Hostname: page-component-78c5997874-v9fdk Total loading time: 0 Render date: 2024-11-17T14:53:10.445Z Has data issue: false hasContentIssue false

The impact of psychiatric and medical comorbidity on the risk of mortality: a population-based analysis

Published online by Cambridge University Press:  28 November 2019

Simon J. C. Davies*
Affiliation:
Centre for Addiction and Mental Health, Toronto, Ontario, Canada Department of Psychiatry, University of Toronto, Toronto, Ontario, Canada
Tomisin Iwajomo
Affiliation:
Centre for Addiction and Mental Health, Toronto, Ontario, Canada Institute of Clinical Evaluative Sciences, Toronto, Ontario, Canada
Claire de Oliveira
Affiliation:
Centre for Addiction and Mental Health, Toronto, Ontario, Canada Institute of Clinical Evaluative Sciences, Toronto, Ontario, Canada Institute of Health Policy, Management and Evaluation, University of Toronto, Toronto, Ontario, Canada
Judith Versloot
Affiliation:
Institute of Health Policy, Management and Evaluation, University of Toronto, Toronto, Ontario, Canada Institute for Better Health, Mississauga, Ontario, Canada
Robert J. Reid
Affiliation:
Institute of Health Policy, Management and Evaluation, University of Toronto, Toronto, Ontario, Canada Institute for Better Health, Mississauga, Ontario, Canada
Paul Kurdyak
Affiliation:
Centre for Addiction and Mental Health, Toronto, Ontario, Canada Department of Psychiatry, University of Toronto, Toronto, Ontario, Canada Institute of Clinical Evaluative Sciences, Toronto, Ontario, Canada Institute of Health Policy, Management and Evaluation, University of Toronto, Toronto, Ontario, Canada
*
Author for correspondence: Simon J. C. Davies, E-mail: simon_davies@camh.net

Abstract

Background

As life expectancy increases, more people have chronic psychiatric and medical health disorders. Comorbidity may increase the risk of premature mortality, an important challenge for health service delivery.

Methods

Population-based cohort study in Ontario, Canada of all 11 246 910 residents aged ⩾16 and <105 on 1 April 2012 and alive on 31 March 2014. Secondary analyses included subjects having common medical disorders in 10 separate cohorts. Exposures were psychiatric morbidity categories identified using aggregated diagnosis groups (ADGs) from Johns Hopkins Adjusted Clinical Groups software® (v10.0); ADG 25: Persistent/Recurrent unstable conditions; e.g. acute schizophrenic episode, major depressive disorder (recurrent episode), ADG 24: Persistent/Recurrent stable conditions; e.g. depressive disorder, paranoid personality disorder, ADG 23: Time-limited/minor conditions; e.g. adjustment reaction with brief depressive reaction. The outcome was all-cause mortality (April 2014–March 2016).

Results

Over 2 years' follow-up, there were 188 014 deaths (1.7%). ADG 25 conferred an almost threefold excess mortality after adjustment compared to having no psychiatric morbidity [adjusted hazard ratio 2.94 (95% CI 2.91–2.98, p < 0.0001)]. Adjusted hazard ratios for ADG 24 and ADG 23 were 1.12 (95% CI 1.11–1.14, p < 0.0001) and 1.31 (95% CI 1.26–1.36, p < 0.0001). In all 10 medical disorder cohorts, ADG 25 carried significantly greater mortality risk compared to no psychiatric comorbidity.

Conclusions

Psychiatric disorders, particularly those graded persistent/recurrent and unstable, were associated with excess mortality in the whole population, and in the medical disorder cohorts examined. Future research should examine whether service design accounting for psychiatric disorder comorbidity improves outcomes across the spectrum of medical disorders.

Type
Original Articles
Copyright
Copyright © Cambridge University Press 2019

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

Antoniou, T, Zagorski, B, Loutfy, MR, Strike, C and Glazier, RH (2011) Validation of case-finding algorithms derived from administrative data for identifying adults living with human immunodeficiency virus infection. PLoS ONE 6, e21748.CrossRefGoogle ScholarPubMed
Austin, PC, Daly, PA and Tu, JV (2002) A multicenter study of the coding accuracy of hospital discharge administrative data for patients admitted to cardiac care units in Ontario. American Heart Journal 144, 290296.CrossRefGoogle ScholarPubMed
Austin, PC, Newman, A and Kurdyak, PA (2012 a) Using the Johns Hopkins Aggregated Diagnosis Groups (ADGs) to predict mortality in a population-based cohort of adults with schizophrenia in Ontario, Canada. Psychiatry Research 196, 3237.CrossRefGoogle Scholar
Austin, PC, Shah, BR, Newman, A and Anderson, GM (2012 b) Using the Johns Hopkins’ Aggregated Diagnosis Groups (ADGs) to predict 1-year mortality in population-based cohorts of patients with diabetes in Ontario, Canada. Diabetic Medicine 29, 11341141.CrossRefGoogle ScholarPubMed
Barnett, K, Mercer, SW, Norbury, M, Watt, G, Wyke, S and Guthrie, B (2012) Epidemiology of multimorbidity and implications for health care, research, and medical education: a cross-sectional study. Lancet 380, 3743.CrossRefGoogle ScholarPubMed
Benchimol, EI, Guttmann, A, Mack, DR, Nguyen, GC, Marshall, JK, Gregor, JC, Wong, J, Forster, AJ and Manuel, DG (2014) Validation of international algorithms to identify adults with inflammatory bowel disease in health administrative data from Ontario, Canada. Journal of Clinical Epidemiology 67, 887896.CrossRefGoogle ScholarPubMed
Bondesson, E, Larrosa Pardo, F, Stigmar, K, Ringqvist, Å, Petersson, IF, Jöud, A and Schelin, MEC (2018) Comorbidity between pain and mental illness – evidence of a bidirectional relationship. European Journal of Pain 22, 13041311.CrossRefGoogle ScholarPubMed
Boyd, C and Fortin, M (2010) Future of multimorbidity research: how should understanding of multimorbidity inform health system design? Public Health Reviews 32, 451474.CrossRefGoogle Scholar
Chiu, M, Lebenbaum, M, Lam, K, Chong, N, Azimaee, M, Iron, K, Manuel, D and Guttmann, A (2016) Describing the linkages of the immigration, refugees and citizenship Canada permanent resident data and vital statistics death registry to Ontario's administrative health database. BMC Medical Informatics and Decision Making 16, 135.CrossRefGoogle ScholarPubMed
Chwastiak, L, Vanderlip, E and Katon, W (2014) Treating complexity: collaborative care for multiple chronic conditions. International Review of Psychiatry 26, 638647.CrossRefGoogle ScholarPubMed
Colton, C and Manderscheid, RW (2006) Congruencies in increased mortality rates, years of potential life lost, and causes of death among public mental health clients in eight states. Preventing Chronic Disease 3, A42.Google ScholarPubMed
Druss, BG (2007) Improving medical care for persons with serious mental illness: challenges and solutions. Journal of Clinical Psychiatry 68(suppl. 4), 4044.Google ScholarPubMed
Fors, BM, Isacson, D, Bingefors, K and Widerlov, B (2007) Mortality among persons with schizophrenia in Sweden: an epidemiological study. Nordic Journal of Psychiatry 61, 252259.CrossRefGoogle ScholarPubMed
Gatov, E, Rosella, L, Chiu, M and Kurdyak, PA (2017) Trends in standardized mortality among individuals with schizophrenia, 1993-2012: a population-based, repeated cross-sectional study. Canadian Medical Association Journal 189, E1177E1187.CrossRefGoogle ScholarPubMed
Gershon, A, Wang, C, Guan, J, Vasilevska-Ristovska, J, Cicutto, L and To, T (2009 a) Identifying individuals with physcian diagnosed COPD in health administrative databases. COPD: Journal of Chronic Obstructive Pulmonary Disease 6, 388394.CrossRefGoogle ScholarPubMed
Gershon, AS, Wang, C, Guan, J, Vasilevska-Ristovska, J, Cicutto, L and To, T (2009 b) Identifying patients with physician-diagnosed asthma in health administrative databases. Canadian Respiratory Journal 16, 183188.CrossRefGoogle ScholarPubMed
Goodrich, DE, Kilbourne, AM, Nord, KM and Bauer, MS (2013) Mental health collaborative care and its role in primary care settings. Current Psychiatry Reports 15, 383.CrossRefGoogle ScholarPubMed
Gulland, A (2016) Action is urged to improve physical health in severe mental illness. British Medical Journal 355, i5729.CrossRefGoogle ScholarPubMed
Hall, S, Schulze, K, Groome, P, Mackillop, W and Holowaty, E (2006) Using cancer registry data for survival studies: the example of the Ontario Cancer Registry. Journal of Clinical Epidemiology 59, 6776.CrossRefGoogle Scholar
Hux, JE, Ivis, F, Flintoft, V and Bica, A (2002) Diabetes in Ontario Determination of prevalence and incidence using a validated administrative data algorithm. Diabetes Care 25, 512516.CrossRefGoogle ScholarPubMed
Joukamaa, M, Heliovaara, M, Knekt, P, Aromaa, A, Raitasalo, R and Lehtinen, V (2006) Schizophrenia, neuroleptic medication and mortality. British Journal of Psychiatry 188, 122127.CrossRefGoogle ScholarPubMed
Katon, W, Fan, M-Y, Unützer, J, Taylor, J, Pincus, H and Schoenbaum, M (2008) Depression and diabetes: a potentially lethal combination. Journal of General Internal Medicine 23, 15711575.CrossRefGoogle ScholarPubMed
Kurdyak, P, Vigod, S, Duchen, R, Jacob, B, Stukel, T and Kiran, T (2017) Diabetes quality of care and outcomes: comparison of individuals with and without schizophrenia. General Hospital Psychiatry 46, 713.CrossRefGoogle ScholarPubMed
Laursen, TM, Munk-Olsen, T, Nordentoft, M and Mortensen, PB (2007) Increased mortality among patients admitted with major psychiatric disorders: a register-based study comparing mortality in unipolar depressive disorder, bipolar affective disorder, schizoaffective disorder, and schizophrenia. Journal of Cliical Psychiatry 68, 899907.CrossRefGoogle Scholar
Mathers, CD and Loncar, D (2006) Projections of global mortality and burden of disease from 2002 to 2030. PLoS Medicine 3, e442.CrossRefGoogle ScholarPubMed
Mercer, SW, Gunn, J, Bower, P, Wyke, S and Guthrie, B (2012) Managing patients with mental and physical multimorbidity. British Medical Journal 345, e5559.CrossRefGoogle ScholarPubMed
Pan, A, Lucas, M, Sun, Q, van Dam, RM, Franco, OH, Manson, JE, Willett, WC, Ascherio, A and Hu, FB (2010) Bidirectional association between depression and type 2 diabetes mellitus in women. Archives of Internal Medicine 170, 18841891.CrossRefGoogle ScholarPubMed
Schultz, SE, Rothwell, DM, Chen, Z and Tu, K (2013) Identifying cases of congestive heart failure from administrative data: a validation study using primary care patient records. Chronic Diseases and Injuries in Canada 33, 160166.CrossRefGoogle ScholarPubMed
Statistics Canada (2006) Census of Population. Available at http://www12.statcan.gc.ca/census-recensement/2006/index-eng.cfm (Accessed 21 August 2018).Google Scholar
Thornicroft, G (2011) Physical health disparities and mental illness: the scandal of premature mortality. British Journal of Psychiatry 199, 441442.CrossRefGoogle ScholarPubMed
Tu, K, Campbell, NR, Chen, Z-L, Cauch-Dudek, KJ and McAlister, FA (2007) Accuracy of administrative databases in identifying patients with hypertension. Open Medicine 1, e18e26.Google ScholarPubMed
Unützer, J and Ratzliff, AH (2015) Evidence base and core principles. In Raney LE (ed.) Integrated Care: Working at the Interface of Primary Care and Behavioral Health. Arlington, VA: American Psychiatric Publishing, pp. 316.Google Scholar
Wahlbeck, K, Westman, J, Nordentoft, M, Gissler, M and Laursen, TM (2011) Outcomes of Nordic mental health systems: life expectancy of patients with mental disorders. British Journal of Psychiatry 199, 453458.CrossRefGoogle ScholarPubMed
Weiner, JP (ed.) (2011) The Johns Hopkins ACG® System, technical reference guide, version 10.0. Baltimore, MD: Johns Hopkins Bloomberg School of Public Health.Google Scholar
Wells, K, Golding, J and Burnam, M (1998) Psychiatric disorder in a sample of the general population with and without chronic medical conditions. American Journal of Psychiatry 145, 976998.Google Scholar
Widdifield, J, Bombardier, C, Bernatsky, S, Paterson, JM, Green, D, Young, J, Ivers, N, Butt, DA, Jaakkimainen, RL, Thorne, JC and Tu, K (2014) An administrative data validation study of the accuracy of algorithms for identifying rheumatoid arthritis: the influence of the reference standard on algorithm performance. BMC Musculoskeletal Disorders 15, 216.CrossRefGoogle ScholarPubMed
Supplementary material: File

Davies et al. supplementary material

Davies et al. supplementary material

Download Davies et al. supplementary material(File)
File 737.2 KB