Decision-Making based on Big Data Analytics for People Management in Healthcare Organizations

Sousa, Maria José; Pesqueira, António Miguel; Lemos, Carlos M.; Sousa, Miguel; Rocha, Álvaro

doi:10.1007/s10916-019-1419-x

Cited by 98 publications

(51 citation statements)

References 42 publications

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“…Thus, to identify the measuring and managing performance indicators is at the heart of performance management and measurement [47]. Prior studies have conducted studies about the financial indicators of social organizations [48,49]. However, Social organizations are mission-driven (rather than profit-driven) organizations and we cannot simply use financial indicators to measure the overall performance of social organizations [50].…”

Section: Performance Management and Evaluationmentioning

confidence: 99%

A SBM-DEA based performance evaluation and optimization for social organizations participating in community and home-based elderly care services

Shao

Yuan

Lin³

et al. 2021

PLoS ONE

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The community and home-based elderly care service system has been proved an effective pattern to mitigate the elderly care dilemma under the background of accelerating aging in China. In particular, the participation of social organizations in community and home-based elderly care service has powerfully fueled the multi-supply of elderly care. As the industry of the elderly care service is in the ascendant, the management lags behind, resulting in the waste of significant social resources. Therefore, performance evaluation is proposed to resolve this problem. However, a systematic framework for evaluating performance of community and home-based elderly care service centers (CECSCs) is absent. To overcome this limitation, the SBM-DEA model is introduced in this paper to evaluate the performance of CECSCs. 186 social organizations in Nanjing were employed as an empirical study to develop the systematic framework for performance evaluation. Through holistic analysis of previous studies and interviews with experts, a systematic framework with 33 indicators of six dimensions (i.e., financial management, hardware facilities, team building, service management, service object and organization construction) was developed. Then, Sensitivity Analysis is used to screen the direction of performance optimization and specific suggestions were put forward for government, industrial associations and CECSCs to implement. The empirical study shows the proposed framework using SBM-DEA and sensitivity analysis is viable for conducting performance evaluation and improvement of CECSCs, which is conducive to the sustainable development of CECSCs.

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Section: Performance Management and Evaluationmentioning

confidence: 99%

A SBM-DEA based performance evaluation and optimization for social organizations participating in community and home-based elderly care services

Shao

Yuan

Lin³

et al. 2021

PLoS ONE

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“…Most of the worldwide HCOs are adopting robust data strategy [35] relying on Big Data techniques and concepts [36][37][38][39], where MDs are playing a decisive role to manage internal procedures and lead advanced diagnostics, treatments, medical prescriptions and consultations as well as hospital discharges/admissions more effectively. According to the literature, some of those activities and key topics can be divided into four major areas: (1) Data transformation, (2) health intelligence, (3) data leveraging, and (4) decision making, as reported in Table 1.…”

Section: Continuous Medical Education and Learningmentioning

confidence: 99%

The Potential of Big Data Research in HealthCare for Medical Doctors’ Learning

et al. 2021

Self Cite

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“…Além do apoio à decisão clínica, o suporte à decisão também deve ser considerado para decisões de negócio. A implementação de sistemas de suporte à decisão em organizações de saúde pode assumir diferentes níveis estratégicos, como abordar algumas perguntas sobre a dimensão operacional; ajudar passivamente na criação de relatórios para execução de procedimento; apoiar a modificação de estratégias; ou tratar os sistemas de apoio à decisão como recursos estratégicos na tomada de decisão [Sousa et al, 2019].…”

Section: Aplicações De Computação Em Nuvem Na Saúdeunclassified

Aplicações em redes de sensores na área da saúde e gerenciamento de dados médicos: tecnologias em ascensão

Santos¹,

Firmino²,

Soto³

et al. 2020

Minicursos SBCAS 2020

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Sensor networks have become increasingly popular in healthcare due to the widespread use of cell phones and accessories capable of capturing medical data and the growth of remote patient monitoring initiatives. Medical data captured by sensors are sensitive and require the guarantee of authenticity, confidentiality, and privacy in the context of the Brazilian regulations, according to "Lei Geral de Proteção de Dados" (LGPD). Besides, the management and guarantee of medical data interoperability depend on the use of syntax and semantics following international standards. Therefore, the cloud computing and the Internet of Things are enabling tools for digital technologies to improve patient care. In this chapter, we present and discuss sensor networks' main concepts and the collection, processing, and protection of data from sensitive medical data. Resumo As redes de sensores têm se tornado cada vez mais populares na área de saúde devido à ampla disseminação dos celulares e acessórios aptos a captar dados médicos e ao crescimento de iniciativas de monitoramento remoto de pacientes. Dados médicos são considerados dados sensíveis e como tal requerem a garantia de autenticidade, confidencialidade e privacidade no contexto da Lei Geral de Proteção de Dados (LGPD). Paralelamente, a gerência e garantia de interoperabilidade de dados médicos dependem do uso de sintaxe e semânticas de acordo com padronizações internacionais. Assim, a utilização da computação em nuvem e a Internet das Coisas são facilitadores para o desenvolvimento de tecnologias digitais para melhorar o atendimento ao paciente. Considerando esse cenário, este capítulo apresenta e discute os principais conceitos relacionados às redes de sensores e à coleta, tratamento e proteção de dados de médicos sensíveis.

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Decision-Making based on Big Data Analytics for People Management in Healthcare Organizations

Cited by 98 publications

References 42 publications

A SBM-DEA based performance evaluation and optimization for social organizations participating in community and home-based elderly care services

A SBM-DEA based performance evaluation and optimization for social organizations participating in community and home-based elderly care services

The Potential of Big Data Research in HealthCare for Medical Doctors’ Learning

Aplicações em redes de sensores na área da saúde e gerenciamento de dados médicos: tecnologias em ascensão

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