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      The effects of the introduction of a chronic care model-based program on utilization of healthcare resources: the results of the Puglia care program

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          Abstract

          Background

          Ageing is continuously increasing the prevalence of patients with chronic conditions, putting pressure on the sustainability of Healthcare Systems. Chronic Care Models (CCM) have been used to address the needs of frail people in the continuum of care, testifying to an improvement in health outcomes and more efficient access to healthcare services. The impact of CCM deployment has already been experienced in a selected cohort of patients affected by specific chronic illnesses. We have investigated its effects in a heterogeneous frail cohort included in a regional CCM-based program.

          Methods

          a retrospective population-based cohort study was carried out involving a non-oncological cohort of adult subjects with chronic diseases included in the CCM-oriented program (Puglia Care). Individuals in usual care with comparable demographic and clinical characteristics were selected for matched pair analysis. Study cohorts were defined by using a record linkage analysis of administrative databases and electronic medical records, including data on the adult population in the 6 local area health authorities of Puglia in Italy (approximately 2 million people). The effects of Puglia Care on the utilizations of healthcare resources were evaluated both in a before-after and in a case-control analysis.

          Results

          There were 1074 subjects included in Puglia Care and 2126 matched controls. In before-after analysis of the Puglia Care cohort, 240 unplanned hospitalizations occurred in the pre-inclusion period, while 239 were registered during follow-up. The incidence of unplanned hospitalization was 10.3 per 100 person/year (95% CI, 9.1–11.7) during follow-up and 12.1 per 100 person/year (95% CI, 10.7–13.8) in the pre-inclusion period (IRR, 0.84; 95% CI, 0.80–0.99). During follow-up a significant reduction in costs related to unplanned hospitalizations (IRR, 0.92; 95% CI, 0.91–0.92) was registered, while costs related to drugs (IRR, 1.14; p < 0.01), out-patient specialist visits (IRR, 1.19; p < 0.01), and planned hospitalization (IRR 1.03; p < 0.01) increased significantly. These modifications can be related to the aging of the population and modifications to healthcare delivery; for this reason, a case-control analysis was performed. The results testify to a significantly lower number (IRR, 0.79; 95% CI, 0.68–0.91), length of hospital stay (IRR, 0.80; 95% CI, 0.76–0.84), and costs related to unplanned hospitalizations (IRR, 0.80; 95% CI, 0.80–0.80) during follow-up in the intervention group. However, there was a higher increase in costs of hospitalizations, drugs and out-patients specialist visits during follow-up in Puglia Care when compared with patients in usual care.

          Conclusion

          In a population-based cohort, inclusion of chronic patients in a CCM-based program was significantly associated with a lower recourse to unplanned hospital admissions when compared with patients in usual care with comparable clinical and demographic characteristics.

          Electronic supplementary material

          The online version of this article (10.1186/s12913-018-3075-0) contains supplementary material, which is available to authorized users.

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          Most cited references34

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          Evidence on the Chronic Care Model in the new millennium.

          Developed more than a decade ago, the Chronic Care Model (CCM) is a widely adopted approach to improving ambulatory care that has guided clinical quality initiatives in the United States and around the world. We examine the evidence of the CCM's effectiveness by reviewing articles published since 2000 that used one of five key CCM papers as a reference. Accumulated evidence appears to support the CCM as an integrated framework to guide practice redesign. Although work remains to be done in areas such as cost-effectiveness, these studies suggest that redesigning care using the CCM leads to improved patient care and better health outcomes.
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            Clinical guidelines: potential benefits, limitations, and harms of clinical guidelines.

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              Translating the chronic care model into the community: results from a randomized controlled trial of a multifaceted diabetes care intervention.

              To determine whether using the chronic care model (CCM) in an underserved community leads to improved clinical and behavioral outcomes for people with diabetes. This multilevel, cluster-design, randomized controlled trial examined the effectiveness of a CCM-based intervention in an underserved urban community. Eleven primary care practices, along with their patients, were randomized to three groups: CCM intervention (n = 30 patients), provider education only (PROV group) (n = 38), and usual care (UC group) (n = 51). A marked decline in HbA(1c) was observed in the CCM group (-0.6%, P = 0.008) but not in the other groups. The magnitude of the association remained strong after adjustment for clustering (P = 0.01). The same pattern was observed for a decline in non-HDL cholesterol and for the proportion of participants who self-monitor blood glucose in the CCM group (non-HDL cholesterol: -10.4 mg/dl, P = 0.24; self-monitor blood glucose: +22.2%, P < 0.0001), with statistically significant between-group differences in improvement (non-HDL cholesterol: P = 0.05; self-monitor blood glucose: P = 0.03) after adjustment. The CCM group also showed improvement in HDL cholesterol (+5.5 mg/dl, P = 0.0004), diabetes knowledge test scores (+6.7%, P = 0.07), and empowerment scores (+2, P = 0.02). These results suggest that implementing the CCM in the community is effective in improving clinical and behavioral outcomes in patients with diabetes.
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                Author and article information

                Contributors
                fabiorobusto@libero.it
                l.bisceglia@arespuglia.it
                v.petrarolo@arespuglia.it
                f.avolio@arespuglia.it
                e.graps@arespuglia.it
                e.attolini@arespuglia.it
                eleonora.nacchiero@yahoo.it
                leporevito792@gmail.com
                Journal
                BMC Health Serv Res
                BMC Health Serv Res
                BMC Health Services Research
                BioMed Central (London )
                1472-6963
                25 May 2018
                25 May 2018
                2018
                : 18
                : 377
                Affiliations
                [1 ]Regional Healthcare Agency of Puglia Region (AReSS Puglia), via Giovanni Gentile n 52 -, 70126 Bari, Italy
                [2 ]AReSS Puglia, Bari, Italy
                Article
                3075
                10.1186/s12913-018-3075-0
                5970509
                29801489
                33e5ab58-209a-4b7c-8f88-4c86535e7e07
                © The Author(s). 2018

                Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License ( http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver ( http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.

                History
                : 29 July 2017
                : 28 March 2018
                Funding
                Funded by: FundRef http://dx.doi.org/10.13039/100011272, FP7 Health;
                Award ID: 2013 12 04
                Categories
                Research Article
                Custom metadata
                © The Author(s) 2018

                Health & Social care
                chronic care model,healthcare expenditure,administrative databases,electronic medical records,unplanned hospitalizations,drug costs,out-patients, ddci, stratification, frailty

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