Data or Garbage
One great benefit touted with computerization of records, be they patient records, licensing forms, or college admission databases, is the ability to “data mine” or gather large amounts of complex data while maintaining anonymity of that data. This data can be used in a myriad of ways, with some examples being: 1) to design health education or promotion programs, clinical decision trees, accurate provider licensing exams; 2) determine distribution rates of diseases or patient or student populations and subsequent allocation of funds and services; and 3) analyze educational, clinical, and administrative healthcare processes. (Rosbon & Boray, 2016; Rojas, Munoz-Gama, Sepulveda, & Capurro, 2016). However, the first big step in the process of data mining is being sure the appropriate data is extracted from the systems. How the data is entered into the system and by whom must also be considered when looking at the accuracy of the information. When examining data from a variety of sources, how the information is obtained and the intent or meaning of the information must be considered. The federal government requires schools to report graduation numbers and licensure exam pass rates, but interpreting the meaning of these numbers is challenging. There are many reasons, some outside the schools’ control, that can lead to delayed graduation or even complete withdrawal from the planned field of study. These various factors are not accounted for in the reporting rates (Cook & Hartle, 2011). Exam pass rates are a stand-alone figure derived from state testing sites; the graduation rate and the overall enrollment are not associated with these numbers. Terminology is also a source of confusion, as attainment and completion rates must also be reported separately from graduation rates and exam pass rates. All four rates pull data from various sources within the university and licensure boards. The schools may also exclude certain students – such as part-time or transfer students, which can eliminate over 60% of the student body per the American Council of Education (Cook & Hartle, 2011). Without reliable, accurate statistics the depth and impact of delayed or discontinued NP education cannot be fully appreciated. Before a solution can be proposed or implemented the problem must be correctly assessed.
Once on the internet…….
Computerization has also altered social connections and networking. All types of organizations (i.e. schools, insurance firms, product development groups, hospitals…) use data mining of social media sites to understand the needs of their consumers. Quick reviews of NP focused websites reveal the desperation of students in need of preceptors. One company taking on the challenge of matching preceptors and students offers a social media site where the student can post a 3-month listing for $99 and preceptors can “shop” for students. Alternatively, you can search preceptors resumes and reach out to them. If they are available to precept, you pay $35 for the direct contact information (http://www.npnation.com/national-preceptor-board). In my simple review of this particular site, I could not find any details on security or confidentiality of information. While direct contact information is concealed there is likely enough information for someone to misuse either through identity theft or credentialing fraud. These companies also appear to come and go rather quickly, as many links found in professional newsletters or blogs are no longer valid. What happens to the stored data at that point?
Is it real or is it simulation?
Simulation and virtual learning environments have great potential to help students apply didactic knowledge to patient scenarios. Simulations can boost a student’s confidence with manual skills as well as decision-making in an environment with no permanent or life-altering consequences; however, decisions in the practice setting do have consequences which the practitioner must learn to incorporate into the patient’s care. Nursing and medical schools have been successfully using simulation to teach assessment, procedures, and basic decision making for several years (Flannery & Villarreal, 2014; Loomis, 2016; Warren, Luctkar-Flude, Godfrey, & Lukewich, 2016). Medical schools have advocated for simulation to ensure competence with procedures, but not as a replacement for required clinical education prior to independent practice (Flannery & Villarreal, 2014). In contrast, undergraduate nursing programs have been replacing hospital or clinic experiences with hours in the simulation lab with evidence of students meeting the learning goals. Evidence regarding the use of simulation in preparing advanced practice nurses, such as NPs, is lacking (Warren et. al., 2016). Since NPs are held to the same quality standards as other independent practitioners (i.e. MD or DO), the education process should also be equitable and produce similar outcomes. Not to say that the education needs to be identical, but it must produce healthcare providers capable of compassionate patient interactions, providing high-quality care, and making appropriate decisions for the wide variety of patient presentations.
Computers and technology offer many possibilities to analyze the NPs process to licensure, and patient care skills, as well as match preceptors and students. Perhaps those applying for initial licensure or renewal could complete a questionnaire on the length of school, type of any delays, and practice preparedness; but this data will take years to collect and analyze. It also omits those who quit pursuing their NP entirely. Leaving students to find preceptors, even with robust social media applications, does not ensure quality and appropriateness of the clinical education. Replacing actual practice setting experiences with simulation deprives the student of learning to interact with the entire team involved during a patient encounter. Simulation also removes the inherent risk and anxiety of making decisions that can truly have life or death results. The looming healthcare provider shortage adds a sense of urgency to getting NPs through school, but it shouldn’t shortchange their education. For the health of our population, we need to be sure the NP has real, quality, precepted experiences prior to becoming an independent practitioner. A combination of time-tested teaching (i.e. apprenticeship or precepted learning) and innovative technology will get strong, safe, qualified NPs to the patient.
Cook, B., & Hartle, T.W. (2011). Why graduation rates matter – and why they don’t. American Council on Education. Retrieved from http://www.acenet.edu/the-presidency/columns-and-features/Pages/Why-Graduation-Rates-Matter%E2%80%94and-Why-They-Don%E2%80%99t.aspx
Flannery, M.T., & Villarreal, K.F. (2014). Training using simulation in internal medicine residencies: An educational perspective. The American Journal of the Medical Sciences, 349, 276-278. doi: 10.1097/MAJ.0000000000000406
Loomis, J.A. (2016). Expanding the use of simulation in nurse practitioner education: A new model for teaching physical assessment. The Journal of Nurse Practitioners, 12, e151-e157. doi: 10/1016/j.nurpra.2015.11.010
Robson, B., & Boray, S. (2016). Data-mining to build a knowledge representation store for clinical decision support. Studies on curation and validation based on machine performance in multiple choice licensing examinations. Computers in Biology and Medicine, 73, 71-93. doi: 10.1016/j.compbiomed.2016.02.010
Rojas, E., Munoz-Gama, J., Sepulveda, & Capurro, D. (2016). Process mining in healthcare: A literature review. Journal of Biomedical Informatics, 61, 224-236. doi: 10.1016/j.bbi.2016.04.007
Warren, J.N., Luctkar-Flude, M., Godfrey, C., & Lukewich, J. (2016). A systematic review of the effectiveness of simulation-based education on satisfaction and learning outcomes in nurse practitioner programs. Nurse Education Today, 46, 99-108. doi: 10.1016/j.nedt.2016.08.023