Poster presentation

Title of Project

Presenter Name

University name

Introduction and Problem

Variables

Descriptive Data

Results

Results (cont.)

Clinical Questions/PICOT

Discussion

Project Limitations

Conclusion and Recommendations

Purpose of the Project

The data analysis was in line with the needs of the project: statistical tests, including t-test and Wilcoxon signed ranks, were employed to determine if there were statistically significant differences between pre- and post-test measurements. This way, the relationships between the independent and dependent variables were reliably inferred (Polit & Beck, 2017)

Data types:

Survey: quantitative, ordinal (Likert scale).

Reports: quantitative, ratio (number of mistakes).

Data analysis approaches:

Software: SPSS.

Survey: Wilcoxon signed ranks test.

Reports: paired t-test.

Data Analysis

The project employed four Advanced Practice Registered Nurses, three Medical Doctors, and one Physician Assistant who exhibited significant resistance to the use of EHR.

References

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Several studies have shown the benefits of the use of electronic health records (EHR) for patients’ safety, as well as their ability to improve efficiency in primary care settings (Porterfield, Engelbert, & Coustasse, 2014). Regardless of the positive effects of the implementation of EHR, health care providers have moved slowly to adopt this technology (King, Patel, Jamoom, & Furukawa, 2014). Practitioners who do not want to adopt EHR, especially electronic prescription, can endanger patient safety.

Medication errors, in turn, are a serious issue that causes numerous safety incidents in primary care. Studies have shown that the use of EHR significantly reduces the number of prescription errors that can harm patients (Liao et al., 2017). Palabindala, Pamarthy, and Jonnalagadda (2016) showed that the use of EHR could reduce medication error while also resulting in improved communications between patients and healthcare teams

The purpose of this quantitative quasi-experimental project was to determine if there was a relationship between the application of an educational program and the improvement of practitioners’ perception of EHR usability, as well as the reduction of the number of prescription medication errors, at a medical group practice in the Southeastern of the United States (US).

The PICOT question created for the project was as follows: (P) Among healthcare practitioners, (I) how does the implementation of an educational program in a primary care medical center in the Southeast of the US (C) compared to the pre-intervention measurements in the prior four weeks (O) influences primary care practitioners’ perceptions of the usability of EHR and the incidence of prescription medication errors (T) within four weeks of participating in the program?

The following clinical questions guide this quantitative project:

Q1: How does the implementation of an educational program influence the perceptions of primary care practitioners regarding EHR usability?

Q2: How does the implementation of an educational program influence prescription medication error incidence?

Variable 1: Quality improvement educational program (independent)

Variable 2: Primary care practitioners’ perception of EHR usability (dependent)

Variable3: Number of prescription medication errors (dependent).

The educational program can enhance the participants’ perceptions regarding EHR, but the described project cannot reject the null hypothesis that the intervention had no effects on the medication error rates. However, since the project was constricted by significant limitations, this finding is not conclusive.

Some of the research recommendations include the proposal to increase the sample size, have a greater timeframe for future projects, and consider randomizing the sample into two groups.

The project can also be used to recommend educational EHR efforts for the reduction of EHR resistance and the specific program that has been tested for the same purpose.

The sample was small (8 participants) and could not be expanded because the facility was small.

The data collection process was limited by the short time allocated to observing the results (4 weeks)

The project employed a quasi-experimental design. Since its sample was so small, trying to split it further was not feasible.

King, J., Patel, V., Jamoom, E. W., & Furukawa, M. F. (2014). Clinical benefits of electronic health record use: National findings. Health Services Research, 49(1pt2), 392–404. doi: 10.1111/1475-6773.12135

Liao, T. V., Rabinovich, M., Abraham, P., Perez, S., DiPlotti, C., Han, J., ... Honig, E. (2017). Evaluation of medication errors with implementation of electronic health record technology in the medical intensive care unit. Open Access Journal of Clinical Trials, 9, 31-40. doi: 10.2147/OAJCT.S131211

Porterfield, A., Engelbert, K., & Coustasse, A. (2014). Electronic prescribing: Improving the efficiency and accuracy of prescribing in the ambulatory care setting. Perspectives in Health Information Management, 2014, 1-13

Palabindala, V., Pamarthy, A., & Jonnalagadda, N. R. (2016). Adoption of electronic health records and barriers. Journal of Community Hospital Internal Medicine Perspectives, 6(5), 1-3. doi: 10.3402/jchimp.v6.32643

Polit, D.F., & Beck, C.T. (2017). Nursing research: Generating and assessing evidence for nursing practice (10th ed.). Philadelphia, PA: Lippincott, Williams & Wilkins.