Boletim Tuberculose 2022 / Tuberculosis Bulletin 2022

A tuberculose (TB) é um grande desafio para as autoridades de saúde pública no mundo. O Brasil é um dos 30 países onde a doença ainda está presente e, portanto, fazendo parte da lista e das prioridades nas agendas internacionais para estratégias de controle do agravo (BRASIL, 2020; 2021b). O plano nacional pelo fim da TB como problema de saúde pública 2021-2025 renova as metas a serem atingidas para melhoria das condições da doença, com redução da incidência para 90% e da mortalidade para 95%. Estas metas tomaram como base o resultado do ano de 2015 no país (BRASIL, 2021; 2022). Com a emergência sanitária causada pelo advento da COVID 19 houve piora das condições da tuberculose com queda dos diagnósticos em 2020 e, consequentemente, do registro de notificações, e aumento dos óbitos, causando piora nos indicadores tanto epidemiológicos quanto operacionais (BRASIL, 2022). O estado do Rio de Janeiro dentro deste quadro da TB situa-se em posição de destaque negativo, sendo o 2º em taxa de incidência e o 1º em taxa de mortalidade, segundo dados do último boletim de 2022 do Ministério da Saúde (BRASIL, 2022). Para que a situação da doença seja acompanhada por gestores e programas de saúde, bem como por toda comunidade científica e social é através do cálculo de seus principais indicadores, por meio dos sistemas oficiais de vigilância padronizados nacionalmente. Sendo os indicadores de morbidade extraídos da alimentação do Sistema de Informação de Agravo de Notificação ­ SINAN, com preenchimento da ficha de notificação/investigação da tuberculose. E para os dados de mortalidade o Sistema sobre Mortalidade ­ SIM, por meio do registro da Declaração de Óbitos.

A cross-sectional survey on awareness of cancer risk factors, information sources and health behaviors for cancer prevention in Japan.

Due to recent increases in cancer burden worldwide, we investigated current awareness of cancer risk factors and the association between information sources and health behaviors for cancer prevention in Japan. A nationwide representative sample aged 20 years or older (563 men and 653 women) responded to a questionnaire as part of a population-based survey in December 2018. Tobacco smoking (55.7% of the mean attributable fraction of cancer risk overall) and cancer-causing infection (52.0%) were regarded more highly than other lifestyle factors as causes of cancer (obesity [36.6%], physical inactivity [31.9%], unbalanced diet [30.9%], and alcohol consumption [26.2%]). The association between information sources and health behaviors for cancer prevention was evaluated using a logistic regression model. The websites of public institutions, and health professionals were associated with a broad range of health behaviors including improving diet, exercise, cancer screening/health check-up, and abstinence from smoking/drinking. Among sources of print media, positive associations were observed between books and improving diet/exercise, brochures and cancer screening/health check-up, and advertisements and abstinence from smoking/drinking. A strategic health communication approach that utilizes various information sources and delivery channels is needed to inform the public about cancer prevention and to motivate risk-reducing behaviors in the population.

Developing a Workflow Composite Score to Measure Clinical Information Logistics. A Top-down Approach.

BACKGROUND: Availability and usage of individual IT applications have been studied intensively in the past years. Recently, IT support of clinical processes is attaining increasing attention. The underlying construct that describes the IT support of clinical workflows is clinical information logistics. This construct needs to be better understood, operationalised and measured. OBJECTIVES: It is therefore the aim of this study to propose and develop a workflow composite score (WCS) for measuring clinical information logistics and to examine its quality based on reliability and validity analyses. METHODS: We largely followed the procedural model of MacKenzie and colleagues (2011) for defining and conceptualising the construct domain, for developing the measurement instrument, assessing the content validity, pretesting the instrument, specifying the model, capturing the data and computing the WCS and testing the reliability and validity. RESULTS: Clinical information logistics was decomposed into the descriptors data and information, function, integration and distribution, which embraced the framework validated by an analysis of the international literature. This framework was refined selecting representative clinical processes. We chose ward rounds, pre- and post-surgery processes and discharge as sample processes that served as concrete instances for the measurements. They are sufficiently complex, represent core clinical processes and involve different professions, departments and settings. The score was computed on the basis of data from 183 hospitals of different size, ownership, location and teaching status. Testing the reliability and validity yielded encouraging results: the reliability was high with r(split-half) = 0.89, the WCS discriminated between groups; the WCS correlated significantly and moderately with two EHR models and the WCS received good evaluation results by a sample of chief information officers (n = 67). These findings suggest the further utilisation of the WCS. CONCLUSION: As the WCS does not assume ideal workflows as a gold standard but measures IT support of clinical workflows according to validated descriptors a high portability of the WCS to other hospitals in other countries is very likely. The WCS will contribute to a better understanding of the construct clinical information logistics.

Integrating Methods to Evaluate Health Information Systems.

There are different methods to evaluate Health Information Systems (HIS), such as Quality Evaluation of software products, human factors, and socio-technical approaches. This work aims to identify the main aspects used to evaluate HIS, and whether there are relationships between issues considered in assessment of software quality and the ones applied specific to the health domain. This was an exploratory study that included a literature search related to HIS evaluation and software quality analyses applying the norms of the International Organization for Standardization (ISO/IEC), to identify aspects and features applied during the assessment process. The result is a proposal of an evaluation method based on the integration of these two evaluative approaches, combining or complementing the considered aspects. The method was applied to an evaluation of a natural language processing system to identify continuity of care in discharge summaries.

Normalization of Phenotypic Data from a Clinical Data Warehouse: Case Study of Heterogeneous Blood Type Data with Surprising Results.

Clinical data warehouses often contain analogous data from disparate sources, resulting in heterogeneous formats and semantics. We have developed an approach that attempts to represent such phenotypic data in its most atomic form to facilitate aggregation. We illustrate this approach with human blood antigen typing (ABO-Rh) data drawn from the National Institutes of Health's Biomedical Translational Research Information System (BTRIS). In applying the method to actual patient data, we discovered a 2% incidence of changed blood types. We believe our approach can be applied to any institution's data to obtain comparable patient phenotypes. The actual discrepant blood type data will form the basis for a future study of the reasons for blood typing variation.

Designing and conducting low-cost in-situ clinical simulations: a methodological approach.

The need to develop more effective and usable systems in healthcare has led to increasing adoption of usability engineering methods. Primary among these methods has been usability testing, which involves observing representative users while they carry out representative tasks using health information systems. However, such testing may not capture the cognitive and social contexts of use of systems in real settings, necessitating the use of clinical simulations. Such simulations involve testing representative users carrying out representative tasks, systems in realistic and representative environments. In this paper we describe our work in both reducing the cost of simulation testing while at the same time increasing the fidelity of the simulations. We describe an approach which involves conducting simulations within real work environments and contexts as a way to achieve a high level of ecological validity. The stages involved in setting up such low-cost in-situ clinical simulations are detailed in this paper.

Revisiting heuristic evaluation methods to improve the reliability of findings.

The heuristic evaluation (HE) method is one of the most common in the suite of tools for usability evaluations because it is a fast, inexpensive and resource-efficient process in relation to the many usability issues it generates. The method emphasizes completely independent initial expert evaluations. Inter-rater reliability and agreement coefficients are not calculated. The variability across evaluators, even dual domain experts, can be significant as is seen in the case study here. The implications of this wide variability mean that results are unique to each HE, results are not readily reproducible and HE research on usability is not yet creating a uniform body of knowledge. We offer recommendations to improve the science by incorporating selected techniques from qualitative research: calculating inter-rater reliability and agreement scores, creating a codebook to define concepts/categories and offering crucial information about raters' backgrounds, agreement techniques and the evaluation setting.

Automatically Assessing the Expert Degree of Online Health Content using SVMs.

More and more people search for health information regarding diseases, diagnoses and treatments over the Web. However, lay people often have difficulties in assessing the understandability of related articles. Therefore, they could benefit from a system, which computes the medical expert degree of a corresponding piece of text in advance. In this paper we present an approach to automatically compute this expert degree using a machine learning approach. For evaluation purposes we constructed a large text corpus and tested our trained text classifier, which is based on Support Vector Machines.

Preliminary comparison of mHealth architectures based on MU2 criteria.

Mobile Health (MH) is a hot topic in the health IT industry because it can make a big difference in healthcare services. Before adopting Mobile Health technology, however, we must ensure that it provides safe and reliable services to users and it should be evaluated by authoritative criteria. In US, Electronic Health Record (EHR) systems are evaluated through Meaningful Use (MU). Although MU focuses on EHR systems, it can't be thought of without MH. So in this paper we derive proper evaluation criteria for MH from MU criteria and evaluate existing MH architectures that are currently being surveyed in ISO/AWI TR 17522 - Provisions for Health Applications on Mobile/Smart Devices.