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

Items 201–300 of 891

Euthyroid sick syndrome as an early surrogate marker of poor outcome in mild SARS-CoV-2 disease
Sparano, C., Zago, E., Morettini, A., Nozzoli, C., Yannas, D., Adornato, V., Caldini, E., Vaudo, M., Maggi, M., & Petrone, L. (2021) · Journal of Endocrinological Investigation · doi:10.1007/s40618-021-01714-1 · Cited by 28
“Patients’ comorbidities were also computed according to the Charlson Comorbidity Index (CCI), to better stratify individual disease burden and prognosis [35, 36].”
Method
Burden of schizophrenia among Japanese patients: a cross-sectional National Health and Wellness Survey
Baba, K., Guo, W., Chen, Y., Nosaka, T., & Kato, T. (2022) · BMC Psychiatry · doi:10.1186/s12888-022-04044-5 · Cited by 32
“The general health characteristics included body mass index (BMI), Charlson Comorbidity Index (CCI) [21, 22], smoking status, alcohol use, and exercise behavior.”
BackgroundInfluential
Factors Associated with a High-Risk Profile for Developing Pressure Injuries in Long-Term Residents of Nursing Homes
Elli, C., Novella, A., Nobili, A., Ianes, A., & Pasina, L. (2022) · Medical Principles and Practice · doi:10.1159/000527063 · Cited by 28
Comparison of Rx-defined morbidity groups and diagnosis- based risk adjusters for predicting healthcare costs in Taiwan
Kuo, R. N.-C., & Lai, M. (2010) · BMC Health Services Research · doi:10.1186/1472-6963-10-126 · Cited by 28
“Diagnosis based comorbidity scales and risk adjustment tools, such as the Charlson Comorbidity Index[1], Elixhauser index[2], the Johns Hopkins Adjusted Clinical Group (ACG) case-mix system[3], and the Diagnostic Cost Group Hierarchical Condition Category (DCG/HCC) model[4,5] have been verified for their effective use…”
Using Self‐Reported Health Measures to Predict High‐Need Cases among Medicaid‐Eligible Adults
Wherry, L., Burns, M. E., & Leininger, L. J. (2014) · Health Services Research · doi:10.1111/1475-6773.12222 · Cited by 30
“In addition, our selection of health conditions was informed by the CCI, but it may overlook other important chronic health conditions that influence health care utilization.”
Influential
[Assessment of comorbidity in elderly].
Rosas‐Carrasco, Ó., González-Flores, E., Brito-Carrera, A. M., Valdez, O. V., Peschard-Sáenz, E., Gutiérrez‐Robledo, L. M., & García-Mayo, E. J. (2011) · PubMed · Cited by 28
Mental health treatment dose and annual healthcare costs in patients with cancer and major depressive disorder.
Mausbach, B. T., Bos, T., & Irwin, S. A. (2018) · Health Psychology · doi:10.1037/hea0000670 · Cited by 27
“More recent evidence indicates the DCCI is also a useful predictor for physician visits, hospitalization, health service cost, and mortality (Charlson et al., 2008; Charlson, Pompei, Ales, & MacKenzie, 1987; Charlson, Szatrowski, Peterson, & Gold, 1994; Charlson, Wells, Ullman, King, & Shmukler,…”
Impact of opioid dose escalation on pain intensity: a retrospective cohort study
Hayes, C. J., Krebs, E. E., Hudson, T. J., Brown, J. D., Li, C., & Martin, B. C. (2020) · Pain · doi:10.1097/j.pain.0000000000001784 · Cited by 27
“Medical covariates included the enhanced Charlson comorbidity score and diagnoses for CNCP andmental health conditions (schizophrenia, major depressive disorder, post-traumatic stress disorder, anxiety disorders, bipolar disorder, multiple mental health conditions).(3) Medication classes used to treat pain or that inc…”
Method
Impact of electronic diabetes registry ‘Meaningful Use’ on quality of care and hospital utilization
Han, W., Sharman, R., Heider, A. R., Maloney, N., Yang, M., & Singh, R. K. P. G. (2015) · Journal of the American Medical Informatics Association · doi:10.1093/jamia/ocv040 · Cited by 28
International consensus on laryngeal preservation strategies in laryngeal and hypopharyngeal cancer
Ferrari, M., Mularoni, F., Smussi, D., Gaudioso, P., Bonomo, P., Friborg, J., Ghi, M. G., Grégoire, V., Harrington, K. J., Hunter, K. D., et al. (2025) · The Lancet Oncology · doi:10.1016/s1470-2045(25)00020-8 · Cited by 26
Identification of Quality of Care Deficiencies in Elderly Surgical Patients by Measuring Adherence to Process-Based Quality Indicators
Bergman, S., Martelli, V., Monette, M., Sourial, N., Deban, M., Hamadani, F., Teasdale, D., Holcroft, C., Zakrzewski, H., & Fraser, S. A. (2013) · Journal of the American College of Surgeons · doi:10.1016/j.jamcollsurg.2013.07.387 · Cited by 25
Systematic Age-Related Differences in Chronic Disease Management in a Population-Based Cohort Study: A New Paradigm of Primary Care Is Required
Buja, A., Damiani, G., Gini, R., Visca, M., Federico, B., Donato, D., Francesconi, P., Marini, A., Donatini, A., Brugaletta, S., et al. (2014) · PLoS ONE · doi:10.1371/journal.pone.0091340 · Cited by 26
“The Charlson index was calculated to assess patients’ comorbidities: this index has proved a valid and reliable method for measuring comorbidities for the purpose of clinical research and, although it was first developed and validated for hospitalized patients, it has since been adapted and validated for primary care…”
Method
The Affordable Care Act improved health insurance coverage and cardiovascular‐related screening rates for cancer survivors seen in community health centers
Angier, H. E., Marino, M., Springer, R. J., Schmidt, T. D., Huguet, N., & DeVoe, J. E. (2020) · Cancer · doi:10.1002/cncr.32900 · Cited by 26
“We did, however, adjust for the Charlson Comorbidity Index score, which considers diseases such as diabetes and heart disease.(37) There may be differential dropout of patients from expansion states in comparison with nonexpansion states leading to bias.”
Method
Longitudinal Trajectories of Quality of Life Among People With Mild-to-Moderate Dementia: A Latent Growth Model Approach With IDEAL Cohort Study Data
Clare, L., Gamble, L. D., Martyr, A., Sabatini, S., Nelis, S. M., Quinn, C., Pentecost, C., Victor, C. R., Jones, R. W., Jones, I. R., et al. (2022) · The Journals of Gerontology Series B · doi:10.1093/geronb/gbac022 · Cited by 26
“The Charlson Comorbidity Index age-adjusted score (Charlson et al., 2008) identified the number of chronic conditions.”
Incidence and risk factors of postoperative delirium following total knee arthroplasty: A retrospective Nationwide Inpatient Sample database study
Yang, Q., Wang, J., Chen, Y., Lian, Q., Shi, Z., & Zhang, Y. (2022) · The Knee · doi:10.1016/j.knee.2022.02.006 · Cited by 27
Chronic Migraine Epidemiology and Outcomes – International (CaMEO-I) Study: Methods and multi-country baseline findings for diagnosis rates and care
Adams, A. M., Buse, D. C., Leroux, É., Lantéri‐Minet, M., Sakai, F., Matharu, M. S., Katsarava, Z., Reed, M. L., Fanning, K. M., Sommer, K., et al. (2023) · Cephalalgia · doi:10.1177/03331024231180611 · Cited by 28
“The Screening Module collected sociodemographic information and information on general health/comorbidities based on a modified Charlson Comorbidity Index (23).”
Method
Has the prevalence of health care services use increased over the last decade (2001–2009) in elderly people? A Spanish population-based survey
Palacios‐Ceña, D., Hernández‐Barrera, V., Jiménez‐García, R., Valle-Martín, B., Fernández‐de‐las‐Peñas, C., & Carrasco‐Garrido, P. (2013) · Maturitas · doi:10.1016/j.maturitas.2013.07.016 · Cited by 26
“The sheer growth in the older population ill likely result in an escalation in the absolute number of perons with morbidity [2] and disability [3], leading to substantial ncreases in both direct and indirect health care costs [4].”
Background
Exploring Health System Responsiveness in Ambulatory Care and Disease Management and its Relation to Other Dimensions of Health System Performance (RAC) – Study Design and Methodology
Röttger, J., Blümel, M., Engel, S., Grenz-Farenholtz, B., Fuchs, S., Linder, R., Verheyen, F., & Busse, R. (2015) · International Journal of Health Policy and Management · doi:10.15171/ijhpm.2015.97 · Cited by 26
Health Care Resource Utilization and Costs Associated with Nonfatal Major Adverse Cardiovascular Events
Korsnes, J. S., Davis, K. L., Ariely, R., Bell, C. F., & Mitra, D. (2015) · Journal of Managed Care & Specialty Pharmacy · doi:10.18553/jmcp.2015.21.6.443 · Cited by 26
“The presence of cardiovascular risk factors, including age of at least 60 years at index, pre-index diabetes requiring treatment, pre-index renal disease, and index diagnosis of ST-elevation MI (STEMI) versus non-ST-elevation MI (NSTEMI; Appendix A, available in online article), as well as index statin use and the Cha…”
Method
The Impact of Social and Clinical Complexity on Diabetes Control Measures
Cottrell, E., O'Malley, J. P., Dambrun, K., Park, B., Hendricks, M. A., Xu, H., Charlson, M. E., Bazemore, A., Shenkman, E. A., Sears, A., et al. (2020) · The Journal of the American Board of Family Medicine · doi:10.3122/jabfm.2020.04.190367 · Cited by 26
Self-citation
Effects of dialysis modality choice on the survival of end-stage renal disease patients in southern China: a retrospective cohort study
He, Z., Hou, H., Zhang, D., Mo, Y., La, Z., Su, G., Lin, J., Lu, L., Huang, J., Gu, Y., et al. (2020) · BMC Nephrology · doi:10.1186/s12882-020-02070-7 · Cited by 25
“CCI was originally used to estimate the 1-year mortality rate of hospitalized patients [26].”
Method
Health-Related Quality of Life Among Patients With HR+/HER2– Early Breast Cancer
Criscitiello, C., Spurden, D., Piercy, J., Rider, A., Williams, R., Mitra, D., Wild, R., Corsaro, M., Kurosky, S. K., & Law, E. H. (2021) · Clinical Therapeutics · doi:10.1016/j.clinthera.2021.04.020 · Cited by 25
Natural language processing-driven state machines to extract social factors from unstructured clinical documentation
Allen, K. S., Hood, D. R., Cummins, J., Kasturi, S., Mendonca, E. A., & Vest, J. R. (2023) · JAMIA Open · doi:10.1093/jamiaopen/ooad024 · Cited by 25
“These measures included age, gender, race, ethnicity, rural/urban status, Modified Townsend Index (social deprivation based on residential zip code),(43) and Charlson Comorbidity score.(44)”
Method
Treatment Patterns and Outcomes of Patients With Metastatic ER+/HER-2− Breast Cancer: A Multicountry Retrospective Medical Record Review
Kurosky, S. K., Mitra, D., Zanotti, G., & Kaye, J. A. (2017) · Clinical Breast Cancer · doi:10.1016/j.clbc.2017.10.008 · Cited by 25
“The Charlson comorbidity index (CCI) (excluding cancer) was calculated to assess comorbidity burden.(12) Clinical characteristics were captured at the time of initial diagnosis and metastatic diagnosis.”
Method
Infective Endocarditis in Cancer Patients ― Causative Organisms, Predisposing Procedures, and Prognosis Differ From Infective Endocarditis in Non-Cancer Patients ―
Kim, K., Kim, D., Lee, S., Cho, I. J., Shim, C. Y., Hong, G., & Ha, J. (2018) · Circulation Journal · doi:10.1253/circj.cj-18-0609 · Cited by 25
Improved access to and continuity of primary care after attachment to a family physician: longitudinal cohort study on centralized waiting lists for unattached patients in Quebec, Canada
Smithman, M. A., Haggerty, J., Gaboury, I., & Breton, M. (2022) · BMC Primary Care · doi:10.1186/s12875-022-01850-4 · Cited by 25
“mortality, but has also been used to predict utilization and provides an assessment disease complexity and burden in administrative data [67, 68].”
Method
Promising algorithms to perilous applications: a systematic review of risk stratification tools for predicting healthcare utilisation
Oddy, C., Zhang, J., Morley, J., & Ashrafian, H. (2024) · BMJ Health & Care Informatics · doi:10.1136/bmjhci-2024-101065 · Cited by 30
Primary anastomosis with a defunctioning stoma versus Hartmann's procedure for perforated diverticulitis—a comparison of stoma reversal rates
Alizai, P. H., Schulze-Hagen, M. F., Klink, C., Ulmer, T. F., Roeth, A. A., Neumann, U. P., Jansen, M., & Rosch, R. (2013) · International Journal of Colorectal Disease · doi:10.1007/s00384-013-1753-2 · Cited by 24
“Comorbidities in both groups were compared using the Charlson comorbidity index [29], a sum score where each comorbid condition is assigned to a score depending on its risk of death.”
Electronic Medication Regimen Complexity Index at admission and complications during hospitalization in medical wards: a tool to improve quality of care?
Lepelley, M., Genty, C., Lecoanet, A., Allenet, B., Bedouch, P., Mallaret, M., Gillois, P., & Bosson, J. (2017) · International Journal for Quality in Health Care · doi:10.1093/intqhc/mzx168 · Cited by 24
Impact of neovascular age-related macular degeneration: burden of patients receiving therapies in Japan
Honda, S., Yanagi, Y., Koizumi, H., Chen, Y., Tanaka, S., Arimoto, M., & Imai, K. (2021) · Scientific Reports · doi:10.1038/s41598-021-92567-4 · Cited by 23
Characteristics of people living with undiagnosed dementia: findings from the CFAS Wales study
Gamble, L. D., Matthews, F. E., Jones, I. R., Hillman, A. E., Woods, B. T., MacLeod, C. A., Martyr, A., Collins, R., Pentecost, C., Rusted, J. M., et al. (2022) · BMC Geriatrics · doi:10.1186/s12877-022-03086-4 · Cited by 25
“The number of health conditions was computed as previously described and in line with the scoring system of the Charlson Comorbidity Index [39, 40].”
Method
Association Between Migraine and Suicidal Behaviors: A Nationwide Study in the USA
Friedman, L. E., Zhong, Q., Gelaye, B., Williams, M. A., & Peterlin, B. L. (2017) · Headache The Journal of Head and Face Pain · doi:10.1111/head.13235 · Cited by 24
Impact of serious mental illness on the treatment and mortality of older patients with locoregional high‐grade (nonmetastatic) prostate cancer: retrospective cohort analysis of 49 985 SEER‐Medicare patients diagnosed between 2006 and 2013
Fried, D. A., Sadeghi‐Nejad, H., Gu, D., Zhou, S., He, W., Giordano, S. H., Pentakota, S. R., Demissie, K., Helmer, D. A., & Shen, C. (2019) · Cancer Medicine · doi:10.1002/cam4.2109 · Cited by 24
Online Supplementary Material
Pant, N., Bushick, K., McAllister, A., Lee, W., Van de Walle, C., & Kioupakis, E. (2015) · The Canadian Journal of Psychiatry · doi:10.1177/070674371506001212 · Cited by 24
The St Vincent's Potentially Inappropriate Medicines Study: Development of a Disease-Specific Consensus List and its Evaluation in Ambulatory Heart Failure Care
Bermingham, M., Ryder, M., Travers, B., Edwards, N., Lalor, L., Kelly, D., Gallagher, J., O’Hanlon, R., McDonald, K., & Ledwidge, M. T. (2014) · European Journal of Heart Failure · doi:10.1002/ejhf.132 · Cited by 24
Patterns of treatment and correction of hyponatremia in intensive care unit patients
Dasta, J. F., Waikar, S. S., Xie, L., Boklage, S., Başer, O., Chiodo, J., & Badawi, O. (2015) · Journal of Critical Care · doi:10.1016/j.jcrc.2015.06.016 · Cited by 23
“Clinical characteristics included modified Charlson Comorbidity Index (CCI) score [23], Acute Physiology and Chronic Health Evaluation (APACHE IV) score [24], Acute Physiology Score [24,25], and Model for End-Stage Liver Disease (MELD) score [26]; outcome variables included hospital and ICU mortality, time to death, a…”
Method
American Society of Anesthesiologists physical status facilitates risk stratification of elderly patients undergoing thoracoscopic lobectomy
Zhang, R., Kyriss, T., Dippon, J., Hansen, M., Boedeker, E., & Friedel, G. (2017) · European Journal of Cardio-Thoracic Surgery · doi:10.1093/ejcts/ezx436 · Cited by 23
“In this study, we adopted an updated version of the CCI that encompassed 23 medical conditions, which are summarized in Table 1 [11].”
Method
Costs of relapsed diffuse large B-cell lymphoma among Medicare patients
Huntington, S. F., Keshishian, A. V., McGuire, M., Xie, L., & Başer, O. (2018) · Leukemia & lymphoma/Leukemia and lymphoma · doi:10.1080/10428194.2018.1459613 · Cited by 23
“Baseline characteristics included demographics (gender, age, race, and US geographic region), comorbidities defined as 1 claims identified via ICD-9-CM diagnosis codes (congestive heart failure, chronic obstructive pulmonary disease, cerebrovascular disease, depression, diabetes, kidney disease, liver disease, periphe…”
Background
Web-based survey to evaluate the prevalence of chronic and subacute cough and patient characteristics in Japan
Tobe, K., Kubo, T., Okuyama, K., Kikuchi, M., Chen, Y., Schelfhout, J. E., Abe, M., & Tokita, S. (2021) · BMJ Open Respiratory Research · doi:10.1136/bmjresp-2020-000832 · Cited by 23
Effect of home-based high-intensity interval training versus moderate-intensity continuous training in patients with myocardial infarction: a randomized controlled trial
Yakut, H., Dursun, H., Felekoğlu, E., Başkurt, A. A., Alpaydın, A. Ö., & Özalevli, S. (2022) · Irish Journal of Medical Science (1971 -) · doi:10.1007/s11845-021-02867-x · Cited by 23
“Comorbidities are scored as 1, 2, 3, and 4, respectively, from mild to severe disease [13].”
Background
Construction and validation of a morbidity index based on the International Classification of Primary Care
Sandvik, H., Ruths, S., Hunskaar, S., Blinkenberg, J., & Hetlevik, Ø. (2022) · Scandinavian Journal of Primary Health Care · doi:10.1080/02813432.2022.2097617 · Cited by 23
The disease burden and quality of life of chronic cough patients in South Korea and Taiwan
Yu, C., Song, W., & Kang, S. H. (2022) · World Allergy Organization Journal · doi:10.1016/j.waojou.2022.100681 · Cited by 23
Activity-related pain predicts pain and functional outcomes in people with knee osteoarthritis: A longitudinal study
Overton, M., Swain, N., Falling, C., Gwynne‐Jones, D., Fillingim, R. B., & Mani, R. (2023) · Frontiers in Pain Research · doi:10.3389/fpain.2022.1082252 · Cited by 27
Delayed surgery is associated with adverse outcomes in patients with hip fracture undergoing hip arthroplasty
Liu, S., Qiang, L., Yang, Q., Fan, L., Wang, J., Yang, Y., Shi, Z., & Li, T. (2023) · BMC Musculoskeletal Disorders · doi:10.1186/s12891-023-06396-9 · Cited by 23
“The strategy described in previous studies was used in this study to assess the severity of these comorbidities [16, 17].”
Method
Resting anal pressure, not outlet obstruction or transit, predicts healthcare utilization in chronic constipation: a retrospective cohort analysis
Staller, K. D., Barshop, K., Kuo, B., & Ananthakrishnan, A. N. (2015) · Neurogastroenterology & Motility · doi:10.1111/nmo.12628 · Cited by 23
Do hospitalists affect clinical outcomes and efficiency for patients with acute upper gastrointestinal hemorrhage (UGIH)?
Go, J. T., Vaughan‐Sarrazin, M., Auerbach, A. D., Schnipper, J. L., Wetterneck, T. B., Gonzalez, D. M., Meltzer, D. O., & Kaboli, P. J. (2010) · Journal of Hospital Medicine · doi:10.1002/jhm.612 · Cited by 23
“Comorbidity was measured using the Charlson comorbidity index.(23) Performance of early endoscopy, usually defined as endoscopy performed within 24 hours from presentation, was previously shown to decrease LOS and need for surgical intervention in patients with acute UGIH.”
Method
Keep it off: A phone-based intervention for long-term weight-loss maintenance
Sherwood, N. E., Crain, A. L., Martinson, B. C., Hayes, M. G., Anderson, J. D., Clausen, J. M., O’Connor, P. J., & Jeffery, R. W. (2011) · Contemporary Clinical Trials · doi:10.1016/j.cct.2011.03.011 · Cited by 23
“Exclusion criteria included 1) history of anorexia nervosa; 2) bariatric surgery; 3) modified Charlson [29] score≥3 (using prior-year diagnoses), non-skin cancer, or congestive heart failure; 4) participation in a phone-based weight-loss program; and 5) current participation in another weight-management researchstudy.”
Payment and economic evaluation of integrated care
Tsiachristas, A. (2015) · International Journal of Integrated Care · doi:10.5334/ijic.2009 · Cited by 23
Medicare Expenditures and Health Care Utilization in a Multiethnic Community-based Population With Dementia From Incidence to Death
Ornstein, K. A., Zhu, C. W., Bollens‐Lund, E., Aldridge, M. D., Andrews, H., Schupf, N., & Stern, Y. (2018) · Alzheimer Disease & Associated Disorders · doi:10.1097/wad.0000000000000259 · Cited by 23
Risk of Psychiatric Disorders in Overactive Bladder Syndrome: A Nationwide Cohort Study in Taiwan
Tzeng, N., Chang, H., Chung, C., Kao, Y., Yeh, H., Yeh, C., Chiang, W.-S., Huang, S., Lu, R., & Chien, W. (2018) · Journal of Investigative Medicine · doi:10.1136/jim-2018-000835 · Cited by 23
Continuity of care for newly diagnosed diabetic patients: A population-based study
Li, Y. (2019) · PLoS ONE · doi:10.1371/journal.pone.0221327 · Cited by 25
Identifying and characterizing cancer survivors in the US primary care safety net
Hoopes, M. J., Schmidt, T. D., Huguet, N., Winters‐Stone, K. M., Angier, H. E., Marino, M., Shannon, J., & DeVoe, J. E. (2019) · Cancer · doi:10.1002/cncr.32295 · Cited by 24
The Complexity of Complex Patients
Safford, M. M. (2015) · Journal of General Internal Medicine · doi:10.1007/s11606-015-3472-6 · Cited by 23
Assessment of Morbidity Over Time in Predicting Health Outcomes
Zeng, C. X., Ellis, J. L., Steiner, J. F., Shoup, J. A., McQuillan, D. B., & Bayliss, E. A. (2014) · Medical Care · doi:10.1097/mlr.0000000000000033 · Cited by 23
Taste alteration and its relationship with nutritional status among cancer patients receiving chemotherapy, cross-sectional study
Al-Amouri, F. M., & Badrasawi, M. (2024) · PLoS ONE · doi:10.1371/journal.pone.0302990 · Cited by 22
Statin use and venous thromboembolism in cancer: A large, active comparator, propensity score matched cohort study
El-Refai, S. M., Black, E. P., Adams, V. R., Talbert, J., & Brown, J. D. (2017) · Thrombosis Research · doi:10.1016/j.thromres.2017.08.001 · Cited by 22
Discontinuity in the Subjective Experience of Self Among People with Mild-To-Moderate Dementia Is Associated with Poorer Psychological Health: Findings from the IDEAL Cohort
Clare, L., Martyr, A., Morris, R. G., & Tippett, L. J. (2020) · Journal of Alzheimer s Disease · doi:10.3233/jad-200407 · Cited by 20
“The number of co-morbid health conditions present alongside dementia was assessed with the Charlson Comorbidity Index [28, 29] and the age-adjusted score calculated.”
Method
Assessing Cancer History Accuracy in Primary Care Electronic Health Records Through Cancer Registry Linkage
Hoopes, M. J., Voss, R., Angier, H. E., Marino, M., Schmidt, T. D., DeVoe, J. E., Soule, J., & Huguet, N. (2020) · JNCI Journal of the National Cancer Institute · doi:10.1093/jnci/djaa210 · Cited by 22
“These included household income as percent of federal poverty level, insurance type, race or ethnicity, preferred language, and Charlson Comorbidity Index (27); all time-varying characteristics were calculated using each patient’s latest visit.”
BackgroundInfluential
Motivation, Physical Activity, and Affect in Community-Dwelling Stroke Survivors: An Ambulatory Assessment Approach
Lau, S. C. L., Connor, L. T., & Baum, C. M. (2023) · Annals of Behavioral Medicine · doi:10.1093/abm/kaac065 · Cited by 24
High-potency statins increase the risk of acute kidney injury: Evidence from a large population-based study
Corrao, G., Soranna, D., Casula, M., Merlino, L. G., Porcellini, M. G., & Catapano, A. L. (2014) · Atherosclerosis · doi:10.1016/j.atherosclerosis.2014.02.022 · Cited by 22
“Information additionally included: 1) the statin employed at starting therapy; 2) use of other drugs such as blood-pressure lowering agents, other cardiovascular, antidiabetic and antidepressant drugs during the 7-year time-window before the index prescription; 3) use of antibiotics and non-steroidal anti-inflammatory…”
Method
Improvements in Heart Rate Variability, Baroreflex Sensitivity, and Sleep After Use of Closed-Loop Allostatic Neurotechnology by a Heterogeneous Cohort
Shaltout, H. A., Lee, S. W., Tegeler, C. L., Hirsch, J. R., Simpson, S. L., Gerdes, L., & Tegeler, C. H. (2018) · Frontiers in Public Health · doi:10.3389/fpubh.2018.00116 · Cited by 22
“An additional model was tested that included age, gender, current beta-blocker usage, and the revised Charlson comorbidity score (25) as covariates.”
Method
Inhospital Complications of Patients With Neuromuscular Disorders Undergoing Total Joint Arthroplasty
Cichos, K. H., Lehtonen, E., McGwin, G., Ponce, B. A., & Ghanem, E. S. (2018) · Journal of the American Academy of Orthopaedic Surgeons · doi:10.5435/jaaos-d-18-00312 · Cited by 22
Factors associated with more frequent diagnostic tests and procedures in patients with irritable bowel syndrome
Lacy, B. E., Ayyagari, R., Guérin, A., Lopez, A., Shi, S., & Luo, M. (2019) · Therapeutic Advances in Gastroenterology · doi:10.1177/1756284818818326 · Cited by 22
Association between quality of care and complications after abdominal surgery
Bergman, S., Deban, M., Martelli, V., Monette, M., Sourial, N., Hamadani, F., Teasdale, D., Holcroft, C., Zakrzewski, H., & Fraser, S. A. (2014) · Surgery · doi:10.1016/j.surg.2013.12.031 · Cited by 22
Oregon Medicaid Expenditures After the 2014 Affordable Care Act Medicaid Expansion
Springer, R., Marino, M., O'Malley, J., Lindner, S., Huguet, N., & DeVoe, J. (2018) · Medical Care · doi:10.1097/mlr.0000000000000907 · Cited by 18
Trends in prevalence and treatment of depressive symptoms in adult patients with epilepsy in the United States
Ajinkya, S., Fox, J., & Lekoubou, A. (2020) · Epilepsy & Behavior · doi:10.1016/j.yebeh.2020.106973 · Cited by 21
The Cost-Effectiveness of Reverse Total Shoulder Arthroplasty Versus Open Reduction Internal Fixation for Proximal Humerus Fractures in the Elderly.
Austin, D. C., Torchia, M. T., Tosteson, A. N. A., Gitajn, I. L., Tapp, S. J., & Bell, J. (2020) · PubMed Central · Cited by 21
Population-based estimates of age and comorbidity specific life expectancy: a first application in Swedish males
Hemelrijck, M. V., Ventimiglia, E., Robinson, D., Gedeborg, R., Holmberg, L., Stattin, P. E., & Garmo, H. (2022) · BMC Medical Informatics and Decision Making · doi:10.1186/s12911-022-01766-0 · Cited by 21
“Charlson Comorbidity Index (CC) [10] was calculated based on data on discharge diagnoses in the National Patient Registry [11].”
Method
Completion of Recommended Tests and Referrals in Telehealth vs In-Person Visits
Zhong, A., Amat, M. J., Anderson, T. S., Shafiq, U., Sternberg, S. B., Salant, T., Fernández, L., Schiff, G. D., Aronson, M. D., Benneyan, J. C., et al. (2023) · JAMA Network Open · doi:10.1001/jamanetworkopen.2023.43417 · Cited by 21
Glycemic Control and Weight Outcomes for Exenatide Once Weekly Versus Liraglutide in Patients with Type 2 Diabetes: A 1-Year Retrospective Cohort Analysis
McAdam‐Marx, C., Nguyen, H. P., Schauerhamer, M. B., Singhal, M., Unni, S. K., Ye, X., & Cobden, D. (2016) · Clinical Therapeutics · doi:10.1016/j.clinthera.2016.11.003 · Cited by 21
“Additional baseline characteristics were captured in the 13 months before the index date to describe the study cohort and to control for confounding, including age, sex, race, baseline HbA1c, body mass index, weight, blood pressure, select comorbidities (by diagnosis codes), and the Charlson Comorbidity Index (CCI).(1…”
Method
Clinical significance of diabetes likely induced by statins: Evidence from a large population-based cohort
Corrao, G., Compagnoni, M. M., Rea, F., Merlino, L. G., Catapano, A. L., & Mancia, G. (2017) · Diabetes Research and Clinical Practice · doi:10.1016/j.diabres.2017.08.008 · Cited by 22
The fat mass index, not the fat-free mass index, is associated with impaired physical performance in older adult subjects: Evidence from a cross-sectional study
Torres, M. R., Valenzuela, R. E. R., Esparza‐Romero, J., López-Teros, M. T., & Alemán-Mateo, H. (2018) · Clinical Nutrition · doi:10.1016/j.clnu.2018.02.013 · Cited by 21
Treatment patterns and survival among older adults in the United States with advanced soft-tissue sarcomas
Parikh, R. C., Lorenzo, M., Hess, L. M., Candrilli, S. D., Nicol, S. J., & Kaye, J. A. (2018) · Clinical Sarcoma Research · doi:10.1186/s13569-018-0094-x · Cited by 21
A Prospective Cohort Study on the Effects of Geriatric Rehabilitation Following Acute Exacerbations of COPD
van Isselt, E. F. V. D., van Eijk, M., van Geloven, N., Groenewegen-Sipkema, K. H., van den Berg, J. W., Nieuwenhuys, C. M. A., Chavannes, N. H., & Achterberg, W. P. (2019) · Journal of the American Medical Directors Association · doi:10.1016/j.jamda.2019.02.025 · Cited by 21
New outcome-specific comorbidity scores excelled in predicting in-hospital mortality and healthcare charges in administrative databases
Shin, J., Kunisawa, S., & Imanaka, Y. (2020) · Journal of Clinical Epidemiology · doi:10.1016/j.jclinepi.2020.06.011 · Cited by 21
Sleep Quality in Patients with Heart Failure in the Spanish Population: A Cross-Sectional Study
Jorge-Samitier, P., Durante, Á., Gea-Caballero, V., Antón‐Solanas, I., Fernández‐Rodrigo, M. T., & Juárez‐Vela, R. (2020) · International Journal of Environmental Research and Public Health · doi:10.3390/ijerph17217772 · Cited by 21
“The Charlson comorbidity index (CCI) predicts the ten-year mortality for a patient who may have a range of comorbid conditions and was used to identify the presence of other pathologies in our sample [24].”
Method
Toxicity-Related Factors Associated With Use of Services Among Community Oncology Patients
Harrison, J. M., Stella, P. J., Lavasseur, B. I., Adams, P. T., Swafford, L., Lewis, J., Mendelsohn‐Victor, K., & Friese, C. R. (2016) · Journal of Oncology Practice · doi:10.1200/jop.2016.010959 · Cited by 21
Nanoray-312: phase III study of NBTXR3 + radiotherapy ± cetuximab in elderly, platinum-ineligible locally advanced HNSCC
Tourneau, C. L., Takácsi‐Nagy, Z., Nuyts, S., Thureau, S., Liu, F., Hoffmann, C., Hackman, T., Lesnik, M., Debard, A., Finzi, L., et al. (2025) · Future Oncology · doi:10.1080/14796694.2025.2496131 · Cited by 20
“…negative prognostic factors, including the majority of patients having a high burden of comorbidities as 67% of patients had an Age-adjusted modified Charlson Comorbidity Index (ACCI) ≥4 [38], which has been shown to correlate with a worse survival for patients with head and neck cancer [32,38,39].”
Real-World Clinical and Economic Outcomes of Liraglutide Versus Sitagliptin in Patients with Type 2 Diabetes Mellitus in the United States
Li, Q., Chitnis, A. S., Hammer, M., & Langer, J. (2014) · Diabetes Therapy · doi:10.1007/s13300-014-0084-9 · Cited by 20
“Baseline clinical characteristics included type of provider for the index therapy (primary care physician, endocrinologists, and other types) and several measures identified over the 6-month washout period: Charlson Comorbidity Index adapted to predict healthcare costs [15], the occurrence of common diabetes-related c…”
Background
Effect of comorbidities and medications on frequency of primary care visits among older patients.
Hu, T., Dattani, N. D., Cox, K. A., Au, B., Xu, L., Melady, D., Jaakkimainen, L., Jain, R., & Charles, J. (2017) · PubMed Central · Cited by 20
A Retrospective Study of Administrative Data to Identify High-Need Medicare Beneficiaries at Risk of Dying and Being Hospitalized
Bélanger, E., Silver, B. C., Meyers, D. J., Rahman, M., Kumar, A., Kosar, C. M., & Mor, V. (2019) · Journal of General Internal Medicine · doi:10.1007/s11606-018-4781-3 · Cited by 20
Treatment Patterns and Outcomes Associated With Palbociclib Plus Letrozole for Postmenopausal Women With HR+/HER2− Advanced Breast Cancer Enrolled in an Expanded Access Program
Brufsky, A., Mitra, D., Davis, K. L., Nagar, S. P., McRoy, L., Cotter, M. J., & Stearns, V. (2019) · Clinical Breast Cancer · doi:10.1016/j.clbc.2019.04.005 · Cited by 20
Early Clinical Prediction of Independent Outdoor Functional Walking Capacity in a Prospective Cohort of Traumatic Spinal Cord Injury Patients
Jean, S., Mac‐Thiong, J., Jean, M.-C., Dionne, A., Bégin, J., & Richard‐Denis, A. (2021) · American Journal of Physical Medicine & Rehabilitation · doi:10.1097/phm.0000000000001812 · Cited by 20
“The ability to predict independent functional walking capacity in the chronic phase as early as possible is a major asset for healthcare professionals and patients alike, as it allows for better planning of rehabilitation resources and helps set realistic expectationswith patients (notably with regard to home accessib…”
Background
Comprehensive Palliative Care Needs in Outpatients with Chronic Heart Failure: A Japanese Cross-Sectional Study
Matsunuma, R., Matsumoto, K., Yamaguchi, T., Sakashita, A., & Kizawa, Y. (2022) · Palliative Medicine Reports · doi:10.1089/pmr.2021.0063 · Cited by 20
“Medication, n (%) ACE 14 (14) ARB 46 (46) b-Blocker 88 (88) MRA 34 (34) Statin 31 (31) Diuretic agents 51 (51)”
Early versus late administration of long-acting injectable antipsychotic agents among patients with newly diagnosed schizophrenia: an analysis of a commercial claims database
Kane, J. M., Chen, A., Lim, S., Mychaskiw, M. A., Tian, M., Wang, Y., Suett, M., & Rubio, J. M. (2023) · International Clinical Psychopharmacology · doi:10.1097/yic.0000000000000452 · Cited by 20
Anxiety, Depression, and Stress Reaction/Adjustment Disorders and Their Associations with Healthcare Resource Utilization and Costs Among Newly Diagnosed Patients With Breast Cancer
Dai, D., Coetzer, H., Zion, S. R., & Malecki, M. J. (2023) · Journal of health economics and outcomes research · doi:10.36469/jheor.2023.70238 · Cited by 20
Health conditions in spousal caregivers of people with dementia and their relationships with stress, caregiving experiences, and social networks: longitudinal findings from the IDEAL programme
Sabatini, S., Martyr, A., Hunt, A., Gamble, L. D., Matthews, F. E., Thom, J. M., Jones, R. W., Allan, L. M., Knapp, M. R. J., Quinn, C., et al. (2024) · BMC Geriatrics · doi:10.1186/s12877-024-04707-w · Cited by 22
“Health conditions were assessed with the Charlson Comorbidity Index (CCI) [53, 54].”
BackgroundMethodInfluential
Mapping the Clinical Chronic Obstructive Pulmonary Disease Questionnaire onto Generic Preference-Based EQ-5D Values
Boland, M. R. S., van Boven, J. F. M., Kocks, J. W. H., van der Molen, T., Goossens, L. M. A., Chavannes, N. H., & Mölken, M. R. (2015) · Value in Health · doi:10.1016/j.jval.2014.11.006 · Cited by 20
“[21] Charlson ME, Charlson RE, Peterson JC, et al.”
BackgroundResult
The pattern of comorbidities in cancer patients in Lagos, South-Western Nigeria
Salako, O., Okediji, P. T., Habeebu, M. Y., Fatiregun, O. A. A., Awofeso, O. M., Okunade, K. S., Odeniyi, I. A., Salawu, K., & Oboh, E. O. (2018) · ecancermedicalscience · doi:10.3332/ecancer.2018.843 · Cited by 20
“The CCI has been used extensively to assess comorbidity burden across populations [33], assess risk of mortality in groups of patients [10], predict costs of treating chronic illnesses [17, 34], and predict a variety of malignancies and other clinical outcomes.”
Method
Advanced Lung Cancer Inflammation Index Predicts Survival Outcomes of Patients With Oral Cavity Cancer Following Curative Surgery
Tsai, Y., Hsu, C., Chang, G., Tsai, M., Lee, Y., Huang, E. I., Lai, C., & Fang, K. (2021) · Frontiers in Oncology · doi:10.3389/fonc.2021.609314 · Cited by 20
Prevalence of Chronic Pain in a Large Integrated Healthcare Delivery System in the U.S.A
Lamerato, L. E., Dryer, R. D., Wolff, G. G., Hegeman‐Dingle, R., Mardekian, J., Park, P. W., & Zlateva, G. (2015) · Pain Practice · doi:10.1111/papr.12334 · Cited by 20
“pain diagnosis, the database was queried to obtain the number of pain conditions, the number of neuropathic pain conditions, and the presence/absence of medical conditions as defined by the Charlson comorbidity index and score.(9) The period of 6 months pre-index was used for identification of comorbid conditions, inc…”
Method
Investigating the association between medication adherence and health-related quality of life in COPD: Methodological challenges when using a proxy measure of adherence
Boland, M. R. S., van Boven, J. F. M., Kruis, A. L., Chavannes, N. H., van der Molen, T., Goossens, L. M. A., & Mölken, M. R. (2015) · Respiratory Medicine · doi:10.1016/j.rmed.2015.11.008 · Cited by 21
“the FEV1%pred at baseline, the total exacerbation rate (moderate or severe) in the 12months prior to the adherencemeasurement, theMRC dyspnoea scale [23] at the start of the adherence measurement and the Charlson comorbidity index at baseline [24].”
BackgroundMethod
Cost of Herpes Zoster in Patients With Selected Immune-Compromised Conditions in the United States
Li, Q., Chen, S.-Y., Burstin, S., Levin, M., & Suaya, J. (2016) · Open Forum Infectious Diseases · doi:10.1093/ofid/ofw067 · Cited by 19
“The Charlson Comorbidity Index (CCI) adapted to predict healthcare costs were estimated based on medical claims during the 6-month preindex period [15].”
Method
Association of the Charlson Comorbidity Index with Renal Outcome and All-Cause Mortality in Antineutrophil Cytoplasmatic Antibody-Associated Vasculitis
Shiber, S., & Molad, Y. (2014) · Medicine · doi:10.1097/md.0000000000000152 · Cited by 20
Adverse events, resource use, and economic burden associated with mantle cell lymphoma: a real-world assessment of privately insured patients in the United States
Goyal, R., Nagar, S. P., Kabadi, S., Kaye, J. A., Seal, B. S., & Mato, A. R. (2018) · Leukemia & lymphoma/Leukemia and lymphoma · doi:10.1080/10428194.2018.1509320 · Cited by 20
“Demographic and other baseline characteristics, including Charlson Comorbidity Index (CCI) score, were assessed on the index date or during the 12month baseline period [14].”
Method
The economic burden of subjective cognitive decline, mild cognitive impairment and Alzheimer's dementia: excess costs and associated clinical and risk factors
Gläser, E., Kilimann, I., Platen, M., Hoffmann, W. U., Brosseron, F., Büerger, K., Coenjaerts, M., Düzel, E., Ewers, M., Fließbach, K., et al. (2025) · Alzheimer s Research & Therapy · doi:10.1186/s13195-025-01785-9 · Cited by 19
Impacts of the Affordable Care Act on Receipt of Women's Preventive Services in Community Health Centers in Medicaid Expansion and Nonexpansion States
Hatch, B., Hoopes, M. J., Darney, B. G., Marino, M., Templeton, A. R., Schmidt, T. D., & Cottrell, E. (2020) · Women s Health Issues · doi:10.1016/j.whi.2020.08.011 · Cited by 19
“Women from expansion state CHCs had slightly higher levels of medical complexity (Charlson Comorbidity Index ≥3: 21.5% vs. 16.9% of nonexpansion patients), as well as higher ambulatory visit rates (mean annual visits, 2.9 expansion vs. 2.1 nonexpansion).”
MethodInfluential
Antiplatelet therapy contributes to a higher risk of traumatic intracranial hemorrhage compared to anticoagulation therapy in ground-level falls: a single-center retrospective study
Vedin, T., Forberg, J. L., Anefjäll, E., Lehtinen, R., Faisal, M., & Edelhamre, M. (2022) · European Journal of Trauma and Emergency Surgery · doi:10.1007/s00068-022-02016-8 · Cited by 19
Herpes Zoster Incidence and Burden in Adults With Type 2 Diabetes in the U.S.: A Retrospective Database Analysis
Poirrier, J., Meyers, J., Nagar, S. P., Patterson, B. J., Glasser, L., & Jabbour, S. A. (2022) · Diabetes Care · doi:10.2337/dc21-2053 · Cited by 22
“Covariates included in propensity score matching included age, sex, health plan type, modified Charlson-Quan comorbidity index (CCI) score (18,19), and baseline health care costs (as measured in the 12 months prior to the index date).”
Method
Patterns of Comorbidity and Multimorbidity Among Patients With Multiple Sclerosis in a Large US Commercially Insured and Medicare Advantage Population
Dai, D., Sharma, A. K., Phillips, A. L., & Lobo, C. P. (2022) · Journal of health economics and outcomes research · doi:10.36469/jheor.2022.38669 · Cited by 19

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