Professional Portfolio
Running Head: INCOMPLETE MEDICATION RECONCILIATION 1
Gap Analysis Plan: Incomplete Medication Reconciliation
Name
Walden University
NURS 6421, Section 01, Supporting Workflow in Healthcare Systems
October 2, 2016
Gap Analysis Plan
McGonigle and Mastrian (2015), defined a workflow as a term used to recount the execution of a sequence of tasks in a recommended sequence. Gap analysis is a form of tool which is used to assess whether the intended requirements are attained at the end of a process.
The purpose of this paper would be to focus on more exploration to incomplete medical reconciliation as a gap that exists within the organization I work for. An in-depth research would be carried out to explain how it has a direct tie to the electronic health record (EHR) system and the related meaningful use (MU) objectives, as well as the goals intended to achieve with the study of the incomplete medical reconciliation. There are some issues that are also going to be explained within this paper, for example, the data collection and sampling techniques and the process systems that would be put in place so as to minimize the disruptions of workflow during the observation process.
Workflow Issue and How it Ties to EHR and Related MU Objectives
As stated above, the workflow issue that I would be exploring for my course project is on the incomplete medical reconciliation. Medication reconciliation is a process of combination of two or more medication list. Medication reconciliation in many times is carried out to avoid medication errors such as omission, duplication, dosing errors and possibilities of drug interactions (Moore et al., 2011). Medication reconciliation usually occurs when there is a transition of care in which there could be the prescription for new medicine, or there is the need to rewrite the current medication (Moore et al., 2011). The increased number of medical errors prompted a research study to establish how they can be reduced. Medical reconciliation is the process of comparing a patient’s medication orders to all of the medications that the patient has been taking. Variations of reconciliation however still exist despite the huge steps undertaken to improve this process (Moore et al., 2011).
There are two processes in the attainment of the reconciliation process. The first process would be creating a list of all the medication that is being received by the patient and secondly communicating the reconciled list to the next provider (Blumenthal & Tavenner, 2010). Electronic health record plays a critical role in the medical reconciliation process. The EHR system is a useful tool which enhances and fastens the process of collecting the Pre-admission Medication List (McGonigle & Mastrian, 2015). This can be accomplished by introducing prior EHR medications sources that could be created by a computerized system. This positive thinking must be tempered with the understanding that the knowledge of medications that have been generated may result in great inconsistencies; usually, a prescription recorded in the electronic medical record, yet has been discontinued and the patient is not taking it anymore. EHR users should, however, be keen on the information which is retrieved from the system for example pharmacy benefits data, visits done outpatient, prescriptions that are sent out electronically, or even dispensing information which may not be in an actual sense a reflection of what a patient is taking (Campbell et al., 2009). The electronic health record should be focused on providing sufficient support for the healthcare workers performing the reconciliation of the medications which includes the existing electronic sources, assist in the recording and reconciliation of drugs prescribed, reusing the information for the subsequent decision support and finally leveraging the existing orders during the discharge reconciliation process (Moore et al., 2011).
Medical reconciliation using the EHR is accomplishing the meaningful use of stage two which has the set objectives of electronically and simultaneously displays the data from at least two list sources in a manner that allows a user to view the data and their attributes, which must include, at a minimum, the source, and last modification date. Enabling users to create a reconciled list and finally validating the accuracy of the data set (Brown, 2010).
Goals for the Gap Analysis
It is more than evident now that there is a gap in the reconciliation of medication. With medication reconciliation effective, a vast number of medication errors would have been significantly reduced. The goals that I would be setting out for this project would be to (1) improve care coordination during transitions between sites of care, (2) improve decision-making at the point of care, and (3) increase patient and clinician knowledge and communication about current medications. I expect that by the end of this research I would have adequately determined the various ways to seal the existing medication reconciliation discrepancies, I would also explore various drug identification modes and try to come up with one better mode and finally is to be able to engage different stakeholders in medication reconciliation.
Data Collection
The key method that would be best applicable for data collection in this is the use of Survey methodology. The survey process is conducted so as to maximize accuracy and participation from all levels of management. The survey process would be able to capture an enormous amount of data ranging from data demographics and the hospital staff structure. During the survey, I would interview some individuals within the system ranging from when a patient is admitted to the discharge. The hospital that I would use for my research uses an EHR, and I would be keen to analyze the effectiveness in reconciling data. I would develop metrics which arrange from 0-1 and each interviewee would be rated according to the metrics.
Minimizing Disruption in the Workflow During Observations
Indeed, during the moment of the survey, there are anticipated disruptions to the workflow process. The best way I would avoid during the observation is through establishing a prior notice to the involved parties before the observation process. Prior notice would mean that each person is aware of my presence and thus minimizing hitches. Secondly, I would ensure I get to learn the workflow process early enough so that I would not look like a stranger and be confused. To this extent, after my understanding, I would even help interested persons in the process if reconciliation. Bias in the study can be avoided by conducting the research in more than one hospital. The analysis will depict just in case of a discrepancy.
Data Recording and Analysis
The data would be recorded in tabular form and finally, the analysis would be based on the SPSS software which generates the general trend and would depend on the various data collected. The accuracy of data can be established using SPSS. I would also analyze data using the various measures of central tendencies, for example, standard deviation, mean, and mode.
Summary
In conclusion, my plan to conduct gap analysis would involve a series of action. One is that I am going to analyze whatever goes on in my place of work and finding out the gaps that exist. I would further visit nearby hospitals to try and establish the gaps within the workflows. My primary method of data collection would be a survey methodology. I will also attempt to access medical histories of the patient from the time of admission and the time of discharge. I will also want to see if my chosen hospitals have attained the meaningful use objectives.
References
Blumenthal, D., & Tavenner, M. (2010). The “meaningful use” regulation for electronic health records. New England Journal of Medicine, 363(6), 501-504. doi: 10.1056/NEJMp1006114
Brown, B. (2010). 25 Steps to Meaningful Use. JOURNAL OF HEALTH CARE COMPLIANCE, 12(3), 33-34. Retrieved from http://web.a.ebscohost.com.ezp.waldenulibrary.org/ehost/pdfviewer/pdfviewer?sid=ee93efdb-cbc6-40e6-8f77-bb0f1d0e3d4c%40sessionmgr4008&vid=1&hid=4212
Campbell, E. M., Guappone, K. P., Sittig, D. F., Dykstra, R. H., & Ash, J. S. (2009). Computerized provider order entry adoption: implications for clinical workflow. Journal of general internal medicine, 24(1), 21-26. doi:10.1007/s11606-008-0857-9
Dennis, A., Wixom, B. H., & Roth, R. M. (2014). Systems analysis and design. John Wiley & Sons.
McGonigle, D., & Mastrian, K. (2014). Nursing informatics and the foundation of knowledge. Jones & Bartlett Publishers.
Moore, P., Armitage, G., Wright, J., Dobrzanski, S., Ansari, N., Hammond, I., & Scally, A. (2011). Medicines reconciliation using a shared electronic health care record. Journal of patient safety, 7(3), 148-154. doi: 10.1097/PTS.0b013e31822c5bf9
