Integrating two different systems will always come with some challenges. While applications are often built to work with others since we know interoperability is a key need in healthcare, it’s not always perfect. Sometimes unforeseen problems arise when the applications get a broader use, or the knowledge an employee has on one system doesn’t translate to what is needed for another. So what challenges arise when integrating back office systems with clinical and front-end applications?
In search of an answer, we reached out to our brilliant Healthcare IT Today Community to ask — what challenges do organizations face when integrating back office systems with clinical and front-end applications, and how are those challenges being addressed? Below are their answers.
Kevin Deutsch, Chief Growth Officer at Softheon
Healthcare organizations are often trying to connect systems that were not built to work together. Enrollment, billing, eligibility, clinical, and member-facing tools all hold different pieces of the same story, often leading to delayed approvals, inaccurate coverage information, billing issues, and a frustrating experience for members.
Solving these integration challenges becomes even more important as models like ICHRA introduce more partners, platforms, and data formats into the operational landscape. Plans need to focus on building more flexible infrastructure, connecting systems in real time, and leveraging modern health plan software to create one reliable view of each member across the business.
Barry (Zevi) Samel, General Manager for New York Solutions at Cantata Health Solutions
Everyone focuses on getting systems connected. Far fewer people ask what happens after. In behavioral health, that question matters enormously — because when data quietly goes wrong between applications, the consequences ripple fast. Getting different systems to share data cleanly isn’t a one-time fix. It’s ongoing work, and most organizations are stretched too thin to keep up with it consistently.
The organizations that stay ahead are the ones watching closely — tracking upgrades, catching errors early, and making sure every record that moves between systems arrives accurate and intact. That kind of vigilance doesn’t just prevent problems. It builds the trust that good care depends on.
Karly Rowe, President, Provider at Inovalon
Revenue cycle management has seen considerable investment in automation over the past decade, and it shows. AI is reducing manual reconciliation, accelerating close cycles, and giving revenue cycle leaders cleaner data to act on. On the front end, eligibility verification and prior authorization workflows are faster and more accurate. On the back end, AI tools can anticipate payer requirements, flag denial risk before submission, and generate appeal documentation, keeping revenue cycle teams in control while reducing the administrative work that slows them down.
The deeper challenge is with integration. Back-office systems rarely share a common data model with clinical or operational platforms, and that gap has real consequences. Errors introduced at intake, including incomplete eligibility data and missing documentation, surface as denials weeks later. When AI is informed by the right data that spans the full cycle, from patient access through payment, organizations can catch issues before they become costly downstream problems.
The organizations seeing the strongest results are moving away from point solutions toward platforms that connect the full revenue cycle. When front-end and back-end systems share a consistent and cohesive data foundation, AI can do more than automate individual tasks. It can identify patterns, predict risk, and surface the right actions at the right moment. That kind of connected intelligence is where the meaningful operational gains are being realized.
Kevin Tsai, Vice President of Product Engineering at DT Research
One of the biggest challenges healthcare organizations face is securely connecting older back office systems with newer clinical applications and connected medical devices. Many hospital systems were implemented separately over time, which creates data silos and inconsistent security approaches. As more devices become connected across the network, managing cybersecurity risk has become even more difficult.
To address this, we’re seeing healthcare organizations adopt more interoperable platforms and hardware-rooted security technologies that establish trust at the device level. Technologies such as TPM-based authentication, secure boot, and hardware-level encryption help protect sensitive patient data while also allowing devices to communicate more securely.
Jeffrey Eyestone, Chief Strategy and AI Officer at P-n-T Data Corp.
Healthcare provider organizations face two related but distinct integration challenges when integrating back-office systems with clinical and front-end applications. The first involves workflows driven primarily by internal data—integrating EHRs with ERP, billing, scheduling, and other back-office systems. While complex, these challenges can often be addressed through internal IT modernization, APIs, and interoperability initiatives. The second, and much more difficult, challenge involves workflows that depend on external data sharing across providers, payers, transaction processors, labs, and other participants.
Claims, remittances, prior authorizations, attachments, eligibility, payment data, and more must move reliably across fragmented networks and formats. These workflows often suffer from friction caused by centralized transaction processors, inconsistent data quality, poor interoperability, weak governance and tracking, and limited real-time orchestration capabilities. As a result, many high-value use cases such as revenue cycle optimization, claims and prior authorizations with attachments, and AI-driven automation remain elusive.
While emerging federal interoperability mandates are pushing the market toward more standardized data access and exchange, the industry still lacks a modern approach to data sharing, governance and integrity, transformation, and orchestration capabilities at scale. Until that foundation exists, many back-office and administrative workflows will remain more manual, fragmented, and costly than they need to be.
David Matalon, Founder and Chief Executive Officer at Venn
The back office in healthcare is no longer just a room down the hall – it’s a distributed workforce of contractors, remote employees, and outsourced teams who need access to systems that touch sensitive patient data. The challenge isn’t integration complexity; it’s that every one of those workers represents a potential exposure point for patient data, and traditional approaches to securing access either create so much friction that people route around them or require IT teams to manage a fleet of devices they don’t own.
The organizations getting this right are the ones moving away from device-centric security and toward isolating work itself – keeping sensitive data contained within a protected environment on any device, regardless of who owns it.
Matthew Sakumoto, Chief Clinical Product Officer at Nabla
The clinical note serves many (maybe too many) purposes, including clinical documentation and care coordination, and also justification for the level of reimbursement or unlocking prior authorization. Ambient solutions start to handle both outputs from a single encounter. The clinician can focus on the patient and the E/M coding rationale, or prior authorization documentation gets generated in parallel. The integration and workflow challenge is simpler when the clinician does not need to reformat the same information for different audiences.
David Schummers, Vice President at Apella
One hospital IT executive has an outgoing voicemail that says: “If you’re a vendor we don’t currently work with, please don’t leave a message.” That captures the state of healthcare IT today. Teams are stretched thin, and most of the integration infrastructure connecting back-office and clinical systems already works. The problem is what flows through it.
Data from procedural areas, especially, is often unreliable before it ever reaches a downstream workflow. Clinical documentation still relies on timestamps entered after the fact, sometimes hours later, and every connected system inherits those limitations. Organizations should focus less on connecting systems and more on capturing accurate data at the point of origin.
Blake Sollenberger, Strategic Services Managing Director – Revenue Cycle at Evergreen Healthcare Partners
The challenge back office stakeholders face when implementing back office systems integrated with clinical and front-end applications is that all stakeholders upstream have implemented their systems and processes tailored to their own needs and preferences, so back office stakeholders are somewhat limited to the clinical input preferences already hard-wired upstream.
Effective strategies I’ve observed that help to maximize the win-win alignment of these areas are operational in nature: more physician compensation tied to cash outcomes instead of volume, or front-end functions aligned with back office under a unified revenue cycle operation.
Isobel Handler, Senior Director of Product Management at Kontakt.io
A lot of back-office systems — staffing, supply chain, productivity, costs — hold data that is essentially incomplete without the right context. That context comes from the EHR and from understanding where resources actually are in a hospital and how they move from place to place. Health system leaders intuitively get this. They know that bringing all of these data sources together would be powerful.
The whole really is greater than the sum of the parts. Even when organizations manage to bring these data together, what they often end up with is an analysis — something that describes a problem. But describing a problem isn’t solving it.
That’s what AI agents change. They’re not just surfacing where the problems are; they’re building solutions and embedding them into the workflows of the people who can actually act. This includes dispatching a biomed technician to a unit about to run short on IV pumps before they even know they need one; making sure transport has the right wheelchair so that a patient makes it to their MRI on time; and letting a medical assistant know when and where to room their next patient, just in time for the provider to walk in. Intelligence meets the caregiver at the moment it matters.
Aditya Bansod, Co-Founder and President at Luma Health
One of the biggest challenges with healthcare IT integration is maintaining the fidelity and privacy of data as it moves to the right place. In large health systems, employees are also patients, which makes it critical to preserve privacy while ensuring a single, trusted system of record.
How do you deal with the privacy of an employee who is off-boarded after working for a few years? Do you have custom data feeds coming in and out of your healthcare stack? These are the types of questions organizations need to be asking themselves (and working to solve).
So many great insights here! Huge thank you to everyone who took the time out of their day to submit a quote to us! And thank you to all of you for taking the time out of your day to read this article! We could not do this without all of your support.
What challenges do you think organizations face when integrating back office systems with clinical and front-end applications? How do you think those challenges are being addressed? Let us know over on social media, we’d love to hear from all of you!
About Sam Peters