Health

Database for Healthcare: the Core and Examples

Read about healthcare databases and their HIPAA requirements.

Data is a key component in healthcare, as in any technology-driven industry. Information and communication technologies help healthcare organizations offer measures to improve people’s quality of life and prevent diseases. They have been indispensable during the coronavirus pandemic. These technologies have helped overcome the impact of ethnic and racial discrimination on access to healthcare.

Statistics predict the digital health market will reach 258.30 billion dollars by 2029. A huge amount of data allows market players to find new directions in innovation, medical research, and improving patient care. It’s facilitated by the vigorous development of big data analytics in healthcare.

Large data sets are stored in so-called databases.

What Is a Database in Healthcare?

It’s an organized collection of large digital info stored electronically. This data can be updated, expanded, and quickly retrieved. Databases in healthcare can be linked to primary, secondary, and supplemental data.

Primary medical data is information healthcare practitioners obtain when interviewing patients and conducting investigations. Electronic health records (EHR) are the most popular database in the healthcare system and an example of primary medical data. It contains information about the patient’s medical diagnoses, demographic data, allergies, test results, prescriptions, etc. Thanks to EHR, healthcare professionals have improved access to clinical information about the patient.

Secondary data is based on primary medical records or is separate from any patient encounter. The physician doesn’t control it and doesn’t use it as the main source of info about specific patients. Secondary use of data is needed for statistics, scientific research, innovation, government management, and so on.  

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The creation of supplemental data was an initiative of the Barack Obama Administration. Taxpayers should have free access to the results of research that was funded by the federal budget.

The client can manage databases using special software — a database management system (DBMS). This technology allows them to organize, store, manipulate, and ensure the integrity of huge amounts of healthcare data. In addition, it’s important to reduce data duplication. A relational database performs this task.

What Is a Relational Database?

It’s easy to imagine a table that contains pieces of info from relational databases. There are predefined relationships between these pieces, such as «this patient has this last name/first name in the insurance client database table and has this plan in the insurance plans database table».

The task of the database developer is to avoid unnecessary duplication. The rules of the game are simple: one data field in a table — one data element. No redundant data: as soon as it appears, immediately delete it. Python is a choice preferred when a client needs a programming language to connect to a relational database.

Python’s extensive capabilities make it fairly easy to program different databases, such as Oracle, MySQL, Sybase, and PostgreSQL. Python’s advantages include a wide ecosystem of libraries (SciPy, Matplotlib, NumPy, machine learning libraries, etc.). Python code is easy to read. Many programmers find this programming language a great place to start because of its simplicity.

A Belitsoft expert Dmitry Baraishuk explains that simple and clean Python code requires little time to make changes, test, and support. When developers originally write an app in Python, in the case of legacy app modernization, it’s easier to carry out refactoring. It requires the specialists of a Python web development company just to update the readable and clear Python code, not to rewrite the app from scratch.

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What Are the Requirements for Healthcare Databases?

Organizations that handle protected health information (PHI) must comply with the Health Insurance Portability and Accountability Act of 1996 (HIPAA). HIPAA requirements govern how a healthcare company securely handles and stores PHI. It includes clinician appointment records, claims requests, patient health and treatment data, procedure and test results, and more. 

The scope of the Health Insurance Portability and Accountability Act was expanded in 2009 when the U.S. government passed the Health Information Technology for Economic and Clinical Health Act (HITECH). This law includes penalties for non-compliance with the HIPAA.

The question arises: is a specific database management system guaranteed to meet these requirements?

The answer to this question is — no specific DBMS. A healthcare organization can choose which technology is appropriate and safe to use.

But there are several mandatory requirements for a database to be HIPAA compliant.

1. The person who seeks access to ePHI must be authorized. In addition, this person must verify to be the one claiming.

2. PHI must be encrypted for secure transmission and storage. Then hackers will not be able to access it directly.

3. Unique user IDs are required. Through them, the organization is able to follow the activities that each user takes in the ePHI database.

4. Motion for access and use of the database must be logged and kept in a different archival infrastructure for a minimum of six years.

5. It is a necessity to implement the database backup creation, then conduct the testing, encryption, and finally the storage in a secured place.

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6. DBMS software must be upgraded regularly as soon as developers release patches of updates. Managing updates with advanced tools and smart planning enhances the security of user data in apps.

7. Trained personnel should be the ones to apply the procedures for the elimination of ePHI in case it is required and the non-recoverable condition is met.

To Summarize

Healthcare organizations need quality software to comply with legal and industry requirements.

Databases help healthcare organizations collect info about all clinical and non-clinical operations that occur daily. To ensure optimal data collection, developers must design simple but detailed databases. It is also important that these databases can quickly and securely exchange data with each other.

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