Brooke–Spiegler Syndrome: Familial Cylindromatosis, a Rare Variant of a Rare Familial Syndrome

Brooke–Spiegler Syndrome (BSS) is a rare autosomal dominant familial disorder resulting in dermatologic neoplasms of copious nodular appendages. Here, we report a case of Familial Cylindromatosis (FC), a subtype of BSS, in a patient with the largest cylindroma of 7.4 × 5.6 × 3.8 cm on the scalp. The patient had undiagnosed cylindromas growing for 36 years at presentation; however, he did not seek out healthcare evaluation. Excision and pathologic investigation of three large masses from different body sites determined a shared phenotype of cylindromas. Subsequent evaluation of the patient's son separately, after primary patient excision, confirmed cylindroma development as well. The pathologic evidence of cylindromas in the patient with a new history of family incidence confirmed the diagnosis of the FC variant of BSS.

Factors Influencing Patient Experience in Primary Healthcare Clinics within the eThekwini Municipality in KwaZulu-Natal

Patient experience is seen as a fundamental measure for healthcare evaluation, which fuels the debate regarding the most relevant factors influencing patient experience. Limited empirical knowledge exists concerning the factors that influence patient experience from the users’ perspective in South Africa. This study addresses the research gap by determining the factors influencing patient experience among primary healthcare users in Waterloo, Grove-End and Stonebridge communities in the eThekwini Municipality of KwaZulu-Natal. The study is quantitative, descriptive and cross-sectional, and utilises a self-administered questionnaire that was distributed among 280 primary healthcare users. They strongly agreed (> 90%) that all the factors presented in the study are contributors to their patient experience. The factor analysis determined the relevance of the factors as perceived by the respondents. It was found that the doctor’s role (0.970), clinic cleanliness (0.943), coordination and continuity of care (0.943), and waiting time (0.914) are the most significant influencers of patient experience. Education (0.898), nurses (0.882), medication (0.854) and the quality of care (0.853) serve as moderate influencers. Access (0.745), family/friend involvement (0.722) and the physical state of the infrastructure (0.714) are mild influencers of patient experience. Patient-centred care (0.639), management effectiveness (0.637), communication (0.596) and information (0.443) were non-influencers of patient experience. User experience is multifaceted and each factor represents a varying level of influence. It is recommended that a patient-experience framework should be developed that can be linked to improvement initiatives within South Africa in an effort to support quality improvement.

Proposal of a novel Artificial Intelligence Distribution Service platform for healthcare

In this paper, we focus on presenting a novel AI-based service platform proposal called AIDI (Artificial Intelligence Distribution Interface for healthcare). AIDI proposal is based on our earlier research work in which we evaluated AI-based healthcare services which have been used successfully in practice among healthcare service providers. We have also used our systematic review about AI-based healthcare services benefits in various healthcare sectors. This novel AIDI proposal contains services for health assessment, healthcare evaluation, and cognitive assistant which can be used by researchers, healthcare service provides, clinicians, and consumers. AIDI integrates multiple health databases and data lakes with AI service providers and open access AI algorithms. It also gives healthcare service providers open access to state-of-the-art AI-based diagnosis and analysis services. This paper provides a description of AIDI platform, how it could be developed, what can become obstacles in the development, and how the platform can provide benefits to healthcare when it will be operational in the future.

USE OF THE RISK MANAGEMENT TECHNOLOGY IN EVALUATION OF HEALTH SERVICES FOR EMPLOYEES OF ENTERPRISES OF A LARGE OIL PRODUCING COMPANY

Protection of personnel health is part and parcel of the corporate social policy adopted by oil producing companies with the divisional structure. The medical care system using outsourcing needs a proficient control of its functioning. Since it incorporates dozens of objects, the control is workable only provided digital technologies are applied. We made choice of the infographic matrix to build up two matrices, i.e. one for health risk management and the other, for resources and processes management. Besides, we developed systems for quantitative risk evaluation, and to score key resources, processes, and medical personnel efficiency on 5-point scales. Weight coefficient was accepted for each factor. The technique has been implemented for health analysis and healthcare evaluation at 49 enterprises. Scrupulous attention was given to the enterprises within the orange zone (51-75 on the scale). Out of 9 to 10 enterprises that traveled in the zone over 3 years of monitoring, 4 were present in both matrices. Analysis of the reports provided guides to develop response measures suitable for specific enterprises. Health risk matrices can find application in a large number of enterprises for online information acquisition, problem identification and solving.

A Proficient Scheme for Detecting Breast Cancer by Classification Techniques

Cancer is a risky disease which could affect the particular area in depth and may risk the body parts. Now a days, more females are subject to breast cancers. So that Machine Learning Techniques has proposed to analyze the risky area in which the information is utilized for forecasting additional incidents. Machine Learning is popular scheme within several programs one remaining healthcare evaluation. Image Classification as well as feature extraction will bring the affected area’s image into several analyzing methods. With this proposed system, we’ve suggested an CNN (Convolution Neural Network) active design which fetches a sequence of pictures coming from a healthcare scanner repository so that the pictures are preprocessed as well as additional segmented feature extraction. The effectiveness on the suggested design is examined and it is as opposed along with other Machine Learning procedures and it is found the proposed system has supplies the greater results. The functionality on the unit tends to be more precise as the unit has an iterative method for include removal inside classifying pictures. There are some images are kept for the training and testing. We have achieved the accuracy level of comparing with existing model.

Common Patient-Reported Outcomes across ICHOM Standard Sets - The potential contribution of PROMIS

The International Consortium for Health Outcomes Measurement (ICHOM) develops condition-specific Standard Sets of outcomes to be measured in clinical practice for value-based healthcare evaluation. Standard Sets are developed by different working groups, which is inefficient and may lead to inconsistencies in selected PROs and PROMs. This study aimed to identify common PROs across ICHOM Standard Sets and examined to what extend these PROs can be measured with a generic set of PROMs: the Patient-Reported Outcomes Measurement Information System (PROMIS®).All PROs and recommended PROMs were extracted from all available ICHOM Standard Sets. Similar PROs were categorized into unique PRO concepts. Subsequently, it was examined which of these PRO concepts can be measured with PROMIS.A total of 216 PROs were identified in 28 ICHOM Standard Sets and 96 PROMs are recommended for measuring these PROs. Inconsistencies were found in selected PROs, terminology used, and recommended PROMs. The 216 PROs could be categorized into 21 unique PRO concepts. More than half (16/21) of these PRO concepts (covering 75% of the PROs and 79% of the PROMs) can be measured with a PROMIS measure.Considerable overlap was found in PROs across ICHOM Standard Sets, and large differences in terminology used and PROMs recommended, even for the same PROs. Inconsistencies in selected PROs and PROMs across Standard Sets questions the validity of the Standard Sets. We recommend a more universal and standardized approach to the selection of PRO and PROM, using PROMIS.

Excess of Cardiovascular Deaths During the COVID-19 Pandemic in Brazilian Capital Cities

IntroductionDuring the COVID-19 pandemic, excess mortality has been reported, while hospitalizations for acute cardiovascular events reduced. Brazil is the second country with more deaths due to COVID-19. We aimed to evaluate excess cardiovascular mortality during COVID-19 pandemic in 6 Brazilian capital cities.MethodsUsing the Civil Registry public database, we evaluated total and cardiovascular excess deaths, further stratified in ACS, stroke and unspecified cardiovascular deaths in the 6 Brazilian cities with greater number of COVID-19 deaths (São Paulo, Rio de Janeiro, Fortaleza, Recife, Belém, Manaus). We compared data from epidemiological weeks 12 to 22 of 2020, with the same period in 2019. We also compared the number of hospital and home deaths during the period.ResultsThere were 69,328 deaths and 17,877 COVID-19 deaths in the studied period and cities for 2020. Cardiovascular mortality increased in most cities, with greater magnitude in the Northern capitals. However, while there was a reduction in ACS and stroke in the most developed cities, the Northern capitals showed an increase of these events. For unspecified cardiovascular deaths, there was a marked increase in all cities, which strongly correlated to the rise in home deaths (r=0.86, p=0.01).ConclusionThe excess cardiovascular mortality was greater in the less developed cities, possibly associated with healthcare collapse. ACS and stroke deaths decreased in the most developed cities, in parallel with an increase in unspecified cardiovascular and home deaths, presumably as a result of misdiagnosis. Conversely, ACS and stroke deaths increased in cities with a healthcare collapse.Clinical PerspectiveWhat is already known about this subject?During the pandemic, beyond deaths due to confirmed COVID-19, there seems to be an increase in the total number of deaths compared to previous years in Brazil. Excess mortality may have occurred due to identified or not COVID-19 or other causes, being an objective and comparable metric for healthcare evaluation.What does this study add?In the 6 Brazilian capitals with higher numbers of deaths due to COVID-19, the impact of the pandemic in the excess all-cause and cardiovascular deaths was noticeable, especially in regions where health systems collapsed, which are the most socioeconomically deprived. In the other capital cities, the decreasing number of deaths associated with well-defined events (ACS and stroke) paralleled with more frequent undefined cardiovascular and home deaths.How might this impact on clinical practice?Investments should be prioritized to areas where the pandemic resulted in health system collapse. During periods of social distancing, campaigns and strategies to increase the population’s awareness of cardiovascular care, health promotion practices, seeking services in the case of acute signs and symptoms, should be prioritized by governments.The Corresponding Author has the right to grant on behalf of all authors and does grant on behalf of all authors, an exclusive license on a worldwide basis to the BMJ Publishing Group Ltd and its Licensees to permit this article to be published in HEART editions and any other BMJPGL products to exploit all subsidiary rights.