Salesforce Health Cloud Tips and Tricks for Effective Healthcare Data Integration
Salesforce Health Cloud is an extension of Customer Relationship Management (CRM) software that puts your customers at the center of your healthcare business to drive outcomes and reduce costs. A key enabler to support successful implementations is to use Health Cloud’s Patient 360, one of the many salesforce tools available, to create comprehensive patient profiles that include medical history, treatment plans, medications, and social determinants of health. This holistic view aids in personalized care in this healthcare CRM model.
Medical records are commonly stored in applications called “Electronic Health Records” or EHRs. An EHR can be thought of as a digital medical chart that contains things such as a patient’s medical history, diagnoses, medications, treatment plans, immunization dates, allergies, radiology images, etc. For context, common EHRs include Epic, Cerner, Allscripts, Athena, eClinicalWorks, NextGen, and more. While EHRs are great for handling medical information, they have not been built to deliver on highly personalized patient engagement. Salesforce Health Cloud’s Patient 360 offers the ability to integrate with EHRs to enable a 360-degree view of the patient, giving medical providers the ability to engage with patients with a holistic understanding of their history of care and transform the patient experience. The beauty of integrating an EHR with Salesforce Health Cloud is that the EHR continues to be the source of truth for all medical records and Salesforce brings all the data together for a connected healthcare journey.
Integrating data into Salesforce Health Cloud is crucial for providing comprehensive patient care and maintaining accurate health records. Here are some tips and tricks for effective healthcare data integration in Salesforce Health Cloud:
1. Design the EHR / Salesforce Health Cloud Integration Pattern
Start with a clear definition and scope of the business requirements of the integration to guide technical decisions. Choose the integration method that best suits your needs, whether it’s real-time, batch, or a combination of both. Real-time integration is ideal for critical patient data, while batch integration can handle less time-sensitive updates. If real-time is not required, batch integration is preferable as it is better suited to high-volume data, it induces less strain on systems and performance, and it is less costly and complex to build. The downside is that batch integration has higher data latency than real-time integration. The optimal approach that is best for you depends on your specific requirements and the systems involved.
Another consideration in integration with Salesforce Health Cloud is whether to make the integration bi-directional. A typical use case for bi-directional sync is provider availability and appointment scheduling functionality. Leveraging the bi-directional integration is common but may present additional complexity with sharing information across platforms. So, ensuring proper design of bi-directional data flows is imperative to keep both systems in sync which is critical for healthcare data integration. Ultimately, integration will enable automation and scalability.
2. Leverage Pre-Built Connectors and Accelerators
Many EHR vendors offer pre-built connectors or APIs for integration. Utilize these tools to streamline the integration process and reduce development time. Alternatively, teams can leverage integration platforms such as MuleSoft Anypoint that offers accelerators for healthcare implementations, which is a collection of technical assets with pre-built integration templates and reference architectures to help speed delivery for common use cases.
3. Use Healthcare Standards for Data Exchange
Data management in healthcare has its own standards for sharing data. While many accelerators offer templates to help, it’s important to standardize data formats, codes, and terminologies to maintain consistency between the EHR and Salesforce Health Cloud.
Below are some of the common healthcare standards to be aware of as part of the implementation while considering data management in healthcare:
- FHIR (Fast Healthcare Interoperability Resources)
A lightweight, flexible and web-friendly standard for data exchange that supports JSON, XML, HTTP, OAuth and enables easier access to data via APIs compared to older standards such as HL7 v2.
- HL7 v2 (Health Level Seven Version 2)
A messaging standard that enables the electronic interchange of clinical and administrative data between different healthcare systems. These messages contain segmented data fields (segments) that use a coded format to represent patient information, lab orders, billing data etc. It uses an asynchronous, point-to-point communication model between sender and receiver. HL7 v2 has rigid message structures and relies on custom interfaces, making it less flexible. It has been widely adopted with 90% of hospitals using it but lacks advanced data exchange features compared to newer standards like FHIR.
- SMART (Substitutable Medical Apps, Reusable Technologies)
An open, standards-based technology platform that enables healthcare applications to securely run on electronic health record (EHR) systems and access patient data and it leverages FHIR and OAuth standards. It aims to spur innovation by making it easy for developers to create apps that work seamlessly across healthcare systems.
- X12
X12 is a widely used standard for electronic data interchange (EDI) that facilitates business transactions between organizations and has specifically been adopted by healthcare. It uses structured transaction sets that follow predefined formats and codes to represent documents. X12 messages can be exchanged in real-time through APIs or as batch transactions through FTP. Its structured approach can sometimes lack flexibility offered by newer API-based exchange methods like FHIR.
4. Data Mapping and Transformation
Salesforce Health Cloud provides a rich set of standard and custom objects to store and access specialized health information, and this works in conjunction with EHRs. This is known as the Health Cloud Data Model. A subset of this data model is called the Clinical Data Model and is used to structure patient records and clinical data. Data mapping and transformation is performed between the EHR and Salesforce. It provides a consistent way to represent and manage patient, provider, location and healthcare data in Salesforce.
Implement strong patient matching logic to link records across systems. Consider if a Master Patient Index (MPI) system is needed to manage patient demographics and eliminate duplicate or mismatched patient records between systems.
5. Prioritize Healthcare Data Security and Compliance
Data security and compliance are critically important in healthcare data security systems due to the sensitive nature of patient health information and the growing number of data privacy laws and regulations that need to be considered. An EHR contains protected health information (PHI) such as patient names, diagnoses, medications etc. This requires stringent access controls. Healthcare data security must be managed in compliance with HIPAA regulations regarding PHI privacy, security and breach notification.
Below are factors for consideration:
- Encryption (both in transit and at rest)
- Auditing capabilities for HIPAA compliance
- Granular permissions and sharing rules for access controls
- Maintaining patient trust
- Credentials to systems must have limited scope and be protected
- Rigorous testing must validate that the integration meets security and compliance requirements before go-live
6. Focus on Sufficient Error Handling
Even with the best intentions and testing techniques, data integration errors are bound to happen. Develop robust error handling procedures to deal with data integration errors and create alerts and notifications to quickly identify and address issues. It is imperative to monitor and troubleshoot integration processes effectively, because if it cannot be measured, then it cannot be improved. The first step is to define the logging requirements and determine what information needs to be documented. Such as error details, timestamps, actions, API requests and so on. Moreover, log levels, debug logs, unique identifiers, log repository and retention policies can also be implemented.
7. Don’t Forget about Data Governance
Institute data governance practices to maintain healthcare data integration integrity. Proper data governance will help maintain data quality, accuracy, and consistency during and after integration and Data Governance is a key pillar to maximize the value of the data integration between the EHR and Salesforce Health Cloud. Strong data governance principles, policies and procedures help manage the complexity of healthcare data integration and are imperative for patient care, safety, privacy and regulatory compliance.
HOW KENWAY CAN HELP GUIDE A SUCCESSFUL SALESFORCE HEALTH CLOUD IMPLEMENTATION
Salesforce tools such as Health Cloud can transform the way you interact with patients and improve collaboration among the many people involved in delivering care. Working with an expert implementation partner allows you to set the foundation to realize the benefits of that transformation.
Kenway works with healthcare organizations to unlock the full potential of Health Cloud and reduce the complexity of implementation. By taking a holistic approach and leveraging Salesforce best practices, we help identify the role that Health Cloud should play in your operations, as well as the processes needed for an effective solution.
Each healthcare organization is different, and we take pride in learning the nuances of each client’s processes, within Health Cloud and beyond. With a Health Cloud implementation guided by our experts, you can be confident that your patients and your partners will see the difference.
If you’re ready to begin your Salesforce Health Cloud journey, we’re ready to help. Connect with us to learn more.