RPA Software Unlocks Patient Data in Salesforce Health Cloud

Do you want to know how to use RPA software to improve the flow of patient data between Salesforce Health Cloud and EMRs? 

Shahzad Khokhar is the Global Head of Salesforce, Healthcare, and Life Sciences at OpenBots. He previously founded araZach, a Salesforce-certified partner focused on the Health and Life Science vertical, which was recently acquired by OpenBots.    

He is an advisor on core Salesforce components like Health Cloud, Marketing Cloud, Service Cloud, and Sales Cloud to solve healthcare and life sciences challenges. He also has a background in robotic process automation as the former Global head of Salesforce at UiPath.   

In this article, we talked with Shahzad about how RPA software integrates with Salesforce Health Cloud and provides greater accessibility between CRMs and EHR systems. 

Watch Video: Salesforce Health Cloud: Unlock Patient Data With OpenBots RPA Software 

Connecting Salesforce Health Cloud and EMRs Using RPA Software  

Electronic medical records (EMRs) are a patient’s medical history in digital form. They include information like provider notes, diagnosis, immunizations, allergies, lab results, and more.

EHR data interoperability1 or the ability to access this data between various systems is a challenge. This issue, in part, is due to the lack of cost-effective and straightforward integrations between EMR systems.   

An average hospital system uses several EMR vendors1, all of which handle data differently. There’s also another layer of complexity when factoring in the type of records like inpatient versus outpatient records.   

A bot automation, or software bot, combined with intelligent document processing can solve these interoperability issues. Learn more about healthcare automation technology.  

Electronic Medical Records Challenges 

The elements within an electronic medical record are consistent, but the formatting is not. 

The lack of template standardization requires a human worker to manually enter the data into Salesforce and EMR since every system uses different conventions.   

Like all data entry, it’s prone to error, leading to missed information, incorrect prescriptions and treatments, and service delays. It’s also time-consuming for staff to update each referral.    

Facilities of all types and sizes deal with these inefficiencies daily. An example is a physical therapy practice with 20 different referral sources. Each source is a manual referral with a distinct format.  

It would be a time-saver if all vendors agreed to use universal electronic medical records, but this is unlikely to happen anytime soon. 

Healthcare Automation Starting Point 

Covid and the Great Resignation have made it critical for facilities to eliminate inefficiencies, improve services, and retain staff. Healthcare automation can fill the gap between staffing issues and manual work with EMRs by doing more with less.  

As mentioned earlier, a significant area is inputting patient referrals. Other inefficiencies are meeting HIPPA compliance, accessing APIs within EMR systems, and the complexity of Salesforce integrations.   

These take a lot of time and are expensive to deploy, which makes it clear why automation in healthcare is in its infancy. Clinical managers, for instance, are expected to manage the movement of patient data into their CRM from multiple systems.  

The manual paperwork and data entry tasks with processes like these can be eliminated with healthcare automation, using robotic process automation as a starting point.  

The value is a win-win for the organization and staff—instead of highly-trained staff spending the bulk of their time on data entry, they can prioritize the patient experience. 

Opportunities in Healthcare Automation 

Native capabilities with document processing within the Salesforce construct are a significant area of opportunity in healthcare automation.   

The data in a patient referral is standard, but how it’s organized is unique to each EMR system. Referrals all have templates but differ. The lack of template consistency requires medical staff to verify and manually transfer the data between systems.   

Tools like Amazon’s Textract use machine learning (ML) to extract data using optical character recognition (OCR) from documents. Salesforce wrapped this solution into the platform under the name Salesforce IDA (only available for Health Cloud users).    

Bringing Textract into the CRM highlights the need for a streamlined way to handle patient intake faster and more accurately. Textract requires complex coding to transfer template variations into Salesforce Health Cloud in a way that will have the most significant impact on the medical staff.  

It’s a step in the right direction but has its limitations, namely mapping to objects within Salesforce.  

Intelligent Document Processing in Salesforce 

Document processing IDP (Intelligent Document Processing) tools like OpenBots Documents allow facilities to automatically create patient records in Salesforce.   

The tool uses propriety algorithms to extract data from required fields from any document, whether structured, semi-structured, or unstructured. The bot automation monitors an inbox for an incoming referral then sends a PDF attachment for data extraction.   

Watch Demo: Intelligent Document Processing in Salesforce  

An intake coordinator (human in the loop) can inspect that the fields are accurate and complete. If the bot misses any fields, the coordinator can make quick adjustments using the text option, then verify the referral in Salesforce.   

The bot collates the fields, saves the data, and sends all values via an API to Salesforce. Staff then can be notified with the new patient information like diagnosis, referring physician, coverage type, and more.   

Salesforce EMR Integration Bot 

Patient referrals can also be automatically created in an EMR with healthcare automation.   

The Health Cloud Referral object includes information on the referral and provides direct access to related data, including the patient, the referring physician, and the rendering physician.   

Note that the Patient Identifier field is typically the EMR MRN number in the patient record. The bot brings back this number once the patient has been created in the EMR successfully.   

Watch Demo: Salesforce EMR Integration Bot  

In the referring physician’s record, you can see the payor (or the insurance company’s record). The data was extracted from a faxed referral document, and all corresponding records were created automatically.  

Once the care coordinator has determined that this patient is ready for an appointment, they click the send to EMR button, which kicks off the integration bot.  

The bot logs into the EMR and creates a case (or a patient chart) record in the EMR. It then returns to Salesforce and adds the EMR case id to the referral.  

The next step is to bring back provider notes (from the EMR into Salesforce) to keep the care team up to date on patient needs and leverage native Salesforce functionality. 

Salesforce Health Cloud Integration With RPA Software 

Most facilities will want to start with healthcare automation by removing manual inefficiencies of managing patient data in Salesforce and EMRs. 

Tools like OpenBots RPA software automatically create patient records within Salesforce (and other CRMs) and pull data from EMRs in real-time. Bot automations free up time for medical staff to focus on quality patient interactions instead of tedious data entry.  

Every facility uses a different EMR systems and will need the expertise to maximize Salesforce. Getting a healthcare automation consultation is the best way to understand the best place to start for quick wins and long-term gains.   

One of the advantages of a bot automation using IDP is that it’s fast to implement, usually taking a matter of weeks. Learn more on how to digitally transform your facility.    

Reach out to Shahzad Khokhar to get started: sk@openbots.ai