Did you only begin to value healthcare employees during the COVID-19 pandemic?
That same pandemic has caused many of them, especially nurses, to rethink their careers. According to a May 11 McKinsey report, the United States could see a shortfall of 200,000 to 450,000 registered nurses available for direct patient care by 2025.
Healthcare managers are facing a future crisis as many of their nurses and other healthcare staff have been quietly resigning, or are considering it.
Healthcare HR, therefore, needs more meaningful ways to recruit and retain its people.
Using people analytics to gather information on employee sentiment is just one way, among many others, to pay more attention.
Data analytics versus people analytics
Data analytics is the science of collecting, managing, and analyzing raw data to discover insights for informed decision-making.
It is a massive game-changer in healthcare, enabling analysts to more easily organize and study data to identify trends, correlations, and patterns that help solve problems and inform better healthcare decisions.
In the past, medical systems used data analytics to deliver better patient service, save on costs, and improve systemic efficiency. For example, standard data analytics for hospital cost-saving goals include average hospital stay, patient drug cost per stay, bed turnover, and medical equipment use.
People analytics is a subset of data analytics. People analytics happens when you collect and analyze employee data to improve your workforce and business outcomes.
Familiar people analytics metrics include data on hours worked, salary competitiveness, earnings per employee, employee engagement, and employee attrition.
Healthcare burnout and high turnover
People analytics in healthcare can help you understand reasons for the high job burnout rates in the sector. The burnout rate became much worse with the COVID-19 pandemic as hospital employees struggled to cope with excessive workloads, insufficient supplies, and emotional grief at patient deaths.
Science journalist Ed Yong chronicled the pandemic overwork and incremental exodus of healthcare workers in “Hospitals are in serious trouble”, an extension of his Pulitzer Prize-winning series on the impact of the pandemic.
Healthcare jobs that have been hardest hit include registered nurses, medical assistants, lab tech positions, and some physicians.
Skilled medical workers are arguably the most important resource in healthcare systems—above and beyond any building or diagnostic machine you can buy. So, applying people analytics to better understand this skilled workforce should be an ongoing HR priority.
How can you use people analytics in healthcare?
People analytics can help healthcare managers strategically plan or restructure workforce requirements based on the data.
You can use people analytics in medical and healthcare environments to
- help recruit skilled employees to deliver quality service to patients,
- better understand and retain talent to ensure a reliable service,
- inform people-related workflow efficiencies, such as reducing patient wait times through better scheduling and staffing, and
- enable speedy, optimal deployment of relevant healthcare teams in emergency situations such as pandemics, mass shootings, fires, accidents, or natural disasters.
Your people analytics goals will help inform your integration strategies
Effective people analytics depends on first articulating clear goals for the analytics. Your analytics goal (or goals) should align with your healthcare organization’s overall goals.
So, let’s consider two common HR goals in healthcare.
ANALYTICS GOAL: Recruit and retain good staff
Staff shortages in hospitals imply decreased quality of care as fewer employees are caring for more patients. To remedy this, hiring new staff and retention of existing workers should be priorities. Also, you may choose to use more automation, so less staff can do more with existing resources.
People analytics data on recruitment, retention, and turnover will help give you the baseline data you need to understand your current situation.
Delivering such metrics may involve connecting your recruitment, HR, and talent systems to allow data to flow between them as needed.
To improve the recruitment process, you need to collect consolidated recruitment data for analytics.
So, your data integration strategy may involve integrating your applicant tracking system, candidate management system, video interviewing system, and HR Information System.
Integrating some or all of these systems will improve candidates’ experiences as they’ll be able to use a single login procedure. The integrated system will also quietly store all candidate information, including any assessment tests, for your future use—for instance, in comparing initial assessment tests with later performance after a candidate is hired.
Meanwhile, to boost retention, useful people analytics might include
- data on compensation and benefits in relation to skills—to help answer questions such as:
- Are some healthcare employees being badly or unfairly paid?
- Do men earn more than women for the same job?
- Are the salaries for nurses or doctors below the industry norm, driving them to seek better opportunities elsewhere?
- data on people’s training and development progress—to help track professional progress, career aspirations, and promotional potential
- data on people’s level of engagement at work tasks—to help identify problems or challenges and resolve them.
The integration strategy to enable this may involve connecting on-premise or cloud-based payroll, compensation, and learning systems.
You may also integrate an employee engagement system that links a performance management system with recognition programs, feedback surveys, coaching and mentorship programs, and other tools to help build a supportive, positive company culture.
ANALYTICS GOAL: Control people-related costs
You can use people analytics to help inform decisions on healthcare workforce costs.
For example, one healthcare organization had a tricky problem. It needed to manage hospital costs by reducing the number of nurses at a hospital with a declining patient count. However, a union agreement meant the last hired would be the first out, making new nurses the target for dismissals.
HR analytics helped the organization realize the new nurses were more expensive to hire and harder to retain. Further workforce analysis revealed this hospital’s location had four times more employees eligible to retire than other hospitals.
Instead of letting new nurses go at a cost of $1.5 million, the organization promoted early retirement and let natural attrition take place. This helped them save $400,000.
In a situation like this case study, the integration strategy might have involved connecting payroll, skills databases, and patient database records, in addition, possibly, to a performance evaluation system to assess which of the categories of nurses were of the most value in terms of work ethic and professional contribution.
Data on salaries, job descriptions, seniority, retention, and patient numbers would also have informed the analysis.
Building a data-informed healthcare culture with useful people analytics depends on first defining clear goals the employee metrics seek to explore or illuminate.
People analytics data can help you recruit better quality people faster, use your healthcare employees more efficiently, understand your workforce better, save costs, boost employee experience and retention, and better deploy people in a health crisis.
If you are interested in healthcare data integration, you may be interested in reading our blog: 7 Tips for Success in Healthcare Data Integration.
Pixentia is a full-service technology company dedicated to helping clients solve business problems, improve the capability of their people, and achieve better results.