ScienceSoft Global
Robotic Process Automation (RPA) in Healthcare
Use Cases and Value
With 20 years of experience in healthcare IT, ScienceSoft develops robotic process automation (RPA) solutions that help free healthcare providers' staff from repetitive, monotonous tasks while reducing errors and costs in processes such as billing and patient records management. Healthcare process automation with RPA can deliver significant cost savings compared to building automation from scratch, as it minimizes the need for custom code.
RPA in the Healthcare Industry: Essence
Robotic process automation in healthcare is used to automate high-volume rule-based tasks such as updating patient records, scheduling appointments, or verifying insurance eligibility. RPA solutions offer low-code or no-code tools, with the help of which the hospital staff or the IT team can configure task automation rules. They can be implemented faster and more cost-effectively than traditional automation because they do not require complex integrations or changes to existing systems and IT infrastructure. Instead, they use software robots (bots or scripts) that can complete the same actions as human users (e.g., a patient registration specialist logging into the insurance verification portal and checking a patient's eligibility) but faster and with more precision. For example, according to Deloitte, RPA and cognitive automation (CA) can execute high-volume transactional processes approximately 15 times faster than a human and help reduce errors and time spent on rework and review by 70% to 99%.
RPA in healthcare is increasingly being combined with AI to achieve a broader automation scale or add advanced analytics capabilities. For instance, a regular RPA solution for patient records management can extract data from structured texts (online forms). When it's powered by AI, it can also extract data from unstructured texts (e.g., emails or discharge summaries).
RPA Market Trends and Adoption in the Healthcare Industry
The global robotic process automation market size was estimated at $3.79 billion in 2024 and is anticipated to grow at a CAGR of 43.9% from 2025 to 2030. The growth of the market can be attributed to the increasing demand for operational efficiency and cost reduction. The segment of RPA in the healthcare industry is expected to grow at 48.2% during the forecast period.
Healthcare Staff Tasks That RPA Can Automate
- Open emails and attachments (e.g., automatically open emails from diagnostic labs containing patient test results).
- Log into a web or a desktop application (e.g., launch a payer portal in a browser and log into it with credentials).
- Download/upload files (for claims submission, prior authorizations, etc.)
- Move files and folders (e.g., automatically move radiology reports from a shared folder to the appropriate patient folder).
- Extract structured data from documents or systems (e.g., extract adverse drug events entries from the EHR system for reporting purposes).
- Compile documents using data from different systems (e.g., EHR or document repository).
- Copy/paste text from different applications into structured fields on a template (e.g., auto-populate insurance eligibility requests, prior-authorization forms).
- Read and write to databases (e.g., retrieve patient demographic information from a hospital database).
- Scrape data from the web (e.g., monitor FDA or CDC websites for updates on drug recalls or new vaccination guidelines and notify relevant staff).
- Make basic calculations (e.g., calculate total cost based on billing codes, copays, and insurance coverage prior to generating a patient invoice).
- Follow 'if/then' decisions/rules (e.g., if a patient has not confirmed their appointment 24 hours in advance, then send a reminder SMS or escalate to front desk staff).
- Deliver files to third parties (e.g., auto-submit compliance reports to regulatory authorities, send invoices to patients).
- Send email/SMS notifications (e.g., appointment confirmations/reminders to patients).
RPA is perfect for straightforward, rule-based routines, but it struggles with more complex operations that require processing unstructured data, understanding context, or making independent decisions. To overcome these constraints, consider reinforcing RPA with AI. Such a combination can work well, for example, for the intelligent triage of GP referrals. RPA bots can pull patient records from the EHR, while NLP (Natural Language Processing) models can read free-text referral letters to predict urgency and the appropriate clinical pathway (e.g., a regular visit to a gastroenterologist or a colonoscopy procedure). Complex cases can still be routed to human clinicians for review.
RPA Applications in Healthcare
Appointment scheduling
An RPA-supported solution can receive an appointment request (e.g., via a patient portal), check doctors' availability and patient health insurance coverage, and then book an appointment slot in the patient scheduling system, practice management software (PMS), or EHR. The solution can also trigger sending a confirmation email, a pre-visit reminder, and a post-visit survey to a patient.
Patient records management
When a new patient is registered or a patient is transferred from a referring physician, an RPA-powered solution can create patient records (one-by-one or in bulk) and auto-populate them with the information extracted from different sources, like electronic patient registration forms and scanned lab tests (using OCR). It can also automatically validate and reconcile the data across multiple systems. For instance, a solution can recheck if medication information from an integrated pharmacy system matches the physician's prescriptions in the EHR.
Verifying insurance eligibility
RPA bots can send eligibility requests to insurance providers or log in directly to the insurance portal and input patient data for the eligibility verification. Then, they receive responses to eligibility requests (covered/not covered), automatically update patient insurance status across the hospital systems (e.g., billing system or claims system), and trigger sending the relevant notifications to hospital staff and patients.
Prior authorization
Based on predefined rules, an RPA bot can identify the service that requires authorization (e.g., MRI scans, surgeries, skilled nursing visits), log into payer portals or access their APIs, and auto-fill and submit prior authorization forms. It can then record the submission confirmation number and periodically check payer systems for status updates. When there is an update, the bot can retrieve approval/denial messages, trigger notifications to the appropriate staff members and patients of status changes, and update the EHR system with the decision details (approved or denied).
Billing
An RPA-powered system can reconcile payments across different accounts, match actual payments with claims, and flag any discrepancies for manual review. Such systems can also automatically generate patient billing statements and reports (e.g., claim status reports) and send reminders to patients for outstanding balances.
Claims processing
An RPA-powered solution can extract a procedure with its CPT code from the appointment records and referrals, verify it against the diagnosis (ICD-10) in the EHR, and flag mismatched codes. The system can also generate claims, submit claims to insurance companies, and check if they're approved. Besides, bots can automate sorting, correcting, and resubmitting denials.
Post-discharge management
RPA bots can automatically extract key data from EHRs and compile standardized discharge summaries. They can trigger sending summaries to primary care providers, specialists, or other care teams. RPA robots can also trigger sending personalized education materials and discharge guidelines to patients. RPA-supported systems can verify discharge medications against the patient's history and current prescriptions, and alert clinicians to discrepancies.
Physician credentialing
An RPA-supported solution can streamline the credentialing process by collecting a physician's personal and employment data from the internal HR system. It can then trigger sending requests to external systems (medical licensing boards and educational institutions) to verify the physician's active medical license and renewal status, as well as confirm their degrees, residencies, and fellowships. Additionally, the RPA bot can check for any malpractice claims and criminal history. To assist the credentialing committee, the bot can scan and upload documents submitted by the physician, assemble the credentialing package and send it to the committee. Afterward, the system can track the status, trigger sending updates and reminders to HR and the physician.
Human resource management
RPA bots can automatically scan candidate CVs for relevant skills and qualifications, schedule interviews with the suitable candidates, and trigger sending interview confirmations and reminders via email or text. RPA-supported systems can automatically update and synchronize employee data across all HR-related systems. They can also pull data from multiple sources to generate reports on performance, workload, and other employee-related metrics.
Medical inventory management
An RPA-powered solution can track the stock levels and expiry dates of medications. If the stocks are below the set threshold, it can trigger notifications to the staff.
Medical device performance control
An RPA bot can pull medical device performance logs from connected systems and send them to the data analytics module to gain insights into a device's efficiency and detect signs of malfunction. When an issue in the device's functioning is identified, the solution can update maintenance or calibration schedules, trigger notifications to the staff about upcoming maintenance, and create work orders for the engineers to perform service activities.
Regulatory compliance
RPA bots can generate scheduled compliance reports and submit them to regulatory authorities, as well as maintain audit logs of all the changes made to patient data. For example, to ensure that a hospital complies with informed consent regulations, an RPA bot can be programmed to check whether a patient's consent form for a surgical procedure is signed and automatically flag the case for human review if the form is missing or incomplete.
System Architecture for Appointment Workflow Automation
While RPA-powered software can be built from scratch, deploying it on the Microsoft Power Automate platform can reduce both development time and overall costs. It can also easily be integrated into the workflows of healthcare organizations already operating within the Microsoft ecosystem. Besides, Power Automate has built-in copilots and native integration with Power BI and AI Builder services, which makes it easier to combine RPA, BI, and AI capabilities for enhanced process optimization and data-driven decision-making.
Below, ScienceSoft's consultants share a reference architecture for the automation of the appointment management workflow based on the Microsoft Power Automate platform. This high-level, generalized overview serves as a conceptual guide; the actual architecture will depend on the specific requirements of the chosen solution.
RPA bots, called flows in Microsoft Power Automate, manage the end-to-end automation process. Cloud flows use Microsoft Power Automate connectors to interact with internal systems (like EHR, PMS, and CRM) and external services (such as email or SMS). Desktop flows automate tasks in systems without modern APIs, such as legacy platforms, by mimicking human actions like logging into these systems. These flows are triggered by cloud flows and run in either attended (with user supervision) or unattended (fully automated) mode.
Automation flows in Power Automate can be built even by non-technical users like hospital administrators. They can ask Microsoft Copilot in natural language, for example, to create a flow that schedules appointments and sends confirmation emails. Copilot then generates a draft workflow, suggesting triggers and actions, which administrators can refine, adding conditions or customizing messages.
Once created, automation logic is stored in Microsoft Dataverse, which houses structured data and activity logs.
An example of an automation flow can be the following:
- A patient submits an appointment request through the patient portal. This triggers an automated cloud flow via an HTTP request.
- The cloud flow captures the requested physician's specialty, date, time, and patient ID, and stores the request in Dataverse.
- The cloud flow connects to the calendar system in the EHR via the FHIR connector and searches the provider's calendar for availability.
- If no slots are found, the cloud flow executes fallback logic (e.g., adjusting the date or time). If no alternative is confirmed by the patient, the flow routes the request to administrative staff (e.g., via Microsoft Teams or email) for manual handling.
- If a suitable slot is found, the cloud flow triggers a desktop flow to perform insurance eligibility verification. The desktop flow logs into the insurance portal and checks the patient's coverage, copay, and deductible information.
- Once availability and insurance are confirmed, the cloud flow sends a tentative appointment notification to the patient. It uses either the Office 365 Outlook connector (for email) or the Twilio connector (for SMS). The message includes confirmation and cancellation links, and the flow logs the communication event.
- When the patient confirms the appointment, a cloud flow is triggered via an HTTP webhook. It generates an appointment ID, creates the record in the EHR calendar system, and updates the CRM and Dataverse.
- One day before the appointment, a scheduled cloud flow runs to retrieve upcoming appointments from Dataverse and sends an email or SMS reminder that includes visit details, pre-visit instructions, and a check-in link for virtual visits.
- After the appointment, another cloud flow is triggered (e.g., based on a status update in the system). It sends a feedback form via email and may analyze responses using AI Builder. Based on the input, the system can suggest follow-up appointments, update the CRM, or flag the patient for care management.
Technologies We Use
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Why ScienceSoft?
- 20 years in healthcare IT.
- ISO 13485, ISO 9001, and ISO 27001 certifications.
- Experience in achieving compliance with the requirements of HIPAA and GDPR.
- Principal architects with experience building complex and secure solutions for the healthcare industry.
- In-house PMO with 60+ project managers holding PMP, PSM I, PSPO I, ICP-APM, and other certifications.
Our Awards and Recognitions
Listed among Healthcare IT Service Leaders in 2022 and 2024
Selected for sustained growth and resilience
Recognized for reliability and trustworthiness
Recognized by Health Tech Newspaper awards for the third time
Top Healthcare IT Developer and Advisor by Black Book™ survey 2023
Best in class in medical device connectivity (2023)
A top outsourcing provider for four consecutive years
ISO 13485-certified quality management system
ISO 27001-certified security management system
