Multimorbidity and healthcare utilisation among high-cost patients in the US Veterans Affairs Health Care System
Donna M Zulman, Christine Pal Chee, Todd H Wagner, Jean Yoon, Danielle M Cohen, Tyson H Holmes, Christine Ritchie, Steven M Asch, Donna M Zulman, Christine Pal Chee, Todd H Wagner, Jean Yoon, Danielle M Cohen, Tyson H Holmes, Christine Ritchie, Steven M Asch
Abstract
Objectives: To investigate the relationship between multimorbidity and healthcare utilisation patterns among the highest cost patients in a large, integrated healthcare system.
Design: In this retrospective cross-sectional study of all patients in the U.S. Veterans Affairs (VA) Health Care System, we aggregated costs of individuals' outpatient and inpatient care, pharmacy services and VA-sponsored contract care received in 2010. We assessed chronic condition prevalence, multimorbidity as measured by comorbidity count, and multisystem multimorbidity (number of body systems affected by chronic conditions) among the 5% highest cost patients. Using multivariate regression, we examined the association between multimorbidity and healthcare utilisation and costs, adjusting for age, sex, race/ethnicity, marital status, homelessness and health insurance status.
Setting: USA VA Health Care System.
Participants: 5.2 million VA patients.
Measures: Annual total costs; absolute and share of costs generated through outpatient, inpatient, pharmacy and VA-sponsored contract care; number of visits to primary, specialty and mental healthcare; number of emergency department visits and hospitalisations.
Results: The 5% highest cost patients (n=261,699) accounted for 47% of total VA costs. Approximately two-thirds of these patients had chronic conditions affecting ≥3 body systems. Patients with cancer and schizophrenia were less likely to have documented comorbid conditions than other high-cost patients. Multimorbidity was generally associated with greater outpatient and inpatient utilisation. However, increased multisystem multimorbidity was associated with a higher outpatient share of total costs (1.6 percentage points per affected body system, p<0.01) but a lower inpatient share of total costs (-0.6 percentage points per affected body system, p<0.01).
Conclusions: Multisystem multimorbidity is common among high-cost VA patients. While some patients might benefit from disease-specific programmes, for most patients with multimorbidity there is a need for interventions that coordinate and maximise efficiency of outpatient services across multiple conditions.
Keywords: GERIATRIC MEDICINE; HEALTH SERVICES ADMINISTRATION & MANAGEMENT; PRIMARY CARE.
Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://group.bmj.com/group/rights-licensing/permissions.
Figures
References
- Cohen S, Uberoi N. Differentials in the concentration in the level of health expenditures across population subgroups in the U.S., 2010. Rockville, MD: Agency for Healthcare Research and Quality Statistical Brief #421, 2013. (accessed 22 Jan 15).
- Joynt K, Gawande AA, Orav E et al. . Contribution of preventable acute care spending to total spending for high-cost Medicare patients. JAMA 2013;309:2572–8. 10.1001/jama.2013.7103
- Sommers A, Cohen M. Medicaid's High Cost Enrollees: How Much Do They Drive Program Spending? Washington, DC: Kaiser Commission for Medicaid and the Uninsured, 2006.
- Garber AM, MaCurdy TE, McClellan MB. Persistence of Medicare expenditures among elderly beneficiaries. In: Garber AM, ed. Frontiers in Health Policy Research. Vol 1 Cambridge, MA: MIT, 1998:153–80.
- Cohen S, Yu W. AHRQ Statistical Brief #354: The concentration and persistence in the level of health expenditures over time: Estimates for the US population, 2008–2009 2012. (accessed 28 Nov 2012).
- Coughlin T, Long S. Health care spending and service use among high-cost Medicaid beneficiaries, 2002–2004. Inquiry 2009;46:405–17.
- Hasselman D. Super-Utilizer Summit: Common Themes from Innovative Complex Care Management Programs. Hamilton, NJ: Center for Health Care Strategies, Inc., 2013.
- Kronick RG, Bella M, Gilmer TP et al. . The Faces of Medicaid II: recognizing the care needs of people with multiple chronic conditions. Center for Health Care Strategies, Inc., 2007.
- Powers BW, Chaguturu SK, Ferris TG. Optimizing high-risk care management. JAMA 2015;313:795–6. 10.1001/jama.2014.18171
- Centers for Medicare and Medicaid Services. Chronic Conditions among Medicare Beneficiaries. Chartbook: 2012 Edition. (accessed 2 Apr 2015).
- Kizer KW, Dudley RA. Extreme makeover: transformation of the veterans health care system. Annu Rev Public Health 2009;30:313–39. 10.1146/annurev.publhealth.29.020907.090940
- Asch SM, McGlynn EA, Hogan MM et al. . Comparison of quality of care for patients in the Veterans Health Administration and patients in a national sample. Ann Intern Med 2004;141:938–45. 10.7326/0003-4819-141-12-200412210-00010
- Phibbs CS, Bhandari A, Yu W et al. . Estimating the costs of VA ambulatory care. Med Care Res Rev 2003;60(3 Suppl):54–73. 10.1177/1077558703256725
- Wagner TH, Chen S, Barnett PG. Using average cost methods to estimate encounter-level costs for medical-surgical stays in the VA. Med Care Res Rev 2003;60(3 Suppl):15S–36S. 10.1177/1077558703256485
- Yu W, Wagner TH, Chen S et al. . Average cost of VA rehabilitation, mental health, and long-term hospital stays. Med Care Res Rev 2003;60(3 Suppl):40S–53S. 10.1177/1077558703256724
- Yoon J, Scott J, Phibbs CS et al. . Recent trends in Veterans Affairs chronic condition spending. Popul Health Manag 2011;14:293–8. 10.1089/pop.2010.0079
- Demakis J, McQueen L, Kizer K et al. . Quality Enhancement Research Initiative (QUERI): a collaboration between research and clinical practice. Med Care 2000;38(6 Suppl 1):I17–25. 10.1097/00005650-200006001-00003
- Yu W, Ravelo A, Wagner TH et al. . Prevalence and costs of chronic conditions in the VA health care system. Med Care Res Rev 2003;60(3 Suppl):146S–67S. 10.1177/1077558703257000
- Yoon J, Zulman D, Scott JY et al. . Costs associated with multimorbidity among VA patients. Med Care 2014;52(Suppl 3):S31–6. 10.1097/MLR.0000000000000061
- Agency for Healthcare Research and Quality. HCUP Chronic Condition Indicator. Healthcare Cost and Utilization Project (HCUP) 2011. (accessed 17 Jul 2013).
- Steinman MA, Lee SJ, Boscardin WJ et al. . Patterns of multimorbidity in elderly veterans. J Am Geriatr Soc 2012;60:1872–80. 10.1111/j.1532-5415.2012.04158.x
- Papke LE, Wooldridge JM. Econometric methods for fractional response variables with an application to 401 (K) plan participation rates. J Appl Econ 1996;11:619–32. 10.1002/(SICI)1099-1255(199611)11:6<619::AID-JAE418>;2-1
- Smith S, Soubhi H, Fortin M et al. . Interventions for improving outcomes in patients with multimorbidity in primary care and community settings. Cochrane Database Syst Rev 2012;4:CD006560.
- Grant RW, Adams AS, Bayliss EA et al. . Establishing visit priorities for complex patients: a summary of the literature and conceptual model to guide innovative interventions. Healthcare 2013;1:117–22. 10.1016/j.hjdsi.2013.07.008
- Guiding Principles for the Care of Older Adults with Multimorbidity: An Approach for Clinicians. American Geriatrics Society Expert Panel on the Care of Older Adults with Multimorbidity. J Am Geriatr Soc 2012;60:E1–25. 10.1111/j.1532-5415.2012.04188.x
- Peterson D, Helfand M, Humphrey L et al. . Evidence Brief: Effectiveness of Intensive Primary Care Programs, VA-ESP Project #09–199. 2012.
- Brown RS, Peikes D, Peterson G et al. . Six features of Medicare coordinated care demonstration programs that cut hospital admissions of high-risk patients. Health Affairs (Project Hope) 2012;31:1156–66. 10.1377/hlthaff.2012.0393
- Boyd C, Leff B, Weiss C et al. . Clarifying multimorbidity patterns to improve targeting and delivery of clinical services for Medicaid populations. Center for Health Care Strategies, Inc., 2010.
- Hutter N, Schnurr A, Baumeister H. Healthcare costs in patients with diabetes mellitus and comorbid mental disorders—a systematic review. Diabetologia 2010;53:2470–9. 10.1007/s00125-010-1873-y
- Molosankwe I, Patel A, Jose Gagliardino J et al. . Economic aspects of the association between diabetes and depression: a systematic review. J Affect Disord 2012;142(Suppl):S42–55. 10.1016/S0165-0327(12)70008-3
- Hutter N, Knecht A, Baumeister H. Health: care costs in persons with asthma and comorbid mental disorders: a systematic review. Gen Hosp Psychiatry 2011;33:443–53. 10.1016/j.genhosppsych.2011.06.013
- Yohannes AM, Willgoss TG, Baldwin RC et al. . Depression and anxiety in chronic heart failure and chronic obstructive pulmonary disease: prevalence, relevance, clinical implications and management principles. Int J Geriatric Psychiatry 2010;25:1209–21. 10.1002/gps.2463
- Medicare Payment Advisory Commission. Issues for risk adjustment in Medicare Advantage. Report to Congress: Medicare and the Health Care Delivery System Washington, DC, 2012.
- Chapko MK, Liu CF, Perkins M et al. . Equivalence of two healthcare costing methods: bottom-up and top-down. Health Econ 2009;18:1188–201. 10.1002/hec.1422
- Newcomer R, Clay T, Luxenberg JS et al. . Misclassification and selection bias when identifying Alzheimer's disease solely from Medicare claims records. J Am Geriatr Soc 1999;47:215–19.
Source: PubMed