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Healthcare data integration brings together information from disparate IT systems, giving medical organizations holistic data management capabilities and a 360-degree view of their data.

Now, integrating healthcare information is more crucial than ever. Annually, providers generate around 30 petabytes of data — clinical, administrative, analytical, and financial. However, almost half of it (47%) remains underutilized when delivering care and business decisions. Thanks to integration, healthcare businesses can tap into all that valuable information scattered across various systems without letting any significant details fall through the cracks.

Trends prompting data integration in healthcare

Aside from the mismatch between data volumes and data utilization, other factors contribute to the rising need for healthcare data integration.

Adoption of cloud-based solutions and APIs

De acordo com PwC, about 81% of healthcare providers have adopted cloud solutions, so medical professionals are getting used to more convenient data access. API-centric medical apps also set the bar high, offering a glimpse into truly integrated healthcare data. These factors contribute to the growing need for organization-wide data integration.

Expansion of telemedicine and remote care

The adoption of telehealth has increased in recent years, and now the technology is used for various medical specialties — primary or urgent care, mental health, cardiology, endocrinology, etc. In the years to follow, care digitization will only grow, venturing into remote surgery and diagnostics realms. It will spur demand for comprehensive patient data that can be conveniently accessed during online consultations.

Growing use of AI, ML, and predictive analytics

The healthcare AI market is predicted to expand at a 37% CAGR between 2024 and 2034, reflecting the growing confidence in predictive, prescriptive, and generative artificial intelligence among the medical community. To distill reliable insights with AI, healthcare data integration is a must, and many medical organizations agree — 55% plan to aggregate unstructured data for further analytics.

Focus on personalized care

Recently, there’s been a much bigger focus on tailored care, accelerated by advances in precision medicine and push for better health outcomes. To personalize care, medical institutions must integrate multiple data points — everything from patient-generated health information to medical history collected by different providers — and it incites the need for data integration.

Adoption of interoperability standards

Government agencies continue to develop regulatory frameworks supporting interoperability standards, like HL7 or FHIR, necessary for healthcare data integration. This has led to steady growth in their use. According to the National Survey of Health Information Exchange Organizations, now more than 80% of healthcare organizations share HL7 v2 messages, and 22% use FHIR APIs for data exchange.

Growing adoption of HIE systems

Recent government initiatives and incentives boost the adoption of HIE (health information exchange) software across the healthcare industry, driving the market CAGR of 9.7% from 2024 to 2030. This regulatory push also stimulates new medical data integration projects among the providers, making data sharing with partnering organizations more seamless than ever.

Rise of IoT-powered real-time health monitoring

Using wearable medical devices proved to be an efficient way for doctors to continuously monitor patient state, compared to in-person assessments and manual vitals tracking. By integrating the device-collected data in patient care, healthcare providers can tackle the onset of chronic diseases, avoid disease complications, and improve treatment outcomes.

Strengthening data security regulations

The regulatory oversight in the healthcare domain becomes even more rigorous, especially regarding data privacy. Storing data in disparate systems with different security measures in place puts data privacy at risk, so it further encourages data integration in healthcare.

Use of blockchain for data management

The global healthcare blockchain market is expected to grow at a CAGR of 63.3% from 2024 to 2030, with a substantial market share belonging to health records storage and exchange solutions. When used to manage integrated medical data, blockchain enables exceptional data access transparency and reliability.

Data security and compliance essentials

In 2023, large-scale data breaches in US healthcare institutions peaked, reaching 745 cases. With privacy threats at an all-time maximum, security and compliance become top priorities during healthcare data integration, highlighting the need for compliant design, robust security measures, and continuous monitoring.

Compliance by design

Compliance with HIPAA, GDPR, or other applicable data privacy regulations is the cornerstone of healthcare data integration projects. From the get-go, it’s best to analyze what regulatory rules apply to your business, detect and address potential compliance risks, and plan security measures respectively. To ensure compliance with the data privacy regulations, we recommend following information security standards, like ISO 27001, and establishing robust data governance frameworks within the organization.

Data encryption and cybersecurity measures

Core security measures for healthcare data integration include SSL and TLS-based data encryption (both in transit and at rest) and API authentication mechanisms, like OAuth or API keys. To add a new layer of security for health data, it’s a good practice to employ data masking during integration testing or data transfer, as well as data segmentation based on sensitivity level.

Continuous security monitoring and routine audits

Security measures do not stop after the healthcare data integration. Automated security monitoring systems — like SIEM and RMM — will help keep an eye out for security threats, detecting vulnerabilities and unauthorized data access attempts in real time. Regular patch management penetration testing, security and compliance audits will help proactively identify and tackle any compliance risks that may eventually lead to hefty fines.

Standards for data integration in healthcare

Thanks to standardization, healthcare systems can speak the same language, using common codes and message formats. This universal approach makes it much easier to share patient information accurately and securely.

Clinical data exchange standards

HL7 v2 and HL7 v3. These messaging standards set guidelines for sharing clinical and administrative data between applications using proprietary or XML-based structures.
FHIR. The standard describes electronic health data exchange rules: formats, key elements, and APIs. FHIR uses the HTTPS protocol, which makes the standard compatible with multiple IT solutions, including legacy ones.
DICOM. This technical standard specifies the ways to share medical images, like ultrasound, X-ray, or MRI scans, and their metadata.
CCD. US-specific XML-based markup standard details exchange protocols for medical summaries.
X12. The standard sets rules for message formatting of Electronic Data Interchange (EDI) documents and is often used by healthcare insurance companies and clearinghouses.
SCRIPT. Developed by NCPDP (The National Council for Prescription Drug Programs), it regulates the ways of sharing electronically transmitted medical prescriptions in the United States.

Terminology standards

SNOMED CT. A comprehensive set of clinical terms and codes covers clinical findings, symptoms, diagnoses, procedures, body structures, substances, pharmaceuticals, etc.
LOINC. The standard provides codes for medical laboratory observations.
CPT. Used in the US, the standard sets codes for medical, surgical, and diagnostic procedures.
HCPCS. It expands the CPT standard and covers non-physician and ambulance services, as well as items and supplies used.
ICD-10. The international coding standard offers a solid framework for the classification of diseases, signs, symptoms, findings, complaints, etc.
RxNorm. A terminology standard aggregating names of clinical drugs available on the US market.

Healthcare data sources to integrate

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Key benefits of data integration in healthcare

Melhores resultados para os doentes

Real-time access to cohesive patient data empowers better diagnostic and treatment choices, leading to better health outcomes. 25% of clinicians agree that integrated data platforms enable better decision-making.

Melhoria da eficiência operacional

Healthcare data integration helps streamline administrative processes: less time is spent on data entry, routine paperwork, compliance and performance reporting, and physicians’ focus is redirected to patient care.

Redução de custos

Integrating data collected by various IT solutions ultimately leads to lower operational expenses. 30% of healthcare providers report that aggregated data platforms lead to cost savings thanks to better resource allocation and workforce management.

Better coordination across healthcare providers

Thanks to HIE adoption, different healthcare providers can access complete patient records, make informed diagnostic and treatment decisions based on reliable data, and avoid unnecessary medical procedures.

Redução de erros médicos

Since the data exchange between applications is performed automatically, the risks of data errors and data duplication are minimal compared to manual data entry and sharing.

Accelerated clinical research and trials

Integrated databases with anonymized patient records can fuel clinical studies, including those related to disease patterns, medication side effects, treatment protocol improvements, and population health management.

Enhanced patient engagement in care

84% of patients agree that having their records available online improved their communication with healthcare providers. Instant access to consolidated health records promotes health awareness and helps patients become more engaged in treatment.

Data integration challenges in healthcare

While the benefits of data integration in healthcare are clear, businesses often face issues when trying to adopt it. Below, we will go over some of the most common data integration challenges in healthcare and offer practical tips on overcoming them.

Desafio

Solução

Ensuring data privacy in line with privacy regulations like HIPAA and GDPR may be especially challenging during clinical data integration.

It’s imperative to consider compliance and security at each stage of data integration: create a risk mitigation plan, implement robust security measures, perform regular monitoring and software audits. To make sure there are no security gaps, we recommend engaging a healthcare data integration services partner with a proven track record of compliant projects.

Different systems across healthcare institutions may use different terminology and data exchange formats, leading to interoperability issues.

It’s essential to standardize data formats and exchange protocols within IT environments so that data integration in healthcare institutions goes smoothly. Implementing middleware that translates data from one standard to another is also a good way to avoid interoperability issues.

The more complex the information flows within the organization are, the more initial investments may be needed to set up the healthcare data integration solution.

We suggest focusing on critical data flows and connecting the core systems first to keep initial costs down and start seeing ROI from healthcare data integration faster. For example, integrating an EHR with a patient app is a great starting point. It merges health records with patient inputs and lays the foundation for more advanced integrations down the road.

Harness the power of data mapping during integration

Core use cases of data integration in healthcare

Healthcare providers collaboration

Healthcare data integration helps care providers exchange medical records via HIE systems and facilitates better care based on all-around patient medical history. Also, integration enables better public health management as it allows consolidation of data from various providers.

Apoio à decisão clínica

Drawing on integrated healthcare data, AI-based CDSSs can assist doctors in patient diagnostics and treatment, helping consider all health aspects, prevent medical errors, spot early disease signs, and make correct care choices.

Personal health records management

Having their health records at their fingertips, patients feel more accountable for their health and are, hence, more willing to follow the treatment plan closely and proactively monitor their health.

Relatórios e análises

Consolidating data across the healthcare organization makes reporting much easier, saving time on manual data collection. It also facilitates real-time analytics of care outcomes, performance metrics, or financial data and helps spot and solve operational bottlenecks faster.

Towards a seamless healthcare data environment

Now, healthcare data integration is going mainstream, particularly when it comes to connecting applications with EHR systems, aggregating data for advanced analytics, or consolidating patient vitals from medical devices. The benefits of healthcare data integration are clear — by aggregating healthcare data into one centralized platform with standardized data, providers get a full picture of the medical records. They also can offer personalized and patient-centric services, better coordinate care, and improve decision-making and organizational efficiency.

Even though the healthcare data integration process does come with challenges — particularly around security, compliance, and interoperability — it shouldn’t prevent medical organizations from integrating their data. Engaging an experienced vendor offering healthcare data integration services can help navigate these challenges and ensure the integration is done securely and efficiently.

Aleh Yafimau Gestor de entregas

Data: Dec 5, 2024

Aleh Yafimau Gestor de entregas

Data: Dec 5, 2024

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