Healthcare data warehousing implementation plays a key role in modern medical practices, becoming integral to information management. Today, as healthcare organizations face vast amounts of data such as clinical records, financial information, and operational data, managing this information effectively and securely has become a top priority. The challenges of data errors, the complexity of accessing critical information, and the need to adhere to strict security standards make it clear that a data warehouse in healthcare is not just a useful tool but a critical necessity.
As experts with 11+ years of experience developing healthcare solutions, the Cleveroad team is ready to share the key details of healthcare data warehouse design and implementation. We will also explore the key benefits of this solution, features and what factors can affect the implementation cost.
What Is Data Warehousing in Healthcare and Why Use It?
The healthcare data warehouse is an organized central repository for large amounts of aggregated data from several sources. A data warehouse in healthcare can contain data from Electronic Health Records (EHR), Electronic Medical Records (EMR), enterprise resource planning systems (ERP), radiology, lab databases, wearables, and even population-wide data. All data is available and updated in real-time.
! Note: A healthcare data warehouse is often confused with a clinical repository. This is an error that usually occurs due to confusion of terms. A data warehouse is a vast repository of information, including clinical data, administrative, financial, and operational information. On the other hand, a clinical repository focuses solely on clinical data such as medical records and diagnoses.
A medical data warehouse acts as a comprehensive and accessible storage for various types of healthcare data. These include:
This category includes patient histories, diagnoses, treatment plans, and outcomes, forming a comprehensive view of an individual's medical history. They play a vital role in enhancing patient care and supporting informed decision-making.
Including billing information, insurance data, appointment scheduling, and operational data, this category streamlines financial processes, optimizes resource allocation, and helps healthcare facilities run smoothly.
In addition to budgeting, financial data includes details about patient care operations, allowing you to track expenses, manage revenue, and analyze costs to ensure the sustainability of healthcare facilities.
Operational data, which includes day-to-day functions, includes staff schedules, patient flow, and resource utilization, which is critical to optimizing efficiency and improving the quality of care.
Research data covering academic studies, medical research, and clinical trials provide insights into disease patterns, treatment effectiveness, and emerging trends in healthcare, advancing medical knowledge and patient care.
Healthcare providers use medical data warehousing for a variety of purposes. Let's take a look at the main ones in more detail:
- Clinical decision support. Access to complete patient histories, test results, and treatment histories to make informed decisions about patient care.
- Population health management. Analyze aggregated patient data to identify trends, manage chronic disease, and improve preventive care for specific populations.
- Financial analytics. Monitor and manage the financial aspects of healthcare facilities, including analyzing revenues, expenses, and costs.
- Operational efficiency. Optimize hospital operations by analyzing resource utilization, patient flow, and staff productivity data.
- Regulatory compliance. Ensuring compliance with healthcare regulations and standards by maintaining accurate and accessible records.
- Research and development. Facilitating medical research by providing scientists with large amounts of anonymized data for research, clinical trials, and the development of new treatments.
- Quality improvement. Identifying areas for enhancements in the quality of caregiving by analyzing data on patient outcomes, patient satisfaction, and adherence to best practices.
- Patient engagement. Increasing patient engagement by giving patients access to their health data, transparency, and active participation in their care.
At its core, data warehousing in healthcare aims to build a unified and efficient platform for managing different data types, enabling healthcare providers, administrators, and researchers to gain valuable insights, improve decision-making, and ultimately enhance patient care.
Features of Healthcare Data Warehouse
A healthcare data warehouse can have different functions depending on the needs of a particular medical establishment. However, there is a set of basic features that should be considered when creating a healthcare data warehouse solution:
This feature involves collecting and integrating data from various sources, such as healthcare providers, laboratories, insurance companies, and finance departments. Integration provides a single and authoritative source of information, providing a complete view of patients and effective analytics.
Analytics and reporting
Medical data warehouses are equipped with powerful analytics tools, including OLAP cubes, data mining, and machine learning in healthcare. Comprehensive analytics enables physicians, administrators, and researchers to deeply analyze medical data, identify trends, predict outcomes, and create informative reports.
Data security and compliance
Protecting patient privacy is a priority. Data warehouse for healthcare provides multifaceted security, including data encryption, authentication, and authorization measures to comply with regulatory requirements for your region.
By the way, the Cleveroad team has obtained ISO security certification, which confirms our ability to deal with data security risks and protect sensitive information according to modern standards.
Medical data warehousing systems provide medical professionals and managers with the tools that simplify decision-making. They include detailed analytical reports, integrated business intelligence tools, and dashboards for operational monitoring of key metrics.
Scalability and flexibility
A health data warehouse must be scalable and capable of handling vast amounts of data from various sources. Flexibility in architecture allows for efficient adaptation to changes in healthcare requirements, new technologies, and expanded functionality.
Leveraging industry standards
Adherence to standards, such as Health Level Seven (HL7) integration for health information exchange, ensures interoperability and ease of incorporation with other systems in healthcare.Additionally, strict adherence to security standards such as the Health Insurance Portability and Accountability Act (HIPAA), Digital Imaging and Communications in Medicine (DICOM), Fast Healthcare Interoperability Resources (FHIR), and others also plays a key role in healthcare data security.
Data history tracking
The healthcare data warehouse supports tracking changes in data over time by creating audit trails. This provides the ability to view patient history, changes in their condition, and other vital parameters essential for quality healthcare delivery.
Core Benefits of Data Warehousing in Healthcare
Data warehousing in healthcare provides clinics many benefits by solving data management problems and optimizing information sharing. Some of the key benefits of healthcare data warehousing include:
Increased reporting efficiency
Traditional healthcare systems often struggle with limited access to comprehensive reporting, making it difficult to analyze data and identify key trends. Insufficient information slows down decision-making and process management. Healthcare data warehouse solves this problem by providing centralized access and the ability to perform in-depth analysis of aggregated medical information from multiple sources. This way, you can generate detailed reports, improving decision-making processes and providing better patient care.
Informed clinical decisions
Limited analytic capabilities impact physicians' ability to make informed clinical decisions. Lack of access to a patient's complete medical picture can make accurate diagnosis and treatment difficult. Data warehousing in healthcare provides physicians with broad and deep access to analytics that improve diagnosis, treatment choices, and overall quality of care. In this way, the system reduces errors and improves treatment efficiency.
Optimize insurance claims and payments
Delays and inaccuracies in insurance claims processing can slow down the financial flow of healthcare establishments», hurting healthcare providers' budgets. Healthcare data warehouse solutions automate insurance claims processing, eliminating errors and reducing processing time. Such automation increases process transparency, facilitating timely payments.
For effective insurance management, you may also consider health insurance software development, which offers numerous advantages. It enables seamless interaction between insurers and policyholders, streamlining tasks such as policy access, claims submission, and real-time updates.
Improved patient experience and outcomes
Standardized approaches to treatment don't always meet the unique needs of patients. Health data warehouse provides access to the data needed for personalized care and treatment. It includes information about previous treatments, medication reactions, and other factors, facilitating more accurate diagnoses and tailoring treatment to each patient's characteristics.
Value-based personalized care
Lack of tools to deliver personalized, value-based care can lead to a lack of patient satisfaction and low effectiveness of care programs. Healthcare data warehouse enables the creation and implementation of personalized, value-based care programs. Treatment plans can be tailored by analyzing patient preferences and needs, resulting in higher satisfaction and more effective care programs.
Explore how patient portal development can help you provide personalized care
Key Steps to Integrate Healthcare Data Warehouse
Now that you know the basic functions and benefits of data warehousing in healthcare, let's look at the process of building and implementing such a solution. It requires a thorough approach and careful execution of all necessary steps:
Step 1. Defining objectives
Before you start actively designing and implementing a healthcare data warehouse, you should define your goals. Decide what tasks you need such software and what problems it will help you solve. For example, it may improve analytical capabilities, enhance patient management, or optimize financial processes such as billing and insurance issues.
Step 2. Analyzing data sources
To ensure a seamless data transfer to the medical data warehouse, you need to understand where the data will come from. Make a list of systems (e.g., to do integrations with EMR or EHR, lab database, remote patient monitoring solutions, etc.) to connect with the data warehouse, and analyze the quality, formats, and features of these data. This analysis will ensure that you don't miss important information and that important medical data is fully integrated into the healthcare data warehouse.
Step 3. Finding an experienced IT vendor
A professional medical software provider is the key to successful healthcare data warehousing. When choosing an IT partner, consider its experience in building healthcare solutions and carefully study the portfolio with successful cases. Also, pay attention to customer reviews on platforms such as Clutch.
When choosing a vendor, you can outsource or assemble your own in-house team. Outsourcing is a much more cost-effective option, saving on administrative costs such as hardware and rent. Moreover, outsourcing will give you access to talent and technology from all over the world.
The Cleveroad team has over 11 years of experience in developing healthcare solutions. One of our recent cases is the Clinic Management System for Rehab Clinics from the USA. Our team developed a clinic management system including functionality for scheduling appointments, medical billing control, managing users, and workflow. We also successfully migrated the data and deployed the solutions on AWS cloud hosting, which meets industry compliance requirements, namely HIPAA.
Find the detail of healthcare software development services provided by Cleveroad
Step 4. Technology selection and architecture design
Choosing the right technologies is crucial to build robust and efficient healthcare data warehouse. IT experts pick the technology stack based on project requirements, focusing on databases, programming languages, and cloud storage. They can also employ specialized APIs for streamlined data transfer and faster development and use robust frameworks for handling health care information.
During the architectural design phase, the dedicated development team will outline the data warehouse framework and specify data integration methods and storage formats. This stage includes:
- Establishing a data integration strategy
- Creating a conceptual data model
- Aggregating facts into OLAP cubes
- Identifying data sources
- Planning transformation processes through ELT or ETL methods
In addition, the team will define and design the chosen data model, plan necessary integrations, and establish protocols for tracking duration and validation procedures. Here is an example of a possible healthcare data warehouse architecture:
Healthcare data warehouse architecture example
Step 5. Development and integration
In the design and integration phase, the development team implements the conceptual data model and performs integration with data sources. They create the medical data warehouse structure, apply ELT or ETL processes to transform the data and design the necessary integrations.
Here are some examples of solutions to integrate with healthcare data warehouse:
Step 6. Deployment
To deploy a healthcare data warehouse, you can choose one of two options:
- On-premise deployment. The system is hosted on your own infrastructure. This approach gives you full control over your data but requires a significant investment in hardware and maintenance.
- Cloud deployment. Organizations can turn to cloud app development to host medical data storage when deploying data storage in the cloud. Cloud services offer flexibility and scalability in deployments.
We have compiled a comparison of the most popular cloud services you can turn to for deploying your solution for data warehousing in healthcare.
|Azure Synapse Analytics
|Oracle Autonomous Database
Optimized for datasets ranging from a few hundred gigabytes to petabyte-scale DWH, ideal for big data warehousing.
Implementing a DWH without additional costs and maintenance issues. Highly recommended for advanced data analytics.
Designed for all business sizes, suitable for data lake, analytical reporting, and read-intensive databases. An ideal choice for hybrid healthcare.
Easy and cost-effective analysis of healthcare data using existing BI tools.
Ready-to-implement cloud-based solution. Allows for immediate and easy design of DW structure.
Robust, reliable, and easy integration with other tools. Efficiently extracts, loads, and transforms data across multiple applications.
$0.25 – $13.04/hour
Step 7. User training
User training is an important step in implementing a healthcare data warehousing system. During this phase, employees are provided with the necessary information and training on using the new system. Training can include a variety of formats, such as webinars, lectures, hands-on training, or individualized instruction. This process aims to provide staff with the necessary skills to work effectively with the data in the warehouse, increase their understanding of the system's functionality, and reduce potential risks associated with misuse of the software.
Step 8. Support and maintenance
To ensure the health data warehouse is functioning properly, you need to monitor its performance, update it regularly, troubleshoot possible failures, and provide technical support for users. The technical support team is responsible for responding to user requests, resolving issues, updating security, and keeping up-to-date with changing healthcare requirements. Regular system maintenance also includes monitoring legislative changes and updates to ensure industry regulations compliance.
Cost to Implement Healthcare Data Warehouse
The cost of implementing healthcare data warehouse can vary depending on various factors. The cost can range from $75,000 for simple software to $250,000+ for large-scale solutions.
Factors affecting the medical data warehouse development price include:
- Data volume. The more data that needs to be processed, stored, and analyzed, the higher the cost. It includes both current data and potential future growth in data volume.
- Functional requirements. Advanced functionality such as sophisticated analytics capabilities, support for multiple integrations, and increased security requirements can increase cost.
- Security level. Protecting medical data requires high security and regulatory compliance standards, which may incur additional costs for technical and organizational security measures.
- Architectural decisions. The choice between cloud-based and on-premise architecture can significantly impact cost. Cloud-based solutions typically require monthly or annual fees, while on-premise solutions may have higher upfront costs.
- Integration with other systems. The complexity of integrating with existing healthcare systems, such as EHR, EMR systems, or hospital management systems, can increase costs.
The location of the software provider you choose also affects the cost of developing healthcare data warehouse solutions. The hourly rate and development cost can vary in different regions due to differences in taxation and average wages. We have collected for you the hourly rates of healthcare developers in the most popular outsourcing regions:
Medical software development hourly rates worldwide
Challenges of Data Warehouse in Healthcare Industry
Implementing medical data warehousing software is associated with difficulties since such solutions are complex and large-scale. In this section, we will look at the main challenges you may encounter when implementing medical data warehousing and describe how to solve them.
Data integration complexity
Challenge: In healthcare, data can come from different sources using different formats and terminology. This creates challenges to harmonizing and integrating the information needed to fully understand the patient's story and provide comprehensive care.
Solution: Implementing data exchange standards, such as HL7 and FHIR, and utilizing ETL technologies that enable data extraction, transformation, and loading facilitates effective integration and provides a unified view of healthcare information. For instance, Cleveroad's experts ensure interoperability using:
- FHIR data exchange protocol
- HL7 (health level seven) protocol
- eRx electronic prescribing, etc.
Challenge: Incorrect records, outdated data, and inconsistencies in healthcare databases pose significant risks, potentially leading to erroneous medical decisions, compromised patient safety, and hindering the overall quality of healthcare services.
Solution: To address these challenges, the implementation of robust data quality systems becomes imperative. Automated error detection and correction mechanisms play a pivotal role in identifying discrepancies promptly. Regular staff training programs further contribute to a culture of data accuracy and awareness. Ensuring the quality of healthcare data involves continuous monitoring, validation processes, and adherence to established data governance protocols.
Security and privacy
Challenge: Medical data contains sensitive personal information that requires high protection against security threats and unauthorized access.
Solution: To ensure robust data security, choose a qualified software provider experienced in Healthcare software development. An experienced partner will implement advanced data encryption techniques, strict role-based access control rules, and security monitoring systems.
We at Cleveroad utilize various healthcare data security tools, including:
- Protected Health Information (PHI)
- Industry-standard data encryption
- Data residency and retention
- Role-based access control (RBAC)
Challenge: Legislation such as HIPAA, GDPR, and others impose strict requirements for processing, storing, and transmitting healthcare data, making compliance difficult.
Solution: Regularly update your system to comply with changes in legislation, use data anonymization techniques when necessary, and conduct audits to confirm compliance with standards. It's also important to ensure your IT partner is experienced in GDPR and HIPAA-compliant software development, as well as building solutions in compliance with other industry and regional regulations.
Compatibility with other healthcare systems
Challenge: With the diversity of information systems in healthcare, enterprise data warehouse in healthcare requires integration with other healthcare systems such as EHRs, EMRs, lab databases, etc.
Solution: Working with an experienced vendor simplifies the integration process and ensures a smoother implementation of the healthcare data warehouse into your existing healthcare infrastructure. Experts will thoroughly analyze the systems to be integrated and create the necessary healthcare APIs and interfaces to ensure effective communication between HDW and other systems. Typically, this includes developing data exchange standards and ensuring they comply with healthcare standards such as FHIR, GDPR, HIPAA, etc.
Lack of technical expertise
Challenge: A lack of technical expertise in medical software can hinder development and maintenance of complex healthcare data storage and processing systems.
Solution: To solve this problem, you should turn to an experienced software vendor that specializes in telemedicine software development services. Such a vendor can provide technical expertise in developing data warehouses in healthcare, implementation support, and long-term technical support. Also, hiring external consultants with relevant experience can further strengthen the team's knowledge and provide a deeper understanding of medical solutions' technical and regulatory requirements.
If you need to expand your team with domain specialists, read our guide on staff augmentation
Cleveroad Assistance in Healthcare DWH Development
Cleveroad is a healthcare software development company located in the CEE region, particularly, Estonia. Our team has 11+ years of experience building full-fledged software solutions for Healthcare. Our Healthcare development services include creating EHR/EMR systems, telemedicine and remote patient monitoring solutions, healthcare CRMs, and other software.
By choosing Cleveroad, you will get such benefits:
- On-demand IT services: from scratch development, cloud development, legacy software modernization, UI/UX design, IT consulting
- Practical experience in developing industry-compliant software under various domain regulations, such as HIPAA, GDPR, PIPEDA, MHRA, FDA, ISO, etc.
- Expertise in providing robust security with industry-standard data encryption, RBAC, and data residency and retention
- System Quality Assurance at each development step and continuous support and maintenance
- Flexible cooperation models according to your needs: Staff Augmentation, Dedicated Team, Time & Material, etc.
- Signing a Non-Disclosure Agreement (NDA) at the beginning of the collaboration to ensure your idea confidentiality
Feel free to check our recent case studies in the Healthcare domain - Clinic Management System with EMR for rehab clinic and IoT system for monitoring EKG and blood oxygen level to asses our Healthcare development experience on practice.
Build healthcare data warehouse with domain experts
Our team with 11+ years of healthcare software development experience is ready to help you build and integrate a robust medical data warehouse to improve clinical data management
Data warehousing in healthcare involves the collection, storage, and management of diverse healthcare-related data in a centralized repository, enabling comprehensive analysis and reporting for informed decision-making.
A data warehouse encompasses a broader range of data types beyond clinical data, including administrative, financial, and operational data. In contrast, a clinical repository focuses specifically on patient-related clinical information, offering a more specialized scope.
Advantages: Enhanced reporting, improved decision-making, optimized financial processes, support for research, and personalized care.
Disadvantages: Integration challenges, data quality concerns, security and privacy issues, regulatory compliance, and potential compatibility issues with other healthcare systems.
Challenges of healthcare data warehouse implementation include data integration complexities, maintaining data quality, ensuring security and privacy compliance, meeting regulatory requirements, achieving compatibility with existing healthcare systems, and addressing the shortage of technical expertise.
Evgeniy Altynpara is a CTO and member of the Forbes Councils’ community of tech professionals. He is an expert in software development and technological entrepreneurship and has 10+years of experience in digital transformation consulting in Healthcare, FinTech, Supply Chain and Logistics
Give us your impressions about this article
Give us your impressions about this article