Data today has earned tremendous importance in every field, and the healthcare sector is no different. The healthcare industry is also adopting various digital solutions and moving towards data-driven healthcare practices to deliver better care and support. Over the last decade, most medical organizations have embraced the EMR system and have access to enormous clinical and operational data. By leveraging this data, health systems can look into deeper insights and create strategies for finer healthcare services.
Data analytics are incredibly crucial as they provide a holographic view of your entire healthcare organization. By analyzing the data, businesses can be efficiently enhanced, patient outcomes can be improved, and the identification of high-risk patients can be made even before they experience symptoms. So to earn maximum profit from your stored data, it is essential to make your healthcare practices data-driven.
This article will guide you through some of the necessary steps that are a must for this change of action. Let us begin.
What is Big Data?
You might have heard this term several times in your life, ‘Big Data.’ Healthcare systems often use this term to refer to vast volumes of electronic health data. It consists of the organization’s data from electronic health records (EHR) and the revenue cycle management (RCM) system.
By studying and analyzing this data, valuable insights can be extracted, which can help provide better care for the patients, increase productivity, and reduce operational costs.
To fulfill their requirement of sophisticated hospital management software, medical organizations can partner with a good IT solution company that can aggregate multiple sources of data and create an efficient system for their healthcare system.
Types of Big Data in Healthcare
The Healthcare industry consists of a variety of data that have their own significance. Following are the types of data in a healthcare institution:
- Electronic health records (EHR)
- HR systems
- Accounting systems
- Clinic management systems
- Lab systems
- Medical images
- Health information exchange (HIE)
- Medical devices and equipment
- Credentialing systems
- Inventory management systems
Now using this data, the following are the analytics that can be derived for making well-structured strategies:
- Operational efficiency analytics
- Patients experience analytics
- Financial performance analytics
- Clinical analytics
- Population health analytics
A robust and reliable hospital management software can efficiently handle all this data and offer you insights for better working of your medical system.
Comprehending the Business Requirements
Foremostly, before jumping to a new approach and working system, it is critical that your healthcare organization should consider its business requirements. A healthcare organization must clearly understand what they want to accomplish and the things they wish to address by integrating a technological solution.
These are some common business requirements that most healthcare systems often look out for:
- Business Problem Statement
- Scope Statement
- Current Business Process
- Key Business Objectives
- Risks & Limitations
- Project Completion Criteria
- New/Modified Business Process
- Cost and Scheduling Parameters
- Stakeholder List
- Training Needs
- Quality Measures
In order to achieve the best results, you should create a data implementation team that can document and work on all your business requirements.
Steps to Build a Data Infrastructure In Your Healthcare System
For data-driven healthcare practices, you need to provide your healthcare organization with tools that help capture, store, and analyze big data. Besides, you also need to build an infrastructure with enough capacity to power these above-given analytics systems.
Before finalizing your analytics software, there is an extensive amount of preliminary work that you will have to do for preparing your organization for the use of data analytics, such as:
Categorizing and Retrieving the Existing Data
It’s been over a decade that most hospitals now make use of digital records and systems to record and store patients and hospital data. The historical data present in these systems should be your primary concern for analysis. Firstly, you will have to retrieve all the valuable data and classify it into different categories. This is a time-consuming process and must be done with a high attention level.
Identifying the Gaps in Existing Data
Not all data holds the same importance as others, and it is up to our intelligence on how we identify the data. You must be aware of the metrics you are looking for to accomplish specific goals in your healthcare organization. So after you retrieve the data in the first step, identify the gaps in the data and fill it with accurate information. Also, this step will help you get rid of redundant or undesired data.
Choosing Your Data Analytics Toolset
Medical data is extremely crucial, and there are a variety of security protocols that software must comply with. The first step is to check if you can use a cloud to store your data. As healthcare data needs on-premise analytic tools, ensure the software can run on your local infrastructure.
Then comes the most crucial step to select a reliable and efficient IT solution partner that can deliver you scalable hospital management software. Remember, selecting a healthcare IT company that is HIPAA compliant and specializes in healthcare analytics should be the basis of your vendor research.
Upgrading Your IT Infrastructure
The final step in building a robust data infrastructure for your healthcare system is the up-gradation of your IT infrastructure. Big data analytics are extremely resource-intensive, particularly if you run complex medical image analysis data like CT and MRI scans.
This requires huge storage and computing capacities for smooth operations. So it is essential you upgrade your systems accordingly. You might get genuine guidance from your IT partners on how to accomplish this successfully.
The healthcare systems of the future demand data to be treated as a strategic asset that can offer a secure and intelligent data-driven healthcare management system. New processes and systems are required that can allow the data to implement efficient decision-making to drive actionable results. Remember, no healthcare practices become data-driven overnight. Hence, you might have to reconsider your approaches and, more essentially, adopt a data-driven mindset.
This post is originally published here: https://www.softclinicsoftware.com/how-to-make-or-build-your-healthcare-practices-data-driven/