Since 1994, America has observed National Nurses Week annually from May 6-12. This year more than ever before, it’s critical that healthcare organizations go beyond recognition and start taking action to more effectively support and serve nurses. One important step in the journey to effect meaningful change is using data to inform decision-making at all levels. While there is no simple cure-all to burnout and turnover, this post will explore three key ways that harnessing the power of analytics can help transform nurse wellbeing and satisfaction.
1. Support post-pandemic healing
Working as a nurse is rarely easy, but working as a nurse during a global pandemic took the challenges and traumas to a new, nearly unfathomable level. The pandemic painfully demonstrated how truly demanding and difficult the profession is. To promote healing — mentally and physically — examine your organization’s COVID-19 patient volumes, comorbidities and mortality over the past 14+ months. These data points and trends can help you identify which service lines, shifts and specific nurses carried the heaviest burden throughout the pandemic – and therefore who may require the most support and focus in recovering.
2. Inform your staffing strategy
Determining the true acuity of patients is essential to making smart, sustainable and safe nurse staffing decisions. Data analytics can be used to analyze and draw insights from clinical codes and charts to ensure that nurse to patient ratios make sense and assignments are being managed appropriately. Ultimately, an effective staffing strategy supports nurse health and longevity, while also allowing them to provide patients with the best care and attention.
3. Encourage growth
When interpreted and applied correctly, data can be incredibly empowering. When shared without context or direction, however, data can be remarkably depressing and feel almost disciplinary. If you simply show nurses a massive dashboard of their patients’ outcomes and situations, they’ll often walk away internalizing guilt and feeling heightened burnout. Conversely, if you can do the leg work of drawing out meaningful insights from the data and facilitating related education and open discussions, nurses are more likely to feel supported and motivated. In turn, patients will have better experiences, marked by data-driven clinical decisions and actions.
At first glance, focusing on data analytics may feel like a departure from the heart of healthcare (patient care). Upon further examination, however, it’s clear that effectively collecting and analyzing data may actually be the key to keeping that heart running smoothly for years to come. Data is not just numbers; it tells stories, teaches lessons and inspires change. As George Santayana so wisely stated, “Those who cannot remember the past are condemned to repeat it.”
This Nurses Week, consider how your organization can deploy analytics solutions that strengthen and equip nurses to heal and support patients.
Get our take on industry trends
More Megatrends: Price Transparency, Telehealth, Individualized Medicine
By Scott Hampel, president of MedeAnalytics Now that we’ve dealt with Megatrends one through three, we’re approaching the next set.…
Read on...2020 Megatrends: Consumerism, Data Privacy and Security, AI
With 2020 two weeks old, it’s becoming clear the data produced in the healthcare industry by providers, consumers and payers will power and propel our 9 megatrends. Healthcare data is the foundation on which we’re building everything from healthcare outreach for the underserved to new Internet of Things-based healthcare programs to treatments designed just for you.
Read on...Why Unconventional Businesses Will Find Success in Healthcare: It’s the Data
It seems everyone is moving into healthcare. It’s a rapidly growing industry, historically dominated by large, well-embedded companies and organizations, and “pure tech” companies have had difficulty breaking in. That, however, is changing.
Read on...Data and Social Determinants of Health
By Scott Hampel – I think a lot–and I’m not the only one–about how we can improve the ways we pull information from data. Data on its own is inert: just waiting to be understood and then used. And that’s a major challenge for many organizations. Data is often trapped in different applications with no easy or convenient way to extract it.
Read on...