Evidence map›Paper›PMID 36687377›Full record

ArticleSocio-economic planning sciences2023

Reshaping healthcare supply chain using chain-of-things technology and key lessons experienced from COVID-19 pandemic.

V Sathiya, K Nagalakshmi, J Jeevamalar, R Anand Babu, R Karthi, Ángel Acevedo-Duque, R Lavanya, S Ramabalan

Open access · greenAbstract read
In one paragraph

Article in Socio-economic planning sciences, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed, 1 pooled it
17.4field-weighted citation impact, top 1% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

7 citing papers in PubMed, 1 synthesis or guideline pooled it, 38 citations in OpenAlex.

  1. Pooled it
  2. Review
  3. Article
  4. Article
  5. Article
  6. Article
  7. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

8 authors at 2 institutions in 2 countries.

V SathiyaDepartment of Electronics and Communication Engineering, E.G.S. Pillay Engineering College, Nagapattinam, India.
K NagalakshmiDepartment of Information Technology, E.G.S. Pillay Engineering College, Nagapattinam, India.
J JeevamalarDepartment of Mechanical Engineering, E.G.S. Pillay Engineering College, Nagapattinam, India.
R Anand BabuDepartment of Information Technology, E.G.S. Pillay Engineering College, Nagapattinam, India.
R KarthiDepartment of Master of Business Applications, E.G.S. Pillay Engineering College, Nagapattinam, India.
Ángel Acevedo-DuqueFaculty of Administration and Business Observatory of Public Policies, Universidad Autonoma de Chile, Chile.
R LavanyaDepartment of Information Technology, E.G.S. Pillay Engineering College, Nagapattinam, India.
S RamabalanDepartment of Mechanical Engineering, E.G.S. Pillay Engineering College, Nagapattinam, India.
Open International University for Alternative Medicines · INUniversidad Autónoma de Chile · CL

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The COVID-19 (Corona virus disease 2019) pandemic continues to slash through the entire humanity on the earth causing an international health crisis and financial uncertainty. The pandemic has formed a colossal disruption in supply chain networks. It has caused piling higher mortality in patients with comorbidities and generated a surging demand for critical care equipment, vaccines, pharmaceuticals, and cutting-edge technologies. Personal protective equipment, masks, ventilators, testing kits, and even commodities required for daily care have been scarce as lockdown and social distancing guidelines have kicked in. Amidst COVID-19, implementing and executing key processes of the healthcare supply chain (HSC) in a secured, trusted, effective, universally manageable, and the traceable way is perplexing owing to the fragile nature of the HSC, which is susceptible to redundant efforts and systemic risks that can lead to adverse impacts on consumer health and safety. Though the crisis shone a harsh light on the cracks and weaknesses of the HSC, it brings some significant insights into how HSC can be made more resilient and how healthcare industries figure out solutions to mitigate disruptions. While there are innumerable experiences learned from the disruption of this crisis, in this paper, five important areas to analyze the most vital and immediate HSC enhancements including building a resilient supply chain, thinking localization, implementing reliable reverse logistics, breaking down extant silos to achieve end-to-end visibility, and redesigning HSC using digitalization are emphasized. This work identifies important features related to CoT and HSC. Also, this study links these lessons to a potential solution through Chain of Things (CoT) technology. CoT technology provides a better way to monitor HSC products by integrating the Internet of Things (IoT) with blockchain networks. However, such an integrated solution should not only focus on the required features and aspects but also on the correlation among different features. The major objective of this study is to reveal the influence path of CoT on smart HSC development. Hence, this study exploits (i) fuzzy set theory to eliminate redundant and unrelated features; (ii) the Decision-Making and Experimental Evaluation Laboratory (DEMATEL) method to handle the intricate correlation among different features. This fuzzy-DEMATEL (F-DEMATEL) model attempts to direct CoT technology towards smart HSC by identifying the most influencing factors and investors are recommended to contribute to the development of application systems. This work also demonstrates how CoT can act a vital role in handling the HSC issues triggered by the pandemic now and in the post-COVID-19 world. Also, this work proposes different CoT design patterns for increasing opportunities in the HSC network and applied them as imperative solutions for major challenges related to traditional HSC networks.

Indexed as

Blockchain technologyChain of thingsHealthcare supply chainInternet of thingsLocalizationResilient supply chainReverse logistics

Identifiers

PMID36687377
PMCPMC9836993
OpenAlexW4316039697

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.