How Automation is Transforming Healthcare & Its Lifesaving Potential

According to Council for Affordable Quality Healthcare (CAQH), the United States spends more on healthcare administration than any other developed nation due to legacy systems, health plan complexity, the number of providers involved, government regulations and inefficient processes. With respect to hospital spending in particular, the largest source of waste is

administrative costs, which account for 25% (1,2). This should come as no surprise given that even small/regional hospitals can have 29 or more different electronic systems that house patient information. Furthermore, transaction volume continues to grow rapidly, with a 17% increase over the last three years (1).

While a large majority of health companies had not used automation in the past, COVID spawned an immediate transformation in the healthcare industry: Bain & Company Research found that a vast majority (81%) of healthcare companies have used automation in response to COVID (15). Furthermore, a quarter of hospital leaders are now looking to invest in Robotic Process Automation (RPA), with half planning to do so by 2021(3, 14). Gartner predicts that, by 2023, half of healthcare companies will invest in RPA(14).

Where are they investing? Where should they be investing?

Six Key Areas of Process Opportunity in Healthcare

McKinsey & Company analyzed 2,000 work activities for more than 800 occupations, quantifying the amount of time spent and feasibility of automation, and found that Healthcare was among the top industries that could be transformed: they estimated that up to 36% of healthcare could be automated with attended robots(4).

Six domains of waste were identified by the Institute of Medicine and quantified in 2019 dollars, as noted below (5). For each domain, we have provided examples of where RPA has actually been used.

cost of healthcare2

 

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10101809375411Administrative Complexity

This category represents the greatest source of waste and includes billing and coding costs and administrative burdens of insurance. The CAQH index collects detailed information about how administrative transactions are handled, how many are conducted and the cost and time to process each transaction. Prior authorization is the costliest and most time consuming transaction to conduct manually, and the 2019 CAQH Index found that the largest automation-related savings came from eligibility and benefit verification. Providers alone can save $10.92 per transaction by automating prior authorization and $5.30 for benefit verification. Here are actual use cases for RPA in this category:

  • Claims Management - bots can be used to collect data from disparate systems required for claims processing. Highmark Health was able to automate claims processing in 4 days, enabling them to process 12,000 new claims each day(8).  A large European hospital was able to reduce claims processing costs by 75%, from $4 per claim to $1(7).

  • Data Integrity - The Family Medical Center of Kentucky deployed a robot which executed an error-free transfer of 30 years of patient data (64,000 records) from one hospital system to another in 24 hours (9).

  • Patient Onboarding - The Cleveland Clinic deployed attended robots to add new patients, accurately record their data and report it to the CDC, saving 8-9 minutes per patient and completely eliminating data transcription errors(15).

  • Insurance Authorization - Bon Secours Mercy Health in Cincinnati used RPA to check payer sites for authorization requirements and status, reducing manually processed accounts by 20% (18).

  • Medical Billing - Bots were used by New York Presbyterian to scan through bills and records about patient encounters to ensure pricing accuracy and speed bill payment and claims follow up (17).

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101018093754Pricing Failure

This category represents the second largest category of waste and includes pricing variability due to complexity, lack of standards-based pricing or lack of cost transparency. Several examples here tend to fall under Inventory Management:

  • Hospital utilization is typically 32-38%, which drives waste and increases costs (particularly for items that expire). Furthermore, unused inventory means that the hospital is not generating revenue on those assets. A 2,000 employee hospital in the UK reduced supply chain costs by using a bot to pull the data necessary to set optimal inventory levels (7).
  • Ascension Health used RPA to update purchase orders and redirect supplies for its 150 hospitals across 2,500 locations based on service demand (8).
  • A hospital system balanced supply and demand to optimize a 10x surge in personal protective equipment orders(16).
  • A major Canadian hospital used bots to deal with supply shortages and address purchase backlogs, rapidly generate accurate inventory totals and deliver medical supplies to the correct storeroom in a timely manner(20).
Coordinate Care
Failure to Deliver Care / Failure to Coordinate Care

Failure to deliver care occurs when care is inefficient or more costly than it should be. Examples of failure to coordinate care include unnecessary ER visits and readmission, and actual use cases are below:

  • Augment Nursing Coverage - with a looming shortage of 510,394 nurses by 2030, finding qualified nurses and maximizing time on patient care will become increasingly critical given that an appropriate patient load directly impacts mortality and readmission rates (12). Mater Misericordiae University Hospital in Dublin saved nurses three hours per day by using bots to login to the hosptial's laboratory system, select correct disease codes and input the test result. This drove more rapid response in the case of infected patients, and increased the time medical personnel could spend on patients (15). All American Healthcare uses RPA to rapidly find the right nurses with the right skills in the geographic location of need (19).
  • Rapid Identification of At-Risk Patients - Yale New Haven Hospital uses data EMR (electronic medical record) data to send mobile alerts about patient deterioration to nursing swat teams (13).
  • Patient Oxygen Monitoring - Northampton General Hospital used bots to monitor oxygen levels, collecting data and measuring flow rates 24x7, without intervention (20)
Overtreatment
Overtreatment/Low Value Care

This category includes overuse of low value/ineffective treatments and testing or overtreatment.

  • Accelerating Diagnoses & Care - Providence St. Joseph in Washington state uses a chatbot named Grace to ask for symptoms up front, and suggests appropriate next steps (e.g., Urgent Care vs. ER) with 90% accuracy (10).
10101809375413Fraud and Abuse

Medical identity theft occurs when an individual is impersonated and gets incorrect bills for medical services, drugs or care. The incidence of medical fraud doubled between 2010 and 2015

  • Payment Integrity - a healthcare payor uses a bot to compare data across Claims Evaluation, Processing, Assignments and Reporting to flag fraudulent claims.
 
 
Conclusion

While Healthcare has been lagging in the adoption of Robotic Process Automation, they are quickly becoming a leader given COVID and across-the-board pressure from boards, management, regulators and customers to slash costs. As Healthcare gets more efficient, resources can be redeployed from administrative activities to  treatment-focused activities that will improve patient outcomes and ultimately save lives.

 

Be sure to review our other use-case focused blogs:

 
References
  1. CAQH, 2019 CAQH Index - Conducting Electronic Business Transactions: Why Greater Harmonization Across the Industry is Needed," 2020, https://www.caqh.org/sites/default/files/explorations/index/report/2019-caqh-index.pdf?token=SP6YxT4u.
  2. Austin Frakt, “The Astonishingly High Administrative Costs of U.S. Health Care,” The New York Times, July 16, 2019, https://www.nytimes.com/2018/07/16/upshot/costs-health-care-us.html.
  3. Heather Landi. "Healthcare Has a Lot of Tedious, Repetitive Tasks. This CEO is Using AI to Fix That," September 26, 2019, https://www.fiercehealthcare.com/tech/yale-new-haven-centura-health-working-ai-company-olive-to-tackle-administrative-burdens.
  4. Chui, Michael; Manyia, James; and Miremadi, Mehdi. "Where Machines Could Replace Humans-and Where They Can't (yet)," McKinsey Digital, July 8, 2016, https://www.mckinsey.com/business-functions/mckinsey-digital/our-insights/where-machines-could-replace-humans-and-where-they-cant-yet.
  5. William H. Shrank, MD, MSHS; Teresa L. Rogstad, MPH; and Natasha Parekh, MD, MS, “Waste in the US Health Care System: Estimated Costs and Potential for Savings,” JAMA. 2019;322(15):1501–1509. doi:https://doi.org/10.1001/jama.2019.13978.
  6. Guiding Metrics, "The Hospital Industry's 10 Most Critical Metrics," https://guidingmetrics.com/content/hospital-industrys-10-most-critical-metrics/.
  7. UI Path. "Cure Healthcare Inefficiencies with RPA," 2020, https://www.uipath.com/solutions/industry/healthcare-automation .
  8. Blue Prism. "How Automation is Helping Companies Pivot in the Pandemic," September 16, 2020, https://venturebeat.com/2020/09/16/how-automation-is-helping-companies-pivot-in-the-pandemic-vb-live/.
  9. Automation Anywhere. "RPA in Healthcare," 2020, https://www.automationanywhere.com/solutions/healthcare.
  10. Heather Landi. "HIMSS19 Roundup-New AI Tools to Address Physician Burnout," Feb. 12, 2019, https://www.fiercehealthcare.com/tech/himss19-roundup.
  11. Automate. "Robotic Process Automation Case Study: Automate Integrates Critical Applications for a Major Medical center," https://www.helpsystems.com/customer-stories/automate-integrates-critical-applications.
  12. American Association of Colleges of Nursing. "Nursing Shortage," September 2020, https://www.aacnnursing.org/Portals/42/News/Factsheets/Nursing-Shortage-Factsheet.pdf.
  13. Nancy Robert. "How Artificial Intelligence is Changing Nursing," September 2019, https://journals.lww.com/nursingmanagement/Fulltext/2019/09000/How_artificial_intelligence_is_changing_nursing.8.aspx.
  14. Gartner. "Gartner Says 50% of US Healthcare Providers Will Invest in RPA in the Next Three Years," May 21, 2020, https://www.gartner.com/en/newsroom/press-releases/2020-05-21-gartner-says-50-percent-of-us-healthcare-providers-will-invest-in-rpa-in-the-next-three-years.
  15. Daniel Pullen. "Robotic Process Automation in Healthcare," Hospital Healthcare, September 14, 2020, https://www.hospitalhealth.com.au/content/technology/article/robotic-process-automation-in-health-care-292738552#axzz6ZNOhVPxL.
  16. Hernan Saenx, Nate Anderson, Dianne Ledingham and Michelle Supko. "The 'New Normal' Is A Myth. The Future Won't Be Normal At All," June 5, 2020, https://www.bain.com/insights/the-new-normal-is-a-myth-the-future-wont-be-normal-at-all/.
  17. Laura Dyrda. "Telemedicine, AI and Robotic Process Automation: How New York Presbyterian is Equalizing Access to Care," Becker's Health IT, May 30, 2019, https://www.beckershospitalreview.com/healthcare-information-technology/telemedicine-ai-and-robotic-process-automation-how-newyork-presbyterian-is-equalizing-access-to-care.html.
  18. Laura Dyrda. "8 Finance Execs Reply: What Revenue Cycle Change Worked?" Becker's Health IT, July 20, 2020,https://www.beckershospitalreview.com/finance/7-finance-execs-reply-what-revenue-cycle-change-worked.html.
  19. All American Healthcare. "How Technology is Transforming Staffing for Nursing Homes," https://www.aahcs.com/how-technology-is-transforming-staffing-for-nursing-homes/.
  20. Team International. "How RPA Proved Its Value During the Covid-19 Times and What's Next," July 31, 2020, https://www.teaminternational.com/rpa-value-during-the-covid-19-times/.
  21. Alexa Cushman. "The Top Health Care and Life Sciences Digital Trends for 2020," Appian, December 17, 2019, https://www.appian.com/blog/the-top-healthcare-life-sciences-digital-trends-for-2020/.