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

The DOI matches its Crossref record; 38 of the 38 references it cites were found in a registry or an index.

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

Open this paper in CoChat — free account

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.

Integrity signals

Registry

Crossref · 10.1016/j.jclinepi.2008.01.006

Cites

38 of 38 references verified0 citation errors · 0 not checkable

Statistics

Recomputing p-values needs the paper’s full text.

Claims the paper makes

This paper’s full text isn’t openly available, so its claims and self-check weren’t run. The registry and citation checks still apply.

R: A Language and Environment for Statistical Computing
R Core Team (2000) · doi:10.32614/r.manuals · Cited by 355,893
A new method of classifying prognostic comorbidity in longitudinal studies: Development and validation
Charlson, M. E., Pompei, P., Ales, K. L., & MacKenzie, C. R. (1987) · Journal of Chronic Diseases · doi:10.1016/0021-9681(87)90171-8 · Cited by 49,742
Self-citation
Adapting a clinical comorbidity index for use with ICD-9-CM administrative databases
DEYO, R. (1992) · Journal of Clinical Epidemiology · doi:10.1016/0895-4356(92)90133-8 · Cited by 10,452
Economic Costs of Diabetes in the U.S. in 2002
American Diabetes Association (2003) · Diabetes Care · doi:10.2337/diacare.26.3.917 · Cited by 4,147
Prevalence, Expenditures, and Complications of Multiple Chronic Conditions in the Elderly
Wolff, J. L., Starfield, B. H., & Anderson, G. F. (2002) · Archives of Internal Medicine · doi:10.1001/archinte.162.20.2269 · Cited by 2,237
Reimbursing Health Plans and Health Providers: Efficiency in Production versus Selection
Newhouse, J. P. (1996) · RePEc: Research Papers in Economics · Cited by 565
Health care costs associated with depressive and anxiety disorders in primary care
(1995) · American Journal of Psychiatry · doi:10.1176/ajp.152.3.352 · Cited by 555
Increased Medical Costs of a Population-Based Sample of Depressed Elderly Patients
Katon, W. J., Lin, E. H. B., Russo, J. E., & Unützer, J. (2003) · Archives of General Psychiatry · doi:10.1001/archpsyc.60.9.897 · Cited by 500
The Growing Burden of Chronic Disease in America
Anderson, G. F., & Horvath, J. (2004) · Public Health Reports · doi:10.1016/j.phr.2004.04.005 · Cited by 494
Potentially avoidable hospitalizations: inequalities in rates between US socioeconomic groups.
Pappas, G., Hadden, W. C., Kozak, L. J., & Fisher, G. F. (1997) · American Journal of Public Health · doi:10.2105/ajph.87.5.811 · Cited by 399

Show all 38 references

Sorted by citations

Measures of Multimorbidity and Morbidity Burden for Use in Primary Care and Community Settings: A Systematic Review and Guide
Huntley, A. L., Johnson, R., Purdy, S., Valderas, J. M., & Salisbury, C. (2012) · The Annals of Family Medicine · doi:10.1370/afm.1363 · Cited by 619
Multimorbidity in chronic disease: impact on health care resources and costs
McPhail, S. (2016) · Risk Management and Healthcare Policy · doi:10.2147/rmhp.s97248 · Cited by 555
The Charlson Comorbidity Index in Registry-based Research
Lagergren, J., & Brusselaers, N. (2017) · Methods of Information in Medicine · doi:10.3414/me17-01-0051 · Cited by 333
“Ramiarina et al 2008 [24] ‐ Combined version ICD10 ‐ 18 categories ‐ Brazil Bottle et al 2011 [18] ‐ Extra codes added ‐ ICD10 ‐ 17 categories ‐ United Kingdom Charlson et al 2008 [14] • 4 disease categories added (to predict costs in primary care) • ICD9 • 23 categories • United States”
Background
COPD and its comorbidities: Impact, measurement and mechanisms
Negewo, N. A., Gibson, P. G., & McDonald, V. M. (2015) · Respirology · doi:10.1111/resp.12642 · Cited by 326
A retrospective cohort study: 10-year trend of disease-modifying antirheumatic drugs and biological agents use in patients with rheumatoid arthritis at Veteran Affairs Medical Centers
Ng, B., Chu, A., & Khan, M. M. (2013) · BMJ Open · doi:10.1136/bmjopen-2012-002468 · Cited by 381
The Charlson Comorbidity Index Can Be Used Prospectively to Identify Patients Who Will Incur High Future Costs
Charlson, M. E., Wells, M. T., Ullman, R., King, F., & Shmukler, C. (2014) · PLoS ONE · doi:10.1371/journal.pone.0112479 · Cited by 262
“Comorbidity was assessed through the Charlson comorbidity index [19].”
BackgroundMethodSelf-citation
The association of race and COVID-19 mortality
Golestaneh, L., Neugarten, J., Fisher, M. C., Billett, H. H., Gil, M. R., Johns, T. S., Yunes, M., Mokrzycki, M. H., Coco, M., Norris, K. C., et al. (2020) · EClinicalMedicine · doi:10.1016/j.eclinm.2020.100455 · Cited by 243
“Charlson comorbidity scores were derived from “Clinical Looking Glass”(see below) and were calculated based on comorbidity data gathered within 6 months prior to the last time they were seen in the outpatient setting between 1/1/2018 1/1/2020 [15].”
Comorbidities in inflammatory bowel disease: a call for action
ARGOLLO, M. C., Gilardi, D., Peyrin-Biroulet, C., Chabot, J.-F., Peyrin‐Biroulet, L., & Danese, S. (2019) · The Lancet. Gastroenterology & hepatology · doi:10.1016/s2468-1253(19)30173-6 · Cited by 242
Risk Factors for Serious Prescription Opioid-Related Toxicity or Overdose among Veterans Health Administration Patients
Zedler, B. K., Xie, L., Wang, L., Joyce, A., Vick, C. C., Kariburyo, F., Rajan, P. K., Başer, O., & Murrelle, L. (2014) · Pain Medicine · doi:10.1111/pme.12480 · Cited by 229
Multimodal cell atlas of the ageing human skeletal muscle
Lai, Y., Ramírez‐Pardo, I., Isern, J., An, J., Perdiguero, E., Serrano, A. L., Li, J., García-Domínguez, E., Segalés, J., Guo, P.-C., et al. (2024) · Nature · doi:10.1038/s41586-024-07348-6 · Cited by 247
“We assessed muscle functionality using (1) the Barthel index, which measures the ability of an individual to carry out daily living activities and their degree of autonomy 10 ; and (2) the Charlson index, which predicts life expectancy on the basis of a person’s comorbidities 11 .”
Food Insecurity, Food “Deserts,” and Glycemic Control in Patients With Diabetes: A Longitudinal Analysis
Berkowitz, S. A., Karter, A. J., Corbie-Smith, G. M., Seligman, H. K., Ackroyd, S. A., Barnard, L. S., Atlas, S. J., & Wexler, D. J. (2018) · Diabetes Care · doi:10.2337/dc17-1981 · Cited by 177
“Clinical characteristics considered includedageat diabetesdiagnosis, Charlson comorbidity score (25), the use of insulin (of any kind), and 3-hydroxy-3-methyl-”
Background
The direct and indirect costs of long bone fractures in a working age US population
Bonafede, M., Espindle, D. M., & Bower, A. G. (2012) · Journal of Medical Economics · doi:10.3111/13696998.2012.737391 · Cited by 174
Economics of hematopoietic cell transplantation
Khera, N., Zeliadt, S. B., & Lee, S. J. (2012) · Blood · doi:10.1182/blood-2012-05-426783 · Cited by 166
Mortality and cause of death of Australians on the autism spectrum
Hwang, Y. I. (., Srasuebkul, P., Foley, K., Arnold, S., & Trollor, J. N. (2019) · Autism Research · doi:10.1002/aur.2086 · Cited by 144
“The Charlson comorbidity index is a weighted classification of comorbid health conditions that predict mortality, used widely by health professionals and researchers to measure burden of disease and case mix (Charlson et al., 1987, 2008).”
Background
Health‐care use and cost in dementia caregivers: Longitudinal results from the Predictors Caregiver Study
Zhu, C. W., Scarmeas, N., Ornstein, K., Albert, M., Brandt, J., Blacker, D., Sano, M., & Stern, Y. (2015) · Alzheimer's & Dementia · doi:10.1016/j.jalz.2013.12.018 · Cited by 137
“Because care recipients’ living arrangement may change over time and patterns of health service utilization and costs may differ substantially between individuals in different living arrangements [34], information on care recipients’ living arrangements (living at home, in retirement homes, in assisted living faciliti…”
Background
Development of a Risk Index for Serious Prescription Opioid-Induced Respiratory Depression or Overdose in Veterans' Health Administration Patients
Zedler, B., Xie, L., Wang, L., Joyce, A., Vick, C., Brigham, J., Kariburyo, F., Baser, O., & Murrelle, L. (2015) · Pain Medicine · doi:10.1111/pme.12777 · Cited by 138
Multiple chronic conditions and healthcare costs among adults
Sambamoorthi, U., Tan, X., & Deb, A. (2015) · Expert Review of Pharmacoeconomics & Outcomes Research · doi:10.1586/14737167.2015.1091730 · Cited by 144
“, diabetes, depression, congestive heart failure and COPD) will have a score of 4 [39].”
Background
Bacteraemia due to OXA-48-carbapenemase-producing Enterobacteriaceae: a major clinical challenge
Francisco, C. N.-S., Mora-Rillo, M., Romero‐Gómez, M. P., Moreno-Ramos, F., Rico-Nieto, A., Carrascoso, G. R., Gómez-Gil, R., Arribas, J. R., Mingorance, J., & Paño‐Pardo, J. R. (2012) · Clinical Microbiology and Infection · doi:10.1111/1469-0691.12091 · Cited by 130
“Charlson comorbidity index (range 0–37) [12] and McCabe–Jackson classification (non-fatal, ultimately fatal or rapidly fatal) [13] were used to evaluate comorbidity and prognosis.”
Method
Alcohol, Cannabis, and Opioid Use Disorders, and Disease Burden in an Integrated Health Care System
Bahorik, A. L., Satre, D. D., Kline-Simon, A. H., Weisner, C. M., & Campbell, C. I. (2017) · Journal of Addiction Medicine · doi:10.1097/adm.0000000000000260 · Cited by 126
“This measure yields a weighted score predicting 10-year mortality risk for patients who present for treatment with a range of diagnosis-based comorbid medical conditions (Charlson et al., 2008).”
BackgroundMethodInfluential
Multiple Comorbid Conditions Challenge Heart Failure Self-Care by Decreasing Self-Efficacy
Dickson, V. V., Buck, H. G., & Riegel, B. J. (2012) · Nursing Research · doi:10.1097/nnr.0b013e31827337b3 · Cited by 125
“Although the CCI was developed to predict mortality (Charlson, Szatrowski, Peterson, & Gold, 1994) and cost (Charlson et al., 2008), it may not capture the HF patient’s experience in chronic illness.”
Method
Validation of a Screening Risk Index for Serious Prescription Opioid-Induced Respiratory Depression or Overdose in a US Commercial Health Plan Claims Database
Zedler, B. K., Saunders, W. B., Joyce, A. R., Vick, C. C., & Murrelle, E. L. (2018) · Pain Medicine · doi:10.1093/pm/pnx009 · Cited by 119
Charlson comorbidity score is a strong predictor of mortality in hemodialysis patients
Rattanasompattikul, M., Feroze, U., Molnar, M. Z., Dukkipati, R. B., Kovesdy, C. P., Nissenson, A. R., Norris, K. C., Kopple, J. D., & Kalantar‐Zadeh, K. (2011) · International Urology and Nephrology · doi:10.1007/s11255-011-0085-9 · Cited by 116
The impact of co-morbidity on the quality of life of people with dementia: findings from the IDEAL study
Nelis, S. M., Wu, Y., Matthews, F. E., Martyr, A., Quinn, C., Rippon, I., Rusted, J. M., Thom, J. M., Kopelman, M. D., Hindle, J. V., et al. (2018) · Age and Ageing · doi:10.1093/ageing/afy155 · Cited by 116
“The CCI does not encompass other physical changes or challenges . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . QoL-AD 1–2 Mild vs. none −1.45 (−2.19, −0.70) −1.35 (−2.09, −0.62) 3–4 Moderate vs. none −4.16 (−5.…”
MethodInfluential
Depression and Healthcare Service Utilization in Patients with Cancer
Mausbach, B. T., & Irwin, S. A. (2016) · Psycho-Oncology · doi:10.1002/pon.4133 · Cited by 104
Factors motivating and affecting health information exchange usage
Vest, J. R., Zhao, H., Jaspserson, J., Gamm, L. D., & Ohsfeldt, R. L. (2011) · Journal of the American Medical Informatics Association · doi:10.1136/jamia.2010.004812 · Cited by 111
“41 The substance abuse and psychoses conditions from Elixhauser and colleagues ’ comorbidity list were included as independent predictors.”
Background
Use and cost of hospitalization in dementia: longitudinal results from a community-based study
Zhu, C. W., Cosentino, S., Ornstein, K., Gu, Y., Andrews, H., & Stern, Y. (2015) · International Journal of Geriatric Psychiatry · doi:10.1002/gps.4222 · Cited by 106
“All items received weights of one, with the exception of chronic renal disease and systemic malignancy, which were weighted two (Charlson et al., 2008).”
Background
Relationship between concomitant benzodiazepine-opioid use and adverse outcomes among US veterans
Gressler, L. E., Martin, B. C., Hudson, T. J., & Painter, J. T. (2017) · Pain · doi:10.1097/j.pain.0000000000001111 · Cited by 109
DALBACEN cohort: dalbavancin as consolidation therapy in patients with endocarditis and/or bloodstream infection produced by gram-positive cocci
Hidalgo-Tenorio, C., García, D. V., Plata, A., Martín‐Dávila, P., Iftimie, S. M., Sequera, S., Loeches, B., López-Cortés, L. E., Fariñas, M. C., Fernández-Roldán, C., et al. (2019) · Annals of Clinical Microbiology and Antimicrobials · doi:10.1186/s12941-019-0329-6 · Cited by 107
Maintaining physical activity among older adults: Six-month outcomes of the Keep Active Minnesota randomized controlled trial
Martinson, B. C., Crain, A. L., Sherwood, N. E., Hayes, M., Pronk, N. P., & O'Connor, P. J. (2008) · Preventive Medicine · doi:10.1016/j.ypmed.2007.08.007 · Cited by 105
Early cardiovascular protection by initial two-drug fixed-dose combination treatment vs. monotherapy in hypertension
Rea, F., Corrao, G., Merlino, L. G., & Mancia, G. (2018) · European Heart Journal · doi:10.1093/eurheartj/ehy420 · Cited by 101
The relationship between pain, fatigue, depression and functional performance in stable heart failure
Conley, S., Feder, S. L., & Redeker, N. S. (2015) · Heart & Lung · doi:10.1016/j.hrtlng.2014.07.008 · Cited by 100
Statins and the Risk of Diabetes: Evidence From a Large Population-Based Cohort Study
Corrao, G., Ibrahim, B., Nicotra, F., Soranna, D., Merlino, L. G., Catapano, A. L., Tragni, E., Casula, M., Grassi, G. M., & Mancia, G. (2014) · Diabetes Care · doi:10.2337/dc13-2215 · Cited by 102
“other drugs during follow-up (antihypertensive, nitrate, digitalis, antiarrhythmic, corticosteroid, oral contraceptive, cyclosporine, antipsychotic, and antidepressant agents); 3) hospitalizations for CV diseases in the 3 years before the index prescription; 4) the Charlson comorbidity index score (13), which was calc…”
Method
Prevalence and characteristics of long COVID in elderly patients: An observational cohort study of over 2 million adults in the US
Fung, K. W., Baye, F. M., Baik, S. H., Zheng, Z., & McDonald, C. J. (2023) · PLoS Medicine · doi:10.1371/journal.pmed.1004194 · Cited by 105
“16 Personal history of COVID-19) on age in years, race, sex, dual eligibility status (a surrogate for income), geographic region, and Charlson comorbidity index [39] (within a range of +/− 2).”
Background
Using Information on Clinical Conditions to Predict High‐Cost Patients
Fleishman, J. A., & Cohen, J. W. (2010) · Health Services Research · doi:10.1111/j.1475-6773.2009.01080.x · Cited by 94
Association of Patient-Centered Outcomes With Patient-Reported and ICD-9-Based Morbidity Measures
Bayliss, E. A., Ellis, J. L., Shoup, J. A., Zeng, C. X., McQuillan, D. B., & Steiner, J. F. (2012) · The Annals of Family Medicine · doi:10.1370/afm.1364 · Cited by 92
Real‐world assessment of therapy changes, suboptimal treatment and associated costs in patients with ulcerative colitis or Crohn's disease
Rubin, D. T., Mody, R., Davis, K. L., & Wang, C. (2014) · Alimentary Pharmacology & Therapeutics · doi:10.1111/apt.12727 · Cited by 89
“6-month pre-index period based on the Charlson Comorbidity Index (CCI).(20)”
Method
Prevalence and determinants of loneliness in people living with dementia: Findings from the IDEAL programme
Victor, C. R., Rippon, I., Nelis, S. M., Martyr, A., Litherland, R., Pickett, J., Hart, N. J., Henley, J., Matthews, F. E., Clare, L., et al. (2020) · International Journal of Geriatric Psychiatry · doi:10.1002/gps.5305 · Cited by 94
A medication adherence and persistence comparison of hypertensive patients treated with single-, double- and triple-pill combination therapy
Xie, L., Frech‐Tamas, F., Marrett, E., & Başer, O. (2014) · Current Medical Research and Opinion · doi:10.1185/03007995.2014.964853 · Cited by 86
Vena Cava Filter Retrieval Rates and Factors Associated With Retrieval in a Large US Cohort
Brown, J. D., Raissi, D., Han, Q., Adams, V. R., & Talbert, J. (2017) · Journal of the American Heart Association · doi:10.1161/jaha.117.006708 · Cited by 85
“Comorbid conditions observed in the pre-index period consisted of Charlson comorbidities along with a Charlson Comorbidity Index, which represents the overall “comorbidity burden” widely used for risk adjustment.(22,23)”
Method
Societal costs of home and hospital end-of-life care for palliative care patients in Ontario, Canada
Yu, M., Guerriere, D. N., & Coyte, P. C. (2014) · Health & Social Care in the Community · doi:10.1111/hsc.12170 · Cited by 84
Effect of interplay between age and low-flow duration on neurologic outcomes of extracorporeal cardiopulmonary resuscitation
Yu, H., Wang, C., Chi, N., Huang, S., Chou, H., Chou, N., & Chen, Y. (2018) · Intensive Care Medicine · doi:10.1007/s00134-018-5496-y · Cited by 86
Epidemiology of iron deficiency anaemia in four European countries: a population‐based study in primary care
Levi, M., Rosselli, M., Simonetti, M., Brignoli, O., Cancian, M., Masotti, A., Pegoraro, V., Cataldo, N., Heiman, F., Chelo, M., et al. (2016) · European Journal Of Haematology · doi:10.1111/ejh.12776 · Cited by 88
“The burden of comorbidities was also accounted for by calculating the patient-specific Charlson Comorbidity Index (CCI) (33, 34).”
Method
Comparative Overall Comorbidity Burden Among Patients With Hidradenitis Suppurativa
Reddy, S., Strunk, A., & Garg, A. (2019) · JAMA Dermatology · doi:10.1001/jamadermatol.2019.0164 · Cited by 87
Antihypertensive Medications, Loop Diuretics, and Risk of Hip Fracture in the Elderly: A Population-Based Cohort Study of 81,617 Italian Patients Newly Treated Between 2005 and 2009
Corrao, G., Mazzola, P., Compagnoni, M. M., Rea, F., Merlino, L. G., Annoni, G., & Mancia, G. (2015) · Drugs & Aging · doi:10.1007/s40266-015-0306-5 · Cited by 82
“Finally, diagnoses available from inpatient charts over 5 years before the initial prescription date were used to calculate the Charlson comorbidity index [39].”
Method
Neighborhood Socioeconomic Disadvantages Associated With Prolonged Lengths of Stay, Nonhome Discharges, and 90-Day Readmissions After Total Knee Arthroplasty
Khlopas, A., Grits, D., Sax, O. C., Chen, Z., Orr, M. N., Klika, A. K., Mont, M. A., & Piuzzi, N. S. (2022) · The Journal of Arthroplasty · doi:10.1016/j.arth.2022.01.032 · Cited by 81
Clinical Trials Targeting Aging and Age-Related Multimorbidity
Espeland, M. A., Crimmins, E. M., Grossardt, B. R., Crandall, J. P., Gelfond, J., Harris, T. B., Kritchevsky, S. B., Manson, J. E., Robinson, J. G., Rocca, W. A., et al. (2016) · The Journals of Gerontology Series A · doi:10.1093/gerona/glw220 · Cited by 73
Treatment patterns and characteristics of patients with migraine in Japan: A retrospective analysis of health insurance claims data
Meyers, J., Davis, K. L., Lenz, R. A., Sakai, F., & Xue, F. (2019) · Cephalalgia · doi:10.1177/0333102419851855 · Cited by 75
“The CCI score includes 20 categories of conditions, deﬁned by ICD-10-CM codes, with weights corresponding to the severity of the condition, and a higher CCI score indicating a patient having a higher baseline disease burden (14).”
Method
Prognostic Value of CRP-Albumin-Lymphocyte (CALLY) Index in Patients Undergoing Surgery for Oral Cavity Cancer
Tsai, Y., Ko, C.-A., Chen, H., Hsu, C., Lai, C., Lee, Y., Tsai, M., Chang, G., Huang, E. I., & Fang, K. (2022) · Journal of Cancer · doi:10.7150/jca.74930 · Cited by 77
“%) patients had a CCI of 2 or greater.”
MethodInfluential
Annual direct medical costs of bronchiectasis treatment
de la Rosa, D., Martínez‐García, M. Á., Olveira, C., Girón, R. M., Máiz, L., & Prados, C. (2016) · Chronic Respiratory Disease · doi:10.1177/1479972316643698 · Cited by 74
“Finally, the Charlson index has already demonstrated its relationship with higher sanitary costs.(35) As age plays a very important role in its final value, it is not surprising that it was also associated with higher costs in our patients.”
Result
Malnutrition and overall survival in older patients with cancer
Zhang, X., Pang, L., Sharma, S. V., Li, R., Nyitray, A. G., & Edwards, B. J.-A. (2020) · Clinical Nutrition · doi:10.1016/j.clnu.2020.06.026 · Cited by 74
Comorbidity polypharmacy score and its clinical utility: A pragmatic practitioner′s perspective
Stawicki, S. P., Kalra, S., Jones, C. D., Justiniano, C. F., Papadimos, T. J., Galwankar, S. C., Pappada, S. M., Feeney, J. J., & Evans, D. (2015) · Journal of Emergencies Trauma and Shock · doi:10.4103/0974-2700.161658 · Cited by 77
“227 Journal of Emergencies, Trauma, and Shock I 8:4 I Oct - Dec 2015 and adding additional predefined points for the patient’s age group.[72,73] More importantly, the Charlson score does not take into account the individualized disease severity for the patient’s many comorbidities.”
Background
Medicare Utilization and Expenditures Around Incident Dementia in a Multiethnic Cohort
Zhu, C. W., Cosentino, S., Ornstein, K., Gu, Y., Scarmeas, N., Andrews, H., & Stern, Y. (2015) · The Journals of Gerontology Series A: Biological Sciences and Medical Sciences · doi:10.1093/gerona/glv124 · Cited by 67
“(measured by Charlson comorbidity index) (27), years of follow-up, and whether the participant died during the study.”
Method
Using structured and unstructured data to identify patients’ need for services that address the social determinants of health
Vest, J. R., Grannis, S. J., Haut, D. P., Halverson, P. K., & Menachemi, N. (2017) · International Journal of Medical Informatics · doi:10.1016/j.ijmedinf.2017.09.008 · Cited by 82
“We also created binary indicators for the 20 most common chronic conditions [20] and tobacco use [21], as well calculated the Charlson comorbidity index using diagnosis codes [22].”
Method
Evaluation of Bioelectrical Impedance Analysis in Critically Ill Patients: Results of a Multicenter Prospective Study
Kuchnia, A., Earthman, C., Teigen, L., Cole, A., Mourtzakis, M., Paris, M., Looijaard, W., Weijs, P., Oudemans‐van Straaten, H., Beilman, G., et al. (2017) · Journal of Parenteral and Enteral Nutrition · doi:10.1177/0148607116651063 · Cited by 91
Obesity in Mexico: prevalence, comorbidities, associations with patient outcomes, and treatment experiences
DiBonaventura, M., Meincke, H. H., Lay, A. L., Fournier, J., Bakker, E., & Ehrenreich, A. (2017) · Diabetes Metabolic Syndrome and Obesity · doi:10.2147/dmso.s129247 · Cited by 72
“comorbidities Respondents self-reported whether they had been diagnosed with the comorbidities associated with the 2008 version of the Charlson Comorbidity Index (CCI).(43) A CCI score was generated for each respondent.”
Home Mechanical Ventilation: A 12-Year Population-Based Retrospective Cohort Study
Povitz, M., Rose, L., Shariff, S. Z., Leonard, S., Welk, B. K., Jenkyn, K. B., Leasa, D. J., & Gershon, A. S. (2017) · Respiratory Care · doi:10.4187/respcare.05689 · Cited by 75
A new simple primary care morbidity score predicted mortality and better explains between practice variations than the Charlson index
Carey, I. M., Shah, S. M., Harris, T. J., DeWilde, S., & Cook, D. G. (2013) · Journal of Clinical Epidemiology · doi:10.1016/j.jclinepi.2012.10.012 · Cited by 71
Assessing the Capacity of Social Determinants of Health Data to Augment Predictive Models Identifying Patients in Need of Wraparound Social Services
Kasthurirathne, S. N., Vest, J. R., Menachemi, N., Halverson, P. K., & Grannis, S. J. (2018) · Journal of the American Medical Informatics Association · doi:10.1093/jamia/ocx130 · Cited by 71
How Do Doctors Respond to Incentives? Unintended Consequences of Paying Doctors to Reduce Costs
Alexander, D. (2020) · Journal of Political Economy · doi:10.1086/710334 · Cited by 70
“the associated risk of death, and has beenwidely validated.21 Furthermore, the Charlson index has been shown to be strongly predictive of hospital resource utilization, whichmakes it uniquely well suited for measuring latent health as it relates to cost of treatment (Charlson et al. 2008).”
Burden of migraine among Japanese patients: a cross-sectional National Health and Wellness Survey
Kikui, S., Chen, Y., Todaka, H., Asao, K., Adachi, K., & Takeshima, T. (2020) · The Journal of Headache and Pain · doi:10.1186/s10194-020-01180-9 · Cited by 69
Early constipation predicts faster dementia onset in Parkinson’s disease
Camacho, M., Macleod, A. D., Maple‐Grødem, J., Evans, J., Breen, D. P., Cummins, G. A., Wijeyekoon, R., Greenland, J. C., Alves, G. W., Tysnes, O., et al. (2021) · npj Parkinson s Disease · doi:10.1038/s41531-021-00191-w · Cited by 71
Adherence With Antihypertensive Drug Therapy and the Risk of Heart Failure in Clinical Practice
Corrao, G., Rea, F., Ghirardi, A., Soranna, D., Merlino, L. G., & Mancia, G. (2015) · Hypertension · doi:10.1161/hypertensionaha.115.05463 · Cited by 68
Improving treatment for obese women with early stage cancer of the uterus: Rationale and design of the levonorgestrel intrauterine device±Metformin±weight loss in endometrial cancer (feMME) trial
Hawkes, A. L., Quinn, M. A., Gebski, V., Armes, J. E., Brennan, D. J., Janda, M., & Obermair, A. (2014) · Contemporary Clinical Trials · doi:10.1016/j.cct.2014.06.014 · Cited by 67
“The Charlson comorbidity index is adapted to predict costs of chronic disease in primary care patients.”
MethodInfluential
Geriatrics index of comorbidity was the most accurate predictor of death in geriatric hospital among six comorbidity scores
Zekry, D., Valle, B. H. L., Lardi, C., Graf, C. E., Michel, J., Gold, G., Krause, K., & Herrmann, F. R. (2010) · Journal of Clinical Epidemiology · doi:10.1016/j.jclinepi.2009.11.013 · Cited by 67
Does Parkinson Disease Increase the Risk of Perioperative Complications After Total Hip Arthroplasty? A Nationwide Database Study
Newman, J. M., Sodhi, N., Dalton, S. E., Khlopas, A., Newman, R. P., Higuera, C. A., & Mont, M. A. (2018) · The Journal of Arthroplasty · doi:10.1016/j.arth.2018.01.006 · Cited by 67
Evaluación de la comorbilidad en la población anciana: utilidad y validez de los instrumentos de medida
Abizanda, P., Mellinas, G. P., Martínez‐Sánchez, E., & Jiménez, E. L. (2010) · Revista Española de Geriatría y Gerontología · doi:10.1016/j.regg.2009.10.009 · Cited by 66
A systematic review of risk stratification tools internationally used in primary care settings
Girwar, S. M., Jabroer, R., Fiocco, M. F., Sutch, S. P., Numans, M. E., & Bruijnzeels, M. A. (2021) · Health Science Reports · doi:10.1002/hsr2.329 · Cited by 64
“Categories ACG categories (1-93), Resource Utilization Bands (RUBs), Expended Diagnosis Clusters (EDC) count Six categories based on chronic condition count Score based on aggregated conditions (70 categories)”
Background
Inferring the role of the microbiome on survival in patients treated with immune checkpoint inhibitors: causal modeling, timing, and classes of concomitant medications
Spakowicz, D. J., Hoyd, R., Muniak, M., Husain, M., Bassett, J. S., Wang, L., Tinoco, G., Patel, S. H., Burkart, J. T., Miah, A., et al. (2020) · BMC Cancer · doi:10.1186/s12885-020-06882-6 · Cited by 62
Validity of the Age-Adjusted Charlson Comorbidity Index on Clinical Outcomes for Patients with Nasopharyngeal Cancer Post Radiation Treatment: A 5-Year Nationwide Cohort Study
Yang, C., Chen, P., Hsu, C., Chang, S., & Lee, C. (2015) · PLoS ONE · doi:10.1371/journal.pone.0117323 · Cited by 62
“The CCI was developed in 1987 and is a prognostic taxonomy that was initially developed to account for the influence of a patients’ adverse medical conditions in longitudinal studies [5–7] and has been validated in many clinical settings [8–10].”
Method
Two treatment approaches for human regular U-500 insulin in patients with type 2 diabetes not achieving adequate glycemic control on high-dose U-100 insulin therapy with or without oral agents: A randomized, titration-to-target clinical trial
Hood, R. C., Arakaki, R. F., Wysham, C., Li, Y. G., Settles, J. A., & Jackson, J. A. (2015) · Endocrine Practice · doi:10.4158/ep15612.or · Cited by 61
Predictors of Complications After Spinal Stabilization of Thoracolumbar Spine Injuries
Dimar, J. R., Fisher, C. G., Vaccaro, A. R., Okonkwo, D. O., Dvorak, M. F., Fehlings, M. G., Rampersaud, R. Y., & Carreon, L. Y. (2010) · The Journal of Trauma: Injury, Infection, and Critical Care · doi:10.1097/ta.0b013e3181cc853b · Cited by 61
Dynamic Data During Hypotensive Episode Improves Mortality Predictions Among Patients With Sepsis and Hypotension*
Mayaud, L., Lai, P. S., Clifford, G. D., Tarassenko, L., Celi, L. A., & Annane, D. (2013) · Critical Care Medicine · doi:10.1097/ccm.0b013e3182772adb · Cited by 62
“The Van Walraven score is a modification of the Elixhauser comorbidity score (20), equivalent to the Charlson score (39, 40), which provides a weighting for 30 comorbidities: it is a validated and easily obtainable proxy for comorbid conditions.”
Method
Verification and evaluation of aldosteronism demographics in the Taiwan Primary Aldosteronism Investigation Group (TAIPAI Group)
Kuo, C., Wu, V., Huang, K., Wang, S.-M., Chang, C., Lu, C., Yang, W., Tsai, C.-W., Lai, C., Lee, T., et al. (2011) · Journal of the Renin-Angiotensin-Aldosterone System · doi:10.1177/1470320310391329 · Cited by 60
Disease burden and quality of life of patients with chronic cough in Japan: a population-based cross-sectional survey
Kubo, T., Tobe, K., Okuyama, K., Kikuchi, M., Chen, Y., Schelfhout, J., Abe, M., & Tokita, S. (2021) · BMJ Open Respiratory Research · doi:10.1136/bmjresp-2020-000764 · Cited by 59
Living Alone with Mild-To-Moderate Dementia: Findings from the IDEAL Cohort
Clare, L., Martyr, A., Henderson, C., Gamble, L. D., Matthews, F. E., Quinn, C., Nelis, S. M., Rusted, J. M., Thom, J. M., Knapp, M. R. J., et al. (2020) · Journal of Alzheimer s Disease · doi:10.3233/jad-200638 · Cited by 58
Association of Lithium Treatment With the Risk of Osteoporosis in Patients With Bipolar Disorder
Köhler‐Forsberg, O., Rohde, C., Nierenberg, A. A., & Østergaard, S. D. (2022) · JAMA Psychiatry · doi:10.1001/jamapsychiatry.2022.0337 · Cited by 59
Impact of fractures on quality of life in patients with osteoporosis: a US cross-sectional survey
Gold, D. T., Williams, S. A., Weiss, R. J., Wang, Y., Watkins, C., Carroll, J., Middleton‐Dalby, C., & Silverman, S. L. (2019) · Journal of Drug Assessment · doi:10.1080/21556660.2019.1677674 · Cited by 58
Prevalence and incidence rates of pressure ulcers in an Emergency Department
Dugaret, E., Videau, M., Faure, I., Gabinski, C., Bourdel‐Marchasson, I., & Salles, N. (2012) · International Wound Journal · doi:10.1111/j.1742-481x.2012.01103.x · Cited by 57
“not), support surface used (bed or stretcher), reason for the admission in this ED, comorbidity score (Charlson’s score (12)), list of treatment and C-reactive protein (CRP) levels (mg/l).”
Background
Real-world treatment patterns and costs in a US Medicare population with metastatic squamous non-small cell lung cancer
Davis, K. L., Goyal, R., Able, S. L., Brown, J., Li, L., & Kaye, J. A. (2014) · Lung Cancer · doi:10.1016/j.lungcan.2014.11.002 · Cited by 57
Health care costs of depression in patients diagnosed with cancer
Mausbach, B. T., Yeung, P., Bos, T., & Irwin, S. A. (2018) · Psycho-Oncology · doi:10.1002/pon.4716 · Cited by 57
Prediction of emergency department revisits using area-level social determinants of health measures and health information exchange information
Vest, J. R., & Ben-Assuli, O. (2019) · International Journal of Medical Informatics · doi:10.1016/j.ijmedinf.2019.06.013 · Cited by 61
“For example, we only included the Charlson index as derived from HIE data and not as calculated from only EHR data.”
BackgroundInfluential
Clinical and economic burden associated with cardiovascular events among patients with hyperlipidemia: a retrospective cohort study
Fox, K. M., Wang, L., Gandra, S. R., Quek, R. G. W., Li, L., & Başer, O. (2016) · BMC Cardiovascular Disorders · doi:10.1186/s12872-016-0190-x · Cited by 56
“The CCI and CDS score have been widely used in many retrospective studies [25–28].”
Method
Are Medicare's “Comprehensive Care for Joint Replacement” Bundled Payments Stratifying Risk Adequately?
Cairns, M., Moskal, P. T., Eskildsen, S. M., Ostrum, R. F., & Clement, R. C. (2018) · The Journal of Arthroplasty · doi:10.1016/j.arth.2018.04.006 · Cited by 55
A Comprehensive Model of Factors Associated With Capability to “Live Well” for Family Caregivers of People Living With Mild-to-Moderate Dementia
Clare, L., Wu, Y., Quinn, C., Jones, I. R., Victor, C. R., Nelis, S. M., Martyr, A., Litherland, R., Pickett, J., Hindle, J. V., et al. (2018) · Alzheimer Disease & Associated Disorders · doi:10.1097/wad.0000000000000285 · Cited by 55
Gender differences in determinants of iron-deficiency anemia: a population-based study conducted in four European countries
Levi, M., Simonetti, M., Marconi, E., Brignoli, O., Cancian, M., Masotti, A., Pegoraro, V., Heiman, F., Cricelli, C. A., & Lapi, F. (2019) · Annals of Hematology · doi:10.1007/s00277-019-03707-w · Cited by 59
Examining the Effect of Medication Adherence on Risk of Subsequent Fracture Among Women with a Fragility Fracture in the U.S. Medicare Population
Keshishian, A. V., Boytsov, N. N., Burge, R. T., Krohn, K., Lombard, L., Zhang, X., Xie, L., & Baser, O. (2017) · Journal of Managed Care & Specialty Pharmacy · doi:10.18553/jmcp.2017.17054 · Cited by 54
Impact of opioid dose escalation on the development of substance use disorders, accidents, self‐inflicted injuries, opioid overdoses and alcohol and non‐opioid drug‐related overdoses: a retrospective cohort study
Hayes, C. J., Krebs, E. E., Hudson, T. J., Brown, J. D., Li, C., & Martin, B. C. (2020) · Addiction · doi:10.1111/add.14940 · Cited by 54
“Medical covariates included diagnoses for CNCP conditions, mental health conditions (schizophrenia, major depressive disorder, post-traumatic stress disorder, anxiety disorders, bipolar disorder, multiple mental health conditions), and the enhanced Charlson comorbidity score(28).”
Background
Prevalence of chronic diseases by immigrant status and disparities in chronic disease management in immigrants: a population-based cohort study, Valore Project
Valore Project, Buja, A., Gini, R., Visca, M., Damiani, G., Federico, B., Francesconi, P., Donato, D., Marini, A., Donatini, A., et al. (2013) · BMC Public Health · doi:10.1186/1471-2458-13-504 · Cited by 53
“It has been demonstrated that this index is a valid and reliable method for measuring comorbidity suitable for use in clinical research and, although it was developed and validated in hospitalized patients, it has since been adapted and validated for primary care and community populations [18].”
Method
Using a Self-Reported Global Health Measure to Identify Patients at High Risk for Future Healthcare Utilization
Blumenthal, K. J., Chang, Y., Ferris, T. G. G., Spirt, J., Vogeli, C., Wagle, N. W., & Metlay, J. P. (2017) · Journal of General Internal Medicine · doi:10.1007/s11606-017-4041-y · Cited by 53
“We extracted clinical diagnoses and calculated an overall outpatient Charlson Comorbidity Index based on encounter codes from medical claims data.(21,22) Comorbidities were determined based on all paid claims going back 12 months prior to the month of survey completion.”
Method
Risk Factors for Serious Prescription Opioid-Induced Respiratory Depression or Overdose: Comparison of Commercially Insured and Veterans Health Affairs Populations
Nadpara, P. A., Joyce, A. R., Murrelle, E. L., Carroll, N. W., Carroll, N. V., Barnard, M., & Zedler, B. K. (2017) · Pain Medicine · doi:10.1093/pm/pnx038 · Cited by 55
Early Predictors of Global Functional Outcome after Traumatic Spinal Cord Injury: A Systematic Review
Richard‐Denis, A., Beauséjour, M., Thompson, C., Nguyen, B.-H., & Mac‐Thiong, J. (2018) · Journal of Neurotrauma · doi:10.1089/neu.2017.5403 · Cited by 53
“Less comorbidities, as quantiﬁed by the Charl-sonComorbidity Index 25 or the Maximum Comprehensive Severity Index, 26 were also associated to greater functional improvement in three studies, 14,16,19 whereas four other studies failed to demonstrate a relationship between functional outcome and the burden of comorbidit…”
Dementia subtype and living well: results from the Improving the experience of Dementia and Enhancing Active Life (IDEAL) study
study, O. B. O. T. I. T. E. O. D. A. E. A. L., Wu, Y., Clare, L., Hindle, J. V., Nelis, S. M., Martyr, A., & Matthews, F. E. (2018) · BMC Medicine · doi:10.1186/s12916-018-1135-2 · Cited by 53
Prevalence and factors associated with malnutrition in older patients with cancer.
Zhang, X., Pang, L., Sharma, S. V., Li, R.-S., Nyitray, A., & Edwards, B. (2019) · Journal of Geriatric Oncology · doi:10.1016/j.jgo.2019.01.021 · Cited by 52
Incidence and risk factors associated with postoperative delirium following primary elective total hip arthroplasty: a retrospective nationwide inpatient sample database study
Yang, Q., Wang, J., Huang, X., Xu, Y., & Zhang, Y. (2020) · BMC Psychiatry · doi:10.1186/s12888-020-02742-6 · Cited by 53
Multimorbidity in risk stratification tools to predict negative outcomes in adult population
Alonso-Morán, E., Nuño-Solínis, R., Onder, G., & Tonnara, G. (2015) · European Journal of Internal Medicine · doi:10.1016/j.ejim.2015.02.010 · Cited by 51
“It is worth noting that diseases such as COPD, CHF, cerebro-vascular disease and diabetes, were strong predictors in some of the models reviewed [10,12,15,16,21,37,39,43].”
BackgroundInfluential
Inequalities in living well with dementia-The impact of deprivation on well-being, quality of life and life satisfaction: Results from the improving the experience of dementia and enhancing active life study
Wu, Y., Clare, L., Jones, I. R., Martyr, A., Nelis, S. M., Quinn, C., Victor, C. R., Lamont, R. A., Rippon, I., Matthews, F. E., et al. (2018) · International Journal of Geriatric Psychiatry · doi:10.1002/gps.4998 · Cited by 50
“Number of chronic conditions was used as an index of physical health and generated based on items from the Charlson Comorbidity Index.(20) Postcodes of people with dementia and carers were cross‐referenced to determine whether they were coresident.”
Method
Implementation of a CKD Checklist for Primary Care Providers
Mendu, M. L., Schneider, L. I., Aizer, A. A., Singh, K., Leaf, D. E., Lee, T. H.-Y., & Waikar, S. S. (2014) · Clinical Journal of the American Society of Nephrology · doi:10.2215/cjn.01660214 · Cited by 51
“We also examined whether sex, race, and an adapted Charlson comorbidity index incorporating hypertension (assigning a score of 1 to hypertension) (21,22) were confounders.”
Background
Comorbidities That Cause Pain and the Contributors to Pain in Individuals With Chronic Obstructive Pulmonary Disease
Chen, Y., Camp, P. G., Coxson, H. O., ROAD, J. D., Guenette, J. A., Hunt, M. A., & Reid, W. D. (2016) · Archives of Physical Medicine and Rehabilitation · doi:10.1016/j.apmr.2016.10.016 · Cited by 54
Age-adjusted Charlson comorbidity index score as predictor of survival of patients with digestive system cancer who have undergone surgical resection
Tian, Y., Jian, Z., Xu, B., & Liu, H. (2017) · Oncotarget · doi:10.18632/oncotarget.18401 · Cited by 51
The impact of comorbidities, regional trends, and hospital factors on discharge dispositions and hospital costs after acoustic neuroma microsurgery: a United States nationwide inpatient data sample study (2005–2009)
Sonig, A., Khan, I. S., Wadhwa, R., Thakur, J. D., & Nanda, A. (2012) · Neurosurgical FOCUS · doi:10.3171/2012.7.focus12193 · Cited by 50

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

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review

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

Abstract

Overview

Integrity signals

Verification

Claims the paper makes

Citations

Cites

Cited by

Related

Metadata

Record

About these checks