Health care service use and costs for a cohort of high-needs elderly diabetic patients

Published:December 25, 2020DOI:


      • A correlation emerged between diabetes comorbidities and health-care service usage.
      • Analyses revealed no differences in hospitalization rates by comorbidity class.
      • The burden of comorbidities increases the usage of primary level care-services.



      To describe the impact of diabetes comorbidities on the health care services use and costs of a cohort of elderly patients with diabetes and high health care needs (HHCN), based on real-world data.


      We focused on a cohort of diabetic patients with HHCN belonging to Resource Utilization Bands 4 and 5 according to the Adjusted Clinical Group (ACG) system. Their comorbidities were assessed using the clinical diagnoses that the ACG system assigns to single patients by combining different information flows. Regression models were applied to analyze the associations between comorbidities and health care service use or costs, adjusting for age and sex.


      Our analyses showed that all health care service usage measures (e.g. access to emergency care; number of outpatient visits) and the total annual costs and pharmacy costs are associated significantly with comorbidity class. Instead, no differences in hospitalization rates by comorbidity class were revealed.


      The association between a larger number of comorbidities and higher total health care service usage and costs was seen mainly for primary care services. This underscores the need to strengthen primary care for today’s aging and multimorbid population.


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        • Zheng Y.
        • Ley S.H.
        • Hu F.B.
        Global aetiology and epidemiology of type 2 diabetes mellitus and its complications.
        Nat. Rev. Endocrinol. 2018; 14: 88-98
        • World Health Organization (WHO) Media Centre
        Diabetes. [Fact sheet].
        2018 (Accessed 17 February 2020)
        • Wild S.
        • Roglic G.
        • Green A.
        • et al.
        Global prevalence of diabetes: estimates for the year 2000 and projections for 2030.
        Diabetes Care. 2004; 27: 1047-1053
        • Iglay K.
        • Hannachi H.
        • Joseph Howie P.
        • et al.
        Prevalence and co-prevalence of comorbidities among patients with type 2 diabetes mellitus.
        Curr. Med. Res. Opin. 2016; 32: 1243-1252
      1. World Health Organization Integrated care for older people (ICOPE) implementation framework: guidance for systems and services. World Health Organization, 2019 ISBN: 9789241515993. Available at: (Accessed 3 August 2020).

        • King H.
        • Aubert R.E.
        • Herman W.H.
        Global burden of diabetes, 1995-2025: prevalence, numerical estimates, and projections.
        Diabetes Care. 1998; 21: 1414-1431
        • Zimmet P.
        • Alberti K.G.
        • Shaw J.
        Global and societal implications of the diabetes epidemic.
        Nature. 2001; 414: 782-787
        • Mathers C.
        • Loncar D.
        Projections of global mortality and burden of disease from 2002 to 2030.
        PLoS Med. 2006; 3e442
        • International Diabetes Federation: Diabetes Atlas
        Economic Impact of Diabetes.
        9th ed. 2019 (Available at: Accessed on 03 Aug 2020)
        • Zhang P.
        • Zhang X.
        • Brown J.
        • Vistisen D.
        • Sicree R.
        • Shaw J.
        • Nichols G.
        Global healthcare expenditure on diabetes for 2010 and 2030.
        Diabetes Res. Clin. Pract. 2010; 87 (Epub 2010 Feb 19. Erratum in: Diabetes Res Clin Pract. 2011 May;92(2):301. PMID: 20171754): 293-301
      2. ARNO (osservatorio) Diabete: Il profilo assistenziale della popolazione con diabete. Rapporto 2019 Volume XXXI - Collana Rapporti ARNO. Availble at (Accessed 03 August 2020).

        • Cortaredona S.
        • Ventelou B.
        The extra cost of comorbidity: multiple illnesses and the economic burden of non-communicable diseases.
        BMC Med. 2017; 15 (Published 2017 Dec 8): 216
        • Lucioni C.
        • Garancini M.
        • Massi-Benedetti M.
        • et al.
        The costs of type 2 diabetes mellitus in Italy: a CODE-2 sub-study.
        Treat. Endocrinol. 2003; 2: 121-133
        • Morsanutto A.
        • Berto P.
        • Lopatriello S.
        • et al.
        Major complications have an impact on total annual medical cost of diabetes: results of a database analysis.
        J Diabetes Complications. 2006; 20: 163-169
        • Hochman M.
        • Asch S.M.
        Disruptive models in primary care: caring for high-needs, high-cost populations.
        J. Gen. Intern. Med. 2017; 32 (Epub 2017 Feb 27): 392-397
        • The Johns Hopkins University
        ACG System Version 11.0. Technical Reference Guide.
        11.0th ed. The Johns Hopkins University, 2014
        • Corti M.C.
        • Avossa F.
        • Schievano E.
        • et al.
        A case-mix classification system for explaining healthcare costs using administrative data in Italy.
        Eur. J. Intern. Med. 2018; 54: 13-16
        • Sancho-Mestre C.
        • Vivas-Consuelo D.
        • Alvis-Estrada L.
        • et al.
        Pharmaceutical cost and multimorbidity with type 2 diabetes mellitus using electronic health record data.
        BMC Health Serv. Res. 2016; 16 (Published 2016 Aug 17): 394
        • Bhuyan S.S.
        • Shiyanbola O.
        • Deka P.
        • et al.
        The role of gender in cost-related medication nonadherence among patients with diabetes.
        J. Am. Board Fam. Med. 2018; 31: 743-751
        • Rolnick S.J.
        • Pawloski P.A.
        • Hedblom B.D.
        • et al.
        Patient characteristics associated with medication adherence.
        Clin. Med. Res. 2013; 11: 54-65
        • Buja A.
        • Boemo D.G.
        • Furlan P.
        • et al.
        Tackling inequalities: are secondary prevention therapies for reducing post-infarction mortality used without disparities?.
        Eur. J. Prev. Cardiol. 2014; 21: 222-230
        • WHO
        Adherence to Long-term Therapies: Evidence for Action.
        WHO Library Cataloguing, 2008 (Available at: (Accessed 03 August 2020))
        • Funnell M.M.
        • Anderson R.M.
        Empowerment and self-management of diabetes.
        Clin. Diabetes. 2004; 22: 123-127
        • Ayanian J.Z.
        • Epstein A.M.
        Differences in the use of procedures between women and men hospitalized for coronary heart disease.
        N. Engl. J. Med. 1991; 325: 221-225
        • Beery T.A.
        Gender bias in the diagnosis and treatment of coronary artery disease.
        Heart Lung. 1995; 24: 427-435
        • Gan S.C.
        • Beaver S.K.
        • Houck P.M.
        • et al.
        Treatment of acute myocardial infarction and 30-day mortality among women and men.
        N. Engl. J. Med. 2000; 343: 8-15
        • Alter D.A.
        • Naylor C.D.
        • Austin P.C.
        • Tu J.V.
        Biology or bias: practice patterns and long-term outcomes for men and women with acute myocardial infarction.
        J. Am. Coll. Cardiol. 2002; 39: 1909-1916
        • Buja A.
        • De Polo A.
        • De Battisti E.
        • et al.
        The importance of sex as a risk factor for hospital readmissions due to pulmonary diseases.
        BMC Public Health. 2020; 20 (Published 2020 Jan 14): 53
        • Watson L.
        • Vestbo J.
        • Postma D.S.
        • et al.
        Gender differences in the management and experience of chronic obstructive pulmonary disease.
        Respir. Med. 2004; 98: 1207-1213
        • Starfield B.
        • Lemke K.W.
        • Herbert R.
        • et al.
        Comorbidity and the use of primary care and specialist care in the elderly.
        Ann. Fam. Med. 2005; 3: 215-222
        • Gruneir A.
        • Markle-Reid M.
        • Fisher K.
        • et al.
        Comorbidity burden and health services use in community-living older adults with diabetes mellitus: a retrospective cohort study.
        Can. J. Diabetes. 2016; 40: 35-42
        • Marengoni A.
        • Angleman S.
        • Melis R.
        • et al.
        Aging with multimorbidity: a systematic review of the literature.
        Ageing Res. Rev. 2011; 10: 430-439
      3. WHO Regional Office for Europe. Integrated care models: an overview. Available at: (Accessed 3 August 2020).

      4. Report ISAT anni 2012-2018: Il sistema dei conti della sanità per l’Italia. Available at: (Accessed 27 October 2020).

      5. An impactability model for population health management in high-cost elderly heart failure patients: a capture method using ACG system Buja.

        • Kapinos K.A.
        • Fischer S.H.
        • Mulcahy A.
        • Hayden O.
        • Barron R.
        Medical costs for osteoporosis-related fractures in high-risk medicare beneficiaries.
        J. Am. Geriatr. Soc. 2018; 66 (Epub 2018 Oct 5. PMID: 30289961): 2298-2304
        • Christianson M.S.
        • Shen W.
        Osteoporosis prevention and management: nonpharmacologic and lifestyle options.
        Clin. Obstet. Gynecol. 2013; 56 (PMID: 24047936): 703-710
        • Kanis J.A.
        • Cooper C.
        • Rizzoli R.
        • Reginster J.Y.
        • Scientific Advisory Board of the European Society for Clinical and Economic Aspects of Osteoporosis and Osteoarthritis (ESCEO) and the Committees of Scientific Advisors and National Societies of the International Osteoporosis Foundation (IOF)
        Executive summary of the European guidance for the diagnosis and management of osteoporosis in postmenopausal women.
        Calcif. Tissue Int. 2019; 104 (PMID: 30796490; PMCID: PMC6422308): 235-238
        • Baccaro L.F.
        • Conde D.M.
        • Costa-Paiva L.
        • Pinto-Neto A.M.
        The epidemiology and management of postmenopausal osteoporosis: a viewpoint from Brazil.
        Clin. Interv. Aging. 2015; 10 (PMID: 25848234; PMCID: PMC4374649): 583-591
      6. Ministero della salute, direzione generale della programmazione sanitaria. Piano nazionale della cronicità. 2016. Available at: (Accessed 27 October 2020).

        • Timpel P.
        • Lang C.
        • Wens J.
        • Contel J.C.
        • Schwarz P.E.H.
        • MANAGE CARE Study Group
        The manage care model - developing an evidence-based and expert-driven chronic care management model for patients with diabetes.
        Int. J. Integr. Care. 2020; 20 (Published 2020 Apr 22): 2
        • Commission for Case Manager Certification
        Code of Professional Conduct for Case Managers with Standards, Rules, Procedures, and Penalties.
        2018 (Available at: (Accessed 27 October 2020))
        • Huntley A.L.
        • Johnson R.
        • King A.
        • Morris R.W.
        • Purdy S.
        Does case management for patients with heart failure based in the community reduce unplanned hospital admissions? A systematic review and meta-analysis.
        BMJ Open. 2016; 6 (PMID: 27165648; PMCID: PMC4874181)e010933
        • Azaïs B.
        • Bowis J.
        • Wismar M.
        Facing the challenge of multimorbidity.
        J Comorb. 2016; 6 (Published 2016 Feb 17): 1-3
        • Starfield B.
        Primary care, specialist care, and chronic care: can they interlock?.
        Chest. 2010; 137: 8-10
        • van Walraven C.
        • Austin P.
        Administrative database research has unique characteristics that can risk biased results.
        J. Clin. Epidemiol. 2012; 65: 126-131