Health Data Management: What it Means for Healthcare Organizations

The healthcare industry is undergoing a data revolution, fundamentally changing how healthcare organizations and professionals approach patient care. A modern healthcare data management system that empowers health providers to better anticipate needs and improve patient outcomes with unprecedented accuracy isn’t optional anymore; it’s the data-driven future of the industry.

The global digital health market, projected to reach a staggering $456.9 billion by 2026, highlights the central role health data management plays in the industry. For healthcare organizations, the sheer volume, variety, and velocity of this data present a goldmine of potential and opportunities. However, to truly transform healthcare and improve clinical decision-making, they must move beyond outdated approaches.

Source: Precedence Research

The fact that traditional data management systems are no longer viable for handling the massive influx of information is making way for advanced analytics and reporting to take center stage in enhancing patient care. The industry is responding by investing in modern healthcare data management solutions, which are essential to navigate the complex landscape of modern healthcare.

What is Health Data Management?

Health data management (HDM) refers to the practice of organizing and controlling health information and medical data, often stored in a digital format as Electronic Health/Medical Records (EHR/EMR). It’s also known as clinical data management and health information management.

Given the critical nature of medical data, there are several factors to be considered for its management. For example, healthcare companies must ensure that the data collected is accurate, cleansed, complete, and accessible to authorized stakeholders when needed. Therefore, healthcare data management involves the complete lifecycle of health information—from its creation and capture to its storage, security, access, analysis, and eventual disposal.

With the digitization of the healthcare industry, organizations store and process all medical records in an electronic format. These records are rich with data, encompassing various categories such as:

• Demographic information: Age, address, gender, etc.
• Health Records: Lab reports, prescriptions, doctor visits, treatment history, etc.
• Administrative Data: Insurance claims, billing details, etc.

Centralized data repositories aggregate these electronic records, powering efficient reporting and analytics. Health data analysts use this data to gain valuable insights critical to drive improvements in patient care efficiency and medical outcomes.

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5 Benefits of Effective Healthcare Data Management

Health data management benefits not only healthcare organizations but also the patients that rely on them:

Elevated patient care through personalized treatment

Aggregating granular patient data—from genomic markers and real-time wearable data to nuanced social determinants of health—allows clinicians to gain unprecedented insights leading to:

• highly precise diagnoses
• therapies tailored to individual genetic predispositions and lifestyles
• proactive risk stratification to prevent disease before it manifests

The result? Measurably improved outcomes and reduced healthcare costs associated with late-stage interventions.

Clinical decisions with actionable insights

Modern health data management has fundamentally changed how clinical decisions are made. Healthcare organizations have moved away from a time when doctors primarily relied on their individual intuition and experience. Now, we’re in the era of evidence-based protocols where data guides the way. The use of sophisticated data management tools enables healthcare professionals to process and analyze large collections of patient records and uncover subtle but crucial insights. For example, they can identify:

• Optimal drug combinations for different conditions
• Early warning signs that predict adverse events before they happen
• Benchmarks for treatment effectiveness across diverse patient groups

Leaner healthcare operations

The national health expenditures for the US healthcare system totaled $4.1 trillion in 2020, making it 19.7 percent of the total GDP. Healthcare organizations are constantly looking for ways to minimize their expenditures.

Effective health data management avoids duplication and wasted effort, improving patient information handling and eliminating waste in healthcare operations. Instead of having separate, disconnected records scattered across different departments (lab, pharmacy, and doctor’s office), all relevant data can be organized and made accessible in one place.

Fortified data security and patient confidentiality

Health data management enables the implementation of multi-layered security architectures, rigorous access controls, and advanced encryption all of which are vital in protecting sensitive information from increasingly sophisticated cyber threats. Moreover, proactive data governance frameworks that uphold patient privacy regulations, like HIPAA and GDPR, are critical to healthcare data management as they help build and maintain patient confidence.

Evaluate medical practitioner’s performance

When healthcare organizations take a closer look at how physicians and other professionals work, they can take measures to fine-tune the way care is delivered. Collecting and reviewing data—like how long appointments take, treatment results, and adherence to best practices—allows managers to spot trends and areas for improvement. The insights gained help teams celebrate their successes and make necessary adjustments to ensure patients receive the best care possible.

At the same time, monitoring healthcare professional activity helps smooth out day-to-day operations. When leaders know how each part of the team contributes to the overall picture, they can plan ahead, provide targeted training, and allocate resources where they’re needed the most.

Top Health Data Management Challenges Affecting the Healthcare Industry

Maintaining healthcare data compliance and security

One of the most crucial challenges in health data management is maintaining strict compliance and fool-proof security. Healthcare data is incredibly sensitive and personal—its protection must be absolute not only to comply with regulations but also to preserve patient trust.

The challenge here lies in implementing advanced security measures, such as encryption and continuous monitoring, without disrupting the seamless flow of information essential for timely patient care. Healthcare organizations must regularly conduct audits, update their security protocols, and train staff to counter emerging cyber threats.

Balancing such stringent security requirements with the need for data accessibility and operational efficiency is an ongoing, complex task that is vital for safeguarding both patient privacy and the integrity of the healthcare system.

Consolidating data from disparate sources

Think about the healthcare world for a moment—it’s bustling with different departments, clinics, labs, and systems, all humming along and generating valuable information. The challenge arises when healthcare professionals need to make important decisions only to find out that the data they need lives in separate systems. Integrating data from these disparate sources, including electronic health record systems, specialized databases, and even paper records still lingering in some places is time consuming and costly without a solid data management strategy.

Yet, consolidating this fragmented data is key to seeing the bigger picture, allowing healthcare organizations to truly join the dots and gain those crucial insights for better patient care and operational improvements.

Learn more about consolidating healthcare data in a data warehouse.

Ensuring data accessibility across the organization

Once all this valuable data is gathered and stored, the next hurdle is ensuring it can be accessed by the right people, at the right time, and in a way that helps them do their jobs better. No wonder seamless data accessibility plays a crucial role in providing high-quality patient care.

Yet, data locked away in a system that’s difficult to navigate or unavailable to those who need it poses a serious challenge for healthcare providers. This fragmentation is often due to legacy systems and disconnected databases that don’t communicate well with one another. When critical information is siloed, healthcare professionals face delays accessing the data they need, which can slow down diagnosis and treatment. Security measures, while essential, sometimes compound these issues if they restrict access too much.

To overcome this challenge, healthcare organizations must prioritize user-friendly, interoperable data management solutions that allow authorized personnel to access the information they need quickly and securely.

Storing and retaining healthcare records

Healthcare data volumes have risen significantly. In fact, the healthcare industry produces 30% of the world’s data alone. Archiving and processing large volumes of data can be complex and present high cost and security challenges. It’s not only about finding enough storage space to keep everything; ensuring this vault of information is secure, reliable, and readily accessible whenever needed is equally important.

Many healthcare providers are moving to advanced cloud storage solutions to ensure compliance with HIPAA and other industry standards.

Transform Healthcare Data Management with Astera

Consolidate health data from EHR/EMR, insurance claims, CRMs, and health-tracking apps into a centralized repository for reliable decision-making and improve patient outcomes. See Astera in action with a free demo.

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Healthcare Data Management Best Practices

To maximize the potential of implementing a healthcare data management system, hospitals and other healthcare facilities must collaborate to effectively manage, organize, safeguard, and transfer patient and provider information.

Establish a unified data integration strategy

Effective health data management begins with unifying information from various sources—whether it’s electronic health records, lab systems, or imaging databases—into a single, cohesive repository. A single source of truth that provide a complete view of a patient’s history minimizes duplication and enables healthcare professionals to make well-informed decisions.

Learn more about healthcare data integration.

Embrace proactive data governance and continuous improvement

Medical errors are the third leading cause of deaths in the US. Healthcare providers must have a proactive approach to data governance in order to keep pace with evolving healthcare challenges. Establishing clear policies, assigning specific roles, and using modern data management solutions with embedded data profiling and validation capabilities is key to continuously monitor data quality and address issues before they escalate.

Enhance data accessibility across the organization

Making sure that every team member can quickly retrieve the right information is critical for efficient patient care. Health data management systems with visual UIs and robust interoperability enable seamless healthcare information exchange (HIE), allowing healthcare professionals to access and share data across applications, devices, systems, and departments.

Implement comprehensive data security, compliance, and privacy measures to protect data

In a 2022 report by IBM, the cost of a breach in the healthcare industry went up 42% since 2020. This was the highest average data breach cost of any industry.

Given the sensitivity of healthcare information and threats of cyber-attacks and breaches, hospitals and health systems must improve detection and containment by implementing modern cybersecurity measures while complying with regulations.

Invest in scalable infrastructure and future-ready technologies

Healthcare organizations must ensure that their infrastructure scales as their data volumes grow. Investing in flexible, cloud-based storage solutions, disaster recovery plans, and emerging technologies like artificial intelligence (AI) and machine learning enhances data management capabilities and prepares healthcare organizations for the future.

Health Data Management Enables Health Data Analytics

Health data management serves as the essential enabler of health data analytics, ensuring data is collected, secured, and organized to a high standard before it’s used for decision-making.

Using advanced analytical techniques, healthcare organizations can move beyond simply managing data to actively using it for strategic planning. The shift not only improves clinical outcomes but also enhances population health management—helping providers identify trends, forecast risks, and tailor interventions to meet both individual and community needs.

Below are four key data analytics approaches used in healthcare:

Descriptive analytics

In health data management, descriptive analytics is mainly used to establish a clear baseline by summarizing historical data (patient demographics, resource utilization, treatment outcomes, etc.) using straightforward statistical measures. The analysis of historical data provides healthcare professionals insights into past performance, enabling them to understand the current state of care and set the stage for targeted improvements.

Diagnostic analytics

Diagnostic analytics is all about uncovering the root causes. Once a baseline is set, the next logical step is to examine the cause-and-effect relationships to understand why a certain trend or outcome occurred. For people in health data management, this type of insight is critical. For example, understanding why infection rates increased or patient outcomes varied will allow clinicians to take the necessary steps to make a difference in how patients are cared for—whether it’s refining processes, reallocating resources, or suggesting targeted changes.

Predictive analytics

Wouldn’t it be amazing if healthcare professionals could get a little glimpse of the future, almost like a weather forecast? That’s essentially what predictive analytics is all about—healthcare organizations rely on predictive analytics to be more proactive. So, instead of reacting to a spike in readmissions after it happens, healthcare professionals use predictive analytics tools to ascertain the risk of readmission before a patient even leaves the hospital. These tools are powered by AI, machine learning, and data mining to process huge amounts of data.

Prescriptive analytics

Prescriptive analytics offers a strategic roadmap that allows healthcare organizations to use data to guide their decisions. In other words, figure out the best course of action using techniques like simulations and scenario analysis. For example, “What if we adjust this treatment protocol?” or “What if we reallocate staff in this way?” Analyzing such scenarios helps healthcare teams develop highly tailored treatment plans for individual patients. It can also help optimize how resources are used across the organization and streamline operational processes.

Simplify Healthcare Data Management with Astera

Astera offers an enterprise-grade, all-in-one data management platform that enables healthcare organizations to unlock the true potential of their data. Using Astera’s AI-driven automation and features, healthcare organizations can seamlessly extract, transform, integrate, store, and use their data to drive faster insights, ensure compliance, and ultimately, improve patient care—all while achieving up to a 90% boost in operational efficiency.

Leading healthcare organizations trust Astera for health data management:

Novartis

Novartis Pharmaceuticals needed a data management solution that could deal with high volumes of data coming in from multiple disparate sources. This meant that the solution had to provide strong data transformation and manipulation features along with pivoting/unpivoting and string capabilities to deal with a multitude of data formats. With Astera’s data management platform, Novartis was able to improve data quality, get analysis-ready sales and forecast data from its retail partners, and increase productivity.

Cherry Heatlh

Cherry Health needed to transform incoming data from production and reporting databases and transfer it to their data warehouse for further analysis. Since the data was in different databases, it was difficult to get a full picture of operations and make data driven decisions. They also wanted a platform that allowed them to integrate data from electronic scanned forms (submitted via mobile devices) into the Cherry Health Electronic Health Record system, which contained electronic patient charts. With Astera, Cherry Health was able to achieve quick turnaround times for executing new projects and saw significant cost savings from not having to print, ship, scan, and shred patient forms.

Chorus Community Health Plans (CCHP)

For many years, CCHP struggled to meet the 95 % Encounter data submission and approval rate for State Medicaid reimbursements because of errors and inconsistencies in the Encounters from vendors and TPAs. Chorus Community Health Plans uses Astera to ensure accuracy and quality in their encounters. CCHP hit a 98% approval rating with the state after implementing Astera into their process. Their error rate decreased significantly. Any changes they need to make take only five minutes, whereas before they could take up to three hours.

Transform Healthcare Data Management with Astera

Consolidate health data from EHR/EMR, insurance claims, CRMs, and health-tracking apps into a centralized repository for reliable decision-making and improve patient outcomes. See Astera in action with a free demo.

View Demo