Hospital Administration Teams, Research Paper Example

Hospital administration teams claim that a major advantage of electronic health record (EHR) systems is that they allow health care professionals to quickly access patient records (Menachemi et al., 2011). Furthermore, these systems provide these individuals a means to determine the medications that a patient has been prescribed during their hospital stays and asses potential drug interactions before offering a new prescription. As a consequence, a potential benefit of EHR use is the ability to prevent against medication errors to a greater extent than the paper record system allowed (Academy of Managed Care Pharmacy, 2010). Although many administration teams claim that the reduction of medication errors is a benefit of health information technology systems, there has been little evidence-based research indicating that this phenomenon reflects reality. Therefore, it is necessary to ask the question “Do health information technology systems reduce medications errors in patients of all ages compared to the common paper systems used in the past?”

To determine whether health information technology systems help reduce medication errors to a greater extent than paper systems, it would be necessary to design a comparative study that determines the rate of medication errors in a healthcare setting that utilizes EHR systems compared to a system that still utilizes paper records. In order to control for variables, it would be necessary to conduct a randomized trial within the same healthcare institution. A minimum of 500 patients should be utilized for this study to ensure that it has valuable statistical power, with 250 patients randomized to a group that will require their healthcare providers to document their cases utilizing paper records and the remaining 250 patients will be randomized to a group that will require their healthcare providers to document their cases utilizing electronic records. All research should be done within the inpatient ward in order to ensure that medical decisions can be tracked over a longer period of time.

Both qualitative and quantitative methods will be necessary to understand the results from such a project. While it is necessary to generate an understanding of statistical measures to be able to objectively compare the study groups, it is important to consider that different medication errors hold different value and this information is best described quantitatively. A major quantitative analysis that should be performed to analyze the results of this study is a determination of the data trends in both the experimental and control group. After determining the rate in which medication errors are made for each individual (in terms of errors per hour in the hospital), it would be beneficial to determine the mean, median, range, mode, and standard deviation of these values separately for each group in order to gain a greater understanding of the information spread. Once the data can be classified as reflecting a normal curve or deviating from this, further statistical analyses can be decided upon.

To compare whether there is variation between the two groups, either the student’s t-test or its non-parametric equivalent should be used. To gain a greater understanding of this data, these analyses should be reconsidered using person-years in lieu of considering each participant individually (Brinks, 2011). This will indicate the total number of mistakes that occur over a period of time rather than for each individual, which is equally useful to a hospital that wishes to determine whether it should change its practices. The null hypothesis for all statistical tests will be that the rate of medication error for patients whose records are kept using the electronic record system will be identical to the rate of medication error for patients whose records are kept using the paper system. The alternative hypothesis will state that the rate of medication error for patients who are kept using the electronic record system will be less than the rate of medication error for patients whose records are kept using the paper system.

A qualitative analysis should be formed to track the severity of the mistakes made by using either recording system and then associating these mistakes with either recording option. Participating healthcare professionals will be required to record the reactions of their patients to the medication error, in terms of symptoms and degree of satisfaction with the hospital. In each case that a medication error is made, the error will be documented in addition to providing a description of the changes that were made to rectify this situation. All descriptions will be coded to indicate whether the change had minimal impact on the health of the patient, whether the change has a slight impact on the health of the patient, whether no change was observed, whether the error was slightly beneficial to the patient, or whether the error was very beneficial to the patient. All participating healthcare professionals will work together to code these descriptions to ensure that a consensus is utilized during the analysis allowing the errors made in each category to reflect the same value. This information will be used to determine the extent to which medication errors are made using either paper recording or electronic recording system.

This study will be evidence-based in that the research design is heavily dependent upon observations that have been made concerning the comparison of electronic record systems and paper systems in the past. However, it will conclusively demonstrate that paper record systems have no place in the current hospital system. It is important for healthcare professionals to keep close track of the medications they prescribe, and this is done more effectively if all workers have instant access to identical records. While it is unavoidable that mistakes will be made due to human and recording error, the implementation of electronic records make it easier to catch these errors (Fernandopulle et al., 2010). The quantitative and qualitative evidence gained from this study will work hand in hand to demonstrate this phenomenon.

References

Academy of Managed Care Pharmacy. (2010). AMCP’s Framework for Quality Drug Therapy. Retrieved from http://www.fmcpnet.org/index.cfm?p=132D8447

Brinks R. (2011). A new method for deriving incidence rates from prevalence data and its application to dementia in Germany. Institute for Biometry and Epidemiology. Retrieved  fromhttp://arxiv.org/pdf/1112.2720.pdf

Fernandopulle R, Patel N. (2010). How The Electronic Health Record Did Not Measure Up To The Demands Of Our Medical Home Practice. Health Affairs, 29(4): 622-628.

Menachemi N, Collum TH. (2011). Benefits and drawbacks of electronic health record systems. Risk ManagHealthc Policy, 4: 47–55.