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The challenges of health data management are increasing almost as quickly as the amount of data providers are collecting. Known as the process of collecting, storing, retrieving, and using health care data, health data management can be a critical factor in a patient’s diagnosis, treatment, and overall experience with a provider or organization.

As health data systems become more streamlined and interoperable, data organization and management should follow suit, but that’s not automatically the case.

Our four-step process can help you take a methodical approach to improve your health data management:

Step 1: Understand the Current Data Collection System

Before you can make improvements to your current data management, you need a deeper understanding of how data flows through your system. Healthcare organizations using fragmented systems may find this to be the most complex step of improvement.

It can be helpful to make a map or flowchart that highlights the various input points and collection methods for patient data. Understanding who is performing the input, who accesses the different types of data, when certain data sets are used, and where data is stored can help organizations dial in on specific improvements that won’t adversely affect existing data collection systems.

Step 2: Identify Areas of Opportunity for Improving Data Organization

Increasing your visibility into current data management better positions you to discover opportunities for improvement. Data analysts, providers, organizational leaders, and customer service should be able to contribute to the conversation. Each has a unique perspective on how data is collected and handled and their insights can help to establish thoughtful protocols and changes to the existing system.

Step 3: Develop a New Framework for Health Data Management

With opportunities in mind and organizational goals at the forefront, you’re ready to create a new framework that allows for better collection, archiving, and retrieval practices. Any changes you make to your existing data space must be able to bring you closer to your organization’s specific goals.

Ideally, your changes should not negatively impact any existing practices. For example, limiting user access to certain data sets might bring more security to your practice, but too many limitations on patient data could increase workloads and response time. Improvement in one regard may not be much of an improvement overall. Keep the big picture in mind at all times.

Step 4: Analyze Your Results Over Time

Just as you’re currently analyzing your data management for new opportunities now, you should continue to do so over time to ensure your processes continue to help you achieve organizational goals. Establishing strong data management practices isn’t a one-and-done activity, but rather something that should be examined each year. Through diligent observations, you can continue to find areas for improvement so that you can collect, protect, and leverage patient data to its full potential.

Improving Health Data Management Must Be Prioritized

Better data practices don’t just happen when you upgrade to a new system or hire new analysts. It must be a thoughtful, directed process and requires participation from all players.

When you approach health data management from a methodical perspective, it’s much easier to maintain a holistic view without getting distracted by smaller objectives that won’t bring about real change.

To find out more about how you can streamline improvements to your health data management, download our free white paper on healthcare interoperability.