The Complete Guide to Healthcare Data Management

The amount of data human activity generates is accelerating at runaway speeds. The total quantity of digital data in the world – also known as the global data sphere – has more than doubled in size in the last three years and will do so again before 2026. In a parallel development, people have never had more access to data than they do now. This includes their personal health data, such as medical histories, family histories, and even genetic makeup. For the organizations that create and store this data, healthcare data management has become a critical responsibility, as 95% of physicians concur that better data interoperability improves transparency and saves lives. 

Multiple factors, including increased regulations of personal data and mounting evidence that better data management improves patient outcomes while driving down costs, contribute to growing investment in healthcare data management solutions. The healthcare data management market had a global value of $9.5 billion in 2021 and, on its current trajectory, will reach $87.5 billion by 2030, demonstrating a sustained compound annual growth rate (CAGR) of 28.2% for the forecast period. 

With vast potential for operational improvement and new data management technologies on the horizon, forward-looking healthcare organizations should prioritize apprizing themselves of current trends and solutions. In this guide, you’ll learn what healthcare data management is and how it can help your organization deliver better patient care. 

Key Takeaways:

• Data management has become a critical and valued capability in the healthcare industry.
• Data management involves capturing, organizing, analyzing, and storing data for the purpose of applying data-driven insights to decision-making processes. 
• Healthcare data management already improves patient outcomes and drives down costs, and it has the potential to provide additional benefits as organizations continue to adopt better and more comprehensive practices.

What Is Data Management?

Data management is the practice of gathering, processing, securing, and storing the data an organization creates to comply with record-keeping regulations and apply analytics to extract actionable insights for decision-making processes. Recent developments in technology over the last ten years – software-as-a-service (SaaS) cloud platforms, AI, machine learning, and the Internet of Things (IoT) – have precipitated rapid growth in data management capabilities and adoption. 

The necessity of data management has spread across industries as diverse as financial services, e-commerce, marketing, software engineering, and healthcare. As large organizations invest in data management, they encounter structural and procedural challenges in data storage, mitigating security risks, and giving structure to vast volumes of unstructured data to render it pliable to meaningful predictive analytics. Nevertheless, the investment tends to pay off, with organizations practicing data-driven decision-making experiencing an average 5.32% annual revenue increase. 

Beyond its general foundational processes, each industry’s data management in practice is unique. 

What Is Healthcare Data Management?

Healthcare data management refers to collecting, organizing, and analyzing digital health data. Sources of data for healthcare data management may include:

• Electronic medical records
• Electronic health records
• Claims data
• Provider data
• Enrollment data
• In-home assessment data
• Disease management program data
• Patient lifestyle information
• mHealth or data gathered from wearable Internet of Things (IoT) devices
• Remote monitoring services
• Survey data

While each of these data sources contributes to a holistic 360-degree view of patient health, healthcare data management is still a developing discipline, and few organizations leverage all – or even most – of the data sources available to them. Nevertheless, the more data sources organizations integrate into a unified system, the better the insights those data stores will yield under analysis. 

Benefits of Healthcare Data Management

Healthcare data management can deliver significant benefits for patient health, operational efficiency, and overall organizational costs. 

1. Holistic View

Integrated data from a wide range of sources can create a more comprehensive understanding of individual patients, households, and various sectors of the population. When delivered to care providers such as physicians, nurse practitioners, nurses, and physical therapists at the point of care, these insights help ensure patients start on better courses of treatment.

2. Improved Patient Engagement

Sound data management practices enable predictive modeling, allowing organizations to identify patients who may be more likely to miss appointments or adhere inconsistently to treatment plans at home. These behaviors affect both patient health and resource allocation. Knowing in advance helps organizations prepare additional reminders for certain patients or more frequent follow-up contact after treatment.

3. Identification of Patients in Need of Early Intervention

The long-term prognoses for progressive diseases and comorbidities vary widely based on when intervention occurs. Identifying patients needing early intervention is mostly guesswork for physicians and other care providers with just individual medical histories. However, data management can create enhanced visibility into patient needs based on statistical correlation in data sets too large for manual interpretation. 

4. Hiring and Marketing Insights

Using data-driven decision-making processes, organizations can better understand staffing needs before critical shortages happen. As the COVID-19 pandemic saw the U.S. healthcare system lose 1.5 million skilled workers, these capabilities have become essential to maintaining healthy organizations. Similarly, medical marketing through digital channels to drive early patient engagement has emerged as a valuable tool in long-term preventative care.

5. Enhanced Monitoring of Effectiveness for Organizations and Physicians

With COVID-19 still contributing to increased hospitalization rates and diminished staffing levels plaguing the healthcare system, efficient resource allocation is more important than ever. Data management can help organizations identify problematic misallocations like hospital overstays that intensify bottlenecks and put other patients at increased risk. At the individual level, better data visibility also allows for better physician oversight through indicators for success rates, time invested in different courses of treatment, and patient satisfaction.

Comprehensive Master Data Management for Healthcare and Life Sciences with Coperor by Gaine

Coperor offers healthcare organizations a scalable, ecosystem-wide master data management platform designed specifically for the healthcare industry. Leveraging a profile-based operational data store (ODS, Coperor handily integrates master and affiliated data in real-time. 

To learn more and schedule a live demo, contact Gaine today.