Optimizing Asset Utilization Through Big Data Implementation

Asset managers in healthcare environments face multiple challenges, including financial constraints, maintaining patient safety, and hospital security. The exponential growth of data volume requires automation of e-science processes, digitalization of artefacts, and advanced security technologies to ensure secure operation of research infrastructures. Big Data implementation in healthcare can accelerate decision-making, create transparency, enable experimentation, and bring innovation via new business models. To optimize asset utilization through the use of Big Data, improvements steps include setting aside traditional mindsets, embracing new approaches, promoting data sharing with appropriate protections, and collaboratively working toward better outcomes at lower costs.

big data in healthcare environment
STUDENT NAME:
16 October 2016

Contents
HOW IS BIG DATA CURRENTLY USED IN HOSPITAL ENVIRONMENTS?..............................2
WHERE BIG DATA IS USED IN HEALTHCARE, IS IT LINKED TO ASSET MANAGEMENT?. 2
WHAT ARE THE CHALLENGES IN IMPLEMENTING BIG DATA (DECISION SUPPORT
SYSTEMS)?..........................................................................................................................................3
WHAT ARE CHALLENGES FACING ASSET MANAGERS IN HEALTHCARE
ENVIRONMENTS?..............................................................................................................................4
WHAT ARE THE BENEFITS OF BIG DATA IMPLEMENTATION IN HEALTHCARE
REGARDING ASSET UTILISATION?...............................................................................................5
WHICH IMPROVEMENT STEPS CAN BE TAKEN TO OPTIMISE ASSET UTILISATION
THROUGH THE USE OF BIG DATA?...............................................................................................6
REFERENCES......................................................................................................................................7

HOW IS BIG DATA CURRENTLY USED IN HOSPITAL
ENVIRONMENTS?
Jared Crapo says “Most health systems have lots of opportunities to improve clinical quality and
financial performance, and analytics are required to identify and take advantage of those
opportunities.”[2] This means that there are a lot of ways in which the utilization of data can be done
easily via use of big data into the filed.
“In healthcare, we do have large volumes of data coming in. EMRs alone collect huge amounts of
data. Most of that data is collected for recreational purposes” according to Brent James of
Intermountain Healthcare.
Further Paul S. Bradley shares his views on use of big data in present. He says “Clinical data sources
can commonly be extracted from electronic health records, hemodynamic systems, medication
administration records, laboratory and information systems, and other various sources. These data
elements include patient demographics and visit (account) level information including progress notes,
problems, medication, and vital signs, past medical history, immunizations, and laboratory data.”[1]
Thus in this way, big data comes into play in healthcare benefitting the system.
WHERE BIG DATA IS USED IN HEALTHCARE, IS IT LINKED
TO ASSET MANAGEMENT?
There are different forms of data present in the healthcare environment. This data varies from the
basic billing data to new digital data. As Jared Crapo says that “Discretely codified billing and
clinical transactions are well suited for relational data models. Digital capture and management of

diagnostic imaging studies required the development of specialized data formats, communication
protocols, and storage systems. While these PACS systems are not typically recognized as big data,
they clearly meet the criteria we have outlined here.” [2]
According to Matthew Herland, “Data mining and Big Data analytics are helping to realize
the goals of diagnosing, treating, helping, and healing all patients in need of healthcare, with the end
goal of this domain being improved Health Care Output”. [3]
“The amount of data produced within Health Informatics has grown to be quite vast, and analysis of
this Big Data grants potentially limitless possibilities for knowledge to be gained.”[3]
“Researchers are studying the complex nature of healthcare data in terms of both characteristics of the
data itself and the taxonomy of analytics that can be meaningfully performed on them.”[7]
WHAT ARE THE CHALLENGES IN IMPLEMENTING BIG
DATA (DECISION SUPPORT SYSTEMS)?
“There are a number of challenges that make it difficult to use health care data to its fullest extent.
First, the data in many health care providers, specifically hospitals, are often segmented or soiled.”[4]
“A second significant challenge in leveraging health care’s big data to its fullest extent is protecting
the patient’s privacy.” [4] “The sharing of health care data between organizations is often stated as a
goal and organizations such as regional health information organizations were specifically formed to
bring together health care data from stakeholders including providers, payers, and public health
organizations. The Health Insurance Portability and Accountability Act requires covered entities to
protect patient information.”[6]
“Possibly the most significant challenge in aggregating and analysing big health care data is the
amount of unstructured data. Structured or discrete data includes data that can be stored and retrieved

in a relational database. Unstructured data in health care include: test results, scanned documents,
images, and progress notes in the patients’ EHR.”[4]
“One important challenge that must be acknowledged in health care data analytics is that the analysis
is often a secondary use of the data.”[4] This means that the data is primarily used for something basic
and analysis is its secondary use. For example use of HER data is done to keep a track of patient’s
health and treatment during a process. Whereas during analysis this data is used as a check for quality.
“The original use of the data must be acknowledged as a potential limitation and may compromise the
reliability and validity of any resulting models.”[4]
WHAT ARE CHALLENGES FACING ASSET MANAGERS IN
HEALTHCARE ENVIRONMENTS?
There are multiple challenges that are faced by asset managers in healthcare. From security to theft to
physical destruction, there are varied challenges they face every day. Michael Sullivan says
“Healthcare organizations are continually battling conflicting priorities. Our customers tell us they
need to focus on delivering high quality patient care, preventing infections, maintaining hospital
security, and ensuring patient safety – all with extremely stretched resources.”[5] Further he lists out
these challenges: [5]
1. Financial challenges and hospital productivity
2. Maintaining patient safety
3. Regulatory standards and emerging energy mandates
4. Hospital security
5. Patient satisfaction
Some other challenges are related to data and its ever increasing complexity and automation.
“Exponential growth of data volume produced by different research instruments and/or collected from

Sensors.”[8]
Also it will require “Automation of all e-Science processes including data collection, storing,
classification, indexing and other components of the general data curation and provenance.” [8]
“Transformation all processes, events and products into digital form by means of multi-dimensional
multifaceted measurements, monitoring and control; digitising existing artefacts and other
content.”[8]
And last but not the least “Advanced security and access control technologies that ensure secure
operation of the complex research infrastructures and scientific instruments and allow creating trusted
secure environment for cooperating groups and individual researchers.” [8]
WHAT ARE THE BENEFITS OF BIG DATA IMPLEMENTATION
IN HEALTHCARE REGARDING ASSET UTILISATION?
There are a number of benefits that arise from the use of big data in healthcare. “Organizations use
Big Data platforms to give them answers to important questions in seconds rather than months. Thus,
the key value of Big Data is to accelerate the time-to-answer period, allowing an increase in the pace
of decision-making at both the operational and tactical levels.”[9]
“According to the McKinsey Global Institute, five key ways in which Big Data creates value for
organizations can be distinguished [9]:”
 Creation of transparency by integrating data. This makes it more easily accessible to all
relevant stakeholders,

 To enable the experimentation to discover needs, expose variability, and improve
performance in the field.
 Segmentation of the populations in order to customize actions
 Replacement of the human decision making or creating a provision of support with automated
algorithms
 Bringing Innovation via use or creation of new business models, products and services.
“Big Data offers huge potential to positively impact on the functioning of organizations generally and
gives them a competitive advantage. Companies are now trying to utilize to an even greater degree the
opportunities and chances that are emerging.”[9]
“Facilitated in part by the enormous investment of the health care sector in information technology
(IT), big data could be among the catalysts driving improvements in health outcomes while lowering
costs. Cleveland Clinic has identified big data as one of the biggest medical innovations in recent
years.”[10]
WHICH IMPROVEMENT STEPS CAN BE TAKEN TO OPTIMISE
ASSET UTILISATION THROUGH THE USE OF BIG DATA?
“The challenges surrounding the full aggregation and use of health care data are not insurmountable.
Meeting those challenges will require a culture shift in health care both internal to providers and
between providers and other portions of the industry.”[4]
“To realize big data’s promise, health organizations and policy makers alike may need to set aside
traditional mind-sets and embrace new approaches, overcoming barriers to promote data sharing with
the appropriate protections, and collaboratively working toward the goal of delivering better outcomes
at lower costs.”[10]
“The sharing of data between organizations must be addressed before the full potential of big data in
health care may be unlocked.”[4]

“As healthcare reimbursement shifts in the United States toward outcome-based models, hospitals
need to make the transition to population health management to stay viable.”[1]
“Today, health systems’ need for data-driven quality and cost improvement is urgent. Healthcare
organizations cannot afford to wait for big data technology to mature before diving into analytics. The
important factor will be choosing a data warehousing solution that can easily adapt to the future of big
data.”[11]
REFERENCES
[1] Bradley, P. S. (2013). Implications of Big Data Analytics on Population Health Management. Big
Data, 152-159.
[2] Crapo, J. (2015). Big Data in Healthcare: Separating The Hype From The Reality. Retrieved from
www.healthcatalyst.com: https://www.healthcatalyst.com/healthcare-big-data-realities
[3] Herland, M. (2014). A review of data mining using big data in health informatics. Journal Of Big
Data.
[4] SE, W. (2014). A review of big data in health care: challenges and opportunities. Open Access
Bioinformatics, 13—18.
[5] Sullivan, M. (2013, October 17). The Top Five Challenges Facing Today’s Hospitals. Retrieved
from blog.schneider-electric.com:
http://blog.schneider-electric.com/building-management/2013/10/17/top-five-challenges-
facing-todays-hospitals/
[6] Department of Health and Human Services. Modifications to the HIPAA Privacy, Security,
Enforcement, and Breach Notification Rules Under the Health Information Technology for Economic
and Clinical Health Act and the Genetic Information Nondiscrimination Act; Other Modifications to
the HIPAA Rules; Final Rule. 45 CFR 160 and 164; 2013.

[7]
Belle, A. (2015). Big Data Analytics in Healthcare. BioMed Research International.
[8] Yuri Demchenko, Z. Z. (n.d.). Addressing Big Data Challenges for Scientific Data Infrastructure.
2012 IEEE 4th International Conference on Cloud Computing Technology and Science.
Amsterdam, The Netherlands.
[9] Wielki, J. (2013). Implementation of the Big Data concept in organizations. Proceedings of the
2013 Federated Conference on Computer Science and Information Systems, (pp. 985–989).
Poland.
[10] Joachim Roski, G. W.-L. (2014). Creating Value In Health Care Through Big Data: Opportunities
And Policy Implications. Health Aff, 1115-1122.
[11] Adamson, D. (2015). Big Data in Healthcare Made Simple: Where It Stands Today and Where It’s
Going. Retrieved from www.healthcatalyst.com:
https://www.healthcatalyst.com/healthcare-big-data-realities