OBJECTIVE: To describe the epidemiological, clinical, paraclinical, therapeutic and evolutionary characteristics of of peripartum cardiomyopathy (PPCM) in the internal medicine department of the Zinder National Hospital (ZNH).
METHODS: This was a descriptive cross-sectional study carried out from 2018 to 2022 at the ZNH Department of Internal Medicine. Included were all patients admitted for PPCM who met National Heart Blood and Lung Institute criteria. The data collected was analyzed using Excel and EPI INFO v7.
RESULTS: We had collected 100 cases of PPCM out of a total of 8706 hospitalized patients, i.e. a hospital prevalence of 1.14%. The mean age of the patients was 27.9 years ± 7.4 [17-45]. The majority of patients were from underprivileged social strata (n=64). The risk factors for PMPC found were essentially hot bath (n=66), home birth (n=40), natron porridge (n=35) and multiparity (n=57). Cardiac symptomatology appeared postpartum in 56% of patients. Dyspnea was the main symptom in 98% of cases. The physical signs were dominated by the functional systolic murmur (66%). Three quarters (75%) of the patients had congestive heart failure. Electrocardiographic signs were dominated by left ventricular hypertrophy (n=65). Cardiomegaly was present in 94% of patients. Left ventricular ejection fraction was altered in all patients. Impaired renal function was found in 31% of patients. Management was based on a low-sodium diet tripod, diuretics and converting enzyme inhibitors. Two cases of death were recorded.
CONCLUSIONS: PPCM is common in the Zinder region. It affects young women with several risk factors and is revealed by signs of congestive heart failure. For a better understanding of this still poorly elucidated condition, it is necessary to pursue research efforts.

UNASSIGNED: Case management is an approach used to help patients locate and manage health resources as well as to enhance effective communication among patients, families, and health systems. Nurses\' role as case managers has been proven effective in reducing healthcare costs among patients with chronic diseases. However, little is known about its implementation in improving access to care in community-based settings.
UNASSIGNED: This scoping review aimed to examine the components of nursing case management in improving access to care within community settings and to identify the issues of community-based nursing case management for future implications.
UNASSIGNED: This study was conducted following the framework of scoping review.
UNASSIGNED: The authors systematically searched five electronic databases (CINAHL, PubMed, Science Direct, Scopus, and Google Scholar) for relevant studies published from January 2010 to February 2021. Only original studies involving nurses as one of the professions performing case management roles in the community-based settings, providing \'access to care\' as the findings, were included.
UNASSIGNED: The article screening was guided by a PRISMA flowchart. Extraction was performed on Google Sheet, and synthesis was conducted from the extraction result.
UNASSIGNED: A total of 19 studies were included. Five components of nursing case management to improve access to care were identified: 1) Bridging health systems into the community, 2) Providing the process of care, 3) Delivering individually-tailored health promotion and prevention, 4) Providing assistance in decision making, and 5) Providing holistic support. In addition, three issues of nursing case management were also identified: 1) Regulation ambiguity, 2) High caseloads, and 3) Lack of continuing case management training.
UNASSIGNED: Care coordination and care planning were the most frequent components of nursing case management associated with access to care. These findings are substantial to improve nurses\' ability in performing the nursing process as well as to intensify nurses\' advocacy competence for future implications.

Mental health resources are an important basis for coping with mental health services. The equity is an important index of a reasonable allocation of health resources. This study aims to evaluate the mental health resources and its equity allocation in Hunan Province, which is one of the typical central south areas of China, so as to provide reference for the development of mental health in China and other areas.
Data related to mental health resources was obtained from the Project of Mental Health Resources in Hunan Province, which was conducted by the Department of Hunan Mental Health Center in 2019. The Gini coefficient, the Theil index and other indicators were employed to quantitatively evaluate the equity of mental health resources\' allocation.
By the end of 2018, there were a total of 141 mental health institutions in Hunan Province of China, the bed density was 5.31 beds per 10,000 people, the ratio of doctors to nurses was 2.20, the number of outpatients of mental health institutions was 1288,047 per year. The mental health resources\' allocation in terms of demographic dimension were in a preferred status with the Gini values all less than 0.3, and the Gini values for mental health resources`allocation in terms of geographical dimension ranged from 0.24 to 0.35. The Theil index for mental health allocation in terms of demographic dimension was lower than 0.05, and the Theil index for mental health allocation in terms of geographical dimension ranged from 0.04 to 0.11.
The shortage of mental health resources is still the priority issue to be increased and optimized by policy-makers in Hunan in the future, especially the human resources. Moreover, the utilization of mental health resources was low though its equity was fair. Policy-makers need to consider the high utilization and geographical accessibility of health resources among different regions to ensure people in different regions could get access to available health services.

BACKGROUND: Maternal and child health (MCH) hospitals play an essential role in providing MCH services in China, while the supply has become increasingly challenging in the past decade, especially among secondary MCH hospitals. In this study we aimed to evaluate the technical efficiency (TE) of secondary MCH hospitals in Hubei province (China) to generate evidence-based decision-making for efficiency improvement.
METHODS: The data were collected from the Department of Maternal and Child Health of Health Commission of Hubei Province in 2019. A total of 59 out of 74 secondary MCH hospitals were included as our study sample. Four input indicators (number of health professionals, number of beds, number of equipment with value greater than 10,000 RMB Yuan, building area for hospital operations) and three output indicators (number of total diagnostic patients, number of discharged patients, and number of birth deliveries) were selected based on previous literature. TE scores of the sample hospitals were estimated by using Bootstrap-Data Envelopment Analysis (Bootstrap-DEA).
RESULTS: After bias-correction with Bootstrap-DEA model, the average TE score of the MCH hospitals was 0.673. 20 (33.89%) MCH hospitals had TE scores below the average. No MCH hospitals achieved excellent efficiency; 16 (27.11%) MCH hospitals reached good efficiency; and 26 (44.06%) MCH hospitals fell into poor and failing efficiency. Besides, 17 MCH hospitals had TE scores of 1 before bias-corrections, while none of them reached 1 after bias correction.
CONCLUSIONS: Significant capacity variations existed among the secondary MCH hospitals in terms of input and output indicators and their overall TE was low in Hubei of China. For better improvement, the secondary MCH hospitals in Hubei need to improve their internal management and strengthen the construction of their information systems. A series of policy supports are needed from the health and insurance administrations to optimize health resources. Third-party performance evaluation can be piloted to improve efficiency and overall performance of the MCH hospitals. The policy recommendations we raise for MCH hospitals in Hubei can be worth learning for some low- and middle- income countries.

Background: Low and medium income countries (LMICs) such as Kenya experience nearly three times more cases of traumatic brain injury (TBI) compared to high income countries (HICs). This is primarily exacerbated by weak health systems especially at the pre-hospital care level. Generating local empirical evidence on TBI patterns and its influence on patient mortality outcomes is fundamental in informing the design of trauma-specific emergency medical service (EMS) interventions at the pre-hospital care level. This study determines the influence of TBI patterns and mortality. Methods: This was a case-control study with a sample of 316 TBI patients. Data was abstracted from medical records for the period of January 2017 to March 2019 in three tertiary trauma care facilities in Kenya. Logistic regression was used to assess influence of trauma patterns on TBI mortality, controlling for patient characteristics and other potential confounders. Results: The majority of patients were aged below 40 years (73%) and were male (85%). Road traffic injuries (RTIs) comprised 58% of all forms of trauma. Blunt trauma comprised 71% of the injuries. Trauma mechanism was the only trauma pattern significantly associated with TBI mortality. The risk of dying for patients sustaining RTIs was 2.83 times more likely compared to non-RTI patients [odds ratio (OR) 2.83, 95% confidence interval (CI) 1.62-4.93, p=0.001]. The type of transfer to hospital was also significantly associated with mortality outcome, with a public hospital having a two times higher risk of death compared to a private hospital [OR 2.18 95%CI 1.21-3.94, p<0.009]. Conclusion: Trauma mechanism (RTI vs non-RTI) and type of tertiary facility patients are transferred to (public vs private) are key factors influencing TBI mortality burden. Strengthening local EMS trauma response systems targeting RTIs augmented by adequately resourced and equipped public facilities to provide quality lifesaving interventions can reduce the burden of TBIs.

暂无摘要。

Despite remarkable academic efforts, why Enterprise Resource Planning (ERP) post-implementation success occurs still remains elusive. A reason for this shortage may be the insufficient addressing of an ERP-specific interior boundary condition, i.e., the multi-stakeholder perspective, in explaining this phenomenon. This issue may entail a gap between how ERP success is supposed to occur and how ERP success may actually occur, leading to theoretical inconsistency when investigating its causal roots. Through a case-based, inductive approach, this manuscript presents an ERP success causal network that embeds the overlooked boundary condition and offers a theoretical explanation of why the most relevant observed causal relationships may occur. The results provide a deeper understanding of the ERP success causal mechanisms and informative managerial suggestions to steer ERP initiatives towards long-haul success.

暂无摘要。

Poised to have the highest number of young people in the world, India will have the onus of providing adequate mental health resources to a demographic considered among the most vulnerable with regard to mental well-being. While the Mental Healthcare Act 2017 pushed for greater accountability and care in supporting individuals with mental illness, these directions were specific to services provided by the state and did not address the care required in non-hospital settings. Since many manifestations and repercussions of mental health issues in young people occur in educational institutions, it becomes vital to address ways in which we can formulate ethical mental health services at those sites. This article is a reflective case study of the ethical dilemmas and challenges around issues of confidentiality and quality of care in relation to demand, contributing to a larger mental health ecology involved in providing mental health resources at the Student Support Centre, Manipal, that caters exclusively to students in an Indian campus town.

Accurate forecasting of medical service requirements is an important big data problem that is crucial for resource management in critical times such as natural disasters and pandemics. With the global spread of coronavirus disease 2019 (COVID-19), several concerns have been raised regarding the ability of medical systems to handle sudden changes in the daily routines of healthcare providers. One significant problem is the management of ambulance dispatch and control during a pandemic. To help address this problem, we first analyze ambulance dispatch data records from April 2014 to August 2020 for Nagoya City, Japan. Significant changes were observed in the data during the pandemic, including the state of emergency (SoE) declared across Japan. In this study, we propose a deep learning framework based on recurrent neural networks to estimate the number of emergency ambulance dispatches (EADs) during a SoE. The fusion of data includes environmental factors, the localization data of mobile phone users, and the past history of EADs, thereby providing a general framework for knowledge discovery and better resource management. The results indicate that the proposed blend of training data can be used efficiently in a real-world estimation of EAD requirements during periods of high uncertainties such as pandemics.