By Chad Holmes
For most healthcare payers and providers, operations are manually intensive, costly, and time-consuming. Governing the pace of decision-making and processing improvements are challenges such as:
Compounding these challenges, the consumerization of healthcare is accelerating at a rapid pace, fueled by new entrants and increasing customer choices and expectations. Healthcare consumerization calls for better information and transparency, which significantly impact operations. This need for increased transparency has even resulted in Congress passing new legislation: the No Surprises Act, which took effect in January 2022, helps protect Americans from surprise medical bills.
With more healthcare options available than ever before, many consumers are abandoning traditional health insurance companies in favor of newer plans and insurance alternatives. According to a 1,000-person national study by Forbes, consumers are increasingly shopping online for healthcare services, particularly when choosing healthcare providers.
Furthermore, operations leaders are being asked to aggressively retire technical debt and improve operating margins—akin to the well-known analogy of changing an airplane’s engine while in flight. It’s a daunting endeavor, to say the least.
Fortunately, technology advancements are paving the way for a new paradigm of intelligent operations, where operating models have be reimagined to be more:
To truly transform the healthcare industry to be more cost-effective and member experience-driven, organizations must place a proper focus on operations. 86% of mistakes made in the healthcare industry are administrative. Worse, preventable medical errors persist as the #3 killer in the U.S.—third only to heart disease and cancer—claiming the lives of some 400,000 people each year.
Healthcare operations and member care can be vastly improved, if not reinvented, through advanced technologies including data lakes, data sharing, predictive analytics, DevOps automation, intelligent process automation (IPA), IoT-enabled telemetry and biometrics, and cloud-based modernized platforms.
Let’s discuss the applicability of each of these advancing technologies and then circle back on the multiplier effect enabled by an intentional, orchestrated combination.
First, by implementing cloud-based data lakes, organizations can securely aggregate, enrich, and validate data of all types - structured, unstructured, and streaming - for reporting and analysis. In turn, that comprehensive, accurate, and timely data supports real-time decision-making. With this high-integrity data as a foundation, artificial intelligence (AI) and machine learning (ML) can be applied to foster:
Using analytics tools to monitor the supply chain and make proactive, data-driven decisions about spending could save hospitals almost $10 million per year.
High-integrity data, cloud-based platforms, robotic process automation (RPA), and AI/ML are key components for intelligent automation at scale. Intelligent automation massively reduces menial tasks by employees, allowing them to focus on high-value, member- or partner-facing activities. I like to refer to AI in this context as “augmented intelligence” rather than artificial intelligence, where machines are working in conjunction with humans, not replacing them.
There are also numerous AI-powered solutions that orgs can layer on top of legacy systems like Epic or Facets to delivery immediate, exponential improvements.
Examples of intelligent process automation (IPA) in healthcare that go beyond chatbots include:
IPA can help healthcare organizations improve care delivery and patient experience while reducing operational costs (reaching up to 34.2% of all US healthcare expenditures). Furthermore, 64% of medical professionals surveyed say connected devices will make their lives easier and increase their productivity and earnings through workflow automation.
In addition to lowering operational costs, investments in intelligence also make remote work more sustainable, collaborative, and secure. That leads to higher job satisfaction and lowers attrition, saving staffing costs as well. It is also worth noting that automation can help ensure business continuity given the trending labor shortages.
Once data is aggregated and optimized, in addition to realizing the benefits of real-time decision making and predictive analytics, select data can also be mastered to be interoperable. The Fast Healthcare Interoperability Resource (FHIR) has quickly become the most popular protocol for joining together disparate data elements. Being able to securely share data with ecosystem partners in a seamless, secure, on-demand manner accelerates operations and member outcome improvements.
Here are a couple ways that will shake out:
1. Technology can humanize care. AI can identify members at risk for a wide range of serious health conditions. Machine learning can facilitate a more coordinated, proactive approach to care that addresses potential trouble spots before they escalate into something more serious or chronic.
2. AI can improve Fraud, Waste, and Abuse (FWA) detection by up to 10x. When applied in FWA environments, AI automates analysis of dynamic data, behaviors, and patterns to identify and stop suspect payments before they go out the door. This also drastically speeds up audit and recovery efforts.
3. Zero trust computing makes the magic happen. Confidential computing technology can be applied to interoperable data to enable multiparty data analytics and ML that combines datasets while keeping data and algorithms completely private. This emerging ability enables organizations to unlock new, collaborative use cases that may even lead to a cure for cancer.
Learn more about how to transform member experience through connected, confidential collaboration in this Launch brief.
While 92% of healthcare providers promote digitization efforts, and 56% of companies indicate they are prioritizing digital transformation, many think incrementally instead of disruptively. Technologies such as AI, ML, telemetry, and RPA are simply tools. Clear business and operations strategies are needed to harness the business value those tools can create. Companies often lack an integrated strategy and technology roadmap that will capture the multiplier effect of positive impact for members, employees, and the bottom line.
Here’s an example: One of Launch’s healthcare clients reduced their claims payment processing time by >90% through the combined use of a modern cloud-based platform, improved data integrity and analytics, event-driven integration, and workflow automation. An intentional and orchestrated approach to deploying these technologies enabled operational excellence comprised of:
Intelligent operations create intelligent organizations, ready to transform and meet whatever market demand comes next. Investing in an integrated data and tech strategy for operations sets the stage for both immediate impact and long-term sustainability, both for processes and for people.
Bottom line: It is absolutely possible to “change the engine while in flight”. Moving to intelligent operating models that reduce costs by a third or more, while improving the member and employee experiences, is what will enable all future initiatives to land smoothly.
Chad Holmes is a Senior Managing Partner with Launch Consulting and leads Launch’s Healthcare Sector. His focus areas include Human Experience design, data transformation, intelligent operations, and transformational change leadership.