Automation is one of the biggest buzzwords in business and IT today, and for good reason. As we move into the era of Industry 4.0, big data, Artificial Intelligence (AI), and the Internet of Things (IoT) are enabling advancements that were unimaginable in years past. However, while manufacturing and technology progress at breakneck speeds, many healthcare processes that are seemingly prime candidates for automation continue to be done manually.
This isn’t because healthcare decision makers are averse to change or unaware of the possibilities, but rather because healthcare is a unique industry with a unique set of challenges. There are regulations and requirements healthcare organizations must navigate that other industries never have to think about. Many of the inner workings of IT systems in a healthcare organization are inherently different than “standard” IT infrastructures. All this comes together to add layers of complexity and make the integrations that could enable automation in healthcare difficult to achieve, despite the fact healthcare organizations are full of mundane, repetitive, data-entry intensive work processes that are prime automation candidates.
In this piece, we’ll review the main drivers of complexity limiting healthcare integrations, explain how Olive is unique in that it was built specifically to help automate healthcare work processes, and review some of the benefits of implementing intelligent automation in healthcare.
Drivers of healthcare integration complexity
As anyone in the industry will tell you, healthcare is complicated. The healthcare industry is different from other industries for a number of reasons. At a high level, two of the biggest drivers of complexity of healthcare system software: data integration challenges and unique security and compliance requirements. Here we will discuss those in more detail and dive into why this is the case.
Data integration challenges
One of the main problems with healthcare is the lack of standardization and consistency between EMR systems. For example, across different systems there can be different ways to do something as simple as identify a patient. This is because EMR systems were built with the intent to be secure and reliable, but interoperability was an afterthought.
This has lead to a scenario where a significant amount of human time and effort is spent manually moving data from one system to another. Where automation is possible, it is often based on APIs (Application Programming Interfaces) or HL7 (Health Level 7) streams that are difficult to integrate and often lack all the information needed to complete a given work process. In addition to HL7, some of the other standards, formats, and databases those working with healthcare data “in the wild” may encounter include:
- FHIR (Fast Healthcare Interoperability Resources)
- NCPDP (National Council for Prescription Drug Programs) SCRIPT
- ICD (International Classification of Diseases)-9&10
- LONIC (Logical Observation Identifiers Names and Codes)
- NPI (National Provider Identifier)
- SNOMED CT (Systematized Nomenclature of Medicine — Clinical Terms)
..and more. As you can imagine, this makes getting data from point A to point B problematic without compromising the integrity of the data a daunting task. For this reason, processes like eligibility checks, claims processing, and other data-entry heavy tasks that would seem prime candidates for automation in other verticals, are labor intensive tasks in the healthcare sector. While each of these formats serves a purpose and has some upside on its own, often being created to improve standardization, solve problems with older standards, or meet new requirements; taken as a whole they aren’t always conducive to interoperability. The end result of a myriad of well-intentioned standards is a number of different systems within a healthcare facility using different standards. This leads to difficulties tying everything together costs a significant amount of time and resources.
Just how bad is the problem is the data integration problem? To try and quantify the scope, consider that HealthData Management reported that data integration issues cost health and human services agencies $342 billion.
Drilling down further, let’s consider what seems to be a very preventable problem that has cost the industry billions: denials. Denials cost hospitals and health systems over $262 billion annually, and over 60% of these denials are related to missing information. This statistic is at least in part symptomatic of the consequences of tasking people with transferring data across multiple, discrete systems. Human error and oversights are bound to occur. There are too many potential points of failure in today’s EMR systems and data entry work processes.
Security & compliance concerns
While information security is vital in all industries, the healthcare market is unique and this contributes to the complexity of healthcare organizations. In most cases, working in the healthcare sector in the United States inherently requires working with PHI (Protected Health Information) and being subject to regulations like HIPAA (Health Insurance Portability and Accountability Act). This means data handled on networks within hospitals and clinics become subject to much more stringent security and handling requirements. As anyone who has ever worked in IT can tell you, adding security also comes with added complexity.
In the world of healthcare IT, administrators must ensure that their handling of electronic PHI is complaint. This means partnering only with compliant vendors, accounting for encryption of data at rest and in transit, using only improve encryption methods, and much more. Given the extremely high costs of falling out of compliance, healthcare organizations must prioritize security and staying within regulatory guidelines. Often this means what may help streamline a process in another industry is a non-starter in the world of healthcare. This further exacerbates the challenges associated with healthcare integrations and often puts true automation out of reach.
How artificial intelligence can address healthcare complexity
Consistent with the same concepts that are driving the popularity of Industry 4.0, AI and automation in healthcare administration can lead to industry-changing improvements. However, in order to be able to achieve the benefits, healthcare organizations must first identify tools that can meet the unique demands of the sector.
The importance of a solution purpose-built for the healthcare sector
In simple terms: a standard intelligent automation solution can’t meet all the challenges of the healthcare market without significant modifications, and significant modifications mean complexity, which is what we’re trying to minimize in the first place. Further, even when modified, using a standard automation solution in the healthcare sector is simply using the wrong tool for the job.
Olive was built to fill this market need and designed specifically for healthcare. For example, Olive is able to “check all the boxes” when it comes to healthcare related security and compliance in the U.S., supporting features and functionalities such as:
- AES256 encryption
- Amazon AWS HIPAA complaint services
- Up to date ciphers
- NIST 800-53
- Encryption of data at rest and in transit
- Multifactor Authentication
- Shamir’s Secret Sharing
- Record Level Access Logs
What is most impressive about how Olive addresses the complexity challenges of healthcare integrations is how she abstracts away complexity. As opposed to forcing dependence on incomplete or non-existent APIs and HL7 streams, Olive works in a manner similar to a human employee, leveraging User Interfaces (UIs) to capture data and streamline workflows. This opens up a world of possibilities for integrating multiple disjointed EHR systems throughout a healthcare facility. With a purpose-built automation solution, what was once prohibitively complex in healthcare becomes easily achievable.
The benefits of artificial intelligence and automation to healthcare
Now that we know automation in healthcare is possible using a purpose-built solution like Olive, the obvious question is: is it beneficial? The answer is a resounding yes. Qualitatively this is because, as mentioned previously, the healthcare sector is full of work processes that are repetitive and heavy on data-entry; prime candidates for automation. Shifting these workloads away from humans and to software enables organizations to optimize healthcare administration and improve the bottom line.
To give just a few real-world examples of the benefits of automation in healthcare, consider the case studies of Heart of Ohio Family Health Centers (PDF) and Hancock Regional Hospital (PDF). By leveraging the power of OliveAI, the former was able to save automate eligibility checks for an average of 90% of daily and save over 200% of the original cost of a workflow offloaded to Olive. The latter was able to eliminate denials for no-coverage from Anthem, Medicaid, and Medicare as well as reduce their days in accounts receivable by 34%. For more micro and macro level statistics related to the power of automation in healthcare, check out this infographic.
Conclusion: Olive can help resolve the challenges of HC integrations & abstract away complexity
As we have seen, the healthcare integrations are uniquely complex and come with a set of challenges other industries don’t have to worry about. What this means is that, while healthcare organizations can reap the benefits of intelligent automation, they must be careful to only use solutions designed to meet the challenges of healthcare. Olive is a holistic process automation solution built from the ground up for healthcare. This means that by making Olive their next “employee”, healthcare businesses can rest assured that they are using the right tool for the job. By using paradigm-shifting technologies like machine learning, AI, computer vision, and RPA, Olive can abstract away the complexities of healthcare and make operations faster and more economical.
If you’re interested in learning more, we’re here to help! At Olive, we are dedicated to building world-class automated intelligence solutions specifically designed to solve the challenges facing the healthcare industry. If you have questions about how A.I. can help drive your healthcare business forward, please contact us today to work with our team of automation experts.