For 8 years, I have been in healthcare, and before I joined Cerner, now called Oracle Health, I worked as a tech architect on the telco/ISP side for VAS(value-added services). I recall conversations with my previous colleagues about APIs and services we had heavily used in Telco.
Cerner has been a remarkable history for me, changing the verticals. Discovering healthcare has been a new world for me. I always use the statement below to keep myself connected to healthcare.
In many industries in compare the healthcare outcomes and failure will have impact on the revenue or customer satisfaction, whereas in healthcare it is direct impact on human life or quality.
Once I dived into healthcare, there was a noticeable gap between enterprise IT companies and healthcare IT on the foundation level of the use of technology. There were many reasons behind it, which healthcare professionals can list. Regulations, legacy systems, lack of interoperability, etc. I would like to focus on interoperability for this post.
Healthcare interoperability, the ability of different healthcare systems and applications to share and exchange patient information seamlessly, is essential for improving patient care and healthcare efficiency. However, several challenges persist in achieving full interoperability, and they have various root causes. Here are some critical challenges, their underlying causes and possible solutions for overcoming them.
1. Data Standards and Formats:
- Challenge: Variability in data standards and formats across healthcare systems hinders seamless data exchange.
- Root Causes: Lack of universal data standards, historical use of proprietary formats, and slow adoption of modern standards like FHIR.
- Solutions:
- Promote the adoption of standardized data formats like FHIR to ensure data consistency.
- Encourage the healthcare industry to adhere to common terminology standards.
- Invest in tools and middleware that can translate between different data formats.
- Investing in dataset standardization can lead the way for moving forward AI and ML datasets in the future.
2. Privacy and Security:
- Challenge: Protecting patient data in transit and at rest is critical, leading to concerns over data breaches.
- Root Causes: Stringent privacy regulations (e.g., HIPAA), variations in data security practices, and cybersecurity threats.
- Solutions:
- Implement robust encryption and access controls to protect patient data.
- Develop and adhere to comprehensive data security policies and practices.
- Educate healthcare professionals on data security best practices.
3. Fragmented Systems:
- Challenge: Many healthcare organizations use different EHR systems that do not communicate effectively.
- Root Causes: Historical adoption of diverse EHR systems, lack of interoperability standards, and reluctance to change.
- Solutions:
- Encourage the adoption of interoperable EHR systems.
- Develop standardized APIs to facilitate communication between different systems.
- Offer incentives for healthcare organizations to upgrade or replace outdated systems.
4. Data Governance and Ownership:
- Challenge: Defining data ownership, access rights, and usage can create legal and ethical challenges.
- Root Causes: Complex legal and ethical considerations, varying data ownership models, and lack of clear guidelines.
- Solutions:
- Develop clear data governance frameworks that specify ownership, access rights, and usage policies.
- Establish legal and ethical standards for data sharing and use.
- Ensure transparency in data governance practices.
5. Cost of Implementation:
- Challenge: Integrating or upgrading systems for interoperability can be expensive.
- Root Causes: High upfront costs, ongoing maintenance expenses, and budget constraints for healthcare providers.
- Solutions:
- Offer financial incentives or grants to help healthcare organizations invest in interoperable systems.
- Explore cost-sharing models or public-private partnerships to reduce financial burdens.
- Promote open-source interoperability solutions as cost-effective alternatives.
- EHR vendors moving to the Cloud will help leverage the SAS model in Healthcare, which will play a key role in the cost of the implementation.
6. Resistance to Change:
- Challenge: Healthcare professionals may resist adopting new technologies or workflows.
- Root Causes: Fear of disruption to patient care, lack of training, and reluctance to embrace new technologies.
- Solutions:
- Provide comprehensive training and support for healthcare staff.
- Engage healthcare professionals in the design and implementation process to address their concerns and preferences.
- Showcase success stories and benefits of interoperability to encourage buy-in.
7. Vendor Lock-In:
- Challenge: Healthcare organizations may be locked into long-term contracts with EHR vendors.
- Root Causes: High switching costs, contractual obligations, and limited interoperability options with proprietary EHR systems.
- Solutions:
- Encourage EHR vendors to adopt open standards and APIs to facilitate data exchange.
- Advocate for transparent and flexible vendor contracts that allow for interoperability.
8. Incomplete Data Sharing:
- Challenge: Not all data is shared due to selective data-sharing practices or data silos.
- Root Causes: Data-sharing policies, competitive concerns, and a lack of incentives for comprehensive data sharing.
- Solutions:
- Develop policies that encourage comprehensive data sharing while respecting privacy and security.
- Establish data-sharing agreements and partnerships between healthcare organizations.
- Provide incentives such as grants or quality improvement programs to motivate data sharing.
8. Incomplete Data Sharing:
- Challenge: Even when interoperable systems exist, not all data is shared due to selective data-sharing practices or data silos.
- Root Causes: Data-sharing policies, competitive concerns, and a lack of incentives for comprehensive data sharing.
9. Lack of Standardized Consent Mechanisms:
- Challenge: Ensuring patient consent for data sharing can be complex, as no standardised approach exists.
- Root Causes: Varied state and national consent regulations and the need for a clear and user-friendly consent framework.
Addressing these challenges requires collaboration among healthcare stakeholders, regulatory changes, investments in technology infrastructure, and a cultural shift towards valuing interoperability as a fundamental aspect of modern healthcare delivery. Solutions must be multifaceted, addressing technical and policy-related issues to achieve true healthcare interoperability.
I strongly advocate using AI tools to alleviate the operational workload of caregivers and enhance the precision of documentation. This marks the initial stride towards incorporating AI in healthcare.
For the next topic, I will focus on Human errors in patient care.
Human error is one of the leading causes of medical errors and patient harm in healthcare. It can be caused by many factors, including lack of knowledge or experience, poor communication, fatigue, and inadequate training. Several steps can be taken to reduce the risk of human error in healthcare.
Bahtiyar Aytac, November 2023.
bahtiyar aytac 