Asset and Facility Management

42

Requirement

Research question:

#How can our hospital implement big data as a decision support system to optimise asset utilisation?

1-How is big data currently used in hospital environments

2-Where big data is used in healthcare, is it linked to asset management

3-What are the challenges in implementing big data (decision support systems)

4-What are challenges facing asset managers in healthcare environments

5-What are the benefits of big data implementation in healthcare regarding asset utilisation

6-Which improvement steps can be taken to optimise asset utilisation through the use of big data

What I need is simple:

Solution

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]
Financial challenges and hospital productivity
Maintaining patient safety
Regulatory standards and emerging energy mandates
Hospital security
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