My DNP program encouraged the mindset of having a spirit of inquiry. I am a nurse with a Doctor of Nursing Practice in leadership who works at an academic facility. For the purpose of this blog post, I am referring to data as it is relevant to nursing documentation in the electronic medical record related to pressure injury prevention. This is my personal record keeping of my goal and journey to help decrease hospital acquired pressure injuries via a quality improvement project that includes the current building of an analytic tool that analyzes nursing documentation.
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It seems logical that healthcare data should drive decision making in a healthcare setting. According to the Agency for Healthcare research and Quality, pressure ulcers are associated with a higher morbidity and mortality rate. Data such as documentation reports are important to understand how nurses are caring for patients. Health systems can benefit from making decisions based on meaningful data. In an ideal site, health care organizations have resources such as statistical software that allows staff to design data visualizations that translate meaning to the bedside. When healthcare data and data files information is provided to staff, this allows for a better understanding of quality improvement for patients.
Analytic tools to visualize data in healthcare
I recently met some of our data scientists with whom I hope to work with in the near future. I am focused on studying the nursing interventions at the bedside that are most impactful in decreasing our pressure ulcers. Is it nursing knowledge pertaining to pressure ulcers? Is it turning compliance and/or frequency? Is it taking action in applying the appropriate wound care orders once a pressure ulcer is identified? Despite much of the research data and recommendations already in place, the prevalence of pressure ulcers is still a priority that calls for analysis of the healthcare data.
Data elements
Data elements included in the tool are patient name, days of service, and admission date or encounter date. Gender, race, and geographic data so far, not needed for this quality improvement project. Data elements of specific clinical information such as the patient’s Braden score for the shift, is important in this analysis in evaluating the interventions necessary to provide quality care.
Access to data
To be able to study the electronic health record data for other units beyond my own, I followed a list of things that were reviewed in my DNP program. There is no open data, meaning that due to HIPPA regulations, you have to get permissions from the appropriate powers to access healthcare data. After several individual and group presentations of my quality improvement project, I obtained written permission from those managers and directors that agreed to grant me access to department data. I also filled out our organizations IRB form to obtain clearance. Since I am only looking at the electronic healthcare record data, this is considered a quality improvement project. To analyze data, it has to be accessible. Health care centers and academic sites have rules and regulations regarding access to protected data. My next step was to obtain access to the database in question for each department that I was planning to work with.
Using relevant data
In my quest to start analyzing any data, I first reached out the informatics department. After meeting with the informatics manager and reviewing my project and goals, the dataset that I was looking for was not available from this department. I wanted to access a report that includes data with specific documentation that prevents pressure ulcer injuries.
Organizational outreach
I presented my quality improvement project to management staff from our hospitals wound care staff as well as someone from Clinical Education. I also reached out to the appropriate nursing authorities to clear up some questions regarding Braden Scale scoring.
Improving the data with education
Content regarding pressure injury prevention measures was placed in an online module with the approval from members of the wound care team as well as Clinical Education. The staff on the targeted units were assigned this module for completion as part of their required modules.
Using Power BI to analyze data
As I continued working on this quality improvement project, I had the idea of reaching out to one of our hospital computer analysts. I have been very lucky with this particular analyst as she is as focused as I am in analyzing the data knowing that it has the potential to make a difference in health care and our patients. I am not analytically savvy, but I have come to play with Power BI lately and love the endless capabilities it offers.
Data visualization of healthcare data
There is something about sharing visuals of specific health data with staff that hits differently. I think many people are visual learners. I have been sharing this public health data with our nursing staff at a specific frequency as part of this quality improvement project. There seems to be a clinical practice compliance improvement as a reaction to data visualization. This confirms to me that nurses learn best when visuals cues are included and not just education in written form.
Data-driven decisions
My organization currently uses analytic data that drives decision making in other areas that involve chronic health conditions, detailed mortality, drug product labeling, adverse events, children’s health, substance abuse, infectious diseases, and even mental health. I conduct research and testing (informally, from my desk) when it comes to sharing data visuals with our staff related to pressure injury prevention. I find that staff will do the nursing interventions you ask them to when these are presented with visuals rather than written only content. The nursing documentation data interestingly takes a positive turn after visuals are shared with staff that include nursing practice compliance rates.
Data-driven triggers
This is an area where I need to become competent. I do not think this lesson is covered in depth in the Udemy courses I bought but I am looking for more training. These are useful because they allow the system to respond dynamically to changes in the data, making for a more effective decision making.
Building Reports in Power BI
I am currently learning on building a report that includes data pertinent to pressure ulcer prevention. There are minimum data sets components that I find relevant include the interventions that align with our pressure injury prevention policy. In these reports, there are target data goals you can set for specific time intervals. I have not included any demographic, geographic, health status, age, or population data in our current reports.
Statistical analysis of the data
I am no statistician, but I do plan to look for correlations in the data. Correlation does not equal causation but in studying our data my goal is to see either of two. Knowing correlation or causation will still provide valuable information about which nursing interventions in practice are most impactful.
Data analysis timeframe
This analytic data tool has been in the making for over some months now and still in progress. It is important to work closely with the analyst who inputs the coding. I have learned that clinical nursing knowledge and analytical skills work best when both come together, questions are asked, and information is explained on both sides. We have checked the ‘raw data’ many times and have corrected many mistakes in this manner. Once the tool is at its best, a trial run of at least 6-9 months is needed.
Beyond the trial period
Once this analytical tool is in its final version, the next step will be to trial it on other hospital units where pressure injury prevention is applicable. As the electronic medical record updates, there may be a need to update the tool as well. One thing I find useful is that the analyst is recording a list of rules for how it is coded, just in case another analyst was to take over.
Organizational hierarchy: building relationships
Relationship building is essential when working on a quality improvement project that requires data sharing from your stakeholders. I chose to start presenting this project and analytical tool ‘at the top’ of the leadership hierarchy and then worked my way down. Tactful communication and presentation of intent of the data is important to maintain the rightful ownership of the project while acknowledging the collaborations across the organization.
Next steps
My next step in this quality improvement journey is to continue analyzing the data and also explore the entrepreneurial aspect of it. In this day in age, it is crucial to understand and apply nursing informatics and data analysis when making patient care decisions. Opportunities seem endless in creating tools that will improve our patient care.