Micro-costing studies still deserving for methods orientation that contribute to achieve a patient-specific resource use level of analysis. Time-driven activity-based costing (TDABC) is often employed by health organizations in micro-costing studies with that objective. However, the literature shows many deviations in the implementation of TDABC, which might compromise the accuracy of the results obtained. One reason for that can be attributed to the non-existence of a step-by-step orientation to conduct cost analytics with the TDABC specific for micro-costing studies in healthcare. This article aimed at exploring the literature and practical cases to propose an eight-step framework to apply TDABC in micro-costing studies for health care organizations. The 8-step TDABC framework is presented and detailed exploring online spreadsheets already coded to demonstrate data structure and math formula building. A list of analyses that can be performed is suggested, including an explanation about the information that each analysis can provide to increase the organization capability to orient decision making. The case study developed show that actual micro-costing of health care processes can be achieved with the 8-step TDABC framework and its use in future researches can contribute to increase the number of studies that achieve high-quality level in cost information, and consequently, in health resource evaluation.

Note: This guideline is for information purposes and should not replace the clinical judgment of a physician, who must ultimately determine the appropriate treatment for each patient.

Implementation of value-based initiatives depends on cost-assessment methods that can provide high-quality cost information. Time-driven activity-based costing (TDABC) is increasingly being used to solve the cost-information gap. This study aimed to review the use of the TDABC methodology in real-world settings and to estimate its impact on the valuebased healthcare concept for inpatient management.Methods: This systematic review was conducted by screening PubMed/MEDLINE and Scopus databases following Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines, including all studies up to August 2019. The use of TDABC for inpatient management was the main eligibility criterion. A qualitative approach was used to analyze the different methodological aspects of TDABC and its effective contribution to the implementation of value-based initiatives.Results: A total of 1066 studies were retrieved, and 26 full-text articles were selected for review. Only studies focused on surgical inpatient conditions were identified. Most of the studies reported the types of activities on a macrolevel. Professional and structural cost variables were usually assessed. Eighteen studies reported that TDABC contributed to value-based initiatives, especially cost-saving findings. TDABC was satisfactorily applied to achieve value-based contributions in all the studies that used the method for this purpose.Conclusions: TDABC could be a strategy for increasing cost accuracy in real-world settings, and the method could help in the transition from fee-for-service to value-based systems. The results could provide a clearer idea of the costs, help with resource allocation and waste reduction, and might support clinicians and managers in increasing value in a more accurate and transparent way.

Background: A review of the literature on economic analyses in cancer (prevention, diagnosis, and treatment) using activity-based costing (ABC) or time-driven activity-based costing (TDABC) for measuring costs and to examine how these approaches have been applied to assess and manage cancer costs. Methods: This review followed the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) statement. We conducted a search for studies that used ABC or TDABC to calculate the cost of cancer in prevention, diagnosis, and treatment. Only English-and Portuguese-language articles were retrieved from Medline, Lilacs, ScieLO, and Embase (January 1990 to August 2016). Results: In total, 421 studies were evaluated. However, only 27 papers were included. The first publications were from the early 2000s, but most of the studies were published in 2016 (n = 10). Most of the studies were carried out in the United States (n = 6) and Belgium (n = 6). Cancer treatment was the major focus of all studies (n = 20), followed by screening programs evaluations (n = 4) and diagnosis (n = 3). Among treatment modalities, economic analysis of radiotherapy was the most common topic of study. Retrospective clinical data represented 57.6% of the studies. More than 50% of the studies presented unspecified economic analysis. The hospital perspective was the most prevalent perspective among the studies (46.1%). Conclusions: ABC and TDABC economic analyses are a promising area of studies in oncology costs.

EXECUTIVE SUMMARY Value-based initiatives are growing in importance as strategic models of healthcare management, prompting the need for an in-depth exploration of their outcome measures. This systematic review aimed to identify measures that are being used in the application of the value agenda. Multiple electronic databases (PubMed/MEDLINE, Embase, Scopus, Cochrane Central Register of Controlled Trials) were searched. Eligible studies reported various implementations of value-based healthcare initiatives. A qualitative approach was used to analyze their outcome measurements. Outcomes were classified according to a tier-level hierarchy. In a radar chart, we compared literature to cases from Harvard Business Publishing. The value agenda effect reported was described in terms of its impact on each domain of the value equation. A total of 7,195 records were retrieved; 47 studies were included. Forty studies used electronic health record systems for data origin. Only 16 used patient-reported outcome surveys to cover outcome tiers that are important to patients, and 3 reported outcomes to all 6 levels of our outcome measures hierarchy. A considerable proportion of the studies (36%) reported results that contributed to value-based financial outcomes focused on cost savings. However, a gap remains in measuring outcomes that matter to patients. A more complete application of the value agenda by health organizations requires advances in technology and culture change management.

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Objective: To develop and validate a rapid scoring system at hospital admission for predicting in-hospital mortality in patients hospitalized with coronavirus disease 19 (COVID-19), and to compare this score with other existing ones. Design: Cohort study Setting: The Brazilian COVID-19 Registry has been conducted in 36 Brazilian hospitals in 17 cities. Logistic regression analysis was performed to develop a prediction model for in-hospital mortality, based on the 3978 patients that were admitted between March-July, 2020. The model was then validated in the 1054 patients admitted during August-September, as well as in an external cohort of 474 Spanish patients. Participants: Consecutive symptomatic patients (≥18 years old) with laboratory confirmed COVID-19 admitted to participating hospitals. Patients who were transferred between hospitals and in whom admission data from the first hospital or the last hospital were not available were excluded, as well those who were admitted for other reasons and developed COVID-19 symptoms during their stay. Main outcome measures: In-hospital mortality Results: Median (25th-75th percentile) age of the model-derivation cohort was 60 (48-72) years, 53.8% were men, in-hospital mortality was 20.3%. The validation cohorts had similar age distribution and in-hospital mortality. From 20 potential predictors, seven significant variables were included in the in-hospital mortality risk score: age, blood urea nitrogen, number of comorbidities, C-reactive protein, SpO2/FiO2 ratio, platelet count and heart rate. The model had high discriminatory value (AUROC 0.844, 95% CI 0.829 to 0.859), which was confirmed in the Brazilian (0.859) and Spanish (0.899) validation cohorts. Our ABC2-SPH score showed good calibration in both Brazilian cohorts, but, in the Spanish cohort, mortality was somewhat underestimated in patients with very high (>25%) risk. The ABC2-SPH score is implemented in a freely available online risk calculator (https://abc2sph.com/). Conclusions: We designed and validated an easy-to-use rapid scoring system based on characteristics of COVID-19 patients commonly available at hospital presentation, for early stratification for in-hospital mortality risk of patients with COVID-19.

BackgroundThe first phase of an enterprise risk management (ERM) program is the identification of risks. Accurate identification is essential to a proactive and effective ERM function. The authors identified a lack of such risk identification in the literature and in practical cases when interviewing the chief risk officers from healthcare organizations. A risk inventory specific to healthcare organizations that includes detailed risk scenarios and risk impacts currently does not exist. Thus, the objective of this research is to develop an enterprise risk inventory for healthcare organizations to create a common understanding of how each type of risk impacts a healthcare organization.MethodERM guidelines and data from 15 interviews with chief risk officers were analyzed to create the risk inventory. The identified risks were confirmed through a survey of risk managers from a range of global healthcare organizations during the ASHRM conference in 2017. Descriptive statistics were developed and cluster analysis was performed using the survey results.ResultsThe risk inventory includes 28 risks and their specific risk scenarios. Cyberattack was ranked as the principal risk by the participants, followed by sentinel events and risks associated with human capital management (organizational culture, use of electronic medical records and physician wellness). The data analysis showed that the specific characteristics of the survey participants, such as the length of time working in risk management, the size of the organization, and the presence of a school of medicine, do not impact an individual’s opinion of the importance of the risks identified. A personal background in risk management (clinical or enterprise) was a characteristic that showed a small difference in the perceived importance of the risks from the proposed risk inventory.ConclusionsIn addition to defining specific risk scenarios, the enterprise risk inventory presented in this research can contribute to guiding the risk identification phase of an ERM program and thereby support the development of a risk culture. Patient data security in hospitals that operate with high levels of technology is fundamental to delivering high quality and safe care to patients. At the top of the risk ranking, the identification of cyberattacks reflects the importance that healthcare risk managers place on this risk by allocating time and other resources. Exploring opportunities to improve cyber risk management and evaluating the benefits of using the risk inventory at the beginning of the risk identification phase in an ERM program are suggestions for future studies.Electronic supplementary materialThe online version of this article (10.1186/s12913-018-3400-7) contains supplementary material, which is available to authorized users.