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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Candrilli, S. D., Meyers, J., Boye, K. S., & Bae, J. P. (2014) · Journal of Diabetes and its Complications · doi:10.1016/j.jdiacomp.2014.12.009 · Cited by 35
Young Adult Substance Use and Healthcare Use Associated With Screening, Brief Intervention and Referral to Treatment in Pediatric Primary Care.
Sterling, S., Parthasarathy, S., Jones, A., Weisner, C., Metz, V., Hartman, L., Saba, K., & Kline-Simon, A. H. (2022) · Journal of Adolescent Health · doi:10.1016/j.jadohealth.2021.11.033 · Cited by 33
“The Charlson comorbidity score was calculated based on diagnosis codes made in the year prior to index, and used to account for medical comorbidity and disease severity where a higher score is associated with worse outcomes (ranging from 0-6) [40].”
Method
Multiple Comorbidities, Psychiatric Disorders, Healthcare Resource Utilization and Costs Among Adults with Essential Tremor: A Retrospective Observational Study in a Large US Commercially Insured and Medicare Advantage Population
Dai, D., Samiian, A., Fernandes, J., & Coetzer, H. (2022) · Journal of health economics and outcomes research · doi:10.36469/001c.37307 · Cited by 34
Treatment Patterns, Costs, and Survival among Medicare-Enrolled Elderly Patients Diagnosed with Advanced Stage Gastric Cancer: Analysis of a Linked Population-Based Cancer Registry and Administrative Claims Database
Karve, S. J., Lorenzo, M. J., Liepa, A. M., Hess, L. M., Kaye, J. A., & Calingaert, B. (2015) · Journal of the Korean Gastric Cancer Association · doi:10.5230/jgc.2015.15.2.87 · Cited by 34
“The Charlson Comorbidity Index (excluding gastric cancer) was calculated to obtain a measure of the patients’ overall comorbidity burden during the 6-month period preceding the gastric cancer index date.(14) The presence of ascites during the follow-up period was also recorded.”
Patient-aligned Care Team Engagement to Connect Veterans Experiencing Homelessness With Appropriate Health Care
Gundlapalli, A. V., Redd, A. M., Bolton, D., Vanneman, M. E., Carter, M. E., Johnson, E. E., Samore, M. H., Fargo, J. D., & O'Toole, T. P. (2017) · Medical Care · doi:10.1097/mlr.0000000000000770 · Cited by 34
Factors associated with the orthopaedic surgeon's decision to recommend total joint replacement in hip and knee osteoarthritis: an international cross-sectional study of 1905 patients
Huynh, C., Puyraimond‐Zemmour, D., Maillefert, J.-F., Conaghan, P. G., Davis, A. M., Günther, K.-P., HAWKER, G. A., Hochberg, M. C., Kloppenburg, M., Lim, K., et al. (2018) · Osteoarthritis and Cartilage · doi:10.1016/j.joca.2018.06.013 · Cited by 34
Risk factors for infection in home health care: Analysis of national Outcome and Assessment Information Set data
Shang, J., Wang, J., Adams, V., & Ma, C. (2020) · Research in Nursing & Health · doi:10.1002/nur.22053 · Cited by 35
“The Charlson comorbidity index, originating in the inpatient setting, is a weighted index of selected comorbid diseases (Charlson et al., 2008; Deyo, Cherkin, & Ciol, 1992), which has been used in the HHC setting previously (Wang, Kearney, Jia, & Shang, 2016).”
Method
Relationship between Multimorbidity and Disability in Elderly Patients with Coexisting Frailty Syndrome
Jędrzejczyk, M., Foryś, W. J., Czapla, M., & Uchmanowicz, I. (2022) · International Journal of Environmental Research and Public Health · doi:10.3390/ijerph19063461 · Cited by 34
“The maximum number of points is 4 for age equal to or greater than 80 [19,20].”
Background
Superior discrimination of the Risk Analysis Index compared with the 5-item modified frailty index in 30-day outcome prediction after anterior cervical discectomy and fusion
Bowers, C. A., Varela, S., Naftchi, A., Kazim, S. F., Hall, D. E., Ng, C., Rawanduzy, C. A., Spirollari, E., Vazquez, S. M., Das, A., et al. (2023) · Journal of Neurosurgery Spine · doi:10.3171/2023.5.spine221020 · Cited by 33
Breast cancer treatment in women over the age of 80: A tailored approach
Glaser, R. L., Marinopoulos, S. S., & Dimitrakakis, C. (2018) · Maturitas · doi:10.1016/j.maturitas.2018.01.014 · Cited by 33
“, Charlson comorbidity index) takes into account the number and seriousness of comorbid conditions, and their effect on mortality [4].”
BackgroundSelf-citation
Refining Risk Adjustment for the Proposed CMS Surgical Hip and Femur Fracture Treatment Bundled Payment Program
Cairns, M., Ostrum, R. F., & Clement, R. C. (2018) · Journal of Bone and Joint Surgery · doi:10.2106/jbjs.17.00327 · Cited by 33
Drinking Patterns of Older Adults with Chronic Medical Conditions
Ryan, M., Merrick, E. L., Hodgkin, D., Horgan, C. M., Garnick, D. W., Panas, L., Ritter, G. A., Blow, F. C., & Saitz, R. (2013) · Journal of General Internal Medicine · doi:10.1007/s11606-013-2409-1 · Cited by 33
Adherence, Persistence of Use, and Costs Associated With Second-Generation Antipsychotics for Bipolar Disorder
Rascati, K. L., Richards, K. M., Ott, C. A., Goddard, A. W., Stafkey-Mailey, D., Alvir, J. M., Sanders, K. N., & Mychaskiw, M. A. (2011) · Psychiatric Services · doi:10.1176/ps.62.9.pss6209_1032 · Cited by 34
Maintaining physical activity among older adults: 24-month outcomes of the Keep Active Minnesota randomized controlled trial
Martinson, B. C., Sherwood, N. E., Crain, A. L., Hayes, M. G., King, A. C., Pronk, N., & O’Connor, P. J. (2010) · Preventive Medicine · doi:10.1016/j.ypmed.2010.04.002 · Cited by 33
“…Charlson comorbidity score N3, a standard index of comorbidity calculated using prior year diagnoses of a broad range of serious medical conditions (Charlson et al., 2008, 1994; Deyo et al., 1992; Rush et al., 2000), or had diagnoses of coronary heart disease (CHD), congestive heart failure (CHF),…”
Method
The Association between Charlson Comorbidity Index and the Medical Care Cost of Cancer: A Retrospective Study
Yoon, S., Kim, E. J., Seo, H., & Oh, I. (2015) · BioMed Research International · doi:10.1155/2015/259341 · Cited by 32
“Previous studies have reported that higherCCI in patients with renal failure or head/neck cancer had increased medical costs and that CCI = 2 patients’ medical costs had the highest rate of increase [20, 21].”
Result
Variation in Care for Patients with Irritable Bowel Syndrome in the United States
Lacy, B. E., Patel, H., Guérin, A., Dea, K., Scopel, J., Alaghband, R., Wu, E. Q., & Mody, R. (2016) · PLoS ONE · doi:10.1371/journal.pone.0154258 · Cited by 32
“Results were reported as adjusted incidence rate ratios (IRRs) with 95% confidence intervals (CIs) [32].”
Background
Identification of Patients in Need of Advanced Care for Depression Using Data Extracted From a Statewide Health Information Exchange: A Machine Learning Approach
Kasthurirathne, S. N., Biondich, P., Grannis, S. J., Purkayastha, S., Vest, J. R., & Jones, J. (2019) · Journal of Medical Internet Research · doi:10.2196/13809 · Cited by 34
“We selected 3 high-risk patient groups: group A: patients with a past diagnosis of depression, group B: patients with a Charlson Comorbidity Index [32] of ≥ 1, and group C: patients with a Charlson Comorbidity Index of ≥ 2.”
Impact of bipolar disorder on health-related quality of life and work productivity: Estimates from the national health and wellness survey in Japan
Kato, T., Baba, K., Guo, W., Chen, Y., & Nosaka, T. (2021) · Journal of Affective Disorders · doi:10.1016/j.jad.2021.07.104 · Cited by 32
Racial/Ethnic Disparities in Health Insurance and Differences in Visit Type for a Population of Patients with Diabetes after Medicaid Expansion
Angier, H. E., Ezekiel-Herrera, D., Marino, M., Hoopes, M. J., Jacobs, E. A., DeVoe, J. E., & Huguet, N. (2019) · Journal of Health Care for the Poor and Underserved · doi:10.1353/hpu.2019.0011 · Cited by 33
Factors Associated with Health Information Exchange System Usage in a Safety-Net Ambulatory Care Clinic Setting
Vest, J. R., Gamm, L. D., Ohsfeldt, R. L., Zhao, H., & Jasperson, J. (2011) · Journal of Medical Systems · doi:10.1007/s10916-011-9712-3 · Cited by 31
“In terms of clinical indicators, we measured patient complexity in terms of the adapted Charlson comorbidity index score (excluding use of warfarin) [25].”
A Comparison of Oral Anticoagulant Use for Atrial Fibrillation in the Pre- and Post-DOAC Eras
Brown, J. D., Shewale, A. R., Dherange, P., & Talbert, J. (2016) · Drugs & Aging · doi:10.1007/s40266-016-0369-y · Cited by 31
The role of marijuana use disorder in predicting emergency department and inpatient encounters: A retrospective cohort study
Campbell, C. I., Bahorik, A. L., Kline‐Simon, A. H., & Satre, D. D. (2017) · Drug and Alcohol Dependence · doi:10.1016/j.drugalcdep.2017.04.017 · Cited by 30
“Income =median neighborhood income. a χ2 test or independent samples t-test (two-tailed). b Charlson Comorbidity Index= higher mean scores indicate greater medical disease burden (Charlson et al., 2008).”
BackgroundMethodInfluential
Alcohol, Marijuana, and Opioid use Disorders: 5-Year Patterns and Characteristics of Emergency Department Encounters
Bahorik, A. L., Satre, D. D., Kline‐Simon, A. H., Weisner, C. M., Young‐Wolff, K. C., & Campbell, C. I. (2017) · Substance Abuse · doi:10.1080/08897077.2017.1356789 · Cited by 31
Malnutrition increases the 30-day complication and re-operation rates in hip fracture patients treated with total hip arthroplasty
Newman, J. M., Sodhi, N., Khlopas, A., Piuzzi, N. S., Yakubek, G. A., Sultan, A. A., Klika, A. K., Higuera, C. A., & Mont, M. A. (2019) · Hip International · doi:10.1177/1120700019862977 · Cited by 31
Clinical and prognostic differences between methicillin-resistant and methicillin-susceptible Staphylococcus aureus infective endocarditis
Hidalgo-Tenorio, C., Gálvez-Acebal, J., Martínez‐Marcos, F. J., Plata, A., Lima, J. D. L. T., López-Cortés, L. E., Noureddine, M., Reguera, J. M., García, D. V., García, M. V., et al. (2020) · BMC Infectious Diseases · doi:10.1186/s12879-020-4895-1 · Cited by 31
Impact of Methicillin Resistant Staphylococcus aureus Contact Isolation Units on Medical Care
Masse, V., Valiquette, L., Boukhoudmi, S., Bonenfant, F., Talab, Y., Carvalho, J.-C., Alarie, I., Carrier, N., & Farand, P. (2013) · PLoS ONE · doi:10.1371/journal.pone.0057057 · Cited by 31
“Charlson comorbidity scores were used to quantify the overall burden of comorbidities [7].”
Method
Parkinson’s disease increases the risk of perioperative complications after total knee arthroplasty: a nationwide database study
Newman, J. M., Sodhi, N., Wilhelm, A. B., Khlopas, A., Klika, A. K., Naziri, Q., Kryzak, T. J., Higuera, C. A., & Mont, M. A. (2018) · Knee Surgery Sports Traumatology Arthroscopy · doi:10.1007/s00167-018-4970-y · Cited by 30
Intracorporeal Versus Extracorporeal Anastomosis for Laparoscopic Resection of the Splenic Flexure Colon Cancer: A Multicenter Propensity Score Analysis
Grieco, M., Cassini, D., Spoletini, D., Soligo, E., Grattarola, E., Baldazzi, G., Testa, S., & Carlini, M. (2019) · Surgical Laparoscopy Endoscopy & Percutaneous Techniques · doi:10.1097/sle.0000000000000653 · Cited by 30
“001† Time to autonomous mobilization (median±SD, range) (d) 2± 1 (1-6) 2± 1.”
Age-Related Frailty: A Clinical Model for Geroscience?
Takeda, C., Angioni, D., Setphan, E., Macaron, T., Barreto, P. D. S., Sourdet, S., Sierra, F., & Vellas, B. J. (2020) · The journal of nutrition health & aging · doi:10.1007/s12603-020-1491-4 · Cited by 31
“There are plenty of tools being used for measuring frailty (4, 5, 52) and multimorbidity (53-55), and these tools are probably not selecting the same profile of individuals.”
A multidisciplinary registry of patients with autoimmune and immune-mediated diseases with symptomatic COVID-19 from a single center
Sarmiento-Monroy, J. C., Espinosa, G., Londoño, M., Meira, F. S., Caballol, B., Llufriú, S., Carrasco, J. L., Moll‐Udina, A., Quintana, L. F., Giavedoni, P., et al. (2020) · Journal of Autoimmunity · doi:10.1016/j.jaut.2020.102580 · Cited by 30
“The age-adjusted Charlson comorbidity index (ACCI) was calculated for each individual [15] at the time of admission.”
Method
Voraussetzungen für ein neues Versorgungsmodell für ältere Menschen mit Multimorbidität
Thiem, U., Hinrichs, T., Mueller, C. A., Holt-Noreiks, S., Nagl, A., Bucchi, C., Trampisch, U. S., Moschny, A., Platen, P., Penner, E., et al. (2011) · Zeitschrift für Gerontologie und Geriatrie · doi:10.1007/s00391-011-0246-6 · Cited by 30
Urologist-Level Correlation in the Use of Observation for Low- and High-Risk Prostate Cancer
Tyson, M. D., Graves, A. J., O'Neil, B. B., Barocas, D. A., Chang, S. S., Penson, D. F., & Resnick, M. J. (2016) · JAMA Surgery · doi:10.1001/jamasurg.2016.2907 · Cited by 29
Association of Positive Airway Pressure Use With Acute Care Utilization and Costs
Kirsch, D. B., Yang, H., Maslow, A. L., Stolzenbach, M., & McCall, A. (2019) · Journal of Clinical Sleep Medicine · doi:10.5664/jcsm.7912 · Cited by 28
Using the BODE Index and Comorbidities to Predict Health Utilization Resources in Chronic Obstructive Pulmonary Disease
Li, C.-L., Lin, M.-H., Chen, P.-S., Tsai, Y.-C., Shen, L.-S., Kuo, H., & Liu, S. (2020) · International Journal of COPD · doi:10.2147/copd.s234363 · Cited by 29
The Cost of Serious Patient Fall-Related Injuries at Hospitals in Turkey: A Matched Case-Control Study
Barış, V. K., İntepeler, Ş. S., & Yeğinboy, E. Y. (2016) · Clinical Nursing Research · doi:10.1177/1054773816671521 · Cited by 29
“The comorbidities of the patients in the case and control groups were calculated using the Charlson Comorbidity Index (CCI), and their effect on the hospitalization cost was analyzed (Charlson et al., 2008; Charlson, Popel, Ales, & MacKenzie, 1987).”
Method
Are GOLD ABCD groups better associated with health status and costs than GOLD 1234 grades? A cross-sectional study
Boland, M. R. S., Tsiachristas, A., Kruis, A. L., Chavannes, N. H., & Mölken, M. R. (2014) · Primary Care Respiratory Journal · doi:10.4104/pcrj.2014.00002 · Cited by 28
Predicting hospital length of stay and short-term function after hip or knee arthroplasty: are both performance and comorbidity measures useful?
Poitras, S., Au, K., Wood, K. S., Dervin, G. F., & Beaulé, P. E. (2018) · International Orthopaedics · doi:10.1007/s00264-018-3833-y · Cited by 28
Impact of socioeconomic status on end-of-life costs: a systematic review and meta-analysis
Yu, C. W., Alavinia, M., & Alter, D. A. (2020) · BMC Palliative Care · doi:10.1186/s12904-020-0538-y · Cited by 30
Overall survival, adverse events, and economic burden in patients with chronic lymphocytic leukemia receiving systemic therapy: Real‐world evidence from the medicare population
Goyal, R., Nagar, S. P., Kabadi, S., Le, H., Davis, K. L., & Kaye, J. A. (2021) · Cancer Medicine · doi:10.1002/cam4.3855 · Cited by 28
Use of the PROMIS-10 global health in patients with chronic low back pain in outpatient physical therapy: a retrospective cohort study
Pak, S. S., Miller, M. J., & Cheuy, V. A. (2021) · Journal of Patient-Reported Outcomes · doi:10.1186/s41687-021-00360-8 · Cited by 28
“Previous studies have shown that CCI holds prognostic value in determining who is likely to incur higher future costs based on the assigned weight of different comorbid health conditions [34, 54].”
Background
Low lean mass is associated with lower urinary tract symptoms in US men from the 2005–2006 national health and nutrition examination survey dataset
Qin, Z., Zhao, J., Li, J., Yang, Q., Geng, J., Liao, R., & Su, B. (2021) · Aging · doi:10.18632/aging.203480 · Cited by 28
“Comorbidity index reflected the health status of patients and was of great significance for disease management, clinical treatment and prognosis [39].”

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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