Nursing Analytics: 
Using Cost and Quality Information to Improve 
Patient Care

Nursing Analytics: 
Using Cost and Quality Information to Improve 
Patient Care

By Dee Donatelli RN, BSN, MBA; and Elizabeth Meyers, RN, BSN, MS, CNOR

Patients in today’s healthcare system benefit from expert caregivers who are supported by advancing technology. The majority of patient care is provided by nurses, who comprise the largest percentage of the healthcare workforce, with more than 3 million nurses practicing in the United States (Health Resources and Services Administration, 2013). Health information technology allows nurses to better monitor patient status, communicate with patients, collaborate with team members, evaluate available care options, and determine best practices. The recent widespread adoption of electronic health records (EHRs) and health information exchanges significantly expands the information available to nurses, which is changing the way decisions are made and providing new nursing leadership roles.

Nurses as Expert Decision Makers

Nurses are experts at providing patient care. They develop expertise through practice, moving from novice to expert over time by providing care for many, varied patients. Nurses learn through experience beginning during practical rotations, first in the lab setting, then in numerous care settings. Learning continues to be hands-on in the first years on the job during which the nurse transitions through stages from novice to expert. As experience is gained, thought processes develop to mirror the complex nature of patient care (Burger, et al, 2010).

Kahneman and Klein (2009) describe expert learning as the building of intuition. Nurses develop automatic responses for tasks through repetition. This process is the same as learning to drive a car. New drivers must pay conscious attention to steering, accelerating, and braking. Drivers observe how their actions affect the direction and speed of the car and adjust accordingly over many repeated experiences. Expert drivers have internalized these processes and no longer need to concentrate on these basic skills.

The process of experiential learning is limited. A driver’s expertise is limited to driving the particular vehicle with which she has experience. When introduced to a new environment, what was automatic becomes effortful for a time while the driver acquires feedback about the new vehicle. In a similar way, expert nurses rely on feedback from their personal experiences to guide future actions. For example, the nurse inserts an intravenous catheter and can immediately assess its patency by watching for a flash of blood in 
the catheter, which provides feedback for further skill 
development.

The complexity of healthcare, however, does not always allow a nurse to properly assess outcomes directly. For instance, a pressure ulcer caused by poor skincare may not manifest for several days. Similarly, a post-operative surgical site infection linked to poor prepping technique could be attributed to any number of possible contributing factors. In these examples, the nurse may never know that the interventions were substandard, because feedback is delayed or non-existent. When feedback is poor, the traditional method of individual expert nurse decision making falls short. It leads nurses to believe they are providing good quality care when, sometimes, they are not.

To improve quality, outcomes must be connected to care interventions in a timely fashion. New healthcare technology is enabling this change. EHRs capture information about nursing interventions at the point of care in the form of nursing documentation. This documentation can then be used to analyze variations in care. If quality is the best intervention for a specific patient at a specific time, it is expected that similar patients in similar circumstances will receive similar treatments. Given this definition of quality, high quality practices will have low levels of variation because best practices are clearly defined. Current nursing practices do not meet this standard of quality, but EHRs provide information allowing variation to be identified and analyzed so quality can be improved (Keenan, et al., 2013).

Health information exchanges allow outcomes to be tracked across multiple providers, organizations, and care settings. Connecting patient outcomes to variations in care observed in EHRs creates an opportunity for quality improvement. Better care can be defined though data analysis, based on the outcomes of many more patients than a single nurse can care for. New information can then 
be shared with nurses in the form of care guides, algorithms, and other decision support. Adoption of these standardized tools and practices is sometimes hard to accept for 
nurses who have come to rely on their expert intuitions. Nevertheless, adoption of healthcare information technology can lead to reduced uncertainty and improved quality of care (Kazandjian & Lipitz-Snyderman, 2011).

Claussen, Garner, and Crow (2013) recently described how a hospital decreased code blue resuscitations by implementing a nursing decision support tool. This tool assigns a color-coded score based on a patient’s vital signs and level of consciousness. The score alerts staff that a patient requires additional assessment, and it includes recommended actions such as rapid response initiation or transfer to a higher level of care. This scoring system is an example of an algorithm that can be developed by analyzing outcomes. It reduces uncertainty about the best care, reduces variation, and improves quality.

In another study, Dowding, Turley, and Garrido (2012) found that EHR adoption was associated with greater completion of specialty assessments. Nurses were more likely to document pressure ulcer and patient fall risk factors when prompted by an EHR. The study revealed that improved documentation can be associated with improved patient outcomes, shown by a decrease in actual patient falls related to increased assessment completion. This is another example of how nursing care can be improved by moving from a world of individualized expertise based on personal experience to best practices refined by outcomes-based information.

Nurses are beginning to view healthcare information technology as an adjunct but not a replacement for expert decision making (Moore & Fisher, 2012). Technology helps coordinate nursing care and encourages standardization. For instance, nurse managers are using technology to optimize staffing, balance workload, and avoid costly overtime (Barton, 2013). But, despite the advantages, expert decision making is still needed to understand the contextual clues to ensure specific interventions are appropriate for specific patients within particular circumstances.

Emerging Roles for Nurses

Nurses have been evaluating nursing practice and developing standardized guides and scoring systems as decision support tools for many years. Distilling the best care from expert practice to develop these care standards can be accomplished in many ways (Crandall & Getchell, 1993; Thompson, Aitken, Doran, & Dowding, 2013). Healthcare reform and the widespread adoption of health information technology are driving the use of data to guide these 
decisions.

In 2010, the Institute of Medicine released a report, The Future of Nursing: Leading Change, Advancing Health. The agency defined how an improved information infrastructure was necessary in order to collect data to inform workforce planning and policy making. Nurses should be full partners with other health professionals in redesigning healthcare and should practice to the full extent of their education and training. These thoughts are echoed by the Healthcare Information and Management Systems Society (HIMSS), “Nurses are key leaders in developing the infrastructure for effective and efficient health IT that transforms the delivery of care” (Sensmeier, 2011).

One key role for nurses that has developed over the last few decades is that of the nurse informaticist. “Nursing informatics is a well established nursing specialty, which today has evolved to be an integral part of healthcare delivery and a differentiating factor in the selection, implementation, and evaluation of health IT that supports safe, high-quality, patient centric care. Nurse informaticists use their depth of knowledge and understanding of the patient care process, combined with the power of technology, to contribute to the care of the individual and the transformation of healthcare” (Sensmeier, 2011).

Nurse informaticists design easy-to-use EHRs, enabling accurate data capture at the point of care. They work with analysts to organize and interpret data, turning it into information. They work with statisticians to correlate specific interventions with patient outcomes. And, they work with software developers to develop computerized decision support algorithms to improve the quality of care by encouraging standardization to the best practices.

What is Value Analysis?

According to the Lawrence D. Miles Value Foundation website (2011), value analysis was developed by General Electric engineer, Lawrence D. Miles in the 1940s to the1960s. He defined value methodology as a process to eliminate unnecessary costs though the substitution of lower cost materials or parts while maintaining function. In manufacturing engineering, value analysis (VA) is performed by product engineers as an adjunct to other types of quality methods (such as Lean or Six Sigma). VA techniques were introduced to healthcare in the 1980s primarily by procurement leaders (Robert W. Yokl, personal communication, 
July 1, 2013).

Building on the success of value engineering in manufacturing, several healthcare supply group purchasing organizations began to offer training to their participating healthcare systems in the 1990s. In healthcare, a team approach was adopted for value analysis, and registered nurses were brought into hospital supply chain departments to lead value analysis teams. Today, healthcare value analysis practitioners have a professional organization, the Association of Healthcare Value Analysis Professionals, with approximately 200 members (2013). The Association’s website states their mission is “to provide and promote processes and information to assist Value Analysis Professionals in evaluating healthcare services for clinical quality and cost effectiveness.”

Several articles describing value analysis are available in the literature. Davis & Doyle (2011) describe an implementation of value analysis processes to optimize the supplies in a pediatric perioperative department. Pennington & DeRienzo (2010) describe their value analysis process’s five steps, which are similar to any quality process: assess, plan, design, implement, and measure/sustain. Jurewicz, Starick, and Diers (2006) describe an “Equipment, Products, and Standards Committee” (p. 72A).

 

Information 
at the 
Point of Decision

Expert decision makers, like nurses, need clear feedback in a timely manner in order to develop and maintain their expertise (Kahneman & Klein, 2009). The best way to improve quality is to shorten the feedback cycle, but current retrospective reporting mechanisms do not meet these needs.

Advanced technology can be used to enable and automate the feedback cycle. Think of the millions of messages that are currently transmitted within a hospital system. Interface engines translate and transmit messages among the various clinical information systems. Radio-frequency identification tags track patient, staff, and equipment movement throughout care delivery. Clinical staff and patient monitoring devices document patient status electronically. Patients track their health status on their smart phones.

Now picture a day when all of this information is collated, cleansed, prioritized, and delivered to a caregiver just when they need it. Welcome to the future of healthcare. The first step to creating this vision was the introduction of electronic health records. Now that computers have entered caregiver workflow, clinical decision-support engines are helping to shorten the feedback loop by providing guidance at the time of care, based on the best available evidence. In the future, these guidelines can be augmented by adding information about the costs of available interventions. Cost information closes the loop, so that interventions can be chosen based on cost and effectiveness. This enables healthcare providers to have a true, value-based, shared decision-making conversation with their patients, augmenting expert opinion with evidenced-based care.

Value Analysis: A New Role for Nurses

Traditionally, healthcare reimbursement in the United States has been based on a fee-for-service model. Physicians and nurses have been free to provide the best care available, regardless of the expense. But not all expensive care has been proven to be the best. And so, insurance companies and academic researchers have developed methods to define cost effectiveness and understand the value of care (Luce & Cohen, 2009). Several academic groups have developed best practice standards for this evaluation. These groups include the Society for Medical Decision Making, the International Society for Pharmacoeconomics and Outcomes Research, and Patient-Centered Outcomes Research Institute. The next step is to build on this foundation, bringing cost and effectiveness information forward in real-time, to the point of decision.

Hospital supply chains have assumed responsibility for proving the value of supplies used through the introduction of nurse-led value analysis committees. To optimize patient outcomes and realize significant cost savings throughout the supply chain requires organizations to make purchasing and care-management decisions based on clinically focused criteria. As leaders of the value-analysis team, nurses can guide their organizations to use evidence-based value analysis (EBVA) processes that incorporate unbiased evidence of efficacy and safety, operational impact, and return on investment, both clinical and financial. Such processes change the purchasing of products and services from a price-focused, nonclinical approach to a fact-based, objective endeavor.

  

Weighing the Evidence

Sorting through pages of search results to find scientific evidence to support practice is not everyone’s idea of a good time. Thankfully there are public and private organizations that concentrate on this important process. Here are some helpful links:

Patient-Centered Outcomes Research Institute
www.pcori.org

The Cochrane Library
www.thecochranelibrary.com

Hayes
www.hayesinc.com

U.S. Preventive Services Task Force
www.uspreventiveservicestaskforce.org

ECRI Institute
www.ecri.org

In addition, many universities have divisions that focus on health technology assessment. A more complete list can be accessed on the International Society for Pharmacoeconomics and Outcomes Research website:
http://www.ispor.org/HTADirectory/Index.aspx

EBVA enables clinicians to deliver high-quality medical care and leads to greater physician buy-in. From a physician perspective, clinical evidence is compelling. As scientists themselves, physicians recognize the value of evidence. Although they can be resistant to contracting and standardization strategies, physicians generally will listen to evidence and be willing to use scientific information as an acceptable rationale on which to participate in cost savings and utilization decisions. More importantly, EBVA enables organizations to achieve cost savings that are sustainable over time, even as new products enter the marketplace. A number of hospitals have already moved in this direction by creating nurse-led teams that are charged with analyzing data to find ways to deliver the highest quality care at an affordable cost.

The explosion of medical information now being collected via medical claims and electronic medical records provides a valuable resource that nurses can tap into in their efforts to eliminate wasteful spending and inefficient patient care. Much as clinicians analyze data from a clinical trial, examination of collected healthcare data offers insight into which treatments work for which patients in real-life situations, helping to provide evidence-based care. Similarly, analyses often reveal trends and patterns in spending and utilization of services. We can identify patients who return repeatedly for readmission, mine the data to determine the cause, and develop a plan to keep those patients out of the hospital for longer periods of time. Coupled with scientific evidence of clinical quality and safety, data analysis becomes a powerful tool nurses can use to support healthcare best practices.

Healthcare reform is driving this change from nurses acting as individual experts to nurses providing uniform, evidence-based care. Hospitals, clinicians, and patients must take a long, hard look at the value associated with the medical care they deliver and receive in order to achieve clinical as well as financial objectives and meet federal quality mandates. Nurses play pivotal new roles as hospitals and healthcare providers focus strategically on the outcomes associated with the products, devices, services, and interventions used to deliver care to patients. Value-based care, informed by data, interpreted and applied by expert nurses, is best care for our patients.

Dee Donatelli is the senior vice president at Hayes, Inc., a company that evaluates evidence-based research to assist health systems in the review of technologies in order to achieve sustainable improvements in outcomes and cost savings. Donatelli is a Certified Material Resource Professional (CMPP), with more than 30 years of experience in the healthcare industry, primarily focused in the areas of supply chain cost reduction and value analysis. She is the current president of AHVAP, the Association of Healthcare Value Analysis Professionals, a Fellow of the Association for Healthcare Resource and Materials Management (AHRMM), and a member of AHRMM’s Annual Conference Education Committee.

Elizabeth Meyers is an industry strategy director for healthcare analytics at Infor. In her role, she is responsible for formulating, communicating, and executing business plans for Infor’s healthcare solutions. Prior to joining Infor, she led Fairview Supply Chain’s business intelligence team, where she was responsible for converting data into actionable information for decision making. Meyers also worked as a perioperative nurse in the U.S. Army and held positions in surgery and clinical management with Baldwin Area Medical Center. Meyers earned a bachelor’s degree in nursing from the University of Minnesota and a master’s degree in technology management from the University of Wisconsin. She is currently pursuing a PhD in healthcare informatics with the University of Minnesota, where she is also a guest lecturer. Meyers may be contacted at Beth.Meyers@infor.com.

 

Donatelli, D. & Meyers, E. (2014). Nursing analytics: Using cost and quality information to improve patient care. Patient Safety & Quality Healthcare, 11(2), 32–37.

References

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