Healthcare Data Breaches: Insights and Implications.

cost effectiveness cost forecasting data analysis data breach forecasting data confidentiality data security healthcare data breaches time series analysis

Journal

Healthcare (Basel, Switzerland)
ISSN: 2227-9032
Titre abrégé: Healthcare (Basel)
Pays: Switzerland
ID NLM: 101666525

Informations de publication

Date de publication:
13 May 2020
Historique:
received: 25 03 2020
revised: 24 04 2020
accepted: 01 05 2020
entrez: 17 5 2020
pubmed: 18 5 2020
medline: 18 5 2020
Statut: epublish

Résumé

The Internet of Medical Things, Smart Devices, Information Systems, and Cloud Services have led to a digital transformation of the healthcare industry. Digital healthcare services have paved the way for easier and more accessible treatment, thus making our lives far more comfortable. However, the present day healthcare industry has also become the main victim of external as well as internal attacks. Data breaches are not just a concern and complication for security experts; they also affect clients, stakeholders, organizations, and businesses. Though the data breaches are of different types, their impact is almost always the same. This study provides insights into the various categories of data breaches faced by different organizations. The main objective is to do an in-depth analysis of healthcare data breaches and draw inferences from them, thereby using the findings to improve healthcare data confidentiality. The study found that hacking/IT incidents are the most prevalent forms of attack behind healthcare data breaches, followed by unauthorized internal disclosures. The frequency of healthcare data breaches, magnitude of exposed records, and financial losses due to breached records are increasing rapidly. Data from the healthcare industry is regarded as being highly valuable. This has become a major lure for the misappropriation and pilferage of healthcare data. Addressing this anomaly, the present study employs the simple moving average method and the simple exponential soothing method of time series analysis to examine the trend of healthcare data breaches and their cost. Of the two methods, the simple moving average method provided more reliable forecasting results.

Identifiants

pubmed: 32414183
pii: healthcare8020133
doi: 10.3390/healthcare8020133
pmc: PMC7349636
pii:
doi:

Types de publication

Journal Article Review

Langues

eng

Subventions

Organisme : Prince Sultan University
ID : 0000xxxxx0000000

Déclaration de conflit d'intérêts

The authors declare no conflict of interest.

Références

Perspect Health Inf Manag. 2014 Oct 01;11:1h
pubmed: 25593574
JAMA. 2015 Apr 14;313(14):1471-3
pubmed: 25871675
J Med Syst. 2018 Nov 28;43(1):7
pubmed: 30488291

Auteurs

Adil Hussain Seh (AH)

Department of Information Technology, Babasaheb Bhimrao Ambedkar University, Lucknow 226025, India.

Mohammad Zarour (M)

College of Computer & Information Sciences, Prince Sultan University, Riyadh 12435, Saudi Arabia.

Mamdouh Alenezi (M)

College of Computer & Information Sciences, Prince Sultan University, Riyadh 12435, Saudi Arabia.

Amal Krishna Sarkar (AK)

Department of Information Technology, Babasaheb Bhimrao Ambedkar University, Lucknow 226025, India.
System Manager, Sanjay Gandhi Post Graduate Institute of Medical Sciences, Lucknow 226014, India.

Alka Agrawal (A)

Department of Information Technology, Babasaheb Bhimrao Ambedkar University, Lucknow 226025, India.

Rajeev Kumar (R)

Department of Information Technology, Babasaheb Bhimrao Ambedkar University, Lucknow 226025, India.

Raees Ahmad Khan (RA)

Department of Information Technology, Babasaheb Bhimrao Ambedkar University, Lucknow 226025, India.

Classifications MeSH