According to the most traditional economic evaluation manuals, all “relevant” costs should be included in the economic analysis, taking into account factors such as the patient population, setting, location, year, perspective and time horizon. However, cost information may be designed for other purposes. Health care organisations may lack sophisticated accounting systems and consequently, health economists may be unfamiliar with cost accounting terminology, which may lead to discrepancy in terms used in the economic evaluation literature and management accountancy. This paper identifies new tendencies in costing methodologies in health care and critically comments on each included article. For better clarification of terminology, a pragmatic glossary of terms is proposed. A scoping review of English and Spanish language literature (2005–2018) was conducted to identify new tendencies in costing methodologies in health care. The databases PubMed, Scopus and EconLit were searched. A total of 21 studies were included yielding 43 costing analysis. The most common analysis was top-down micro-costing (49%), followed by top-down gross-costing (37%) and bottom-up micro-costing (14%). Resource data were collected prospectively in 12 top-down studies (32%). Hospital database was the most common way of collection of resource data (44%) in top-down gross-costing studies. In top-down micro-costing studies, the most resource use data collection was the combination of several methods (38%). In general, substantial inconsistencies in the costing methods were found. The convergence of top-down and bottom-up methods may be an important topic in the next decades.

Background: Longer time intervals to diagnosis and treatment are associated with worse survival for various types of cancer. The patient, diagnostic, and treatment intervals are considered core indicators for early diagnosis and treatment. This review estimated the median duration of these intervals for various types of cancer and compared it across high- and lower-income countries. Methods and findings: We conducted a systematic review with meta-analysis (prospectively registered protocol CRD42020200752). Three databases (MEDLINE, Embase, and Web of Science) and information sources including grey literature (Google Scholar, OpenGrey, EThOS, ProQuest Dissertations & Theses) were searched. Eligible articles were published during 2009 to 2022 and reported the duration of the following intervals in adult patients diagnosed with primary symptomatic cancer: patient interval (from the onset of symptoms to first presentation to a healthcare professional), diagnostic interval (from first presentation to diagnosis), and treatment interval (from diagnosis to treatment start). Interval duration was recorded in days and study medians were combined in a pooled estimate with 95% confidence intervals (CIs). The methodological quality of studies was assessed using the Aarhus checklist. A total of 410 articles representing 68 countries and reporting on 5,537,594 patients were included. The majority of articles reported data from high-income countries (n = 294, 72%), with 116 (28%) reporting data from lower-income countries. Pooled meta-analytic estimates were possible for 38 types of cancer. The majority of studies were conducted on patients with breast, lung, colorectal, and head and neck cancer. In studies from high-income countries, pooled median patient intervals generally did not exceed a month for most cancers. However, in studies from lower-income countries, patient intervals were consistently 1.5 to 4 times longer for almost all cancer sites. The majority of data on the diagnostic and treatment intervals came from high-income countries. Across both high- and lower-income countries, the longest diagnostic intervals were observed for hematological (71 days [95% CI 52 to 85], e.g., myelomas (83 days [47 to 145])), genitourinary (58 days [50 to 77], e.g., prostate (85 days [57 to 112])), and digestive/gastrointestinal (57 days [45 to 67], e.g., colorectal (63 days [48 to 78])) cancers. Similarly, the longest treatment intervals were observed for genitourinary (57 days [45 to 66], e.g., prostate (75 days [61 to 87])) and gynecological (46 days [38 to 54], e.g., cervical (69 days [45 to 108]) cancers. In studies from high-income countries, the implementation of cancer-directed policies was associated with shorter patient and diagnostic intervals for several cancers. This review included a large number of studies conducted worldwide but is limited by survivor bias and the inherent complexity and many possible biases in the measurement of time points and intervals in the cancer treatment pathway. In addition, the subintervals that compose the diagnostic interval (e.g., primary care interval, referral to diagnosis interval) were not considered. Conclusions: These results identify the cancers where diagnosis and treatment initiation may take the longest and reveal the extent of global disparities in early diagnosis and treatment. Efforts should be made to reduce help-seeking times for cancer symptoms in lower-income countries. Estimates for the diagnostic and treatment intervals came mostly from high-income countries that have powerful health information systems in place to record such information.

The high prevalence of women that do not reach the recommended level of physical activity is worrisome. A sedentary lifestyle has negative consequences on health status and increases health care costs. The main objective of this project is to assess the cost-effectiveness of a primary care-based exercise intervention in perimenopausal women. The present study is a Randomized Controlled Trial. A total of 150 eligible women will be recruited and randomly assigned to either a 16-week exercise intervention (3 sessions/week), or to usual care (control) group. The primary outcome measure is the incremental cost-effectiveness ratio. The secondary outcome measures are: i) socio-demographic and clinical information; ii) body composition; iii) dietary patterns; iv) glycaemic and lipid profile; v) physical fitness; vi) physical activity and sedentary behaviour; vii) sleep quality; viii) quality of life, mental health and positive health; ix) menopause symptoms. All outcomes will be assessed at baseline and post intervention. The data will be analysed on an intention-to-treat basis and per protocol. In addition, we will conduct a cost effectiveness analysis from a health system perspective. The intervention designed is feasible and if it proves to be clinically and cost effective, it can be easily transferred to other similar contexts. Consequently, the findings of this project might help the Health Systems to identify strategies for primary prevention and health promotion as well as to reduce health care requirements and costs. ClinicalTrials.gov Identifier: NCT02358109 . Date of registration: 05/02/2015

Adequate physical activity levels and a healthy lifestyle may prevent all kinds of non-communicable diseases, promote well-being and reduce health-care costs among perimenopausal women. This study assessed an exercise programme for perimenopausal women. A total of 150 women (aged 45-64 years) not engaged in regular physical activity were randomly assigned to either a 16 week exercise intervention or to the control group. The study was conducted from the perspective of the National Health System. Health outcomes were quality-adjusted life years (QALYs), measured by the EuroQol-5D-5L questionnaire. The total direct costs of the programme were the costs of visits to primary care, specialty care, emergency, medicines, instructor cost and infrastructure cost. The results were expressed as the incremental cost-effectiveness ratio. Sensitivity analysis was undertaken to test the robustness of the analysis. Mean QALYs over 16 weeks were.228 in the control group and.230 in the intervention group (mean difference: .002; 95% confidence interval [95%CI]: -0.005 to 0.009). Improvements from baseline were greater in the intervention group in all dimensions of the EuroQol-5D-5L but not statistically significant. The total costs at the end of the intervention were 160.38 € in the control group and 167.80 € in the intervention group (mean difference: 7.42 €; 95%CI: -47 to 62). The exercise programme had an incremental cost-effectiveness ratio of 4,686 €/QALY. The programme could be considered cost-effective, although the overall difference in health benefits and costs was very modest. Longer term follow-up is needed.