Current-State Workflow

This research paper would be focusing on more exploration to incomplete medical reconciliation as a gap that exists within the healthcare system. An in-depth research would be carried out to explain how it has a direct tie to the EHR system as well the goals intended to archive with the study if the incomplete medical reconciliation. There are a number of 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.

As stated above, the workflow issue that I would be exploring for my course project is on the incomplete medical reconciliation. Medical errors have been described to cause a number of patient injuries to a number of patients worldwide. The increased number of medical errors prompted a research study to establish how they can be reduced. Medical reconciliation as earlier described 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.

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. 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 is done by presenting pre-existing electronic medication sources that could be developed into an automated process. This optimism must be tempered with the understanding that system generated medication information may result in significant discrepancies; most commonly a medication listed in the EMR but no longer prescribed for the patient. EHR users should, however, be keen on the information which is retrieved from the system for example outpatient visit, electronic prescriptions, pharmacy benefits data, 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 clinicians conducting the medical reconciliation 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 PAML and existing orders during the discharge reconciliation process.

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 (Bayer et al., 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

1. Improve care coordination during transitions between sites of care

2. Improve decision-making at the point of care

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

They 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 a number of individuals within the system ranging from when a patient is admitted to the End. 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 rate 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 a stranger and 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.

References

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.

Bayer, S., Petsoulas, C., Cox, B., Honeyman, A., & Barlow, J. (2010). Facilitating stroke care planning through simulation modelling. Health Informatics Journal, 16 (2), 129–143

Dennis, A., Wixom, B. H., & Roth, R. M. (2015). Systems analysis and design (6th ed.). Hoboken, NJ: Wiley.

McGonigle, D., & Mastrian, K. G. (2015). Nursing informatics and the foundation of knowledge (3rd ed.). Burlington, MA: Jones and Bartlett Learning