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

The association between Patient Assessment of Chronic Illness Care Scores and quality of life in type 2 diabetes patients

Background

Chronic illness care is an important factor for health promotion in diabetes since it affects health outcomes such as quality of life.

Aims

The aim of this study was to investigate the relationship between the Patient Assessment of Chronic Illness Care and the quality of life in type 2 diabetes patients.

Methods

The study used a cross-sectional and correlational design. The sample included 317 patients with type 2 diabetes. A socio-demographic and disease-related questionnaire form, the Patient Assessment of Chronic Illness Care (PACIC) scale and the WHOQOL-BREF Quality of Life Scale were used to collect data.

Results

According to the regression analysis, the stronger predictor affecting all domains of quality of life was the overall PACIC. This study demonstrated the importance of satisfaction level of chronic illness care in the improvement of quality of life. Therefore, the factors affecting the satisfaction level with chronic care services should be determined to improve the quality of life of patients. In addition, healthcare based on the chronic-care model should be provided in the care of the patients.

Conclusions

PACIC had an important effect on quality of life of the patients. This study demonstrated the importance of satisfaction level on chronic illness care in the improvement of quality of life.

Comparison between drug therapy-based comorbidity indices and the Charlson Comorbidity Index for the detection of severe multimorbidity in older subjects

BACKGROUND

To know burden disease of a patient is a key point for clinical practice and research, especially in the elderly. Charlson's Comorbidity Index (CCI) is the most widely used rating system, but when diagnoses are not available therapy-based comorbidity indices (TBCI) are an alternative. However, their performance is debated. This study compares the relations between Drug Derived Complexity Index (DDCI), Medicines Comorbidity Index (MCI), Chronic Disease Score (CDS), and severe multimorbidity, according to the CCI classification, in the elderly.

METHODS

Logistic regression and Receiver Operating Characteristic (ROC) analysis were conducted on two samples from Italy: 2579 nursing home residents (Korian sample) and 7505 older adults admitted acutely to geriatric or internal medicine wards (REPOSI sample).

RESULTS

The proportion of subjects with severe comorbidity rose with TBCI score increment, but the Area Under the Curve (AUC) for the CDS (Korian: 0.70, REPOSI: 0.79) and MCI (Korian: 0.69, REPOSI: 0.81) were definitely better than the DDCI (Korian: 0.66, REPOSI: 0.74). All TBCIs showed low Positive Predictive Values (maximum: 0.066 in REPOSI and 0.317 in Korian) for the detection of severe multimorbidity.

CONCLUSION

CDS and MCI were better predictors of severe multimorbidity in older adults than DDCI, according to the CCI classification. A high CCI score was related to a high TBCI. However, the opposite is not necessarily true probably because of non-evidence-based prescriptions or physicians' prescribing attitudes. TBCIs did not appear selective for detecting of severe multimorbidity, though they could be used as a measure of disease burden, in the absence of other solutions.

Chronic Care Model in Italy: a narrative review of the literature

Aim:

To analyze scientific literature on the development and implementation of the Chronic Care Model (CCM) in treating chronic diseases in the Italy context. Besides, to evaluate the effects of the activities carried out by the operators participating in the CCM on clinical care.

Background:

Italy is the second country globally for longevity, with 21.4% of citizens over 65 and 6.4% over 80. The CCM fits into this context, a care model aimed primarily at patients suffering from chronic diseases, especially in emergencies, as the recent COVID-19 pandemic.

Methods:

PubMed, Embase, Scopus, Cinahl, and Cochrane Library scientific databases were consulted, and the records selected as relevant by title and abstract by nine independent scholars, and disagreements were resolved through discussion. Finally, the studies included in this review were selected based on the eligibility criteria.

Results:

Twenty potentially relevant studies were selected, and after applying the eligibility criteria and screening by the Critical Appraisal Skills Program tool, eight included in this review. The studies showed the effectiveness of CCM for managing patients with heart failure in primary care settings and significant improvements in clinical outcomes, the reduction of inappropriate emergency room access for chronic patients, and the improvement of patients’ overall health with diabetes. The CCM organizational model is effective in improving the management of metabolic control and the main cardiovascular risk factors. Furthermore, this modality also allows doctors to dedicate more space to patients in the disease’s acute phase.

Conclusion:

The CCM, with its fundamental pillars of empowering self-management of care, could represent a valid alternative to health management. The managers of health services, especially territorial ones, could consider the CCM for the improvement of the treatments offered.

The cost and cost implications of implementing the integrated chronic disease management model in South Africa

BACKGROUND

A cost analysis of implementation of interventions informs budgeting and economic evaluations.

OBJECTIVE

To estimate the cost of implementing the integrated chronic disease management (ICDM) model in primary healthcare (PHC) clinics in South Africa.

METHODS

Cost data from the provider's perspective were collected in 2019 from four PHC clinics with comparable patient caseloads (except for one). We estimated the costs of implementing the ICDM model current activities for three (facility reorganization, clinical supportive management and assisted self-management) components and additional costs of implementing with enhanced fidelity. Costs were estimated based on budget reviews, interviews with management teams, and other published data. The standard of care activities such as medication were not included in the costing. One-way sensitivity analyses were carried out for key parameters by varying patient caseloads, required infrastructure and staff. Annual ICDM model implementation costs per PHC clinic and per patient per visit are presented in 2019 US dollars.

RESULTS

The overall mean annual cost of implementing the ICDM model was $148 446.00 (SD: $65 125.00) per clinic. Current ICDM model activities cost accounted for 84% ($124 345.00) of the annual mean cost, while additional costs for higher fidelity were 16% ($24 102.00). The mean cost per patient per visit was $6.00 (SD:$0.77); $4.94 (SD:0.70) for current cost and $1.06 (SD:0.33) for additional cost to enhance ICDM model fidelity. For the additional cost, 49% was for facility reorganization, 31% for adherence clubs and 20% for training of nursing staff. In the sensitivity analyses, the major cost drivers were the proportion of effort of assisted self-management staff and the number of patients with chronic diseases receiving care at the clinic.

CONCLUSION

Minimal additional cost are required to implement the ICDM model with higher fidelity. Further research on the cost-effectiveness of the ICDM model in middle-income countries is required.

Estudo comparativo das inovações sobre condições crônicas na atenção primária em Porto Alegre, RS, Brasil e Ferrara, Itália

Resumo Este estudo visa comparar os principais desafios referentes às inovações na atenção às condições crônicas percebidos por profissionais de atenção primária de Porto Alegre, Brasil, e Ferrara, Itália. Trata-se de pesquisa exploratória descritiva de abordagem qualitativa realizada em unidades da atenção primária, cujos dados foram coletados por meio de entrevistas semiestruturadas com profissionais da Unidade Sanitária Local de Ferrara e grupos focais e entrevistas semiestruturadas com trabalhadores do Serviço de Saúde Comunitária do Grupo Hospitalar Conceição de Porto Alegre. Os dados foram discutidos por meio de análise temática. Colocando em análise os dois casos, destaca-se como desafios, a resistência tanto dos profissionais, quanto dos usuários diante das práticas inovadoras, dificuldades na gestão do cuidado e deficiência no processo de formação, que ainda não prepara o profissional para o novo modelo de atenção. Conclui-se que estes desafios influenciam claramente no dia a dia dos serviços e desestimulam a incorporação de práticas inovadoras no cuidado das pessoas com condições crônicas.

Both pre-frailty and frailty increase healthcare utilization and adverse health outcomes in patients with type 2 diabetes mellitus

Background

Diabetes mellitus (DM) correlates with accelerated aging and earlier appearance of geriatric phenotypes, including frailty. However, whether pre-frailty or frailty predicts greater healthcare utilization in diabetes patients is unclear.

Methods

From the Longitudinal Cohort of Diabetes Patients in Taiwan (n = 840,000) between 2004 and 2010, we identified 560,795 patients with incident type 2 DM, categorized into patients without frailty, or with 1, 2 (pre-frail) and ≥ 3 frailty components, based on FRAIL scale (Fatigue, Resistance, Ambulation, Illness, and body weight Loss). We examined their long-term mortality, cardiovascular risk, all-cause hospitalization, and intensive care unit (ICU) admission.

Results

Among all participants (56.4 ± 13.8 year-old, 46.1% female, and 84.8% community-dwelling), 77.8% (n = 436,521), 19.2% (n = 107,757), 2.7% (n = 15,101), and 0.3% (n = 1416) patients did not have or had 1, 2 (pre-frail), and ≥ 3 frailty components (frail), respectively, with Fatigue and Illness being the most common components. After 3.14 years of follow-up, 7.8% patients died, whereas 36.6% and 9.1% experienced hospitalization and ICU stay, respectively. Cox proportional hazard modeling discovered that patients with 1, 2 (pre-frail), and ≥ 3 frailty components (frail) had an increased risk of mortality (for 1, 2, and ≥ 3 components, hazard ratio [HR] 1.05, 1.13, and 1.25; 95% confidence interval [CI] 1.02–1.07, 1.08–1.17, and 1.15–1.36, respectively), cardiovascular events (HR 1.05, 1.15, and 1.13; 95% CI 1.02–1.07, 1.1–1.2, and 1.01–1.25, respectively), hospitalization (HR 1.06, 1.16, and 1.25; 95% CI 1.05–1.07, 1.14–1.19, and 1.18–1.33, respectively), and ICU admission (HR 1.05, 1.13, and 1.17; 95% CI 1.03–1.07, 1.08–1.14, and 1.06–1.28, respectively) compared to non-frail ones. Approximately 6–7% risk elevation in mortality and healthcare utilization was noted for every frailty component increase.

Conclusion

Pre-frailty and frailty increased the risk of mortality and cardiovascular events, and entailed greater healthcare utilization in patients with type 2 DM.

Electronic supplementary material

The online version of this article (10.1186/s12933-018-0772-2) contains supplementary material, which is available to authorized users.