Prevalence of multimorbidity in medical inpatients
OBJECTIVE: To validate the estimates of the prevalence of multimorbidity based on administrative hospital discharge data, with medical records and chart reviews as benchmarks.
DESIGN: Retrospective cohort study.
SETTING: Medical division of a tertiary care teaching hospital.
PARTICIPANTS: A total of 170 medical inpatients admitted from the emergency unit in January 2009.
MAIN MEASURES: The prevalence of multimorbidity for three different definitions (≥2 diagnoses, ≥2 diagnoses from different ICD-10 chapters, and ≥2 medical conditions as defined by Charlson/Deyo) and three different data sources (administrative data, chart reviews, and medical records).
RESULTS: The prevalence of multimorbidity in medical inpatients derived from administrative data, chart reviews and medical records was very high and concurred for the different definitions of multimorbidity (≥2 diagnoses: 96.5%, 95.3%, and 92.9% [p = 0.32], ≥2 diagnoses from different ICD-10 chapters: 86.5%, 90.0%, and 85.9% [p = 0.46], and ≥2 medical conditions as defined by Charlson/Deyo: 48.2%, 50.0%, and 46.5% [p = 0.81]). The agreement of rating of multimorbidity for administrative data and chart reviews and administrative data and medical records was 94.1% and 93.0% (kappa statistics 0.47) for ≥2 diagnoses; 86.0% and 86.5% (kappa statistics 0.52) for ≥2 diagnoses from different ICD-10 chapters; and 82.9% and 85.3% (kappa statistics 0.69) for ≥2 medical conditions as defined by Charlson/Deyo.
CONCLUSION: Estimates of the prevalence of multimorbidity in medical inpatients based on administrative data, chart reviews and medical records were very high and congruent for the different definitions of multimorbidity. Agreement for rating multimorbidity based on the different data sources was moderate to good. Administrative hospital discharge data are a valid source for exploring the burden of multimorbidity in hospital settings.
- van den Akker M, Buntinx F, Metsemakers JF, Roos S, Knottnerus JA. Multimorbidity in general practice: prevalence, incidence, and determinants of co-occurring chronic and recurrent diseases. J Clin Epidemiol. 1998;51(5):367–75.
- van den Akker M, Buntinx F, Knottnerus JA. Comorbidity or multimorbidity: What’s in the name? A review of literature. Eur J Gen Pract. 1996;2(2):65–70.
- De Groot V, Beckerman H, Lankhorst GJ, Bouter LM. How to measure comorbidity: A critical review of available methods. J Clin Epidemiol. 2003;56(3):221–9.
- Schneider KM, O’Donnell BE, Dean D. Prevalence of multiple chronic conditions in the United States' Medicare population. Health Qual Life Outcomes. 2009;7:82.
- Laux G, Rosemann T, Korner T, Heiderhoff M, Schneider A, et al. Detailed data collection regarding the utilization of medical services, morbidity, course of illness and outcomes by episode-based documentation in general practices within the CONTENT project. Gesundheitswesen. 2007;69(5):284–91.
- Marengoni A, Winblad B, Karp A, Fratiglioni L. Prevalence of chronic diseases and multimorbidity among the elderly population in Sweden. Am J Public Health. 2008;98(7):1198–1200.
- Laux G, Kuehlein T, Rosemann T, Szecsenyi J. Co- and multimorbidity patterns in primary care based on episodes of care: results from the German CONTENT project. BMC Health Serv Res. 2008;8:14.
- Marengoni A, Angleman S, Melis R, Mangialasche F, Karp A, et al. Ageing with multimorbidity: a systematic review of the literature. Ageing Res Rev. 2011;10(4):430–9.
- John R, Kerby DS, Hennessy CH. Patterns and impact of comorbidity and multimorbidity among community-resident american indian elders. Gerontologist. 2003;43(5):649–60.
- Walker AE. Multiple chronic diseases and quality of life: patterns emerging from a large national sample, Australia. Chronic Illn. 2007;3(3):202–18.
- Loza E, Jover JA, Rodriguez L, Carmona L. Multimorbidity: prevalence, effect on quality of life and daily functioning, and variation of this effect when one condition is a rheumatic disease. Semin Arthritis Rheum. 2009;38(4):312–9.
- Fortin M, Bravo G, Hudon C, Vanasse A, Lapointe L. Prevalence of multimorbidity among adults seen in family practice. Ann Fam Med. 2005;3(3):223–8.
- Uijen AA, van de Lisdonk EH. Multimorbidity in primary care: prevalence and trend over the last 20 years. Eur J Gen Pract. 2008;14(Suppl 1):28–32.
- Wolff JL, Starfield B, Anderson G. Prevalence, expenditures, and complications of multiple chronic conditions in the elderly. Arch Intern Med. 2002;162(20):2269–76.
- Schram MT, Frijters D, van de Lisdonk EH, Ploemacher J, de Craen AJ, et al. Setting and registry characteristics affect the prevalence and nature of multimorbidity in the elderly. J Clin Epidemiol. 2008;61(11):1104–12.
- Horschik D. Die Bedeutung der Polymorbidität im internistischen Krankengut. Medizinische Fakultät. 2000;Universitätsspital Zürich.
- Charlson ME, Pompei P, Ales KL, MacKenzie CR. A new method of classifying prognostic comorbidity in longitudinal studies: development and validation. J Chronic Dis. 1987;40(5):373–83.
- Ramiarina RA, Ramiarina BL, Almeida RM, Pereira WC. Comorbidity adjustment index for the international classification of diseases, 10th revision. Rev Saude Publica. 2008;42(4):590–7.
- Needham DM, Scales DC, Laupacis A, Pronovost PJ. A systematic review of the Charlson comorbidity index using Canadian administrative databases: a perspective on risk adjustment in critical care research. J Crit Care. 2005;20(1):12–9.
- Quan H, Parsons GA, Ghali WA. Validity of information on comorbidity derived rom ICD-9-CCM administrative data. Med Care. 2002;40(8):675–85.
- Malenka DJ, McLerran D, Roos N, Fisher ES, Wennberg JE. Using administrative data to describe casemix: a comparison with the medical record. J Clin Epidemiol. 1994;47(9):1027–32.
- Kieszak SM, Flanders WD, Kosinski AS, Shipp CC, Karp H. A comparison of the Charlson comorbidity index derived from medical record data and administrative billing data. J Clin Epidemiol. 1999;52(2):137–42.
- Humphries KH, Rankin JM, Carere RG, Buller CE, Kiely FM, et al. Co-morbidity data in outcomes research: are clinical data derived from administrative databases a reliable alternative to chart review? J Clin Epidemiol. 2000;53(4):343–9.
- Jollis JG, Ancukiewicz M, DeLong ER, Pryor DB, Muhlbaier LH, et al. Discordance of databases designed for claims payment versus clinical information systems. Implications for outcomes research. Ann Intern Med. 1993;119(8):844–50.
- Wong A, Boshuizen HC, Schellevis FG, Kommer GJ, Polder JJ. Longitudinal administrative data can be used to examine multimorbidity, provided false discoveries are controlled for. J Clin Epidemiol. Mar 29 2011.
- Yiannakoulias N, Svenson LW, Hill MD, Schopflocher DP, Rowe BH, et al. Incident cerebrovascular disease in rural and urban Alberta. Cerebrovasc Dis. 2004;17(1):72–8.
- Iezzoni LI. Assessing quality using administrative data. Ann Intern Med. 1997;127(8 Pt 2):666–74.