Projecting Demand-Supply Gap of Hospital Capacity in India in the face of COVID-19 pandemic using Age-Structured deterministic SEIR model

Verma, Veenapani Rajeev; Saini, Anuraag; Gandhi, Sumirtha; Dash, Umakant; Koya, Shaffi Fazaludeen

doi:10.1101/2020.05.14.20100537

Cited by 4 publications

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References 6 publications

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“…According to Ramírez-Pereira et al [27], this challenge is more relevant and complex in pandemic scenarios. Moreover, Grossman [28], Alcalde-Rabanal et al [29], Braithwaite and Nolan [30], Solanki et al [31], Verma et al [32] pointed out that this situation, and others, such as the inability to manage the health problems of patients with available resources, generate important gaps between the health demand and the care supply that healthcare services must manage.…”

Section: Waiting List: the Gap Between Supply And Demand In Healthcarementioning

confidence: 99%

An Intelligent System for Patients’ Well-Being: A Multi-Criteria Decision-Making Approach

et al. 2022

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The coronavirus pandemic has intensified the strain on medical care processes, especially waiting lists for patients under medical management. In Chile, the pandemic has caused an increase of 52,000 people waiting for care. For this reason, a high-complexity hospital (HCH) in Chile devised a decision support system (DSS) based on multi-criteria decision-making (MCDM), which combines management criteria, such as critical events, with clinical variables that allow prioritizing the population of chronic patients on the waiting list. The tool includes four methodological contributions: 1) pattern recognition through the analysis of anonymous patient data that allows critical patients to be characterized; 2) a score of the critical events suffered by the patients; 3) a score based on clinical criteria; and 3) a dynamic–hybrid methodology for patient selection that links critical events with clinical criteria and with the risk levels of patients on the waiting list. The methodology allowed to 1) characterize the most critical patients and triple the evaluation of medical records; 2) save medical hours during the prioritization process; 3) reduce the risk levels of patients on the waiting list; and 4) reduce the critical events in the first month of implementation, which could have been caused by the DSS and medical decision-making. This strategy was effective (even during a pandemic period).

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Section: Waiting List: the Gap Between Supply And Demand In Healthcarementioning

confidence: 99%

An Intelligent System for Patients’ Well-Being: A Multi-Criteria Decision-Making Approach

et al. 2022

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Applications of digital health for public health responses to COVID-19: a systematic scoping review of artificial intelligence, telehealth and related technologies

et al. 2021

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The coronavirus disease 2019 (COVID-19) pandemic has overwhelmed healthcare services, faced with the twin challenges in acutely meeting the medical needs of patients with COVID-19 while continuing essential services for non-COVID-19 illnesses. The need to re-invent, re-organize and transform healthcare and co-ordinate clinical services at a population level is urgent as countries that controlled initial outbreaks start to experience resurgences. A wide range of digital health solutions have been proposed, although the extent of successful real-world applications of these technologies is unclear. This study aims to review applications of artificial intelligence (AI), telehealth, and other relevant digital health solutions for public health responses in the healthcare operating environment amidst the COVID-19 pandemic. A systematic scoping review was performed to identify potentially relevant reports. Key findings include a large body of evidence for various clinical and operational applications of telehealth (40.1%, n = 99/247). Although a large quantity of reports investigated applications of artificial intelligence (AI) (44.9%, n = 111/247) and big data analytics (36.0%, n = 89/247), weaknesses in study design limit generalizability and translation, highlighting the need for more pragmatic real-world investigations. There were also few descriptions of applications for the internet of things (IoT) (2.0%, n = 5/247), digital platforms for communication (DC) (10.9%, 27/247), digital solutions for data management (DM) (1.6%, n = 4/247), and digital structural screening (DS) (8.9%, n = 22/247); representing gaps and opportunities for digital public health. Finally, the performance of digital health technology for operational applications related to population surveillance and points of entry have not been adequately evaluated.

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An Overview of Hospital Capacity Planning and Optimisation

et al. 2022

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Health care is uncertain, dynamic, and fast growing. With digital technologies set to revolutionise the industry, hospital capacity optimisation and planning have never been more relevant. The purposes of this article are threefold. The first is to identify the current state of the art, to summarise/analyse the key achievements, and to identify gaps in the body of research. The second is to synthesise and evaluate that literature to create a holistic framework for understanding hospital capacity planning and optimisation, in terms of physical elements, process, and governance. Third, avenues for future research are sought to inform researchers and practitioners where they should best concentrate their efforts. In conclusion, we find that prior research has typically focussed on individual parts, but the hospital is one body that is made up of many interdependent parts. It is also evident that past attempts considering entire hospitals fail to incorporate all the detail that is necessary to provide solutions that can be implemented in the real world, across strategic, tactical and operational planning horizons. A holistic approach is needed that includes ancillary services, equipment medicines, utilities, instrument trays, supply chain and inventory considerations.

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Projecting Demand-Supply Gap of Hospital Capacity in India in the face of COVID-19 pandemic using Age-Structured deterministic SEIR model

Cited by 4 publications

References 6 publications

An Intelligent System for Patients’ Well-Being: A Multi-Criteria Decision-Making Approach

An Intelligent System for Patients’ Well-Being: A Multi-Criteria Decision-Making Approach

Applications of digital health for public health responses to COVID-19: a systematic scoping review of artificial intelligence, telehealth and related technologies

An Overview of Hospital Capacity Planning and Optimisation

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