The Quick Guide to Data Integration in Healthcare

Why is data integration in healthcare important? It’s all about the data – and what to do with it.

According to the CDC, Americans made more than 860 million visits to their doctors in 2018 – the last year data was available. The amount of data generated by those visits is voluminous. Healthcare providers capture information about the patient’s medical history, current condition and symptoms, medications taken, past medical procedures, and more on every visit.

The challenge is to integrate this data so different departments can access it across various healthcare providers and other healthcare/biotech organizations. That’s why it’s essential to understand what data integration is, why it’s necessary, and the obstacles faced in integrating healthcare data across multiple providers.

Key Takeaways

• Data integration in healthcare involves sharing data across and with multiple systems and sources.
• System interoperability is necessary for disparate systems to exchange data with one another.
• Data integration helps eliminate duplicative tests and procedures and improves patient outcomes.
• Data integration is essential for speeding up patient intake, reducing data entry time, exposing fraud, and marketing directly to patients.

What is Data Integration in the Healthcare Industry?

Data integration is the process of sharing data across a variety of sources. In most instances, the shared data is located in a shared database, although real-time system-to-system data sharing is also possible.

Image source: https://marksmanhealthcare.com/how-integration-of-multiple-data-sources-can-improve-patient-insights/

Every doctor’s office, clinic, hospital, healthcare system, insurance provider, and other life science organizations keep their own records. Sometimes data within a single system, clinic, or hospital is siloed in individual departments or practices. This data is seldom shared because the disparate systems are not connected and often not technically compatible.

Data integration seeks to bring together data from all these different systems and sources to serve patient needs better, create a more efficient healthcare system, and make more effective use of that data. The integration process is challenging and often discouragingly slow but necessary to reduce costs, provide more effective patient care, and market directly to patients.

Why System Interoperability is Essential to Data Integration

Image source: Create by author

System interoperability is essential to successful data integration. The Healthcare Information and Management Systems Society (HIMSS) identifies four tiers of interoperability in the healthcare industry:

• Foundational interoperability, which enables data transmitted from one system to be received by the other
• Structural interoperability, which defines the data exchange format and messaging standards used
• Semantic interoperability, which establishes a common “vocabulary” for system-to-system communications
• Organizational interoperability, which facilitates the secure and timely use of data both within and between organizations

Why Data Integration in Healthcare is Important

It must be securely stored and integrated into the provider’s systems to get the most use of all the available data. More value comes when data from one provider is shared across systems with other providers and organizations. Properly integrated and analyzed, all this data can result in numerous benefits to patients, healthcare providers, and biotech/life sciences organizations.

Identify and Eliminate Duplicative and Unnecessary Care

When more than one provider sees a patient, it’s not uncommon for one provider to be unaware of treatment and prescriptions provided by the other. This often results in unnecessary tests, duplicative treatment, and even incompatible prescriptions. This wastes everyone’s time, incurs unnecessary costs, and can even put the patient’s health at risk. By integrating records across multiple providers, all doctors and facilities will access the same data, reducing or eliminating these issues.

Identify Effective Treatments and Strategies

Healthcare professionals can more quickly identify which treatments are most effective in specific conditions by sharing data about treatment results. This benefits both patients and biotech organizations that are seeking to market new treatments directly to patients.

Better Track Contagious Diseases

Integrating data from various sources provide scientists and researchers with the information to see more prominent trends. They can more easily track the progress of contagious diseases and thus better guide responses to COVID and other large-scale illnesses.

Speed Up Patient Intake

Providers don’t need to perform lengthy intake procedures on every patient visit by reusing previously supplied patient information and medical data. Data integration should significantly speed up initial patient visits to new providers.

Reduce Data Entry Time

In addition to speeding up patient intake, integrating healthcare data also reduces the amount of time workers spend entering that data. According to the State of Mobility in Healthcare 2020/2021 report, 56% of frontline healthcare workers’ time is spent accessing and updating customer records. Data integration can substantially reduce this time spent, freeing up staff for more productive patient-facing activities.

Decrease Healthcare Costs

By reducing time spent on patient intake and data input, data integration promises to reduce labor costs throughout the system. Cost savings also result from eliminating duplicative tests and procedures and enabling faster patient assessments.

Enable Marketing Direct to Patients

When patient data is integrated across systems and organizations, that data can help provide helpful information about treatments and medications directly to patients. Rather than relying on the current system of transmitting that information through providers to their patients, biotech/life sciences organizations can now provide targeted messaging directly to patients, bypassing providers, insurance companies, and other intermediaries.

Expose Fraud

Today malicious actors can perpetrate serial fraud on multiple providers without fear of being caught. When data is integrated across systems, this type of serial fraud will be more quickly and easily exposed, further reducing costs to healthcare organizations.

The following video presents even more benefits from the big data created by healthcare data integration.

Video source: HuffPost via YouTube

What are the Main Obstacles to Integrating Healthcare Data?

If data integration in healthcare promises so many benefits, why is it so slow to happen? The industry faces several obstacles, including:

• The sheer volume of data generated every day
• Difficulty consolidating data generated from a large number of disparate sources
• Much legacy healthcare data is unstructured, making it difficult to extract and integrate into structured systems
• Many systems are incompatible with each other
• Much medical data is still entered manually, which is slow and prone to human error
• Difficulty incorporating data from new sources, such as personal health devices and telehealth services
• Consolidated data needs to be presented in a way that is accessible to different users
• Cost of upgrading systems and equipment
• The necessity of complying with data privacy and other regulations, including HIPAA and HITECH
• The necessity of providing adequate security against ransomware and other cyberattacks

The issue of privacy and security is paramount. Healthcare data is valuable to cybercriminals because of its high value on the black market – up to $250 per record, compared to just $5.40 for credit cards. An attack on one provider could result in data breaches for other providers in an integrated system, increasing security risks for all involved.

Despite all these challenges, data integration is coming to the healthcare industry. The numerous benefits outweigh the obstacles faced and promise to revolutionize healthcare in the 21st century.

Let Gaine Help Integrate Essential Healthcare Data

Master data management (MDM) involves cleansing and rationalizing essential data for successful data integration. Coperor E-MDM by Gaine enables medical providers, healthcare systems, and biotech/life sciences organizations to create complete, accurate, and up-to-date master data across all internal systems.

The Coperor E-MDM platform supports real-time data integration, including data from CMS, patient records, state license and medical boards, and more. Let us help your organization use MDM to enable successful data integration.

Contact Gaine today to learn more about MDM and data integration in healthcare.