healthcare resource utilization and associated costs for DN patients. Findings from this study can be incorporated into economic models of diabetes care and are relevant to inform healthcare providers of diabetic patients and policy makers interested in the economic impact of DN. Patients who were covered by commercial insurance (18–64 years of age) and patients over age 65 with employer-sponsored Medicare supplemental insurance were assessed separately, and trends were compared across the two populations. Multivariate regression analysis was undertaken to examine the effects of having comorbid depression or anxiety disorders on the likelihood and number of healthcare services, as well as on costs after controlling for differences in demographic and clinical characteristics.
The Thomson Medstat MarketScan Commercial Claims and Encounters and Medicare Supplemental databases (2004–2006) were used for the analysis for patients aged 18–64 and 65+, respectively. This database contains administrative claims and eligibility records for approximately 20 million patients in distinct sets of files for commercially insured (i.e., working age adults and their dependants) and Medicare supplemental insured individuals from approximately 45 large health plans geographically located in the United States. The databases include separate files for enrollment records, medical and pharmacy claims. The files are linkable based on an encrypted patient identification number. Enrollment records contain demographic information, including age, sex, and geographic region. Medical claims files include inpatient, outpatient, facility and services claims records. They report up to 15 International Classification of Diseases, 9th Revision, Clinical Modification (ICD-9-CM) codes for diagnoses and up to fifteen ICD-9-CM procedures codes, date of service, place of service, provider type, and plan and patient paid amounts. Pharmacy claims files provide information for each prescription with the National Drug Code (NDC), dispense dates, quantity and days supplied, and plan and patient paid amounts. Because data used in this study were purchased from a third party which had removed identifying information prior to its release, institutional review board (IRB) and similar approvals were neither needed nor sought.
Identification of Study Population
Medical problems that each individual encountered were identified based on ICD-9-CM codes associated with medical claims. A patient diagnosed with diabetes (ICD-9-CM: 250.xx) was included in the study if the patient had at least one DN claim (250.6x and/or 357.2) [12–14] in the calendar year of 2005, and the first observed DN claim was set as the index date. Patients may or may not have a DN claim in the 12 months prior to the index date. Furthermore, included patients were required to be at least 18 years of age as of the index date and to have continuous health plan enrollment from 12 months prior to the index date (i.e. pre-index period) through 12 months following the index date (i.e. follow-up period).
We separately assessed study patients who were covered by commercial insurance (working age adults 18–64 years of age) and those of age 65 and above with employer-sponsored Medicare supplemental insurance. For each analysis, two study cohorts were identified based on the presence of 1+ medical claim for depression (ICD-9-CM: 296.2, 296.3, 300.4, 309.1, 311.0) or for anxiety disorders (ICD-9-CM: 300.0x, 300.2x, 300.3, 309.81) either in the pre-index period or in the post-index period. DN patients with depression and/or anxiety made up the "DN-DA" cohort and those without such disorders constituted the "DN-only" cohort.
Patient demographic characteristics in the pre-index period included age, sex, and geographic regions (i.e. northeast, north central, west, south). Dichotomous variables (1 = Yes, 0 = No) were created to measure clinical characteristics over the 12 month pre-index period that included: 1) use of insulin only, use of oral anti-diabetic drugs (OADs) only, or use of insulin and OADs identified based on the NDC codes in pharmacy claims; 2) the presence of diabetes-related co-morbidities and complications identified based on ICD-9-CM codes in medical claims such as:
Cardiovascular disease (CVD; ICD-9-CM: 390-398.xx, 401.x-403.xx, 404.1, 404.9, 405.xx, 410.xx-417.x, 420.xx-429.xx),
Cerebrovascular/peripheral vascular disease (CPVD; ICD-9-CM: 430-437.x, 440.xx-444.xx, 447.x-454.x, 457.x-459.xx, 785.4),
Diabetes related infections (ICD-9-CM: 038.xx, 790.7),
Other metabolic diseases (ICD-9-CM: 251.3, 270.3, 276.xx),
Nephropathy (ICD-9-CM: 580.9, 581.81, 581.9, 582.9, 583.xx, 588.8x, 593.9),
Obesity (ICD-9-CM: 278.xx),
Retinopathy (ICD-9-CM: 362.0x-362.2x, 362.41, 363.31, 365.44, 366.41),
Hypoglycemic events (ICD-9-CM: 250.8x, 251.0–251.2),
Skin problems (ICD-9-CM: 680.x-686.xx, 707.xx), and
Leg amputation (ICD-9-CM: 278.80–278.82, 278.84, 278.86);
and 3) being hospitalized. Overall and diabetes-related healthcare expenditures (in 2006 dollars) in the pre-index period were also calculated. Diabetes-related expenditures were estimated based on the medical service claims with diabetes diagnoses (ICD-9-CM: 250.xx) coded anywhere in the diagnosis file and medication costs recorded in the pharmacy claims. Diabetes-related medication costs were estimated based on prescription of insulin and OADs.
All-cause healthcare resource utilization and associated direct costs in the follow-up period were quantified for major service components. Specifically, the percentage of patients with any medical services and the number of services for each patient were calculated for components of healthcare resource utilization including hospitalization, skilled nursing facilities (SNF), emergency room (ER), hospital outpatient, home health, and outpatient physician office visits. Similarly, DN-related healthcare utilization and costs were extracted based on the medical service claims with such diagnoses coded anywhere in the diagnosis file. DN-related medication costs were estimated based on prescriptions of pharmacologic therapies recommended for DN treatment : 1) tricyclic antidepressants, 2) venlafaxine, 3) duloxetine, 4) pregabalin, 5) gabapentin, and 6) opioids (e.g., tramadol, oxycodone, morphine, hydrocodone, methadone, levorphanol). All costs included deductibles, copayments, coinsurance, and coordination-of-benefits payments recorded in the databases, and all costs were adjusted to 2006 U.S. dollars using the medical component of the consumer price index.
Descriptive statistics were summarized. Percentages were reported for categorical variables and cohort differences were analyzed using Cochran-Mantel-Haenszel tests. For continuous variables, mean and standard deviations were reported and student t-tests were used to analyze cohort differences. Logistic regressions were employed to analyze effects of comorbid depression or anxiety disorders on the likelihood of resource use. Ordinary least squares (OLS) regressions were used to assess the association between comorbid disorders and the number of services, whereas generalized least squares models (assuming a gamma distribution specification) were employed for healthcare costs. We conducted our analyses for commercially-insured and Medicare-insured populations separately because the reimbursed amount by Medicare is generally lower than the commercial insurance companies. Explanatory variables in all regressions included age groups, male gender, insurance type, geographic regions, each of the diabetes-related complications and comorbidities listed above, and pre-index use of insulin or OADs. All analyses were conducted using SAS version 9.1 (SAS Institute, Inc., Cary, North Carolina), and findings of p values of < 0.05 were considered statistically significant.
About 50% of all patients diagnosed with diabetes in 2005 also had at least 1 DN diagnosis (Figure 1), which is similar to the rate summarized in a recent review . The DN prevalence rate was slightly higher among patients with Medicare supplemental insurance than those with commercial coverage. Of all DN patients identified in 2005, approximately 4% were diagnosed with depression and/or anxiety disorders, and the prevalence rate was higher for females (5.1%) than for males (3.4%) (data not shown). About 3.1% of DN patients with Medicare supplemental insurance had comorbid depression or anxiety disorders compared with 5.4% among patients with commercial coverage (data not shown).
Pre-index demographic characteristics by insurance type and cohort
Medicare supplemental insurance
Age (mean, SD)
Plan types (%)**
pre-index clinical characteristics by insurance type and cohort
Medicare supplemental insurance
Diabetes related complications and comorbidities (%)
Cardiovascular disease (CVD)
Cerebro/peripheral vascular disease (CPVD)
Other metabolic diseases
Infections related to diabetes
Anti-diabetic treatment (%)
Oral antidiabetic agent only
Insulin with oral anti-diabetic therapy
Resource use and costs
% Patients with any hospitalization
Total diabetes-related healthcare expenditures$ (mean, SD)
Total healthcare expenditures$ (mean, SD)
Compared with the DN-only cohort, a significantly higher proportion of DN-DA patients were prescribed insulin for both the Medicare supplemental insured (40% vs. 36%, p < 0.05) and the commercially insured (50% vs. 45%, p < 0.05). The percentage of patients with any inpatient admission was significantly higher for the DN-DA cohort compared to the DN-only cohort for both populations (46% vs. 28% among Medicare supplemental insured, 36% vs. 20% among commercially insured, both p < 0.05). The overall and diabetes-related healthcare expenditures for the Medicare supplemental insured patients were approximately $10,000 and $3,500 higher (both p < 0.05), respectively, for the DN-DA cohort. For commercially insured patients, the difference in the overall healthcare expenditures of DN-DA cohort over DN-only cohort was approximately $12,000 (p < 0.05), while the difference in diabetes-related healthcare expenditures was about $4,500 (p < 0.05).
Resource use in post-index 12 months by insurance type and cohort
Medicare supplemental insurance
(95% confidence interval) or adjusted mean difference
(95% confidence interval) or adjusted mean difference
Inpatient hospital admissions
% patients with any admission
2.0 (1.8, 2.2)1
2.0 (1.8, 2.2)1
Number of hospitalized days (mean, SD)
% patients with any admission
2.9 (2.6, 3.3)1
2.0 (1.6, 2.5)1
Number of admissions (mean, SD)
% patients with any ER visit
2.1 (1.9, 2.3)1
1.8 (1.6, 2.0)1
% patients with any hospital outpatient visit
1.3 (1.1, 1.5)1
1.5 (1.3, 1.6)1
Outpatient physician office visits
% patients with any visit
0.7 (0.4, 0.95)1
1.6 (0.9, 2.9)1
Number of visits (mean, SD)
Home health care visits
% patients with any visit
1.0 (0.9, 1.1)1
1.3 (1.2, 1.4)1
Number of visits (mean, SD)
Compared with the commercially insured, a higher proportion of DN-DA (54% vs. 44%) and DN-only patients (35% vs. 26%) with Medicare supplemental insurance were hospitalized (Table 3). For both the DN-only and DN-DA cohorts, the population with Medicare supplemental insurance also had higher utilization rates of SNF admissions as well as home health care visits. Emergency room, hospital outpatient, and physician office encounters were similar between both populations.
Healthcare costs in post-index 12 months by insurance type and cohort
Medicare supplemental insurance
Adjusted cost difference1
Adjusted cost difference1
Overall healthcare expenditures
Skilled nursing facility
Outpatient physician office
Home health care
DN-related healthcare expenditures (mean, SD):
Using the administrative claims from the Thomson MedStat MarketScan databases, this study was the first to examine the impact of comorbid depression and anxiety disorders on healthcare resource use and costs among DN patients separately for the Medicare supplemental insured patients and the commercially insured. Not only were DN patients with depression or anxiety disorders more likely to have encounters for inpatient hospitalization, ER, SNF, and outpatient hospital services than those without such disorders, they also had longer hospital days, more SNF admissions, and more ER and outpatient hospital visits. While the likelihood of using outpatient physician office services was not different between DN-DA and DN-only cohorts, the former was associated with a significantly higher number of the services over the one year follow-up period. Controlling for differences in demographic and clinical characteristics, patients in the DN-DA cohort had significantly higher total costs and higher costs for each of the components than those in the DN-only cohort. For both cohorts in each population, inpatient hospital costs constituted the largest proportion of overall costs. Outpatient prescriptions and hospital outpatient costs were ranked as the second and third highest cost items for the Medicare supplemental insured DN patients; however, they contributed to similar proportion of the total costs for the commercially insured sample.
For both the commercially insured and the Medicare supplemental insured DN patients, the prevalence rates of all other diabetes-related complications and comorbidities except retinopathy were higher among those in the DN-DA cohort than those in the DA-only cohort. Specifically, the biggest differences in prevalence rates between those cohorts were in CVD, CPVD, and other metabolic diseases. Although it is unclear about the causality between depression/anxiety and other diabetes-related complications and comorbidities among DN patients, special attention is needed to monitor other diabetes-related complications and/or comorbidities when managing DN patients comorbid with depression and/or anxiety.
This study found lower utilization rates of many components of healthcare services among the commercially insured patients compared with those with Medicare supplemental insurance. This is especially true for hospital and SNF admissions, as well as home health care visits. However, healthcare costs were higher among the commercially insured patients. One possible explanation for this finding is that the various resource-based payment systems currently employed by Medicare have made the unit cost per healthcare service less expensive than similar services covered by commercial insurance. Despite of the difference between various payment systems, DN patients with depression or anxiety disorders had over $9,000 more total costs than those without such disorders in both populations after controlling for differences in patient demographic and clinical characteristics.
The actual direct costs associated with DN treatment could be much higher than what was captured in the study since DN is under-reported to physicians and subsequently under-treated [17, 18]. Older DN patients could be less likely to seek treatment for depression or anxiety disorders than younger patients. Previous research has also found a high rate of comorbid anxiety disorders among patients with depression . Several intervention trials have found that proper treatment for comorbid depression among diabetes patients was associated with lower medical costs [20–22]. Therefore, it is important to recognize that the need for treatment of comorbid depression or anxiety disorders is considerable, particularly among patients with Medicare supplemental insurance, who were also associated with significantly higher levels of resource use compared to the commercially insured patients.
Several limitations need to be noted when interpreting results for this study. Firstly, a selection bias could exist where DN patients with comorbid depression or anxiety disorders had unobserved heterogeneity that correlated with levels of disease severities and study outcomes. Despite the best efforts to capture patient heterogeneity by demographic and clinical characteristics over pre-index period, the study was unable to control for unobserved confounding characteristics using a retrospective study design. Secondly, as patients' actual medical records could not be accessed for the study, the identification of DN, depression or anxiety disorders and other diabetes related complications and comorbidities were based on the ICD-9-CM diagnosis codes in medical claims. This information could be subject to clerical errors or other reporting errors, leading to potentially inaccurate identification of patients' conditions. Additionally, we only required 1 DN diagnosis to identify the DN cohort. We might misclassify some of non-DN patients to the DN cohort due to coding errors. Similarly, the study was unable to directly measure the severity of DN or depression or anxiety disorders, which was found to be a significant predictor of healthcare utilization and costs  and to be associated with decreased quality of life outcomes . Thirdly, our study did not assess other pain related conditions between the study cohorts. However, we are not aware of any published studies that report differences in pain-related conditions within subgroups of DN patients. Fourthly, the study calculated direct treatment costs based on plan payment and patient co-payment for each service, and therefore did not capture other indirect costs incurred by patients such as lost productivity and opportunity costs associated with time lost seeking treatment. Also, as over-the-counter medications were not captured in the administrative claims databases, the study could be underestimating the pharmacy utilization and thus associated costs. Furthermore, we may overestimate the diabetes- and DN-related costs as we used diabetes or DN diagnoses recorded anywhere in the claims to assign such costs. We also lack of information regarding the health plan-specific benefit structure, which may influence healthcare utilization. Finally, the results presented here could only be taken as associations instead of causations. While the study found that DN patients with comorbid depression or anxiety disorders used more resources and incurred higher costs for treatment, it cannot be established whether such increased resource use and costs were a result of comorbid disorders.
This study assessed healthcare resource use and costs between patients diagnosed with DN with and without diagnosed depression or anxiety disorders among those aged 18–64 commercially insured and those of age 65 and above with employer-sponsored Medicare supplemental insurance. We found significantly higher healthcare resource utilization and costs among DN patients who had comorbid depression or anxiety disorders versus those without such diagnoses, even after controlling for demographic and clinical differences. Properly treating these comorbid depression or anxiety disorders among DN patients may have an impact on the economic burden of DN.
depression or anxiety
International Classification of Diseases, 9th Revision, Clinical Modification
oral anti-diabetic drugs
Cerebrovascular/peripheral vascular disease
skilled nursing facilities
ordinary least squares.
This project was funded by Eli Lilly and Company. However, the sponsor had no role in the design, methods, data collection, analysis, or preparation of the manuscript. The interpretation and reporting of these data are the sole responsibility of the authors.
- Centers for Disease Control and Prevention (CDC). What is Diabetes?. 2006, [http://www.cdc.gov/diabetes/pubs/general.htm#what]
- National Institute of Diabetes and Digestive and Kidney Diseases (NIDDK). Diabetic Neuropathies: The Nerve Damage of Diabetes. NIH Publication No. 02-3185. 2002, [http://diabetes.niddk.nih.gov/dm/pubs/neuropathies/index.htm]
- Adler AI, Boyko EJ, Ahroni JH, Stensel V, Forsberg RC, Smith DG: Risk factors for diabetic peripheral sensory neuropathy: results of the Seattle Prospective Diabetic Foot Study. Diabetes Care. 1997, 20: 1162-1167. 10.2337/diacare.20.7.1162.View ArticlePubMedGoogle Scholar
- The Diabetes Control and Complications Trial Research Group: The effect of intensive insulin treatment of diabetes on the development and progression of long-term complications in insulin-dependent diabetes mellitus. N Engl J Med. 1993, 329: 977-986. 10.1056/NEJM199309303291401.View ArticleGoogle Scholar
- Gordois A, Scuffham P, Shearer A, Oglesby A, Tobian JA: The health care costs of diabetic peripheral neuropathy in the US. Diabetes Care. 2003, 26: 1790-1795. 10.2337/diacare.26.6.1790.View ArticlePubMedGoogle Scholar
- Le TK, Able SL, Lage MJ: Resource use among patients with diabetes, diabetic neuropathy, or diabetes with depression. Cost Eff Resour Alloc. 2006, 4: 18-10.1186/1478-7547-4-18.View ArticlePubMedPubMed CentralGoogle Scholar
- Stewart WF, Ricci JA, Chee E, Hirsch AG, Brandenburg NA: Lost productive time and costs due to diabetes and diabetic neuropathic pain in the US workforce. J Occup Environ Med. 2007, 49 (6): 672-679. 10.1097/JOM.0b013e318065b83a.View ArticlePubMedGoogle Scholar
- Egede LE, Zheng D, Simpson K: Comorbid depression is associated with increased health care use and expenditures in individuals with diabetes. Diabetes Care. 2002, 25 (3): 464-70. 10.2337/diacare.25.3.464.View ArticlePubMedGoogle Scholar
- Gore M, Brandenburg N, Dukes E, Hoffman DL, Tai KS, Stacey B: Pain severity in diabetic peripheral neuropathy impacts patient functioning, symptoms levels of anxiety and depression, and sleep. J Pain Symptom Manage. 2005, 30 (4): 374-385. 10.1016/j.jpainsymman.2005.04.009.View ArticlePubMedGoogle Scholar
- Gore M, Brandenberg N, Hoffman D, Tai K: Pain severity affect perceived health status in patients with diabetic peripheral neuropathy [abstract]. Value Health. 2004, 7: 344.View ArticleGoogle Scholar
- Gore M, Brandenburg NA, Hoffman DL, Tai KS, Stacey B: Burden of Illness in Painful Diabetic Peripheral Neuropathy: The Patients' Perspectives. J Pain. 2006, 7: 892-900. 10.1016/j.jpain.2006.04.013.View ArticlePubMedGoogle Scholar
- Zhao Y, Ye W, Boye KS, Holcombe JH, Hall JA, Swindle R: Prevalence of Other Diabetes-Associated Complications and Co-morbidities and Its Impact on Healthcare Charges among Patients with Diabetic Neuropathy. J Diabetes Complications. 2008.Google Scholar
- Zhao Y, Ye W, Le TK, Boye KS, Holcombe JH, Swindle R: Comparing Clinical and Economic Characteristics between Commercially-Insured Patients with Diabetic Neuropathy with Demographically-Matched Diabetic Controls. Curr Med Res Opin. 2009, 25: 585-597. 10.1185/03007990802706289.View ArticlePubMedGoogle Scholar
- Zhao Y, Ye W, Boye KS, Holcombe JH, Swindle R: Healthcare Charges and Utilization Associated with Diabetic Neuropathy: Impact of Type 1 Diabetes and Presence of Other Diabetes-Related Complications and Comorbidities. Diabet Med. 2009, 26: 61-69. 10.1111/j.1464-5491.2008.02616.x.View ArticlePubMedGoogle Scholar
- Argoff CE, Backonja MM, Belgrade MJ, Bennett GJ, Clark MR, Cole BE, Fishbain DA, Irving GA, McCarberg BH, McLean MJ: Consensus guidelines: treatment planning and options. Diabetic peripheral neuropathic pain. Mayo Clin Proc. 2006, 81: S12-S25. 10.4065/81.1.12.View ArticlePubMedGoogle Scholar
- Sadosky A, McDermott AM, Brandenburg NA, Strauss M: A Review of the Epidemiology of Painful Diabetic Peripheral Neuropathy, Postherpetic Neuralogia, and Less Commonly Studied Neuropathic Pain Conditions. Pain Pract. 2008, 8: 45-56. 10.1111/j.1533-2500.2007.00164.x.View ArticlePubMedGoogle Scholar
- Daousi C, Benbow SJ, Woodward A, MacFarlane IA: The natural history of chronic painful peripheral neuropathy in a community diabetes population. Diabetic Medicine. 2006, 23: 1021-1024. 10.1111/j.1464-5491.2006.01904.x.View ArticlePubMedGoogle Scholar
- Berger A, Dukes EM, Oster G: Clinical characteristics and economic costs of patients with painful neuropathic disorders. J Pain. 2004, 5: 143-149. 10.1016/j.jpain.2003.12.004.View ArticlePubMedGoogle Scholar
- Lenze EJ, Mulsant BH, Shear MK, Schulberg HC, Dew MA, Begley AE, Pollock BG, Reynolds CF: Comorbid anxiety disorders in depressed elderly patients. Am J Psychiatry. 2000, 157 (5): 722-728. 10.1176/appi.ajp.157.5.722.View ArticlePubMedGoogle Scholar
- Katon W, Unutzer J, Fan MY, Williams JW, Schoenbaum M, Lin EH, Hunkeler EM: Cost-effectiveness and Net Benefit of Enhanced Treatment of Depression for Older Adults with Diabetes and Depression. Diabetes Care. 2006, 29: 265-270. 10.2337/diacare.29.02.06.dc05-1572.View ArticlePubMedGoogle Scholar
- Simon GE, Katon WJ, Lin EH, Rutter C, Manning WG, Von Korff M, Ciechanowski P, Ludman EJ, Yang BA: Cost-effectiveness of Systematic Depression Treatment among People with Diabetes Mellitus. Arch Gen Psychiatry. 2007, 674: 65-72. 10.1001/archpsyc.64.1.65.View ArticleGoogle Scholar
- Katon WJ, Lin EH, Russo JE, Ludman E, Von Korff M, Ciechanowski PS: Long-term Effects on Medical Costs of Improving Depression Outcomes in Patients with Depression and Diabetes. Diabetes Care. 2008, 31: 1155-1159. 10.2337/dc08-0032.View ArticlePubMedGoogle Scholar
- Currie CJ, Poole CD, Woehl A, Morgan CL, Cawley S, Rousculp MD, Covington MT, Peters JR: The financial costs of healthcare treatment for people with Type 1 or Type 2 diabetes in the UK with particular reference to differing severity of peripheral neuropathy. Diabetic Medicine. 2007, 24: 187-194. 10.1111/j.1464-5491.2006.02057.x.View ArticlePubMedGoogle Scholar
- Currie CJ, Poole CD, Woehl A, Morgan CL, Cawley S, Rousculp MD, Covington MT, Peters JR: The health-related utility and health-related quality of life of hospital-treated subjects with type 1 or type 2 diabetes with particular reference to differing severity of peripheral neuropathy. Diabetologia. 2006, 49: 2272-2280. 10.1007/s00125-006-0380-7.View ArticlePubMedGoogle Scholar
- The pre-publication history for this paper can be accessed here:http://www.biomedcentral.com/1472-6963/9/111/prepub
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