Healthcare business intelligence gathers health data from various sources like electronic health records, labs, health apps, and wearable devices, as well as government agencies, accounting tools, and CRM platforms. It then saves, analyzes, and reports this information. Some top providers like Amazon QuickSight, Microsoft Power BI, Google’s Looker, Oracle, SAP, and other Business Intelligence Software for Healthcare are recommended by Gartner.
Healthcare BI tools merge internal and external data, including medical research and market trends.
Healthcare providers use this information to enhance patient satisfaction and financial performance across medical centers, clinics, hospitals, insurance companies, research facilities, pharmaceutical firms, and tech companies.
Cloud database development streamlines healthcare data storage, retrieval, and analysis, making it more efficient, scalable, and secure.
Key Features to Seek in Healthcare Business Intelligence Software
A modern healthcare BI solution prioritizes visual self-service and might include AI for automated insights. These platforms enable non-technical users to model, analyze, and share data insights easily. In healthcare, most BI customers prefer cloud deployments due to the rising complexity of analytics and growing data volumes.
What opportunities do they offer health-related companies?
Security
- User Administration. It refers to the functionalities that allow managing and controlling user roles, permissions, and access levels within the system. It involves creating, modifying, or removing user accounts, assigning specific roles or privileges, and overseeing user activity and access to data and features within the BI platform.
- Platform access. It involves tracking and monitoring the usage and interactions within the BI system. It maintains a record of who accessed the platform, when they accessed it, what actions were performed, and any changes made within the system. This auditing is crucial for security, compliance, and accountability purposes, ensuring that authorized users are using the system appropriately and tracking any potential security breaches or irregularities.
- Authentication management. It stands for the processes and mechanisms used to verify and confirm the identities of users accessing the BI system. It involves implementing secure methods such as passwords, multi-factor authentication, or other verification procedures to ensure that only authorized individuals can access the system. Authentication management helps safeguard sensitive healthcare data, preventing unauthorized access, and maintaining the integrity and security of the BI platform.
Cloud-Readiness
It refers to the capability to create, launch, and control the BI software in the cloud, supporting multi-cloud and hybrid cloud setups.
Data Source Connectivity
It empowers users to link and bring in data from diverse storage platforms, whether on-premises or in the cloud. It assists users in merging data from different sources through a simple drag-and-drop interface.
Natural Language Searching
It allows users to query data by typing or speaking search terms into a search box.
Data visualization
It supports highly interactive dashboards, enabling users to explore data by manipulating various chart images such as heat maps, tree maps, geographic maps, scatter plots, and other specialized visuals.
Automated Reports, Creating Text Automatically, and Telling Stories with Data
They use machine learning to generate insights and highlight critical attributes within a dataset. They automatically craft descriptions that explain key findings in data or the significance of charts and dashboards. Additionally, they create news-style data stories, combining headlines, narrative text, data visualizations, and audiovisual content, continually updating based on ongoing findings.
Reporting
This functionality offers parameterized, paginated, and pixel-perfect reports that can be scheduled and distributed to a large user community.
BI Software for Healthcare
Amazon QuickSight
This BI platform is for AWS customers. It connects well with Amazon data tools, offering scalability, high performance, and competitive pricing. Amazon QuickSight includes features like natural language queries, embedded analytics, scheduled reporting, and serverless cloud setup for big BI projects.
It easily integrates with AWS security and data sources. Yet, it’s limited to running solely on AWS, not ideal for multi-cloud users.
Microsoft Power BI
Microsoft Power BI is an extensive data analytics tool offered as a software-as-a-service on Azure. It handles data preparation, visual exploration, interactive dashboards, and augmented analytics. Power BI Premium includes AI-driven text, sentiment, and image analysis. It integrates smoothly with Office 365, like Microsoft Teams, Excel, and SharePoint.
Adding Power Apps into its dashboards enhances Power BI, and Power Automate automates tasks using data. However, it’s limited to deployment on Azure and lacks options for other cloud infrastructure. Though it allows multi-cloud and hybrid cloud data connections, managing self-service usage is a common concern.
The on-premises Power BI Report Server offers a more limited set of features, missing dashboards, streaming analytics, prebuilt content, natural language queries, automated insights, and alerting.
Google’s Looker for Healthcare BI
It is a cloud-based BI platform that offers self-service visualization and dashboard capabilities. It supports multi-cloud deployment and database connectivity, integrating well with Google Cloud products like BigQuery. Looker’s extension framework allows developers to build data-driven applications.
It provides direct query access to cloud databases and applications, using LookML’s virtualized semantic layer without data movement. Google aims to open LookML to other BI platforms, allowing integration with Microsoft Power BI, Tableau, Data Studio, Google Sheets, and Google Slides.
Looker’s APIs, SDKs, and extension framework, including the Data Dictionary, help in creating customer-facing applications and embedding analytics in business workflows. The Looker Marketplace provides ready-made data and machine-learning model Blocks to handle typical analytical patterns.
Despite potential coding requirements, Looker offers prebuilt data and ML model Blocks. Yet, it lacks automated insights, data storytelling, and robust Natural Language Generation features compared to its competitors.
Oracle Healthcare BI
Oracle offers a complete BI cloud solution covering infrastructure, data management, and analytics apps. With data centers in 30 regions, Oracle caters to multicloud needs through an open architecture. It emphasizes conversational user experiences and automated data storytelling, like generating audio podcasts that highlight trends and insights.
It supports Natural language queries in 28 languages and offers Oracle Analytics Day by Day for mobile devices. For on-premises use, there’s Oracle Analytics Server, and for Oracle Cloud Applications, there are prebuilt analytics solutions via Fusion Analytics Warehouse.
However, the packaged analytic applications (like Fusion Analytics Warehouse and NetSuite Analytics Warehouse) are primarily designed for Oracle enterprise applications. Non-Oracle app users might need to create their own applications using Oracle Analytics Cloud for similar capabilities.
Notably, customers have expressed below-average satisfaction with Oracle’s service and support. Additionally, the older Oracle Healthcare Foundation (OHF) analytics solution is no longer actively supported.
SAP Healthcare BI
SAP Analytics Cloud, a cloud-based platform, connects with SAP cloud applications and can query both cloud and on-premises SAP resources, like SAP Business Warehouse for live data. Its user-friendly tools, the Story Viewer and Story Designer, help non-technical users create and interact with dashboards and reports.
The Analytics Designer allows low-code development using APIs to create analytics applications. SAP Analytics Cloud excels in planning, analysis, and prediction with “what-if” analysis, change tracking, and calculation capabilities. It also features natural language generation, natural language processing, and automated insights.
For healthcare and related businesses, SAP Analytics Cloud offers pre-built business content, like data models and visualizations. However, it’s mainly used by existing SAP application customers and legacy BI users. Those without a SAP-centric setup typically don’t choose it.
While SAP Analytics Cloud can query on-premises data, those preferring on-premises deployment might need standalone SAP BusinessObjects BI for complete hybrid deployment.
