A Guide for Healthcare Payers on Getting Data Architecture Right

According to some estimates, the total data we produce daily is about 2.5 quintillion bytes. This vast data must be processed, stored, and evaluated to be valid. This is the goal of data architecture.

Healthcare is a dynamic sector that uses cutting-edge technology, and there is an enormous opportunity for more accurate and comprehensive patient data collection. The implementation of technology results in instantaneous access to patient records throughout the system, and joint initiatives within any medical system can enhance the accuracy of data gathering.

Healthcare providers possess a large amount of data but often have difficulty making it accessible and ready for analysis. For providers worldwide, it is essential to construct vital bases, such as organisation, digital delivery skills and data processing on a large scale, to remain competitive and take full advantage of digital opportunities.

Growth Jockey helps you to stay ahead of the competition by handling the digital agenda of your organisation.

Data Warehouse in Healthcare

A digital data collection gathered from many sources and organised for analysis is known as a healthcare data warehouse. It might have data from lab tests, prescriptions from the pharmacy, medical records, insurance claims, or even population-wide studies.

According to a study by BlueWave Consulting, the market for worldwide healthcare data storage is expected to increase from $3.08 billion in 2020 to $6.12 billion by 2027 at a CAGR of 10.7%.

Data Warehouse Architecture

The structure for collecting and storing data within an organisation is called its data warehouse architecture.

An efficient data set and minimal data storage are the main goals of single-layer warehouse design. Although it is good for eliminating redundancies, it is ineffective for firms with several streams and huge data requirements.

Two-tier warehouse designs separate the actual resources from the building housing them. Although it is better at sorting and storing data, it is not scalable and only accommodates a small number of end users.

To get the data architecture right, the most common design, three-tier architecture, enables a more systematic flow of data from unstructured collections to useful insights.

Benefits of Data Architecture in Healthcare

1. Preservation of Medical Data

Traditional databases frequently delete useless data, to get rid of it. Healthcare data warehouses are repositories that may hold 10 years old or older data.

2. Accessibility of necessary data

The number of departments with databases designed for particular purposes increases as a healthcare institution grows. Thus, analytics departments must do several transformations before discovering the required data to build and assess a cohesive picture.

3. Improved Clinical Decisions

You can deal with data that has been structured rather than attempting to swiftly digest disorganised information from siloed databases. You'll have a highly effective and adaptable framework that can provide clinical judgments precisely when you require them.

4. Easy insurance claims

Easy insurance claims are very important for healthcare payers in every guide for healthcare data architecture. You may rapidly gain an overview through data architecture of massive volumes of claim-related data. A hospital or other healthcare institution would greatly benefit from reviewing its insurance compensation policies to spot potential problems and stop fraud.

Key Considerations of Data Architecture Software

The first step in building a data architecture is to identify the criteria that must be met. As a result, the disciplined and systematic technique known as requirements engineering is employed to define and manage requirements. There are functional and non-functional requirements.

Growth Jockey is a foundation that would weigh the requirements as per your need and choose the best for you.

The Architecture of Healthcare Data Warehouse

1. Data Source Layer

Data from various sources within and outside the organization, such as clinical, administrative, research, precise, and patient-generated, comprise the data source layer.

2. Staging Layer

The staging layer, sometimes called interim storage, is where data has been obtained from various sources. After being processed through ETL (extraction, transformation, and loading), they are brought together into a unified, consistent data set.

3. Data Storage Layer

The layer of data storage serves as a central repository for combined data. The layer may include information about many topic areas or data marts, smaller sets of information assigned to certain departments or organisational units.

4. Data Analytics and Reporting Layer

This tier of database system architecture involves programs for providing reports, creating dashboards, and utilizing business intelligence systems to generate descriptive, predictive, and prescriptive analytics.

Best Model of Database Warehouse Architecture

A lot of variables influence the data architecture of the healthcare business. These factors include the size of your firm, its area of expertise, and the precise business objectives you want to accomplish by implementing a DWH.

Growth Jockey advises enlisting the aid of a software provider to evaluate your unique requirements and select the best architecture that will satisfy them. The two types of popular data models are-

1. Individual Data Mart Model

For small businesses that want to focus on only one or a few key parts of their business, this healthcare data warehouse strategy has the best chance of success. It may be used for customer service improvement, insured events, and other use cases.

This concept suggests merging several data sources from various fields from a practical standpoint. This strategy offers fantastic prospects for further scaling while simultaneously avoiding the need forlarge initial financial expenditures and completely restructuring the current digital infrastructure.

2. Enterprise Data Model

For medium-sized and larger businesses, the healthcare data warehouse approach works well. It offers sophisticated analytics, reporting, and processing tools and combines various data sources. Such Data Warehouse Healthcare solutions sometimes require bespoke development since they are wholly suited to the operational procedures of a certain enterprise.

Data Challenges in Healthcare

• Data Security

The Health Insurance Portability and Accountability Act in the US requires that health data be protected (HIPAA). Data warehouses must be HIPAA compliant for their adoption to be effective. A Business Associate Agreement must be in place between all parties if it is necessary to share sensitive patient data with them.

• Lack of technical expertise

Healthcare data warehouse specialists must be involved since developing a DWH needs careful planning and a lot of work. This is particularly true for large-scale medical organisations, where the volume of data and the variety of data kinds are sometimes enormous.

It's critical to assess your internal IT team's capabilities and expertise in a realistic manner. Find a software development business to go on this path with that has the necessary experience and a proven track record.

• Complexity in data architecture

When developing a clinical data warehouse in healthcare, data interoperability, a major source of pain for many medical organisations, will undoubtedly come up. When financial and administrative data are added to the mix, translating data from multiple sources to satisfy a single standard becomes immensely burdensome.

Aa solid ETL or ELT pipeline must be built for a successful data integration project. There could, however, be challenges on the road.

Final Thoughts

Because data analysis has a strong potential to improve people's lives, the range of data applications in the area of medicine should be steadily expanded. With the use of information technology, it is now feasible to diagnose an individual's illnesses and forecast the health of broad social groupings. Big data architecture in healthcare is essential to create preventative measures and save lives.

Remember, if you need help with the implementation process in a well-planned manner by knowledgeable professionals, Growth Jockey is a perfect choice.

At Growth Jockey, we are committed to building customised solutions that effectively address the critical challenges faced by our clients across diverse industries. Regardless of the size of your company, whether it's a small-scale enterprise or a large corporation, you can now optimise your IT architecture. Take the decisive step towards unlocking the next level of growth for your brand by contacting us today!