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How Analytics Is Changing Nursing

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Whether they realize it or not, nurses play a critical role in the rise of health care Big Data. And we’re not just talking about those who specialize in data organization and analytics: even nurses who never open a spreadsheet are integral to this modernizing trend. When nurses administer a screening interview, measure blood pressure and temperature, and record lab results — the sort of information-gathering activities that claim about 25% of daily nursing practice, according to the American Medical Informatics Association — they engage with data science and its ever-growing impact.

As frontline health care professionals who typically spend even more time with patients than physicians do, nurses are well-positioned to leverage the vast amounts of health care information generated by EHR systems and related technologies. Some nurses spend more time aggregating, tracking, and examining Big Data to enhance clinical care and the patient experience. These nurses often have advanced credentials, such as University of Michigan School of Nursing’s Online MSN in Leadership, Analytics, and Innovation.

An analytics-focused master’s degree program like the one offered at the University of Michigan trains nurses to apply analytics and related technologies as clinical practitioners, department managers, and educators. Those are already valuable skills in today’s health care job market, and they will likely become more so as the role of data in health care delivery and management continues to expand. They enable nursing candidates to stand out because data facility is not considered a core nursing skill — yet. Nurses who know their way around computers and databases may enjoy a competitive edge. In the future, proficiency in technologies such as predictive analytics may be expected of all nurses. After all, these advances have already proven that they can make care delivery more efficient, more effective, and less expensive.

Analytics in nursing improves workflows, reduces burnout, increases productivity, and enhances clinical decision-making. It may even improve patient outcomes, though research suggests there’s not yet enough data to back up that claim. Nurses with advanced analytics and informatics skills may well be the health care professionals to lead the way toward a data-driven health care future in which data analytics improves diagnostics, catches errors, and suggests money-saving efficiencies. Predicting the future of Big Data in nursing is difficult because technology evolves so rapidly. Still, we can learn a lot about where medicine is headed by looking at how analytics is changing nursing today.

What Analytics in Nursing Looks Like

Although computing and massive data sets are relatively new additions to the health care repertoire, the application of information to nursing is hardly novel. The practice dates back to at least the 1800s, when pioneering nurse and statistician, Florence Nightingale, recognized the power of data in medicine. During the Crimean War, Nightingale developed data collection and analysis methods to determine which techniques were effective and which might actually produce deleterious results. Gathering datasets on note cards, Nightingale conducted a study to assess the impact of sanitation practices on hospital outcomes.

Today, nurses work across all health care disciplines. They constitute the largest segment of the U.S. health care workforce, representing 30% of hospital employees and approximately one-third of all health care practitioners and technicians. Their ubiquity means that the many digital systems incorporated into their daily routines could shape everything from the patient experience to population health research.

The steady and thorough stream of health care data enables health care systems to analyze provider-patient interactions, making it easier for nurses to:

  • Coordinate care more efficiently
  • Create data-driven standards of nursing care
  • Evaluate a more extensive set of available care options
  • Identify patients at risk of readmission
  • Monitor patient status in real time
  • Optimize staffing to balance workloads

Analytics are already improving nursing in the following ways:


AMN Healthcare reports that analytics can help nurse managers forecast patient demand, allowing them to schedule sufficient staff. At a time of significant staffing shortages around the U.S., this capability is critical. Data-driven scheduling also helps managers track workloads to prevent nursing burnout, a concerning program that affects about 43% of nurses in hospitals and 37% of nurses in nursing homes. Big Data and informatics help nurse leaders manage their workforce effectively and compassionately in these and other ways.

Optimizing Workflows

Analytics are ideally suited to enhancing workflows. According to Intel, “Care delivery management applications offer fundamental advantages for improving the quality of care while enhancing productivity.” They enable providers to “streamline primary and specialty care workflows, including clinical documentation, quality reporting, analytics, and surveillance.” Nurses can even tap into the power of data when caring for patients to determine the best course of treatment more quickly. At the macro level, workflow data can drive policies and inform state and federal regulations and legislation related to working hours and patient load.

Reducing Costs

Health care analysts can plumb data to discover operational inefficiencies that slow patient flow, increase waste, and add unnecessary procedures and costs. Multiple studies indicate that the U.S. health care system incurs between $760 billion to $935 billion in waste each year. That’s approximately 25% of all health care spending in the country. A Mercy Hospital Network case study found that applying analytics to staffing optimization produced a $4.3 million reduction in costs. It also increased nurse satisfaction rates and reduced staff turnover.

Improving Patient Care

Data provides the foundation for personalized medicine/precision medicine and therapeutic decision support, which utilizes data’s predictive power to bolster preventative care. That’s just one of the many ways data can make patient care more precise and effective. Data in EHR systems can prevent medical and pharmaceutical errors. Some even have built-in safeguards that alert practitioners to drug interactions. Data systems can also be integrated into patient diagnosis. For example, Kheiron Medical developed deep learning software that helps detect breast cancers in mammograms. Another example is Fractal Analytics incubated, which uses deep learning and artificial intelligence to improve radiology and speed up the analysis of diagnostic x-rays.

As analytics and informatics systems evolve, nurses may eventually have hand-held devices providing real-time, insightful data visualizations when treating patients or working on administrative tasks. This should improve both patient outcomes and the day-to-day experience of nurses.

The Utility of Predictive Analytics in Nursing

Predictive analytics, which uses historical data and machine learning to project future outcomes, represents a particularly promising analytics field. In combination with nurses’ knowledge and experience, analytics can improve many aspects of patient care, as discussed below.

Providing Timely Early Warnings

Predictive analytics can alert practitioners to a potential impending downturn in a patient’s condition. For example, predictive analytics might assign patients a risk score based on vital signs, lab results, and similar data. As these metrics change, software can compare them to historical data and match them to situations that preceded rapid deterioration. At that point, nurses can initiate care designed to prevent further decline or transfer the patient to higher-level care.

Identifying At-Risk Patients

Predictive analytics can scan patient data for indicators of high-risk conditions. Engineers have developed AI systems to analyze patient data to predict who is most likely to have heart attacks or strokes. Even everyday technologies can contribute. For example, an Apple Watch saved the life of a 46-year-old father by detecting and reporting his irregular heartbeat.

Informing End-of-Life Care

Predictive analytics can comb patient EHR data for indicators that death is approaching. This allows nurses and other medical professionals to consult with the patient’s family to discuss end-of-life care within an appropriate time frame.

Preventing Costly Hospital Readmissions

By correlating vast amounts of health care data to corresponding outcomes, health analytics professionals can use data to identify patients most at risk of rehospitalization. EHR data measuring a patient’s condition, comorbidities, medications, vital sign values, and demographics help determine that patient’s likelihood of staying in the hospital either too long or not long enough. These insights empower nurses to personalize discharge planning and outpatient care in a way that optimizes outcomes.

Health care analytics loom large in the future of medical practice. Nurses who proactively train in and adopt these emerging technologies may, in the process, create opportunities to advance into senior administrative roles or gain influence in clinical roles more quickly.

How Analytics Is Creating New Career Paths in Nursing

As analytics assumes greater importance in health care delivery and management, nurses who have developed expertise in the field may discover opportunities to assume new roles. Analytics-savvy nurses could qualify for such titles as:

  • Chief nursing informatics officer: Executive officer who leads technology development and oversees technology implementation within a health care delivery system
  • Clinical IT specialist: Tech professional who designs and manages patient information, database systems, and security measures
  • Clinical nurse leader: Nurse who oversees clinical nursing staff, providing guidance, coordinating work, and assessing performance
  • Health data analyst: Tech professional who compiles, organizes, and interprets medical health data
  • Health data scientist: Health care engineer who develops and tests data analytics programs and applications
  • Informatics nurse: Nurse who operates and analyzes health informatics systems and who works with developers to improve existing systems and create new ones
  • Nurse data analyst: Nurse who studies and interprets health care data
  • Nurse researcher: Nurse who studies health care and illness

The global recruitment and employment site Monster calls informatics the “one thing all nurses need to know” to future-proof their careers. Informatics and analytics together offer keys to future health care advances, but they require a specialized skillset. A Master of Science in Nursing degree program, like the analytics-focused MSN at University of Michigan School of Nursing, provides those skills as well as the credentials needed to advance to management and executive roles.

Will Intelligent Analytics Systems Ever Replace Nurses?

Of course, no one can predict the future, but it seems safe to say that intelligent analytics systems are unlikely to replace skilled nurses. Even as health care computing advances, human judgment and in-person observation remain crucial elements of health care delivery. There’s no indication that will ever change.

Predictive systems function in health care settings as assistive intelligence. They support clinical care functions rather than provide them. Nurses have been and continue to be decision-makers and action-takers in health care facilities in which predictive analytics systems are employed. They assess clinical situations, make decisions, and put those decisions into action. Looking at data-driven insights generated by AI and machine learning doesn’t change that. It simply provides more and better tools to enhance patient safety, improve patient outcomes, and bolster confidence in medical decisions.

Because nurses spend more time with patients than other providers, it stands to reason that they will be leaders in the widespread adoption of analytics in patient care. “Nurses are key leaders in developing the infrastructure for effective and efficient health IT that transforms the delivery of care,” according to the Healthcare Information and Management Systems Society’s position on transforming nursing with technology. That means demand should grow for nurses qualified to implement and lead the integration of new technologies into medical practice.

Earning an MSN in informatics or analytics can put you at the forefront of the tech-driven changes taking place in health care today. Demand for nurse data scientists, skilled nurse informaticists, and nurses comfortable working with complex health IT systems is growing, opening opportunities for nurses with the right skills. In a program like U-M School of Nursing’s part-time Online MSN in Leadership, Analytics, and Innovation, you’ll develop competencies that will help you bridge the gap between nurses on the front lines of health care and the technologists sharpening medical acuity.