Predictive and Prescriptive Analytics in Healthcare: A Survey

Lopes, João; Guimarães, Tiago; Santos, Manuel Filipe

doi:10.1016/j.procs.2020.03.078

Cited by 30 publications

(9 citation statements)

References 7 publications

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“…[45] proposes a system that collects Big Data using wearables and applies AI techniques to predict the potential risk for a patient's health and Ref. [76] refers to a few study cases such as the early cancer detection or mortality risk for patients with acute leukaemia. A further predictive model has been proposed by Ref.…”

Section: � Main Relevant Applications Based On Big Data Include Butmentioning

confidence: 99%

“…It can be a driver for healthcare organisations to understand the industry better, as well as the characteristics of the market, improve margins, optimise revenue streams and provide market feedback of the revenues [35,67]. The use of Data Analytics and the interconnectivity of devices can decrease unnecessary visits to hospitals and the pressure to the healthcare system they cause, while also limiting the negative impact that no-shows or lastminute cancellations have [28,76].…”

Section: Business' Organisation and Decision-makingmentioning

confidence: 99%

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Industry 4.0 and healthcare: Context, applications, benefits and challenges

et al. 2022

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Industry 4.0 refers to the digital transformation in the manufacturing domain through new technology. Currently, it expands well beyond manufacturing, affecting many areas of life and posing implications for all types of business. This paper focuses on the relationships between Industry 4.0 and Healthcare which transitions to increased interconnectivity, automation and smart decision making. The integration context of Industry 4.0 into Healthcare is only partly understood. Little was done until now to consolidate what is known on the integration benefits and the challenges. This article reports results of a systematic mapping study that analysed 69 papers to extract knowledge about the concepts of Industry 4.0 and the emerging Healthcare 4.0., and the relationships between them. We found 10 different perspectives of Healthcare 4.0, ranging from strategic to tactical and operational levels. Next, our results show: (i) nine applications of Industry 4.0 in the Healthcare domain: Augmented Reality and Simulation, Autonomous Robotics, Cybersecurity, Big Data Analytics, Internet of Things, Cloud Computing, Additive Manufacturing and Systems Integration; and (ii) 10 benefits and nine challenges in Healthcare 4.0. The most frequently mentioned benefits are patients' diagnosis, monitoring, treatment, and financial benefits. The most researched challenges are data fragmentation, heterogeneity, complexity, and privacy.

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Section: � Main Relevant Applications Based On Big Data Include Butmentioning

confidence: 99%

Section: Business' Organisation and Decision-makingmentioning

confidence: 99%

Industry 4.0 and healthcare: Context, applications, benefits and challenges

et al. 2022

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“…A lot has changed in the last five years, from the mainstreaming of IOT to the rise of artificial intelligence (AI) and machine learning (ML) 6 . The fundamental shift these advanced computing tools have brought to the industry is to make it more predictive rather than reactive 7 . Healthcare has been a reactive industry 8 , i.e.…”

Section: Introductionmentioning

confidence: 99%

Novel 4A Framework for Measuring Outcomes of Technological Implementation in The Healthcare Industry

Rajaram

Pandey

Saproo³

et al. 2023

Int J Life Sci Pharm Res

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The healthcare industry is ever-evolving, and advancements in this industry are happening on multiple fronts, i.e. scientific, medical, regulatory etc. This industry has witnessed significant changes concerning technology usage, which has changed the overall complexion. The advent of advanced computing tools, such as AI, ML etc., has significantly augmented the capabilities within the industry and is making this industry future ready. The healthcare industry has been reactive, i.e. it treats individuals after they get the disease; however, with the application of the latest tools, the healthcare industry is becoming more predictive, i.e. it can predict the risk profile. This is the most significant impact advanced tools have brought to this industry. Advanced computing tools are being applied to multiple functions across the industry, such as drug development, patient treatment, diagnosis, insurance reimbursement etc. As there are multitudes of applications projecting different kinds of benefits, it becomes essential that we have a tool or framework which can measure the impact. This study aimed to develop a framework to evaluate the benefits of implementing these advanced computing tools. The primary objective of this technology application should be to impact the primary outcomes, i.e. accessibility, speed and accuracy, patient compliance and affordability. We must have a framework that objectively assesses the impact and provides guidance to all the stakeholders. This paper proposes a novel 4A framework to help all stakeholders assess the effects. The central idea in healthcare is to improve a patient's life. One can do that by making medicines more productive, reducing adverse effects, improving predictability, reducing cost, improving access etc. This paper provides a strategic framework to assess the impact on the suitable parameters. Novel 4A framework measures the effect on these critical parameters, i.e. access, accuracy, affordability and adherence. As this industry touches patient's life, there are multiple concerns and the primary amongst them, especially for the technology applications, are the ones related to legal and ethical. The overall archetype proposed in this research paper takes into account and provides a framework for the impact assessment. The novel 4A framework presented in this article will serve as a tool to evaluate the impact advanced computing tools will have on the healthcare industry.

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“…4 While the first step is for predictive analytics to provide forecast capabilities, the next step is for prescriptive algorithms to generate automated recommendations. 5 Likewise, this transformation will drive greater personalisation of care and precision medicine by the addition of genomics medicine data and technology, while also embracing the increasing social call to achieve greener and accessible hospitals. 6 Every new technological development in recent decades has helped spur the terms 'smart hospital' and 'intelligent hospital' to portray a more futuristic image of these facilities.…”

Section: Introductionmentioning

confidence: 99%

Digital Technology: Introduction to the cognitive hospital

Rovira-Simón

Sales-i-Coll

Pozo‐Rosich

et al. 2022

Future Healthcare Journal

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The third industrial revolution has radically impacted the transformation of hospitals. Through the adoption of key digital technologies, hospitals have become more accessible, flexible, organised, responsive and able to deliver more personalised care. The digitalisation of patient health records, one of the most remarkable achievements to date in healthcare management, has enabled new opportunities, including the idea of hospitals evolving to become artificially intelligent. In parallel, the adoption of electronic and mobile internet technologies in hospitals has introduced new structural concepts, seeing a variety of terms blossom such as 'smart', 'intelligent', 'green' and 'liquid'. Now in the early fourth industrial revolution, driven by AI and internet-of-things technologies, this article unveils a new concept adapted to the upcoming era.

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Predictive and Prescriptive Analytics in Healthcare: A Survey

Cited by 30 publications

References 7 publications

Industry 4.0 and healthcare: Context, applications, benefits and challenges

Industry 4.0 and healthcare: Context, applications, benefits and challenges

Novel 4A Framework for Measuring Outcomes of Technological Implementation in The Healthcare Industry

Digital Technology: Introduction to the cognitive hospital

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