Cited by 894Chronic Disease Management StrategiesHealth Systems, Economic Evaluations, Quality of LifeHealthcare Policy and Management

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The Charlson comorbidity index is adapted to predict costs of chronic disease in primary care patients

Charlson, Mary E., Charlson, Robert E., Peterson, Janey C., Marinopoulos, Spyridon S., Briggs, William M., Hollenberg, James P.·2008·Journal of Clinical Epidemiology

DOI 10.1016/j.jclinepi.2008.01.006

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Abstract

Objective (1) To determine chronic illness costs for large cohort of primary care patients, (2) to develop prospective model predicting total costs over one year, using demographic and clinical information including widely used comorbidity index.Study design and setting Data including diagnostic, medication, and resource utilization were obtained for 5,861 patients from practice-based computer system over a 1-year period beginning December 1, 1993, for retrospective analysis. Hospital cost data were obtained from hospital cost accounting system.Results Average annual per patient cost was $2,655. Older patients and those with Medicare or Medicaid had higher costs. Hospital costs were $1,558, accounting for 58.7% of total costs. In the predictive model, individuals with higher comorbidity incurred exponentially higher annual costs, from $4,317 with comorbidity score of two, to $5,986 with score of three, to $13,326 with scores greater than seven. To use an adapted comorbidity index to predict total yearly costs, four conditions should be added to the index: hypertension, depression, and use of warfarin with a weight of one, skin ulcers/cellulitis, a weight of two.Conclusion The adapted comorbidity index can be used to predict resource utilization. Predictive models may help to identify targets for reducing high costs, by prospectively identifying those at high risk.

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Physical health disparities and severe mental illness: A longitudinal comparative cohort study using hospital data in Northern Ireland
McCarter, R. V., Rosato, M., Thampi, A., Barr, R. S., & Leavey, G. (2023) · European Psychiatry · doi:10.1192/j.eurpsy.2023.2441 · Cited by 8
Effect of preoperative hospital stay on surgical site infection in Chinese cranial neurosurgery
Yang, L., Yi, F., Xiong, Z., Yang, H., & Zeng, Y. (2023) · BMC Neurology · doi:10.1186/s12883-023-03431-z · Cited by 9
“Preoperative variables included BMI, ASA (II, III, IV), type of surgery (tumor 1, vascular 2, others 3), and Charlson comorbidity index(CCI) ( 0, 1, 2, 3) [20, 21].”
Background
Predictors of Organ Damage in Systemic Lupus Erythematosus in the Asia Pacific Region: A Systematic Review
Ramnarain, A., Liam, C., Milea, D., Morand, E. F., Kent, J. R., & Kandane‐Rathnayake, R. (2024) · Arthritis Care & Research · doi:10.1002/acr.25291 · Cited by 9
“56 In a study of 502 patients by Kim et al, a higher CCI score was predictive of organ damage at study enrollment in SLE.”
Background
Health Fluctuations in Dementia and its Impact on the Assessment of Health-Related Quality of Life Using the EQ-5D-5L
Michalowsky, B., Engel, L., Buchholz, M., Weber, N., Kohlmann, T., & Xie, F. (2024) · Value in Health · doi:10.1016/j.jval.2024.04.010 · Cited by 9
Effect of dietary live microbe intake on the prevalence and mortality risks of depression and suicidal ideation in adults: Evidence from a nationwide population-based study
Chen, M., Huang, H., Jiang, Q., & Wu, Y. (2024) · Journal of Affective Disorders · doi:10.1016/j.jad.2024.09.127 · Cited by 9
Integrated environmental and clinical surveillance for the prevention of acute respiratory infections (ARIs) in indoor environments and vulnerable communities (Stell-ARI): Protocol
Carducci, A., Arzilli, G., Atomsa, N. T., Lauretani, G., Verani, M., Pistelli, F., Tavoschi, L., Federigi, I., Fornili, M., Petri, D., et al. (2024) · PLoS ONE · doi:10.1371/journal.pone.0309111 · Cited by 9
The Impact of Home-Based Primary Care on Outcomes Among Older Adults in South Korea
Choi, J. W., & Yoo, A. J. (2023) · Journal of the American Medical Directors Association · doi:10.1016/j.jamda.2023.03.009 · Cited by 9
Real-World Epidemiology, Treatment Patterns, and Disease Burden of Chronic Hepatitis B and HDV Co-Infection in South Korea
Cho, Y., Park, S., Park, S., Choi, W., Kim, B., & Han, H. (2023) · Infectious Diseases and Therapy · doi:10.1007/s40121-023-00860-8 · Cited by 9
“The Charlson comorbidity index (CCI) score, utilized with administrative databases based on the presence of 17 comorbidities and their severity was determined; the higher the score, the greater the disease burden [19].”
Method
Real-World Investigation of Eosinophilic-Associated Disease Overlap (REVEAL): Analysis of a US Claims Database
Brăilean, A., Kwiatek, J., Kielar, D., Katial, R. K., Wang, X., Xu, X., Kim, Y. J., Stokes, M., & Stirnadel-Farrant, H. A. (2023) · Allergy Asthma and Immunology Research · doi:10.4168/aair.2023.15.5.580 · Cited by 9
Ceft-to-Ceft Study: Real-Life Experience with Ceftaroline and Ceftobiprole in Treatment of the Principal Infectious Syndromes in a Spanish Multicenter Hospital Cohort
Arnés-García, D., Robles, I., Parra, J. C., SALVADOR, M. C., Rodríguez, C. H., Gisbert, L., & Hidalgo-Tenorio, C. (2023) · Antibiotics · doi:10.3390/antibiotics12121692 · Cited by 9
“The age-corrected Charlson index was calculated for each patient [42].”
Method
Clinical and economic characteristics of hip fracture patients with and without muscle atrophy/weakness in the United States
Zhao, Y., Chen, S.-Y., Lee, Y.-C., & Wu, N. (2013) · Archives of Osteoporosis · doi:10.1007/s11657-013-0127-2 · Cited by 9
“In both the Commercial and Medicare populations, the pre- and post-MAW cohorts had significantly higher CCI scores and a significantly longer stay for the index hip fracture hospitalization.”
MethodInfluential
Achievement of Adequate Glycemic Control in Patients With Type 2 Diabetes and Comorbid Mental Health Conditions Treated in a Primary Care Setting
Brown, K. M., Fortenberry, K. T., Gren, L. H., Gunning, K. M., & McAdam‐Marx, C. (2017) · Diabetes Spectrum · doi:10.2337/ds16-0038 · Cited by 9
“Additional clinical characteristics included BMI, systolic and diastolic blood pressure, triglycerides, LDL cholesterol, HDL cholesterol, and overall comorbidity measured by the Charlson Comorbidity Index (25).”
Method
Longitudinal changes in comorbidity patterns over time in relation to mortality in older Korean adults
Kim, J., Rhee, Y., & Lee, Y. (2018) · Archives of Gerontology and Geriatrics · doi:10.1016/j.archger.2018.08.004 · Cited by 9
The Impact of Intestinal Complications on Health Care Costs Among Patients With Inflammatory Bowel Disease Treated With Anti-Tumor Necrosis Factor Therapies
Rubin, D. T., Griffith, J. M., Zhang, Q., Hepp, Z., & Keshishian, A. V. (2020) · Inflammatory Bowel Diseases · doi:10.1093/ibd/izaa270 · Cited by 9
Comparison of Healthcare Costs Associated With Patients Receiving Traditional Negative Pressure Wound Therapies in the Post-Acute Setting
Law, A. L., Krebs, B., Karnik, B., & Griffin, L. P. (2020) · Cureus · doi:10.7759/cureus.11790 · Cited by 9
“The Charlson comorbidity score was computed for the six-month pre-index period [20].”
Method
Out of reach? Correlates of cervical cancer underscreening in women with varying levels of healthcare interactions in a United States integrated delivery system
Malone, C., Buist, D. S. M., Tiro, J. A., Barlow, W. E., Gao, H., Lin, J. W., & Winer, R. L. (2020) · Preventive Medicine · doi:10.1016/j.ypmed.2020.106410 · Cited by 10
“[17] In this study and others, comorbidities have been associated with higher use of health services overall,[68] but lower use of cancer screening, including Pap screening.”
Background
Microbiota-Based Live Biotherapeutic RBX2660 for the Reduction of Recurrent Clostridioides difficile Infection in Older Adults With Underlying Comorbidities
Tillotson, G., Archbald‐Pannone, L. R., Johnson, S., Ng, S., Ando, M., Harvey, A., Bancke, L. L., & Feuerstadt, P. (2022) · Open Forum Infectious Diseases · doi:10.1093/ofid/ofac703 · Cited by 9
“Older adults (65–74 years and ≥75 years of age) were categorized using the age-adjusted CCI, a commonly used index that incorporates a subset of 16 conditions and participant age to estimate 10-year survival based on comorbidity burden [22, 23].”
Method
Patient Factors Associated With Use of Adult Primary Care and Virtual Visits During the COVID-19 Pandemic
Ritzwoller, D. P., Goodrich, G. K., Tavel, H. M., Odelberg, M. R., Davis, T. L., Gander, J. C., McCracken, C., Weinfield, N. S., & Roblin, D. W. (2023) · Medical Care · doi:10.1097/mlr.0000000000001792 · Cited by 9
Management, prognosis and predictors of unfavourable outcomes in patients newly hospitalized for transient ischemic attack: a real-world investigation from Italy
Corrao, G., Rea, F., Merlino, L. G., Mazzola, P., Annoni, F., & Annoni, G. (2017) · BMC Neurology · doi:10.1186/s12883-017-0796-3 · Cited by 9
“Gender, age, nationality (Italian born or migrant), and the Charlson comorbidity index score [19] calculated by using the diagnostic information available from inpatient charts in the five-year period prior the index date, were recorded at baseline for each study and reference cohort member.”
Method
Antidepressants and the risk of arrhythmia in elderly affected by a previous cardiovascular disease: a real-life investigation from Italy
on behalf of the Italian Group for Appropriate Drug prescription in the Elderly (I-GrADE), Biffi, A., Rea, F., Scotti, L., Mugelli, A., Lucenteforte, E., Bettiol, A., Chinellato, A., Onder, G., Vitale, C., et al. (2017) · European Journal of Clinical Pharmacology · doi:10.1007/s00228-017-2352-x · Cited by 9
Healthcare Costs of Smokers Using Varenicline Versus Nicotine-Replacement Therapy Patch in the United States: Evidence from Real-World Practice
Lee, L. J., Li, Q., Bruno, M., Emir, B., Murphy, B., Shah, S., Reynolds, M. W., Marchant, N., & Park, P. W. (2018) · Advances in Therapy · doi:10.1007/s12325-018-0858-y · Cited by 10
Triage and flow management in sepsis
Pires, H. H. G., Neves, F. F., & Pazin‐Filho, A. (2019) · International Journal of Emergency Medicine · doi:10.1186/s12245-019-0252-9 · Cited by 10
Timing of do-not-resuscitate orders and health care utilization near the end of life in cancer patients: a retrospective cohort study
Cui, P., Ping, Z., Wang, P., Bie, W., Yeh, C. H., Gao, X., Chen, Y., Dong, S., & Chen, C. (2020) · Supportive Care in Cancer · doi:10.1007/s00520-020-05672-x · Cited by 9
The economic impact of symptomatic menopause among low-socioeconomic women in the United States
Keshishian, A. V., Wang, Y., Xie, L., & Başer, O. (2015) · Expert Review of Pharmacoeconomics & Outcomes Research · doi:10.1586/14737167.2015.1073589 · Cited by 8
“Average pre-index Charlson Comorbidity Index scores were calculated for both cohorts [27].”
Method
Extraarticular manifestations of juvenile idiopathic arthritis and their impact on health-related quality of life
Tharwat, S., Nassar, M. K., Salem, K. M., & Nassar, M. K. (2024) · Clinical Rheumatology · doi:10.1007/s10067-024-07008-0 · Cited by 8
“In the context of HRQoL, comorbidity has been identified as a significant element that differentiates between the different degrees of functioning of individuals [44].”
Severe Polypharmacy Increases Risk of Hospitalization Among Older Adults With Inflammatory Bowel Disease
Drittel, D., Schreiber-Stainthorp, W., Delau, O., Gurunathan, S. V., Chodosh, J., Segev, D. L., McAdams‐DeMarco, M., Katz, S., Dodson, J. A., Shaukat, A., et al. (2024) · The American Journal of Gastroenterology · doi:10.14309/ajg.0000000000003036 · Cited by 8
Nationwide implementation of the international multidisciplinary best-practice for locally advanced pancreatic cancer (PREOPANC-4): study protocol
Stoop, T. F., Seelen, L. W. F., Land, F. R. V. ‘., der Hout, A. C. A. V., Scheepens, J. C. M., Ali, M., Stiggelbout, A. M., van der Kolk, B. M., Bonsing, B. A., Lips, D. J., et al. (2025) · BMC Cancer · doi:10.1186/s12885-025-13554-w · Cited by 8
“Patient performance and comorbidity status will be defined following the Eastern Cooperative Oncology Group (ECOG) classification, American Society for Anesthesiologists (ASA), and the age-adjusted Charlson Comorbidity Index (CCI) [61–63].”
A population-based study of the humanistic burden among cancer patients in Japan
Ohno, S., Chen, Y., Sakamaki, H., Matsumaru, N., & Tsukamoto, K. (2019) · Journal of Medical Economics · doi:10.1080/13696998.2019.1707213 · Cited by 9
Predictors of the Development of Mental Disorders in Hospitalized COVID-19 Patients without Previous Psychiatric History: A Single-Center Retrospective Study in South Korea
Kim, J., Seo, Y. E., Sung, H. K., Park, H. Y., Han, M. H., & Lee, S. H. (2022) · International Journal of Environmental Research and Public Health · doi:10.3390/ijerph19031092 · Cited by 9
“003) including diabetes, prior myocardial infarction, mild liver disease, and acquired immune-deficiency syndrome [22].”
Background
Characteristics, treatment patterns, health care resource utilization and costs in patients with bullous pemphigoid: A retrospective analysis of US health insurance claims data
Stirnadel-Farrant, H. A., Xu, X. P., Kwiatek, J., Jain, P., Meyers, J., Candrilli, S. D., Mines, D. I., & Datto, C. J. (2023) · JAAD International · doi:10.1016/j.jdin.2023.04.014 · Cited by 8
Impact of antiepileptic-drug treatment burden on health-care-resource utilization and costs
Rajagopalan, K., Candrilli, S. D., & Ajmera, M. (2018) · ClinicoEconomics and Outcomes Research · doi:10.2147/ceor.s180913 · Cited by 8
“Additional preindex independent variables included “comorbidity burden”, measured using Charlson Comorbidity Index (CCI) score.(19,20)”
Method
The Impact of Malnutrition on 30-Day Postoperative Complications following Surgical Fixation of Distal Radius Fractures
Newman, J. M., Coste, M., Dua, K., Yang, A. J., Cautela, F. S., Shah, N. V., Patel, A. M., Chee, A., Khlopas, A., & Koehler, S. M. (2020) · Journal of Hand and Microsurgery · doi:10.1055/s-0039-3400433 · Cited by 8
Oncological outcome of videoscopic groin dissection for lymph node metastasis from melanoma
Sommariva, A., Cona, C., Tonello, M., Pilati, P., & Rossi, C. R. (2020) · Surgical Endoscopy · doi:10.1007/s00464-020-07675-5 · Cited by 8
Association between discontinuing chronic opioid therapy and newly diagnosed substance use disorders, accidents, self‐inflicted injuries and drug overdoses within the prescribers' health care system: a retrospective cohort study
Hayes, C. J., Krebs, E. E., Li, C., Brown, J. D., Hudson, T. J., & Martin, B. C. (2021) · Addiction · doi:10.1111/add.15689 · Cited by 8
Utilization of an Electronic Health Record Integrated Risk Score to Predict Hospitalization Among COVID-19 Patients
Nyman, M., Jose, T., Croghan, I. T., Parkulo, M. A., Burger, C. D., Schroeder, D. R., Hurt, R. T., & O’Horo, J. C. (2022) · Journal of Primary Care & Community Health · doi:10.1177/21501319211069748 · Cited by 8
Burden of opioid use for pain management among adult herpes zoster patients in the US and the potential impact of vaccination
Poirrier, J., DeMartino, J., Nagar, S., Carrico, J., Hicks, K., Meyers, J., & Stoddard, J. (2022) · Human Vaccines & Immunotherapeutics · doi:10.1080/21645515.2022.2040328 · Cited by 7
“The CCI score takes into account 20 categories of comorbidities, as defined by ICD9-CM and ICD-10-CM diagnosis and procedure codes, with associated weights corresponding to the severity of the comorbid conditions of interest.(21,22) The number of subjects developing PHN or other HZ-related complications at any point i…”
Method
Factors associated with quality of life and its prediction in kidney patients on haemodialysis
López, M. T. M., Rodríguez‐Rey, R., Montesinos, F., de Galvis, S. R., Ágreda-Ladrón, M. R., & Mayo, E. H. (2022) · Nefrología (English Edition) · doi:10.1016/j.nefroe.2022.07.007 · Cited by 8
Risk factors for infections caused by multidrug-resistant bacteria in patients with solid tumours
Horasan, E. Ş., Ersöz, G., Horoz, M., GÖKSU, M., Karaçorlu, S., & Ali Hakan, K. A. Y. A. (2010) · Scandinavian Journal of Infectious Diseases · doi:10.3109/00365548.2010.534500 · Cited by 8
“Clinical data were recorded on standardized forms and analyzed for age, gender, underlying diseases, Charlson co-morbidity score [14], chemotherapy (in the 30 days prior to infection), broad-spectrum antibiotic (BSA) treatment (anti-pseudomonal penicillins, third-generation cephalosporins, carbapenems, β -lactamase-re…”
Method
The Cost of Absenteeism and Short-Term Disability Associated With Colorectal Cancer
Yaldo, A. Z., Seal, B. S., & Lage, M. J. (2014) · Journal of Occupational and Environmental Medicine · doi:10.1097/jom.0000000000000186 · Cited by 8
Neutrophil-to-lymphocyte ratio and mesenteric ischemia: can it predict the etiology of mesenteric ischemic at computed tomography?
Núñez, M. A. R., Gijón, L. R., Chen, Y. T., Gracia, M. M. D., Weiland, G. B., & Tascón, Á. D. (2019) · Emergency Radiology · doi:10.1007/s10140-019-01699-8 · Cited by 8
Health Care Expenditures Among Adults With Diabetes After Oregon’s Medicaid Expansion
Lindner, S. R., Marino, M., O'Malley, J., Angier, H., Bailey, S. R., Hoopes, M. J., Springer, R., McConnell, K., DeVoe, J., & Huguet, N. (2019) · Diabetes Care · doi:10.2337/dc19-1343 · Cited by 9
“We also included the Charlson Comorbidity Index, which was developed to classify comorbidity conditions associated with mortality risk and includes diabetes as a comorbidity (28,29).”
Method
Impact of a Nosocomial COVID-19 Outbreak on a Non-COVID-19 Nephrology Ward during the First Wave of the Pandemic in Spain
Montero, M., López, C. H., López-Montesinos, I., Sorlí, L., González, C., Villar, J., Güerri‐Fernández, R., Herranz, M., Crespo, M., Jiménez, M. D. A., et al. (2021) · Antibiotics · doi:10.3390/antibiotics10060619 · Cited by 8
“Demographic, clinical, laboratory, and epidemiological data were collected from hospital and primary care electronic medical records and included the following: age, sex, presence, and severity of comorbidities assessed using the Charlson comorbidity index [22], days from exposure to positive PCR test for COVID-19, cl…”
Method
The sociodemographic and health‐related characteristics of a regional population with chronic disease at an interprofessional student‐assisted clinic in Q ueensland C apricornia A llied H ealth P artnership
Frakes, K., Brownie, S. M., Davies, L., Thomas, J., Miller, M., & Tyack, Z. F. (2013) · Australian Journal of Rural Health · doi:10.1111/ajr.12017 · Cited by 8

Authors: Charlson, M. E., Charlson, R. E., Peterson, J. C., Marinopoulos, S. S., Briggs, W. M., & Hollenberg, J. P.
Affiliations: Weill Cornell Medicine (US)
Yale New Haven Hospital (US)
Johns Hopkins University (US)
Central Michigan University (US)
Corresponding author: Charlson, Mary E.
ORCID: Charlson, Mary E.
Marinopoulos, Spyridon S.
Briggs, William M.
Venue: Journal of Clinical Epidemiology
Publisher: Elsevier BV
Published: 2008-12
Volume: 61
Issue: 12
Pages: 1234-1240
ISSN: 0895-4356 (ISSN-L)
DOI: 10.1016/j.jclinepi.2008.01.006
OpenAlex: W2110548428
Cited by: 894
References: 38
Citations by year: 2026: 35 · 2025: 52 · 2024: 79 · 2023: 74 · 2022: 80 · 2021: 77 · 2020: 81 · 2019: 66 · 2018: 83 · 2017: 56 · 2016: 42 · 2015: 51 · 2014: 37 · 2013: 21 · 2012: 22
FWCI: 9.15
Type: journal article
Language: en
Open access: closed
Licence: www.elsevier.com/tdm/userlicense/1.0/ (tdm)
www.elsevier.com/legal/tdmrep-license (tdm)
Locations: Journal of Clinical Epidemiology (publishedVersion)
PubMed (publishedVersion)
Topics: Health Sciences › Medicine › Epidemiology › Chronic Disease Management Strategies
Social Sciences › Economics, Econometrics and Finance › Economics and Econometrics › Health Systems, Economic Evaluations, Quality of Life
Social Sciences › Economics, Econometrics and Finance › Economics and Econometrics › Healthcare Policy and Management
Keywords: Charlson Comorbidity Index, chronic disease costs, health care costs, primary care patients, cost prediction model, hospital costs, resource utilization (health care), hypertension, depression, warfarin, skin ulcers, cellulitis, Medicare and Medicaid, elderly patients
MeSH terms: Adolescent, Adult, Aged, Aged, 80 and over, Chronic Disease, Epidemiologic Methods, Female, Health Resources, Health Services Research, Hospitalization, Humans, Male, Middle Aged, New York City, Primary Health Care, Prognosis, Drug Costs, Health Care Costs, Hospital Costs, Young Adult

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The Charlson comorbidity index is adapted to predict costs of chronic disease in primary care patients

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