An application of lean healthcare tools to improve management capability in a teaching hospital clinical pharmacy service

Background: The pharmacist's profession has gone from a dispensary-based function for the provision of clinical services. So that, we must consider the importance of management inserted in the clinical routine in order to ensure success of the professional actions of pharmacist in the care process. To identify opportunities for the best use of the clinical pharmaceutical resource in hospitals requires understand how such resources are effectively consumed by patients. Objectives and Methods: This study applied Lean principles and tools aiming to understand how clinical pharmacists’ resources are effectively consumed by the patients in an academic hospital, using tools such as value stream mapping, the time of the professional involved in those activities, the value-added based activity and activity designation matrix. The data was mainly obtained through interviews with the professionals, time-motion observational studies, chronoanalysis and meeting with head of the sector. Results: The clinical pharmacy services have its value stream map designed considering the relationship of the activities and added-value based. Exploring the map, it is demonstrated that the activity “clinical round” is the most time consuming (27%) is not necessarily considered as value-added for both parts. In addition, there is a long time dedicated to activities that are not identified as valued activities by the pharmacists, and also activities of high value to patient being performed and monitored by trainees. Conclusion: Lean healthcare may become a truly positive force once it encourages reflection of the activities performed by the pharmacist professional in a hospital which works in a patient oriented-based care

Modelos para automatização de análises de desfechos clínico-assistenciais

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Value-based healthcare initiatives in practice : a systematic review

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

Stroke outcome measurements from electronic medical records : cross-sectional study on the effectiveness of neural and nonneural classifiers

Background: With the rapid adoption of electronic medical records (EMRs), there is an ever-increasing opportunity to collect data and extract knowledge from EMRs to support patient-centered stroke management. Objective: This study aims to compare the effectiveness of state-of-the-art automatic text classification methods in classifying data to support the prediction of clinical patient outcomes and the extraction of patient characteristics from EMRs. Methods: Our study addressed the computational problems of information extraction and automatic text classification. We identified essential tasks to be considered in an ischemic stroke value-based program. The 30 selected tasks were classified (manually labeled by specialists) according to the following value agenda: tier 1 (achieved health care status), tier 2 (recovery process), care related (clinical management and risk scores), and baseline characteristics. The analyzed data set was retrospectively extracted from the EMRs of patients with stroke from a private Brazilian hospital between 2018 and 2019. A total of 44,206 sentences from free-text medical records in Portuguese were used to train and develop 10 supervised computational machine learning methods, including state-of-the-art neural and nonneural methods, along with ontological rules. As an experimental protocol, we used a 5-fold cross-validation procedure repeated 6 times, along with subject-wise sampling. A heatmap was used to display comparative result analyses according to the best algorithmic effectiveness (F1 score), supported by statistical significance tests. A feature importance analysis was conducted to provide insights into the results. Results: The top-performing models were support vector machines trained with lexical and semantic textual features, showing the importance of dealing with noise in EMR textual representations. The support vector machine models produced statistically superior results in 71% (17/24) of tasks, with an F1 score >80% regarding care-related tasks (patient treatment location, fall risk, thrombolytic therapy, and pressure ulcer risk), the process of recovery (ability to feed orally or ambulate and communicate), health care status achieved (mortality), and baseline characteristics (diabetes, obesity, dyslipidemia, and smoking status). Neural methods were largely outperformed by more traditional nonneural methods, given the characteristics of the data set. Ontological rules were also effective in tasks such as baseline characteristics (alcoholism, atrial fibrillation, and coronary artery disease) and the Rankin scale. The complementarity in effectiveness among models suggests that a combination of models could enhance the results and cover more tasks in the future. Conclusions: Advances in information technology capacity are essential for scalability and agility in measuring health status outcomes. This study allowed us to measure effectiveness and identify opportunities for automating the classification of outcomes of specific tasks related to clinical conditions of stroke victims, and thus ultimately assess the possibility of proactively using these machine learning techniques in real-world situations

Economic evaluation of a telemedicine service to expand Primary Health Care in Rio Grande do Sul : TeleOftalmo’s microcosting analysis

Este estudo avaliou o custo de um serviço público de telediagnóstico em oftalmologia. O método de custeio baseado em atividades e tempo (TDABC) foi adotado para examinar os componentes de custos relacionados à teleoftalmologia. Com este método, também foi possível estabelecer o custo unitário padrão que o telediagnóstico deveria ter, dada a capacidade instalada e utilização de profissionais. Dados de um ano de telediagnósticos foram considerados, e avaliou-se a mudança do custo por telediagnóstico ao longo do período de adaptação da tecnologia no sistema. O custo padrão calculado por diagnóstico oftalmológico a distância foi de R$119, considerando a emissão de 1.080 laudos de telediagnóstico oftalmológico por mês. Foi identificado um desequilíbrio entre as atividades que sugere a capacidade do método TDABC orientar ações de gestão e melhoria na alocação dos recursos. Ao longo de um ano, o custo unitário real passou de R$ 783 para R$283, ainda havendo espaço para se aproximar do custo padrão estimado. Avaliações econômicas parciais possuem importante aporte para subsidiar a incorporação de novas tecnologias. O TDABC merece destaque nesse sentido, pois permite obter informações mais precisas sobre custo da tecnologia, melhorando a capacidade de dimensionamento e gerenciamento da organização de saúde.This study evaluated the cost of public telediagnostic service in ophthalmology. The time-driven activity-based costing method (TDABC) was adopted to examine the cost components related to teleophthalmology. This method allowed us to establish the standard unit cost of telediagnosis, given the installed capacity and utilization of professionals. We considered data from one year of telediagnoses and evaluated the cost per telediagnosis change throughout technology adaptation in the system. The standard cost calculated by distance ophthalmic diagnosis was approximately R$ 119, considering the issuance of 1,080 monthly ophthalmic telediagnostic reports. We identified an imbalance between activities, which suggests the TDABC method’s ability to guide management actions and improve resource allocation. The actual unit cost fell from R$783 to R$ 283 over one year – with room to approach the estimated standard cost. Partial economic evaluations contribute significantly to support the incorporation of new technologies. The TDABC method deserves prominence, as it enables us to retrieve more accurate information on the cost of technology, improving the scalability and management capacity of the healthcare system.Teleducaçã

Zika Virus Impairs Neurogenesis and Synaptogenesis Pathways in Human Neural Stem Cells and Neurons

Growing evidences have associated Zika virus (ZIKV) infection with congenital malformations, including microcephaly. Nonetheless, signaling mechanisms that promote the disease outcome are far from being understood, affecting the development of suitable therapeutics. In this study, we applied shotgun mass spectrometry (MS)-based proteomics combined with cell biology approaches to characterize altered molecular pathways on human neuroprogenitor cells (NPC) and neurons derived from induced pluripotent stem cells infected by ZIKV-BR strain, obtained from the 2015 Brazilian outbreak. Furthermore, ZIKV-BR infected NPCs showed unique alteration of pathways involved in neurological diseases, cell death, survival and embryonic development compared to ZIKV-AF, showing a human adaptation of the Brazilian viral strain. Besides, infected neurons differentiated from NPC presented an impairment of neurogenesis and synaptogenesis processes. Taken together, these data explain that CNS developmental arrest observed in Congenital Zika Syndrome is beyond neuronal cell death