NLN Nursing EDge Unscripted

Scholarship - Integrating Big Data into Nursing Education: A Call to Action for Faculty

January 11, 2024 Roy Simpson Season 3 Episode 32
NLN Nursing EDge Unscripted
Scholarship - Integrating Big Data into Nursing Education: A Call to Action for Faculty
Show Notes Transcript

This episode of the NLN Nursing EDge Unscripted Scholarship track features guest Roy Simpson. Learn more about his editorial, "Integrating Big Data into Nursing Education: A Call to Action for Faculty."

Simpson, Roy L.. Integrating Big Data Into Nursing Education: A Call to Action for Faculty. Nursing Education Perspectives 44(6):p 333-334, 11/12 2023. | DOI: 10.1097/01.NEP.0000000000001202 

Dedicated to excellence in nursing, the National League for Nursing is the leading organization for nurse faculty and leaders in nursing education. Find past episodes of the NLN Nursing EDge podcast online. Get instant updates by following the NLN on LinkedIn, Facebook, Twitter, Instagram, and YouTube. For more information, visit NLN.org.

[Music] Welcome to this episode of NLN podcast Nursing EDge Unscripted the Scholarship track. I'm your  host, Dr. Steven Palazzo, and a member of the editorial board for Nursing Education  Perspectives. Nursing EDge Unscripted and our track entitled Scholarship celebrates the  published work of select nurse educators from the NLN's official journal, Nursing Education  Perspectives and the NLN Nursing EDge blog. The conversations embrace the author's unique  perspectives on teaching and learning innovations and the implications for nursing program  development and enhancement. In this episode, we will discuss the use of large data sets to inform  nursing education pedagogy. We will discuss the perspectives of my guest today Dr. Roy Simpson,  a professor and Assistant Dean of Technology at the Nell Hodgson Woodruff School of Nursing at  Emory University in Atlanta. The guest editorial, Integrating Big Data Into Nursing Education:  A Call to Action for Faculty, can be found in the November December issue of Nursing Education  Perspectives. Dr. Simpson, welcome! Thank you Dr. Palazzo. It's great to be here and great  opportunity to share my personal experience as well as my thoughts on big data so thank  you. You're very welcome. We're excited to hear your perspectives here. So one of the things that  I think we all have to look at when I wrote the editorial is the context of big data and I don't  think we can lose sight of the fact that big data is millions of data points and most nurse  data doesn't collect in that manner. We don't usually have large data sets, but my concern comes  in that the data sets that we do have we're not investigating. We're not looking at them for evidence.  We're not looking at them for directing our new opportunities in the future. We don't look at them  in the way that we should be looking to advance our discipline and our profession. We have enormous  data from State Boards of Nursing that we have access to and there are other data points that  are proprietary in nature and those proprietary ones we have to work with their organizations  because they feel that they are unique to their organization and that they are the core of their  business and what we have to make people understand and organizations understand is  that we need that data in order to define our future opportunities. I look at, quite  often when I'm evaluating and having been a chief nurse executive, having been in business operations  and now in academe, I look at that old triage of data in a way that some people don't and that  is because we look at shortages in the hospital and yet, when I wrote my editorial there were two  references that over 56% of nurses turnover within three years, much less a year. And when you look at  that height of turnover, you really need to look at demand and supply equations. What are we admitting  to the schools that people are not able to be able to understand the environment that they're  going to to practice? We can blame a lot on operations and hospitals and those  types of things, but we as academicians have to look at what are the students that we let in? Do  they understand what it is or are we just letting them in for revenue production? It's very easy  to create revenue production when you have open access to schools. You let in anybody that has the  grades that they think are okay because grades are inflated today compared to when I was in school  and it's very apparent that these students do not have the understanding of what they're going to  be moving to and it's really key. Yeah you make a but not in the way you just described.  Usually, we obviously are attracted to students who  have an interest in providing care and understand some aspect of health, but how how do we prepare  them for what they are going to see or how they're going to, I guess, not see necessarily but what are  the realities of the system in which they're going to operate in once they leave the the the confines  of the campus, right? So they get a taste of that when they're in their clinical settings, but  they don't have a full immersion into that, the political, the environment of the  facility or agency they're going to be at until that first six months or year. What is it that  we could actually do in reference to big data to help prepare students better for that experience?  I think we have to mind that data. I think we have to mine the data on entry of students. I  mean, every school I know takes data points about students over their career opportunities in their  four-year programs and their two-year programs and even in some diploma schools. They all take  data and we need to start mining that data to see what correlations there are, what statistical  alignments there are, and evaluate what we need to let into a school. And I say that "let in" just like  med schools let in. They don't open the door to everyone. They don't open with open access. They  don't open open with limited access. They say you have to have these criteria in order to be  into the med school. Now, granted, they are a post- baccalaureate degree program, but at the same time,  look at other universities that focus in on other opportunities and that increases diversity  at the same time because then you know what people have the ability in order to create those  opportunities to move forward in the data because state boards already know who can pass, who can't  pass, what they lack, what they don't lack, and how do they publish that data. How does the National  Council of State Boards publish that data? Clearly they have revenue production. I've looked at their  their 1090 forms. They have enormous amounts of holdings of assets. They need to spend that money,  they are a not for-profit organization, on mining that data. We don't have that data do we? We can't access that data. No, no we don't and they need to do it because they are not for-profit organization  they claim 501c3 status and therefore they are required by law to use their money to advance  the causes of their data points and they're not doing it, not anybody is doing it and we  don't even have a minimum data set in nursing education. We have one in nursing management. We  have one in nursing practice, but we need one in nursing education not only for students but for  faculty. I mean, I am constantly amazed when faculty have difficulties and they concurrently  have difficulties and we're not able to coach them through our data to what they need to do to have  better engagement with their students. And some of the harder courses, let's be upfront - there  are harder courses in nursing than there are other courses in nursing, and those professors have the  heavy workload, the heavy lift and they get the poorest evaluations when in reality they are the  ones that hold the key to advancing our cause as professional nurses because if you're not  academically prepared, you get lost when you get into practice. You're completely lost in practice.  What about resources? What are the resources you suggest that would be needed for this?  That's a great question about resources because we do have limited people in nursing that have PhDs and academic preparation. And we're not producing a lot more of them, that's for sure. No, and so we have to  capitalize on looking at people who do have AI/ML experience and knowledge and work with them  on what's nursing data. I think that's the other thing when you look at schools of nursing  that begins our core of nursing data. And we need to distinguish our data from that of allopathic, which  is medical practice. Now, the government's going to call us medicine forever. They're not going  to separate allopathic, chiropractic, nursing practice, psychiatric practice, they're not going to separate  all those. What they're going to separate is up to us and we have to find those data points that  make it unique to our contribution because I am here to tell you if we don't we will be a  generic health care worker. And I can look at it from my basic diploma education at Grady  in the 60s. We all had physical therapy, we had nutrition...no one said we couldn't  do those things and all of a sudden they tell us we can't do this in PT anymore. And you're like,  

really? You close at 5:

00 in the afternoon and I'm responsible. I think I can do it. And we really need  to recognize we have a larger scope than we are practicing in and that's a scope that we  can push, we can legally push it and we can with data and evidence push those boundaries.  So what's the next steps? You highlight some really great points there. So what is the next steps, so what do we do with this? I think we gain with our PhD colleagues who are non- nurses  and work with them to develop those data things. The other thing I think we have to recognize is  that people who are in DNP education and after they've been in practice and they are looking at  doing jobs that are not as physically demanding but mentally challenging, they are great people  to work with software. They can work with software. You can teach them a program and they can run your  data. I run data for my colleagues all the time because I've always been involved in databases  and so once you get into databases you kind of can run databases for people in science and so  that's one thing we have to do is we have to look to anyone who has those skills and knowledge and  wants to work in that domain to be able to push that knowledge forward. That's the first thing. The  second thing is that we have to start pushing on professional organizations and on ourself to  look at what and where is our nursing data. And third, I think collectively NLN should drive  the components to develop a nursing minimum data set. And you know it's interesting. We talk about  others not releasing proprietary knowledge. We could brand that as the NLN nursing minimum data set  in education for students and for faculty and for pedagogy and environmental practices that we  all have and we could say that's it, push it out and people would start collecting that data and  now when you collect that data you can just send that data to a holding company like NLN and they  can run it for you. Have you proposed that to NLN? I've talked to Dr. Malone before about it. Actually  talked to her at an NLN meeting because NLN has a little bit of funding every now and then that we  can get, NSF has funding and those are areas that we have to look at for our funding that are NIH.  NINR is not going to focus on big data, whereas all the others are. I can tell you, my funding through NSF and private foundations etc. They look to nursing for data. Oh that's great. So to summarize your position from your editorial, big data is there, we need to be able to access it, interpret it, and then do something with it to move the profession forward both in education and in  industry. And if not, someone else is going to do it and get their hands on it and we're going to lose  opportunities not only to advance education but lose opportunities in our generalist practice as we go out there in our our day-to-day work that we're doing. Dr. Palazzo, you have summarized  it equitably and perfect. We will end up not being able to understand what it is that we're  going to be doing in practice from the education that gap of learning to practice. I mean,  we talk about data to information to knowledge to wisdom. You can also talk about from student to  practitioner to advanced practice to leadership skills, right, the whole dynamics of the continuum  that we as nurses experience over our lifetime becomes very important. One of  the other things is that a lot of the data may not be as succinct as we want it to be. An example of that would be pressure ulcers. You and I and nurses think of pressure ulcers in  our domain, what to do etc. and so forth, but in so many organizations, they have to have orders from  the physicians or providers to do that. That that is our domain. We should not lose those  pressure ulcer knowledge bases. Well don't we, I would suggest we lose that because of reimbursement because we can't reimburse for for ourselves for it, right? Well, we can. We can reimburse. We can as a practitioner, right, but as a registered nurse, how are you doing that? Well you know, this is interesting, Dr. Palazzo, you ask a very pertinent question to the domain of  clinical care and that comes to reimbursement for all. Our physicians, midlevel providers whatever you  want to call them, nurses at the bedside, are we all driven by revenue production in our organizations  and that's our key. If that's our key, then we need to train and educate our nurses to revenue  production and they don't have a business course in their model. That's not within the domain of  state boards and yet that's what they hit when they run into practice. So we teach them to take  care of things that revenue production blocks them from doing. And that's a very good point, but there are things that we can, if we had a classification system in our domain that we use,  that we could end up billing, charging and that's the other thing. We have to remember that  costing, pricing, billing, and charging for services are all different components. I can bill all day  long to somebody but I may not get the money. I may have contracted for lesser amount. They may pay me  on a different payment scheme. Their payment scheme may be once every six months so you got to  have cash flow to run through it. There's so many business opportunities when you say costing of  nursing services because it just envelops a whole other sphere, but the point of it is big data could get us there. It could, but right now nurses are looked at as cost. They're not looked at as revenue producers. That is true. And until we're seen as revenue producers, for good or bad, until we can bill for our services, someone else is going to bill for those services, right? So when you're talking about... Well that is true and that is that has some implications to how we educate people. If we're going to drive the organizations they practice in  by revenue production, we should give them tools to understand the environment that they walk to and  does that show up on our National Council of State Boards? I doubt it. I haven't taken a state board in  50 years so I wouldn't really know except students tell me that it's not there. It's not there because it's not an expectation, right? Right. So it's not there. That's the practice environment  they're going should we let people in that are all about - I'm gonna to save the world and  we're gonna kill them the minute they walk into a hospital on revenue production. That's kind of antithesis of the original mission. I don't think yeah and I want to make  it clear I'm not looking at it from a revenue generating perspective meaning that we need to  bill for services to generate revenue. It's from who is currently billing for services to generate  this revenue, there's a protection there, right? So who would want to give up that revenue  generated from diagnosing pressure ulcers and treating those pressure ulcers to nursing, right?  If nursing can obviously recognize a pressure ulcer, intervene, which we do in many  cases, and care for that pressure ulcer, that doesn't get billed to nursing as a service. That  gets billed to whoever the physician is or the health care provider that's on record for that  client or organization whatever it may be. So we're not generating any revenue for the system. We are indirectly generating revenue through other people or entities. You speak of the financial structure and yet, in reality, the financial structure is that the physician is not  billing either. There's already a cost capped on on all the commercial carriers so you've really  stepped into another whole domain of nursing knowledge when it comes to finance and that  is because they're already capped. So they're only billing for a percentage of the cap that the  hospital negotiated, which then puts us back into the nurse practitioner and the hospitalist. And  why do we have them now? Because hospitalists are capped on what they can bill for. They only get a  percentage of it and independent practitioners said I'm not going to bill anymore. You hire somebody at  the hospital to take care of it. So you know, we've moved into another domain that financial  structures have created. However, we have to relate our data to cost data. Ann Van Slyck in the 1980s  did costing, pricing, and billing of nursing services in Arizona and it went nowhere. Part  of the reason it went nowhere out of Arizona is because nurses realize the accountability  associated with financial structure. Right, okay, yeah. And that creates a liability for you. To be sure, you carry malpractice insurance. That's a good point. 90% of nurses don't carry malpractice insurance,  which is always stunning to me. You can be assured and if you think that the hospital and  the academic institution are going to cover you in a lawsuit, they're going to cover themselves  first and you second and you better figure out how you're going to cover yourself and that's  what's called independent practice. So it gets a model that needs to come together with  the whole delivery of the health care system and that's why I think it's so important that ANA,   NLN, AONE, and the National Council of State Boards and now the American Board of Certification all get  together and make sure they understand the whole dynamics at play and there's data there to help  them figure out what they do and what they don't do that is correct. For instance, I just  had a student to do a DNP project on the data at Emory Healthcare through our product called  NeLL, which is over 32 trillion data points and she was convinced that people were treated differently  based upon their diversity when they entered Emory EHRs through STEMI. Now, I'm not a clinician, so I  didn't know a lot about STEMI so I had to go look it up there are three major requirements for it. Do  you know every patient regardless of race, color, creed, or religion, all were treated exactly the  same way. Now that's powerful data when you already think that you're in a predominantly  white environment that people people would be treated differently and the data shows they're not. So it changes the narrative right. It does. It changes the narrative completely. Now that's only for STEMI and I know there's 15 million other diagnoses but at least the data is beginning  to show where we have leaks and where we have flaws and where we have opportunities to increase  quality and I think that's where we really have to look at big data. That was a great example of how big data can impact change. It does. And it, you know, it's very upsetting to me when people say, well, I don't see any clinical advancement in getting a DNP. Whoever thought  that we would start DNPs for clinical advancement? It's so they can understand complexity management.  All this revenue production. I have seen people talk about well, we got to bill for our own services. Well, what is all that downstream effect from billing for our services? What is  the accountability associated? Maybe we don't want to. Maybe what we want to do is make sure we have  the right piece of the pie that makes decision making at the executive level appropriate for  nurse executives so that they can defend us. I mean, you can't go in there as a bleeding heart liberal  at the financial table and tell them how wonderful you are. You got to go in with data. I mean, Luther  Chrisman in the 80s gave us tremendous motivation for data and we're a long way from the 80s. Yes, we are. A long way. Well, I tell you, what was interesting for me about the editorial and  just in our conversation is also seeing where my gaps and knowledge are. So this whole idea  about the system and working within a system of a complex system like health care and being an  

academic here in a university it:

two similar, but very completely different worlds in some respects.  And where that gap is and that gap then translates to our students who come out into this  health care environment and may not be sure... they're exposed to these type of things you just  talked about and not sure how to navigate through them or become disillusioned or disenfranchised  from them and you've gave some really great alternatives and ideas of going forward and  what we could do with this idea of big data and you gave a really good example there with the  STEMI. Well, I want to thank you so much for joining us. This has been a great insightful  conversation. I appreciate your time and expertise and you sharing it with the audience. I definitely  think there's a lot of great gems here that will be helpful at least for those listening to get  exposure to this topic and and maybe stimulate some interest in the area. To our listeners,  if you have not had the opportunity, please look at Dr. Simpson's guest editorial, Integrating Big  

Data Into Nursing Education:

A Call to Action for Faculty. And again, the editorial can be found in  this November December issue of Nursing Education Perspectives and I want to thank all of you for  joining us so thank you and thank you Dr. Simpson. Thank you Dr. Palazzo. I appreciate this great opportunity.