Healthcare organisation pursues RPA operational excellence to heal inefficiencies across revenue cycle, supply chain and more

Businesses the world over are adopting Robotic Process Automation (RPA) to lower costs, increase efficiency and improve operational quality. Some businesses have begun by implementing readily available off-the-shelf RPA technology, only to find coding a few bots is not sufficient to build a sustainable RPA programme.

Succeeding with RPA — that is, deriving the greatest value from the RPA investment — calls for a strategic approach. In most discussions of RPA, the focus is on implementation, but RPA software can be deployed with relative ease in comparison to other technologies. Succeeding with an in-house RPA programme also requires establishing a model for the programme’s ongoing operation and acquiring the skills and know-how to develop and improve the RPA programme over time. Businesses will want to consider the full operating ecosystem to ensure their RPA investment not only delivers immediate results but is sustainable and scalable over time.

Recently, a successful healthcare nonprofit circulated a request for proposals (RFP) to implement RPA to increase efficiencies in specific areas of their shared services organisation. The company identified a variety of processes spanning human resources, supply chain and other functions in advance of engaging with Protiviti. Many of the identified process opportunities were for revenue cycle improvement. Like other healthcare providers, the organisation targeted the revenue cycle for its high volume of transactions and plentiful opportunities to increase processing speed and reduce error rates. The RFP specified RPA software that the company had short-listed, and the company sought a partner to assist with technology selection and implementation, as well as with developing its first several bots.

While bots are core to automation, to achieve the desired results our client needed to consider foundational elements of the programme as a new adopter of RPA, including RPA centralised leadership and governance across Shared Services, coordination with IT Operations, integration with the primary EMR, security and data protection that is HIPAA compliant, and other key considerations post-implementation.
Tony Abel

The client found that the very first run of its new “return to provider” bot eliminated a backlog of 12,000 records. Since each of these records would have taken an individual worker 12 minutes to process, the new bot’s first run alone saved over 1,000 hours.

 

Protiviti responded with a proposal to answer each of the client’s requirements, but we also submitted a second proposal — one that outlined a more comprehensive programme that would establish a model not only for successful implementation of the desired RPA technology but would enable a high-performing RPA operating model to sustain future implementations as well.

Our alternative approach called for additional team roles, a solution architect to lead design and development of the RPA solution, and business analysts to validate and translate existing business processes into design requirements for the bots while also surfacing opportunities to improve processes as they were automated. We described a DevOps-style structure to govern ongoing bot implementations and manage changes to the automation environment. The client was quick to grasp the value of the second proposal. Stakeholders saw right away that adding skill sets and structure would result in a more robust and effective in-house RPA programme, and they embraced the expanded vision.

Focus on Short- and Long-Term Value

The RFP had specified several revenue cycle processes the organisation hoped to automate. We reviewed this list with the stakeholders to identify ideal candidates for the initial automations. Good candidates for a new RPA programme won’t necessarily be the processes in most urgent need of automation. Instead, the best early candidates are likely to be processes that offer a good return on the automation effort — typically, self-contained processes with a high manual component. The organisation focused on these early wins to prove the RPA concept to stakeholders, create encouragement and foster skill-building while returning value.

Line-item adjustments, direct data entry/return to provider and distribution of payments were among the client’s earliest revenue cycle automation opportunities. For each of these, automation would not only reduce the volume of backlogs but also diminish error rates.

Direct data entry/return to provider, for instance, bore an estimated 26,000 errors per day, many of which were attributable to rekeying of data. Automation would reduce those errors while also reducing the elapsed duration between claim submission and payment. In fact, the client found that the very first run of its new “return to provider” bot eliminated a backlog of 12,000 records. Since each of these records would have taken an individual worker 12 minutes to process, the new bot’s first run alone saved over 1,000 hours.

Ultimately, by adopting the second proposal, our client delivered valuable bots across revenue cycle, finance, information technology (IT), human resources and supply chain. The client also selected and implemented an RPA platform and built an operating environment for continued RPA programme success, with bot-generated data to track key performance indicators.

The healthcare nonprofit IT staff across five shared-services departments grew their RPA skills so that in the future, these business units could design, build, operate, maintain and govern automated processes for themselves. They learned to estimate future RPA bot development efforts and instituted RPA implementation and change management.

 

Skills Development and More

Through collaboration with Protiviti, the healthcare nonprofit IT staff across five shared-services departments grew their RPA skills so that in the future, these business units could design, build, operate, maintain and govern automated processes for themselves. They learned to estimate future RPA bot development efforts and instituted RPA implementation and change management.

While focusing on RPA’s technical aspects is critical to any effective RPA programme, technical competence is insufficient on its own. To build a sustainable in-house RPA programme, organisations must choose early candidates with care; partner with the right experts; and implement an RPA operating framework that incorporates governance structure, analytical and design thinking skill sets, continuous learning and DevOps discipline.

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