Long-term cost-effectiveness analysis of sacral neuromodulation in the treatment of severe faecal incontinence.

AIM: The aim of this study was to evaluate the long-term cost-effectiveness of sacral neuromodulation in the treatment of severe faecal incontinence as compared with symptomatic management. METHODS: In the public health field, a micro-costing evaluation method was conducted from the perspectives of the health system and the society. The incremental cost-effectiveness ratio was used as a decision index, and we considered various scenarios to evaluate the impact of the cost of symptomatic management and percutaneous nerve evaluation success rate in its calculation. Clinical data were retrieved from a consecutive cohort of 93 patients with severe faecal incontinence undergoing sacral neuromodulation after a failure of conservative (pharmacological and biofeedback) and/or surgical (sphincteroplasty) first-line treatments were considered. RESULTS: The long-term incremental cost-effectiveness ratio comparing sacral neuromodulation versus symptomatic management was 14347€/QALY and 28523€/QALY from the societal and health service provider's perspectives, respectively. If the definitive pulse generator implant success rate was 100%, incremental cost-effectiveness would correspond to 6831€/QALY and 16761€/QALY, respectively. CONCLUSIONS: Sacral neuromodulation may be considered a cost-effective technique in the long-term treatment of severe faecal incontinence from the societal and health care sector perspectives. Improving patient selection and determining the predictive outcome factors for successful sacral neuromodulation in the treatment of faecal incontinence would improve cost-effectiveness.

Tailoring integrated care services for high-risk patients with multiple chronic conditions: a risk stratification approach using cluster analysis.

BACKGROUND: The purpose of this study was to produce a risk stratification within a population of high-risk patients with multiple chronic conditions who are currently treated under a case management program and to explore the existence of different risk subgroups. Different care strategies were then suggested for healthcare reform according to the characteristics of each subgroup. METHODS: All high-risk multimorbid patients from a case management program in the Navarra region of Spain were included in the study (n = 885). A 1-year mortality risk score was estimated for each patient by logistic regression. The population was then divided into subgroups according to the patients' estimated risk scores. We used cluster analysis to produce the stratification with Ward's linkage hierarchical algorithm. The characteristics of the resulting subgroups were analyzed, and post hoc pairwise tests were performed. RESULTS: Three distinct risk strata were found, containing 45, 38 and 17% of patients. Age increased from cluster to cluster, and functional status, clinical severity, nursing needs and nutritional values deteriorated. Patients in cluster 1 had lower renal deterioration values, and patients in cluster 3 had higher rates of pressure skin ulcers, higher rates of cerebrovascular disease and dementia, and lower prevalence rates of chronic obstructive pulmonary disease. CONCLUSIONS: This study demonstrates the existence of distinct subgroups within a population of high-risk patients with multiple chronic conditions. Current case management integrated care programs use a uniform treatment strategy for patients who have diverse needs. Alternative treatment strategies should be considered to fit the needs of each patient subgroup.

Perceived Health and Earnings: Evidence from the European Working Conditions Survey 2015.

This paper aims to analyse the relationship between perceived health and earnings across Europe. Empirical analysis is based on the last published round from the European Working Conditions Survey (N = 43,850) and offers updated evidence on the effect of earnings on perceived health in 35 countries. The main findings show a positive and significant relationship between earnings and health, which is consistent with the existing literature. Moreover, health seems to be U-shaped relative to earnings. On the other hand, age is negatively related to health, which is consistent with previous research. This paper shows the health differences between countries, where cultural, geographic, and economic differences imply health inequalities across countries. From a practical perspective, understanding the dynamics of perceived health and earnings' processes can contribute to health policy.

Multisystem chronic illness prognostication in non-oncologic integrated care.

OBJECTIVES: To develop a mortality-predictive model for correct identification of patients with non-cancer multiple chronic conditions who would benefit from palliative care, recognise predictive indicators of death and provide with tools for individual risk score calculation. DESIGN: Retrospective observational study with multivariate logistic regression models. PARTICIPANTS: All patients with high-risk multiple chronic conditions incorporated into an integrated care strategy that fulfil two conditions: (1) they belong to the top 5% of the programme's risk pyramid according to the adjusted morbidity groups stratification tool and (2) they suffer simultaneously at least three selected chronic non-cancer pathologies (n=591). MAIN OUTCOME MEASURE: 1 year mortality since patient inclusion in the programme. RESULTS: Among study participants, 201 (34%) died within the 1 year follow-up. Variables found to be independently associated to 1 year mortality were the Barthel Scale (p<0.001), creatinine value (p=0.032), existence of pressure ulcers (p=0.029) and patient global status (p<0.001). The area under the curve (AUC) for our model was 0.751, which was validated using bootstrapping (AUC=0.751) and k-fold cross-validation (10 folds; AUC=0.744). The Hosmer-Lemeshow test (p=0.761) showed good calibration. CONCLUSIONS: This study develops and validates a mortality prediction model that will guide transitions of care to non-cancer palliative care services. The model determines prognostic indicators of death and provides tools for the estimation of individual death risk scores for each patient. We present a nomogram, a graphical risk calculation instrument, that favours a practical and easy use of the model within clinical practices.