ML-Enabled Informed Intervention for Crowdsourcing-Based Optimization of Medical Resources

ML-Enabled Informed Intervention for Crowdsourcing-Based Optimization of Medical Resources

Irfan Siddavatam, Ashwini Dalvi, Abhishek Patel, Aditya Panchal, Aditya S. Vedpathak, Viraj Thakkar
DOI: 10.4018/978-1-7998-7709-7.ch017
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Abstract

It is said that every adversity presents the opportunity to grow. The current pandemic is a lesson to all healthcare infrastructure stakeholders to look at existing setups with an open mind. This chapter's proposed solution offers technology assistance to manage patient data effectively and extends the hospital data management system's capability to predict the upcoming need for healthcare resources. Further, the authors intend to supplement the proposed solution with crowdsourcing to meet hospital demand and supply for unprecedented medical emergencies. The proposed approach would demonstrate its need in the current pandemic scenario and prepare the healthcare infrastructure with a more streamlined and cooperative approach than before.
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Introduction

Data points to predict the progression of Covid-19 have highly researched, making the work for epidemic spread research considerably easier. Though the epidemic spread models helped overcome significant roadblocks in managing Covid-19 challenges, the research slightly overlooks the most important aspect, hospital resource planning and management. The research documented the challenges faced by hospitals during the pandemic, but either from the perspective of managing other health treatments in the wake of Covid spread (Korytkowski et al., 2020; Ueda et al., 2020) or managing individual units (Kotfis et al., 2020). The researcher also mentioned challenges faced by medical professionals (Sethi et al., 2020; Spoorthy et al., 2020).

Further, the research extended to learn the hospital resource management during the Covid-19 pandemic. The spread of Covid-19 through human-to-human contact could be minimised by using protective gear such as PPE (Personal Protection Equipment) kits, gowns, masks, and protection kits for respiratory systems and eyes. Medical resources like PPE kits and other protection gear not be stored in hospitals in large quantities. Thus, taking a proactive approach to managing the supply of essential protection gears is a requirement of the hospital management during the course of stirring the Covid-19 pandemic. There were reports of limited supplies of critical protection for health workers (Grimm, 2020).

The problem of effective hospital management is not even new; in 2016, the founder of Logistics Bureau stated:

It's widely recognised that internal hospital logistics is even more complex than the external side and that medical staff spend disproportionate amounts of paid time performing logistics activities—time which would be better used to provide patient care. - Rob O'Byrne (Logistics Bureau, 2016).

In the early period of the Covid-19 epidemic spread in India, the hierarchical structure of health management was implemented, including Dedicated Covid-19 Hospitals (DCH) and Dedicated Covid-19 Health Centers (DCHC). The report published on June 2020 (Times of India, 2020) mentioned that the fatality rate due to Covid-19 in India was 2.83%, but there was continuous transmission rate growth. On the other hand, the recovery rate was slow. The statistics of June 3, 2020, stated that the bed occupancy of DCH and DCHC was already 94%, i.e., ICUs were running with a capacity of 98%, and 85% of ventilators were occupied. Now after almost 11 months these statistics have not yet improved much. As of April, 25 2021, the bed occupancy of DCH and DCHC is 80.303%. ICUs were running with a capacity of 98.30%, and 98.41% of ventilators were occupied. Upscaling the hospital resources at a given time posed a significant problem with the existing setup. Thus, the authors realised the need to comprehend and predict the stage wherein the utilisation of hospital resources reach 100% is a requirement of healthcare infrastructure.

The other challenge that emerged for hospital infrastructure management during a pandemic is meeting the need for non-Covid-19 medical emergencies such as cancer treatment, diabetic treatment, dialysis treatment, and so on (Kuhlen et al., 2020; Ralli et al., 2020; Ueda et al., 2020). The hospital infrastructure has realised the need for minimum preparedness for teleconsultation with patients, such as updating the patient's record digitally, creating a digital record of the patient's current state from his/her home. The health sector realises the need for patient data omnipresence to handle unprecedented medical situations during a pandemic.

Though the researchers studied medical informatics in the past few years, as mentioned in (Asadzadeh et al., 2020), the medical domain's applied IT (Information Technologies) setup is neglected. The work presented gaps in existing IT technologies to contain medical emergencies such as the Covid-19 pandemic. The utilisation of IT technologies to predict epidemic and manage health services during a pandemic is of utmost importance.

Medical informatics is an amalgamation of Information Technology with different disciplines of medicines for efficient health services. The pandemic role of medical informatics is studied to comprehend the implementation and effectiveness of various medical services.

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