16 research outputs found
Data Science in Healthcare
Data science is an interdisciplinary field that applies numerous techniques, such as machine learning, neural networks, and deep learning, to create value based on extracting knowledge and insights from available data. Advances in data science have a significant impact on healthcare. While advances in the sharing of medical information result in better and earlier diagnoses as well as more patient-tailored treatments, information management is also affected by trends such as increased patient centricity (with shared decision making), self-care (e.g., using wearables), and integrated care delivery. The delivery of health services is being revolutionized through the sharing and integration of health data across organizational boundaries. Via data science, researchers can deliver new approaches to merge, analyze, and process complex data and gain more actionable insights, understanding, and knowledge at the individual and population levels. This Special Issue focuses on how data science is used in healthcare (e.g., through predictive modeling) and on related topics, such as data sharing and data management
Emerging infectious diseases
Emerging Infectious Diseases is providing access to these abstracts on behalf of the ICEID 2012 program committee (www.iceid.org), which performed peer review. Emerging Infectious Diseases has not edited or proofread these materials and is not responsible for inaccuracies or omissions. All information is subject to change. Comments and corrections should be brought to the attention of the authors.Influenza preparedness: lessons learned -- Policy implications and infectious diseases -- Improving preparedness for infectious diseases -- New or rapid diagnostics -- Foodborne and waterborne infections -- Effective and sustainable surveillance platforms -- Healthcare-associated infections -- Molecular epidemiology -- Antimicrobial resistance -- Tropical infections and parasitic diseases -- H1N1 influenza -- Risk Assessment -- Laboratory Support -- Zoonotic and Animal Diseases -- Viral Hepatitis -- E1. Zoonotic and animal diseases -- E2. Vaccine issues -- E3. H1N1 influenza -- E4. Novel surveillance systems -- E5. Antimicrobial resistance -- E6. Late-breakers I -- Antimicrobial resistance -- Influenza preparedness: lessons learned -- Zoonotic and animal diseases -- Improving preparedness for infectious diseases -- Laboratory support -- Early warning systems -- H1N1 influenza -- Policy implications and infectious diseases -- Modeling -- Molecular epidemiology -- Novel surveillance systems -- Tropical infections and parasitic diseases -- Strengthening public health systems -- Immigrant and refugee health -- Foodborne and waterborne infections -- Healthcare-associated infections -- Foodborne and waterborne infections -- New or rapid diagnostics -- Improving global health equity for infectious diseases -- Vulnerable populations -- Novel agents of public health importance -- Influenza preparedness: lessons learned -- Molecular epidemiology -- Zoonotic and animal diseases -- Vaccine-preventable diseases -- Outbreak investigation: lab and epi response -- H1N1 influenza -- laboratory support -- effective and sustainable surveillance platforms -- new vaccines -- vector-borne diseases and climate change -- travelers' health -- J1. Vectorborne diseases and climate change -- J2. Policy implications and infectious diseases -- J3. Influenza preparedness: lessons learned -- J4. Effective and sustainable surveillance platforms -- J5. Outbreak investigation: lab and epi response I -- J6. Late-breakers II -- Strengthening public health systems -- Bacterial/viral coinfections -- H1N1 influenza -- Novel agents of public health importance -- Foodborne and waterborne infections -- New challenges for old vaccines -- Vectorborne diseases and climate change -- Novel surveillance systems -- Geographic information systems (GIS) -- Improving global health equity for infectious diseases -- Vaccine preventable diseases -- Vulnerable populations -- Laboratory support -- Prevention challenges for respiratory diseases -- Zoonotic and animal diseases -- Outbreak investigation: lab and epi response -- Vectorborne diseases and climate change -- Outbreak investigation: lab and epi response -- Laboratory proficiency testing/quality assurance -- Effective and sustainable surveillance platforms -- Sexually transmitted diseases -- H1N1 influenza -- Surveillance of vaccine-preventable diseases -- Foodborne and waterborne infections -- Role of health communication -- Emerging opportunistic infections -- Host and microbial genetics -- Respiratory infections in special populations -- Zoonotic and animal diseases -- Laboratory support -- Antimicrobial resistance -- Vulnerable populations -- Global vaccine initiatives -- Tuberculosis -- Prevention challenges for respiratory diseases -- Infectious causes of chronic diseases -- O1. Outbreak investigation: lab and epi response II -- O2. Prevention challenges for respiratory diseases -- O3. Populations at high risk for infectious diseases -- O4. Foodborne and waterborne infections -- O5. Laboratory support: surveillance and monitoring infections -- O6. Late-breakers IIIAbstracts published in advance of the conference
Job evaluation model of major public hospitals in China
The current economic climate has contributed to an increasingly competitive
environment among organizations. In order to ensure competitive advantage, they must be
able to promote high levels of professional performance. This research is part of this theme
and aims to analyze how the job characteristics, professional knowledge, skills, competencies,
training and work engagement influence the job evaluation and, consequently, the
performance of employees of six public hospitals, China.
The sample consists of 546 subjects aged between 21 and 58 years (M = 37.9; SD =
8.73), with the majority being females (55.5%). For the collection of data, such scales were
used as the Job Diagnostic Survey (JDS), the Knowledge, Skills, Abilities, and Other Personal
Characteristics Scale (KSAOS), the Competencies and Training Scale (CTS) and the Utrecht
Work Engagement Scale (UWES).
The results obtained show that the job characteristics, the professional knowledge, the
skills, the training and the work engagement influence the job evaluation. It was also found
that the male respondents, those belonging to the older age group, those with higher academic
qualifications and those with higher positions present higher average performance in all
dimensions under study.
It was also possible to verify that Autonomy is the JDS variable with greater effect on the
Job evaluation and the bigger the Autonomy, Skill variety and Feedback given to the
employees, the more positive their perception of Job evaluation. Data analysis also reveals
that KSAO moderate the relations between job characteristics and job evaluation and the
dimension with the most effect on Job evaluation is Professional Ethics and Health Law. On
the other hand, the higher the competencies and professional training in the area of
Organization and finance, the greater the Job evaluation. Finally, it was verified that Vigor is
the only variable with significant effect on Job evaluation.
It is hoped that these results may inspire further research that contributes to a better
understanding of these relationships; and at the practical level, it is intended to alert the
justified investment by the organizations in the implementation of a performance evaluation
model. Taking into account the current competitiveness at the organizational level, it is
considered that the analysis of the relationships between these dimensions is crucial to an organization. In this way, this project is intended to build a new process of performance
evaluation in public hospitals in China, based on the competencies identified for each job.Atualmente, o clima económico contribuiu para um ambiente cada vez mais competitivo entre as organizações e para garantir a vantagem competitiva, as organizações devem ser capazes de promover altos nÃveis de desempenho profissional. Esta investigação insere-se nesta temática e tem como objetivo estudar como as caracterÃsticas da função, o conhecimento profissional, as habilidades, as competências e o envolvimento no trabalho influenciam a avaliação do trabalho e, consequentemente, o desempenho dos funcionários de seis hospitais públicos . China.
A amostra é composta por 546 sujeitos com idades compreendidas entre os 21 e os 58 anos (M = 37.9; DP = 8.73), sendo a maioria do sexo feminino (55.5%). Os dados foram recolhidos através das seguintes escalas: Job Diagnostic Survey (JDS), Escala de Conhecimento, Habilidades, Aptidões e Outras Escalas Pessoais (KSAOS), Escala de Competências e Formação (CTS) e Escala de Envolvimento no Trabalho de Utrecht ( UWES).
Os resultados obtidos mostram que as caracterÃsticas da função, o conhecimento profissional, as habilidades, a formação e o envolvimento no trabalho influenciam a avaliação do trabalho. Constatou-se também que os entrevistados do sexo masculino, os que pertencem à faixa etária mais avançada, os que possuem maior qualificação académica e que ocupam posições hierárquicas mais elevadas, apresentam um desempenho médio superior em todas as dimensões em estudo.
Também foi possÃvel verificar que a Autonomia é a variável do JDS com maior efeito na avaliação do trabalho e que quanto maior é a Autonomia, a variedade de competências e o feedback dado aos funcionários, mais positiva é a sua perceção da avaliação do trabalho. A análise dos dados também revelou que o KSAO modera a relação existente entre as caracterÃsticas da função e a avaliação do trabalho e que a variável com maior efeito na avaliação do trabalho é a Ética Profissional e a Lei da Saúde. Por outro lado, quanto maiores são as competências e a formação profissional na área de Organização e Finanças, melhor é a avaliação do trabalho. Por último, verificou-se que o Vigor é a única dimensão do envolvimento no trabalho com efeito significativo na avaliação do mesmo.
Espera-se que esses resultados possam inspirar pesquisas futuras e que possam contribuir para uma melhor compreensão dessas relações; a nÃvel prático pretende-se alertar os gestores para a implementação de um modelo de avaliação de desempenho. Considerando a atual competitividade a nÃvel organizacional, considera-se que a análise da relação entre estas dimensões é crucial para qualquer organização. Esta investigação pretende assim construir um novo processo de avaliação do trabalho nos hospitais públicos na China, com base nas competências identificadas para cada função
Strategic development of hospitals for infectious diseases: a dynamic capability approach
Public health emergencies have the characteristics of sudden, devastating and
unpredictable. The novel coronavirus (COVID-19) pandemic has spread worldwide in
2019, posing enormous threats to human health, global politics, and economy. The whole
world is encountering a severe situation of responding to emerging epidemics. Chinese
hospitals for infectious diseases undertake the special responsibilities for emergency
response and treatment to emerging and re-emerging infectious diseases, and make
contributions to safeguarding people's health and social stability. However, affected by the
continuous decline of the incidence of infectious diseases and the insufficient government
compensation mechanism, the survival and development of specialized hospitals for
infectious diseases are severely restricted and generally facing survival crisis.
In terms of data collection, this study combined dynamic capability theory,
resource-based view theory and strategic alliance theory. Through multiple-case study, the
qualitative data are processed with QSR NVivo 12 software. This thesis comprehensively
analyzes the development status, hospital resources, core competitiveness, dynamic
capabilities, strategic alliances (Medical Treatment Alliance), strategic adjustment and
performance of infectious disease hospitals in China. On the basis of data analysis, this
research constructs the development strategy model of infectious disease hospitals in the
rapidly changing environment, and puts forward the coping strategies for the survival and
development of infectious disease hospitals. The research conclusion is consistent with the
propositions and the existing literature, and considers that the competitive advantage is the
concrete embodiment of the dynamic capability, and the capability of public health events’
emergency response and disposal is the most important dynamic capability of Chinese
infectious disease hospitals. The research results provide scientific basis and useful
reference for the infectious disease hospitals to formulate the sustainable development
strategies and the government to formulate public health policies.As emergências da saúde pública não só são inesperadas, como são devastadoras e
imprevisÃveis. A nova pandemia (COVID 19), ao espalhar-se por todo o mundo, colocou
novos e enormes desafios à saúde pública, à economia e à polÃtica internacional. Todo o
mundo necessita de preparar-se para responder às epidemias emergentes. Os hospitais
chineses para doenças infeciosas têm como missão dar uma resposta rápida às doenças
infeciosas emergentes e re-emergentes e contribuir para a salvaguarda da saúde pública e
da estabilidade social. Contudo, devido ao declÃnio, nos últimos anos, das doenças
infeciosas e ao insuficiente mecanismo de compensação governamental, os hospitais
chineses viviam numa permanente crise de sobrevivência.
Para a recolha de dados, esta tese combinou a teoria das capacidades dinâmicas com a
teoria baseada nos recursos e a teoria das alianças estratégicas. Os dados foram
posteriormente tratados com o software NVivo 12. Esta tese analisa de um modo
compreensivo os recursos, as competências nucleares e as capacidades dinâmicas, assim
como as alianças estratégicas dos hospitais chineses de doenças infeciosas. Baseando-se na
análise dos dados, esta tese propõe uma estratégia de desenvolvimento para os hospitais de
doenças infeciosas para os tempos de mudança que vivemos. As conclusões estão de
acordo com as proposições extraÃdas da revisão de literatura e uma das conclusões é que
vantagem competitiva é a personificação das capacidades dinâmicas. Os resultados desta
tese podem contribuir para a formulação de uma estratégia sustentada para os hospitais de
doenças infeciosas e ajudar o governo na formulação de polÃticas públicas
PREDICTIVE MODELING FOR STUDYING THE DISEASE PROCESS OF OSTEOPOROSIS
Background:
Osteoporosis exerts a burden on the national health services. Hip fractures cause significant pain, functional disability, and lengthy inpatient treatment. Therefore, prevention is of utmost importance for patients and physicians, as well as insurance payers and insurance providers.
Significance:
There are gaps in knowledge about the complex interactions among the multiple factors which control the disease process. Computational modeling can aid in understanding the intermingled relations between the various factors at different levels and provide further insight into the disease development mechanism.
Methodology:
In the first aim, we built a computational model using Agent-Based Modeling (ABM) to investigate osteoporosis disease’s progression by simulating the interactions among the cellular and biochemical factors within the BMU and external factors such as weight, and physical activity. In the second aim, we added a therapeutic agent to predict the changes in patients who are receiving that treatment. In the third aim tested the model’s ability to estimate the bone density without the use of an initial DXA Scan reading. In the three aims, we validated the model by performing statistical tests to compare the model’s predictions and the DXA scan readings from the patients.
Results:
The Paired Sample T-test results was statistically not significant t (16) = -1.6, p = 0.12 in first aim and t (42) = 8.1, p = 0.28 and in the second aim. The sensitivity was between 85.7% and 100%, and the specificity was 90% to 100%. In the third aim, the model successfully predicted the bone density in the first group (40-50 years age group) of patients Wilcoxon-sign (13), p=0.196. The model was not able to estimate the bone density for the other age groups.
Conclusion:
We successfully built an ABM that can predict the bone density changes in osteoporosis patients and patients who are receiving alendronate drug treatment. The model, however, requires further improvement and testing to be able to estimate the bone density as a diagnostic tool. We conclude our ABM model can be used in research for studying the process of osteoporosis and has the potential to be developed into a clinical diagnostic tool
Systems Thinking Analyses for Health Policy and Systems Development
Using systems-thinking tools for the first time to understand an entire national health system, this book will be of immense value to academics, students and policymakers. The case study of Malaysia shows that a people-centred health system can be constructed successfully within existing and evolving resource constraints and priorities.