Healthcare Data Warehouse

What we offer

Data integration

Kept in one virtual venue, aggregated data in compatible formats is the vital value of a health care data warehouse (DWH). To guarantee this asset, we provide ingesting of all kinds of medical data (unstructured, semi-structured, and structured), their transformation (summarization, conversion, etc.), load and retrieval, high-end data management, and information querying via SQL.

Data storage

When all the data is collected and integrated, it should be securely stored. We use the healthcare data warehouse schema to obtain protected health information and metadata storage where historical and current subject-oriented medical data is kept. Also, we offer you a choice of data storage environments (on-premises, cloud, or hybrid).

DWH development

DICEUS specialists, as seasoned healthcare data warehouse vendors, create professional DWH solutions and focus on two essential components. The first is the back-end side which embraces high-quality software, efficient infrastructure, and security protocols. The second is the front end with an easy-to-operate dashboard and a gamut of data management and analytics tools.

DWH modernization

The healthcare data warehouse model we deliver is never carved in stone. As new technologies and approaches to data storage and management push in and novel discoveries in medicine are made, we update the DWH to provide the best service for patients and meet doctors’ needs halfway. Special attention is paid to automating as many workflow operations as possible.

Security and compliance

Personal and clinical information security is paramount in medical data warehousing. To address this requirement, we introduce granular column- and row-level security monitoring, multi-factor authentication, healthcare data encryption, vulnerability detection, and threat assessment. Besides, we control compliance with HIPAA, FDA, HITECH, and other healthcare regulations.

Self-service BI development

Even the most complete and transparent collection of medical data is of little use unless the clinicians can draw some insights from them. The DWHs we develop enable clear visualization of data hoarded there, allow for the creation of user-friendly dashboards to work with patients’ demographics, and provide automated reporting opportunities to keep a hospital’s records in apple-pie order.

Examples of healthcare data

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Healthcare data warehouse

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Benefits of data warehouse in healthcare

Healthcare providers are often trendsetters among organizations across various industries that employ an enterprise data warehouse. DICEUS supports their state-of-the-art data storage and management aspirations by delivering top-notch DWH solutions that can significantly enhance their services to patients.

Now, most healthcare organizations switch to digital information storage as a part of electronic health records (EHR). We can take your medical treatment services to a new level by uniting all your siloed on-premises data systems into a cloud-based clinical data warehouse with its enormous business intelligence (BI) opportunities and advanced analytics. Our approach to data warehousing in healthcare allows for fast solution delivery according to your specific needs.

Augmented patient experience

This is an overarching goal of implementing a data warehouse in healthcare. By combining EHR information, diagnostic and clinical data, follow-ups, and long-term outcomes, hospitals obtain a 360-view of the patient and make their medical journey seamless, thus achieving a higher standard of care.

Personalized services

Like customers in any other field, consumers of healthcare services like to feel they are unique and special. When they create a data warehouse, clinics make a decisive step in this direction. The high-end analytics tools DWH possesses provide deeper insights into each use case and open broad perspectives for the personalization of healthcare.

Improved clinical decisions

Reliance on siloed databases full of unstructured and unclassified information does no good either to strategic planning or to immediate choices doctors make regarding treatment. Transparent and integrated data kept in unified storage and a range of first-class tools for processing it that a data warehouse provides spell the spike of quality of clinical decisions.

Efficient reporting

While monitoring patient conditions, personnel performance, or pharmacy consumption in real life, you can present these data to stakeholders, pinpoint problem zones, and step-up clinical research. But DWH opportunities extend even further than analyzing what has happened. With its advanced tools, you can also predict what will occur next.

Our DWH development process

Building a data warehouse for any use case is a serious endeavor that can be tackled only by high-profile software experts. Our vetted mavens have top-notch skills and sufficient experience in data warehouse design for hospitals across the globe which allowed us to develop a comprehensive and efficient strategy for accomplishing such projects. It includes the following steps.

Healthcare DWH architecture devisingIt all starts with analyzing business requirements for the solution we will build. The portfolio of healthcare data model examples that we have applied in our previous projects serves as a basis for choosing the architectural pattern of the solution-to-be. We opt for a one-tier, two-tier, or three-tier organizational structure depending on the volume of data it will contain.

Front-end designThe key to efficient data management within a data warehouse is a user-friendly interface providing seamless access to various data processing and analytics tools. While creating these elements of the healthcare DWH, our designers pay special attention to developing a foolproof mechanism for sharing the stored data and generated reports with all stakeholders in the sphere.

Back-end developmentEven if the front end has excellent usability and the tools are easy to operate, it won’t take you far unless it has a first-rate server side to power it. The specialists of DICEUS meticulously build this data warehouse component, consisting of a met-data unit and a collection of APIs. They are called to integrate disparate data sources the hospital relies on in its workflow.

Testing and QASince efficient data warehouse operation in the healthcare industry is often a life-or-death issue, our solution is never launched until thoroughly tested. We run all necessary checks (functional, compliance, security, etc.) to expose any bugs or malfunctions the DWH may have and eliminate them as soon as they are detected.

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What impacts your project duration

How long will it take to create a DWH for your healthcare organization? We can give you a more or less accurate estimation after we know the following information:

Project requirements
Expected deadlines
Team composition
Selected platforms and tech stack
The complexity of the DWH to build

What affects your project costs

The sum you will have to allocate to obtain a fully functional healthcare data warehouse depends on five factors:

Chosen technology
Project scope and complexity
The urgency of project completion
Engagement model
The cloud platform for your DWH

What we need from your side

Our team is qualified enough to complete any data warehouse project within the stipulated budget and timeframe. Yet, you can speed up and promote this process if you cooperate closely with the project crew. It will be a win-win outcome for both of us if you provide the following:

The project vision, goals, and roadmap (if it exists)
High-level project requirements
Available project-related documentation (software architecture, mockups, etc.)
Project deadlines
Your accessibility schedule (several hours a week)

Our tech stack

Programming languages

JavaScript

SQL

Python

Java

PHP

TypeScript

C++

Kotlin

Ruby

Swift

Scala

Haskell

Web frameworks

jQuery

React.js

Angular

ASP.NET

ASP.NET Core

Vue.js

Spring

Angular.js

Django

Laravel

Ruby on Rails

Other frameworks

Node.js

.NET Core

.NET

React Native

Flutter

Teraform

Xamarin

Apache Spark

Hadoop

Chef

Databases

MySQL

PostgreSQL

Microsoft SQL Server

SQLite

MongoDB

Redis

MariaDB

Oracle

Elasticsearch

DynamoDB

Cassandra

IBM DB2

Couchbase

Platforms

Linux

Windows

Docker

AWS

Android

MacOS

Microsoft Azure

Google Cloud Platform

iOS

Kubernetes

IBM Cloud

IBM Watson

Explore our case studies

Discovery Phase and MVP development of the Tribe fitness mobile app

USA
Healthcare

Improvements of Google Cloud Platform environment for Clear Labs

USA
Healthcare

Mobile and web app development for digital healthcare products

United Kingdom
Healthcare

.NET application for dental industry

Norway
Healthcare

SaaS product for HealthyWage

USA
Healthcare

Frequently asked questions

What is a data warehouse in EHR?

Serving as a backbone of the electronic health record system, a data warehouse accumulates information from medical dossiers, lab tests, medication prescriptions, and even insurance claims. Within a DWH, the data are unified, structured, visualized, and prepared for further analysis, which can be implemented with the help of special tools the data warehouse is equipped with.

How does a clinical data warehouse work?

First, data from internal and external sources are gathered, aggregated, and transformed through an ETL (extract, transform, load) or ELT (extract, load, transform) process. Then, they are placed into centralized storage (conventionally a cloud-based one), where BI, reporting, and visualization tools can access, retrieve, and analyze them.

What is the difference between a data warehouse and a clinical repository?

Both of them act as data storage facilities. However, for a clinical repository, collecting and hoarding raw data is the only function. A healthcare data warehouse is a more advanced form of an information depot. DWH stores data, can draw it from multiple sources, and transform and structure them. Moreover, its high-end tools enable in-depth data analytics.