- While a great deal of attention in the clinical analytics world is focused on decision support and quality assessments for physicians who must order treatments and conduct procedures, nurses are often the ones who have to make clinical decisions first. Whether it’s altering a physician that a patient’s mental state has altered due to a medication reaction, ensuring that pressure ulcers don’t begin to form, or suspecting that sepsis is on the way, quality patient care begins with nurses who have just as much need for health IT support as any other member of the care team.
Nurses are also in need of ways to effectively monitor their actions and choices to ensure that all patients are receiving safe, appropriate, and timely care. Healthcare organizations are constantly reporting on a slew of clinical quality measures for CMS programs, but Christina Dempsey, Chief Nursing Officer at Press Ganey, believes that a quality analytics database specific to the role and needs of nurses can better analyze the quality of care while measuring staff performance and satisfaction.
After acquiring the National Database of Nursing Quality Indicators (NDNQI) from the American Nursing Association (ANA), Press Ganey is using the project to further its work into improving the patient experience by ensuring that clinical staff have the data they need to make the best decisions possible.
“Nurse-sensitive indicators reflect the structure, the process and the outcomes of nursing care,” Dempsey explained to HealthITAnalytics. “The structure of nursing care is indicated by the supply of the nursing staff, the skill level of the nursing staff, and the education of the nursing staff. Process indicators measure things like assessments, intervention, and job satisfaction. And then outcomes are those things that improve if there’s a greater quantity or quality of nursing care, such as pressure ulcers and falls.”
“NDNQI has clinical quality measures, and many of them are endorsed by the National Quality Strategy (NQS) from AHRQ. The database measures clinical quality indicators, and nurse engagement or the nursing environment. That falls squarely into what we are doing around our compassionate connected care network in terms of the clinical, operational, cultural, and behavioral domains of patient experience.”
“We are doing a lot of work around trying to distill the data into those four domains of patient experience, so that we are able to help organizations understand where to target their improvement resources and effort,” Dempsey continued. “Being able to bring some of that data together will allow managers, clinicians, and nurses at the bedside better understand what they need to do for which population of patients to get the highest and best return.”
When Press Ganey correlated their own patient experience data with data from the NDNQI, they found higher HCAHPS scores at organizations that had more nursing hours per patient day. Higher performance on Press Ganey’s patient experience domains was also associated with fewer injuries from falls, central line and catheter-related infections, and pressure ulcers.
Unsurprisingly, the data also showed that patients were much happier with their care experience when their nurses expressed greater job satisfaction. When nurses felt as if they were adequately staffed and had a clear sense that nurses are a valued part of the organization, they were better able to provide satisfactory patient care.
The availability of national nursing benchmarks collected by NDNQI gives hospitals a way not only to examine their own internal processes on a unit level, but also to set benchmarks and goals for improvement while helping them to understand where they rank among similar organizations.
“It very much helps to drive nursing quality,” said Dempsey. “We have so much clinical and operational data now that sometimes our organizational leaders – and certainly nurses at the bedside – are not sure how to use the data to drive improvement and where to focus their efforts. Just having the data is not enough. You have to actually use the data to drive improvement. You have to be sure that data, not anecdotes, are what is driving the decisions. With electronic health records, we just have so much more data than we’ve ever had before.”
Nurses are often the heaviest users of EHR technology, and stand to benefit the most from workflow improvements and tools that harness electronic data for predictive analytics and decision-making aids. But patients still complain about distracted clinicians spending more time at the keyboard than making eye contact, which can put a big dent in satisfaction scores collected by databanks like NDNQI, and a bigger dent in potential revenue from patients who may prefer to have their elective procedures performed somewhere a little more welcoming the next time.
“One of the things we still need to do a little work on is establishing a culture that allows you to focus on the patient,” Dempsey asserted. “We want to use the computer to its fullest capacity, but we also want to be sure that we are involving the patient in their care and not focusing exclusively on data entry. And sometimes that’s difficult to do. So we have to blend technology into the culture while making sure that the care that we provide is patient-centered.”
“But it can be done. I think patients understand now that we live in a world where we have electronic health records, and they get that. But even little things, like positioning the computer in the room in relation to the patient, can make a huge difference in the way the patient perceives the interaction. We still have some work to do, but tools like NDNQI can really help us gauge and improve our quality, and make sure we’re doing the right thing for the patient.”