Cognitive systems can help reduce healthcare worker burnout
I recently came across an article titled: “One in 10 social workers ‘would quit’ over stress.” I’ve been working in the human services field for my entire 30+ year career, so the title didn’t really surprise me.
It turns out that the job of social worker consistently ranks as one of the most stressful jobs; right up there with enlisted military personnel, fire fighter, police officer and airline pilot. In the UK, it’s ranked the #3 most stressful job. In the US, #9. In Australia #5.
Stress among caseworkers appears to be a worldwide phenomenon. The cause(s) seem to be universal. And while low salaries do play a role, it’s not a major role. Nobody, after all, goes into social work to get rich. Nor do they go into social work to do paper work, write reports, or spend hours in their car commuting from the field to their office. But they do go into social work to make a difference in people’s lives. Fortunately, cognitive systems can help reduce the workload and accompanying stress, and allow caseworkers to spend more time doing the work that is important to them.
When interviewed, caseworkers describe workloads that never allow them to get caught up. A survey of social workers in Taiwan found that excessive caseloads caused a range of health problems including insomnia and anxiety among respondents. Turnover among social workers in the US has been reported as being as high as 90% per year (It’s more commonly reported to be around 40%) with heavy workloads and paperwork identified as contributing factors. The average tenure for these workers is less than two years according to a report from the US General Accounting Office.
There is naturally a price to pay for this trend. By one estimate, it costs about $20,000 to train a new caseworker. But that’s only the monetary cost. Turnover can impact the timeliness of child protective investigations, the quality and amount of contact that a worker spends with clients, and the overall safety and well-being of a child.
One study found that a child in the child welfare system with only one caseworker over the course of a year had a 74% chance of permanency. That rate dropped to 17% when the child had two caseworkers. Three caseworkers dropped the rate of achieving permanency to 5%.
A recent study by Frost & Sullivan, Making the Leap in Outcomes, Efficiency, and Client and Employee Satisfaction in Social Programs: Leveraging cognitive tools and best practices, suggested that governments are starting to explore new ways of enhancing job satisfaction among social program staff while at the same time driving better outcomes for clients. And they’re looking at data analytics and cognitive computing technology as a means for achieving these goals.
Cognitive systems, like IBM Watson, are self-learning systems that use data mining, pattern recognition and natural language processing to mimic the way the human brain works. They are already transforming an array of industries ranging from finance, to law, healthcare, transportation, to drug research.
These systems are also beginning to play a role in social programs and are helping to meet the need for data-driven, evidence-based decision making. But it’s a limited role. And that’s why, according to Frost & Sullivan, health and human services leaders need to be more assertive in implementing cognitive systems to help drive program and staff success.
To learn more about the cognitive systems awareness gap in health and human services programs, read the Frost & Sullivan report: : Making the Leap in Outcomes, Efficiency, and Client and Employee Satisfaction in Social Programs: Leveraging cognitive tools and best practices.
To learn more about Watson and how Watson Health solutions can help health and human services organizations focus more on what’s most important: connecting citizens with the support and programs they need, check out the Watson Health Social Program Management web page.
A longer version of this blog appeared first at IBM’s Watson Health Perspectives.