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By Monica E. Oss

Every meeting of health and human service managers ends up, at some point, talking about “the workforce problem”—the shortage of psychiatrists, the shortage of nurse practitioners, the shortage of direct support professionals, and the shortage of home care workers. (We’ve covered these issues recently in Staff Vacancies Just Got A Little More Important & Complicated, Workforce Shortages As A Strategy Issue, and Where Have All The Psychiatrists Gone?)

There are many reasons. Topping the list—demographics, professional choices, and the gap between reimbursement rates and compensation rates. On the demographic side of the issue, the aging population is creating a sharp increase in the demand for more direct care workers. Currently, about 50% of the population over age 65 need some form of long-term services and supports, and the population over 65 is predicted to double between now and 2050. With that growth, the Bureau of Labor Statistics predicts that we will need one million more direct care workers by 2024. Additionally, women make up about 90% of the home health and nursing assistant workforce, but the pool of women between the ages of 25 and 64 will grow by less than one percent during that time frame, creating a further gap in the available workforce (see 8 Signs the Shortage in Paid Caregivers Is Getting Worse). And we have the immigration situation—see A Picture of Foreign-Born Workers in Long-Term Services and Supports and Filling the Care Gap: Integrating Foreign-Born Nurses and Personal Care Assistants into the Field of Long-Term Services and Supports.

And the gap between reimbursement rates and compensation rates has turned into a struggle, as low reimbursement rates prevent organizations from increasing pay for much of the workforce. Rates for units of service are likely not going up and reducing wages to hire more staff is likely not possible. In 2017, the average annual wage for home health aides was $23,210, and $23,100 for personal care aides; this is up about 16% for both positions, which made $20,000 in 2010 (see Will Clinical Professional Compensation Drive Task Shifting?). Hourly, personal care aides earn an average of $10.92/hour, while home care workers earn $11.03/hour (see Home Care Workers Income $11.03 Per Hour, Up 3.5% In A Decade). Low wage rates lead to high turnover rates—one in every two direct care workers leave their job within the first 12 months of employment, with most citing low wages as the cause. Nearly 20% of home care workers do not have health insurance; about 39% rely on public health care coverage; about 19% live below the federal poverty level; and about 51% receive some sort of public assistance, including food and nutrition assistance (30%), Medicaid (30%), and receive cash assistance (3%). Unsurprisingly, turnover rates among the direct support professionals are around 45% (see High Turnover, The Other Staffing Issue).

One observation I have about the workforce issue conversations that there is rarely a discussion of how to use technology to address the issue—a strategy that is common in other fields. A recent article in The Harvard Business Review, AI Will Change Health Care Jobs for the Better, provided a framework for thinking about how to apply “smart machines” to this problem solving. The authors provided a framework for the three types of functionality that applied technologies provide to extend our staffing:

Amplifying staff—What health care staff are capable of can dramatically increase with smart technologies. I think of two types of technology in this category. First, there are the technologies that remove the need for consumers and professionals to be physically together or even communicate at the same time. For example, asynchronous “store-and-forward” diagnostic services are becoming more common, allowing recorded diagnostic interviews of consumers, consumer brain scans, and other consumer “images” to be assessed by clinical professionals at a more convenient time (see First Telehealth-Now Virtual Health). Then there is the continued adoption of augmented intelligence to assist with decisionmaking in the use of decision support tools. This does not replace professional insight, but rather provides professionals and consumers with the most recent research to inform diagnoses, treatment planning, and on-going care management.

Interacting with consumers—Another category of technologies to address the workforce issue is to leverage technology to interact with consumers, such as using technology to remind consumers to take medication or participate in physical and cognitive exercises. The recent Humana/Fitbit collaboration (Humana Expands Pact With Fitbit To Rein In Claim Cost) is just one example. And then there is technology-driven mental health therapy, a huge tech bucket that can include remote monitoring, web portals, robots, smartphones, machine learning tools, and much more. For example, Mindstrong Health uses a smartphone app to provide real-time measurement and support for consumers through messaging and telehealth from Mindstrong’s licensed provider care team (see Virtual Care Comes To Complex Consumers). Tech that uses artificial intelligence can also be equipped to recognize voice, emotion, or gestures to further improve its precision and accuracy. For example, Canary Speech is a software algorithm that analyzes speech patterns and uses machine learning to help diagnose conditions such as Alzheimer’s disease, dementia, and Parkinson’s disease.The program can be used with voice-actived devices, such as the Amazon Echo system (see Can Your Voice Reveal Whether You Have An Illness?). That isn’t the only way voice-actived “virtual assistant” devices are being used.

I’ve been surprised at the adoption of the Amazon Alexa in serving consumers with autism and consumers in need of assistance with daily living. For consumers with autism, voice commands can be used to provide consumers with autism with reminders, such as when to eat or use the restroom, and can help consumers to practice language and social skills by engaging in conversations with the virtual assistant (see Amazon Alexa Can Help People With Autism Do More On Their Own and How Amazon’s Alexa Is Helping My Son With a Disability). For older consumers in need of assistance, Alexa can be used as an extender for home health care staff by using the system to remind older consumers when to take their medication or to manage the household by turning on lights or changing the thermostat. The devices can also be used to call for help in case of an emergency or to send messages to loved ones (see How Alexa’s Best Skill Could Be As A Home Health-Care Assistant and Alexa? How Voice-First Technology Helps Older Adults).

Embodying caregivers—Another way that smart machines can assist staff is to augment their physical performance. Yes, this is robots: “physically embodied systems capable of enacting physical change in the world” or “a machine resembling a human being and able to replicate certain human movements and functions automatically”. This is the use of augmented intelligence in a physical form. The U.S. has emerging adoption of robotics in health care and personal support (other countries are further ahead).

There are robots in facilities that can transport medications, linens, and lab specimens—like Tugs by Aethon or North American RoboCourier. Or Xenex, a robot that uses high-intensity ultraviolet light to disinfect facilities. And, robots like Robotic IV Automation, or RIVA, that can automate functions in pharmacies. There are robots capable of lifting a consumer from standing position or from the floor, transferring a consumer to a wheelchair, carrying a consumer, and turning consumers in bed—like RIBA and ROBEAR. There are personal health care companions for a physical presence to assist in care management, like Mabu and Baymax (see Mabu, A Robot Helping Patients With Congestive Heart Failure, Is Working With The American Heart Association and Healthcare Robotics). And, there are companion robots—like Paro, Pepper, and Dinsow—designed to provide consumer interaction and monitoring functions.

The prospect of strategic initiatives to create hybrid human/technology service delivery systems may seem daunting. The challenge for health and human service organizations isn’t the lack of technology to augment the workforce and address some key workforce issues. The challenge is the disconnect between the developers of new technologies and the management practices of health and human service organizations. But the key is to have an overarching plan, proceed at a slow but steady pace, use metrics-based management to guide the process, and realize the plan will change with experience, new competition, and new technologies. In a field where 90%+ of operating expenses are people, creating a tech-enabled workforce is a competitive advantage. The executive team that can overcome that disconnect will be the executive team with the winning solution.

For more, on a tech-enabled workforce, see these resources in the OPEN MINDS Industry Library:

  1. Staff Vacancies Just Got A Little More Important & Complicated
  2. Developing A Value-Based Care Model With Peer Support-Two Case Studies
  3. Workforce Shortages As A Strategy Issue
  4. Will Clinical Professional Compensation Drive Task Shifting?
  5. The Innovation Conundrum
  6. Task Shifting To Bend The Cost Curve
  7. Would This List Bend The Cost Curve?
  8. Can A Virtual Assistant Make A Dent In Your Workload?
  9. The Digital Decision Crossroads
  10. First Telehealth-Now Virtual Health
  11. Addiction Treatment Innovation: New Treatment Technologies Coming Down The Pipeline

For even more, join OPEN MINDS Senior Associate Joseph P. Naughton-Travers on February 13, 2019 in Clearwater Beach, Florida for his 2019 OPEN MINDS Performance Management Institute executive seminar, “Making The Right Tech Investments For Your Organization: An Executive Seminar On Technology Budgeting & Planning.”

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