Good Electronic Medical Record Systems Essay Example

Introduction

Electronic medical record system is one area of health information technology that can be used to enhance medical services by health informatics professionals. This involves the use of computerized system to control medical operations in such a way that effectiveness is improved in terms of throughput and response tone as well as accuracy. The use of automated medical system is also expected to improve the quality of health care services. Consequently, improved savings have been achieved in the course of implementing electronic medical record (EMR) systems with an aim of improving office environment practice by the physician in Canada (Lau et al., 2012)

Part A: Literature review for Electronic medical record systems

There are logical reviews concerning the use of information technology based electronic medical record system (EMRs) in primary care as well as in the common settings in practice. This type of system can be used for effective management of diabetes, improvement of quality for patient records, decision support tools, and electronic communication and to enhance provider performance in addition to patient outcomes. Nevertheless, various issues reported in past research concerning EMRs include accuracy of content in the patient record, variable consistency, the need for sufficient training and support as well as lack of time and funding to manage or deal with the changing technology. The electronic health record system can be a stand alone or can be integrated with other large health maintenance organizations which have EMRs that are interconnected with multiple hospitals and other clinics (Lau et al., 2012).
The impact of this system is its adoption and the effect on physician practice, depending on evaluation measures employed in studies. The success of automated medical record system can be described as the enhancement that EMRs can make within the office of physician. In general, the success of EMRs relies on having strong EMR aspects that supports the ongoing clinical operations by paying close attention to interface design. Secondly, the success can also be achieved by redesigning work support for electronic automated record practices for maximum fit by means of reorganizing clinical work flow so as to make complete use of enhanced EMR features. Third is by having practical anticipation on the EMR effort of implementation by setting realistic goals and putting in the time, commitment and resources necessary. Forth is by demonstrating the value of money in order to encourage EMR adoption. Last but not least, the success of EMR system can be achieved by engaging patients in the process for with the main aim of improving the overall encounter experience (Lau et al., 2012).
Electronic medical record has also become a promising opportunity for the investment of the governments in several countries following the increasing mobility of the population. EMR oriented project normally involve large grant and require tight management of output. Nevertheless, the majority of measuring tools for the quality of paper based medical records centered on the format of data in addition to compliance with law. This may not be adequate and sufficient in measuring the quality of EMRs. Data quality, data model quality, data content quality and information quality are the constructs of EMR quality. However, only the quality of data content and information can affects user satisfaction considerably (Chang et al., 2012).
The electronic medical record systems thus engage in the development of approaches and best practices for the use of automated medical records as a tool for genomic research. This implies that clinical data gotten from the electronic medical records can be employed successfully for genomic research (Gottesman et al., 2013). The electronic health records such as EMR system are associated with higher achievement and with greater improvement in care and outcomes. This improvement also cuts across all insurance type (Cebul et al., 2011). The implementation of EMR can also be used to improve on team care which can then be updated very fast, permitting teams to customize notes, order sets, flow sheets and many more. The team can then meet after a pre-determined period of time to discuss enhancements to EMR and communication (Mitchell et al., 2012), The system can also be used by patients in reporting their health in terms of symptoms, physical functioning and mental health (Bennett, Jensen & Basch, 2012).

Part B: How to assess the effectiveness of automated medical Record system

Performing a needs assessment for the project
The needs assessment can be carried out by using or designing questionnaire for patient reported outcome and for all other users of the electronic medical record system. Different users and stakeholders are thus made to supply their respective responses in the questionnaire which mainly contains questions targeting the requirements of the system as per the needs of the organization, hospital or clinic.

How to formulate research question

The research question is formulated by stating it as a simple statement to understand. The statement is geared towards the problem statement. The research question is also made to appear as one problem to be solved and not a class of several problems since this may increase the complexity of it. The research question in simple terms should be made specific to the problem in question.

How to develop hypotheses

I will develop the hypotheses by considering two options which include accepting the problem or rejecting the problem stated in the research question. This results to two statements to be proved by the results of the research. The accept statement will be termed as the null hypotheses while the reject statement (the negative part of it) becomes the alternative hypotheses. The results of the research will thus lead to either accepting the null hypotheses or rejecting it(accepting the alternative hypotheses). For example, if the null hypotheses reads,” The ERM system is of high and expected quality”, then the opposite of it becomes the alternative hypotheses which will read as, “ The ERM system is not of high and expected quality”( Persons, 2012).

The purpose of your research

The purpose of the research is to investigate the effectiveness of automated medical record systems used by health informatics professionals in the management of patient’s health records. The system being effective will imply that it meets the right or expected quality of data content and information as far as patient reported outcome is concerned, else the system is considered ineffective.

Research method best fit the situation

Qualitative method of research will be best for this situation. This is because of measurement parameters such as quality of the system as well as effectiveness which cannot be quantified. For this reason it is not clear how generalizations are made on the basis of qualitative research. In addition, the results gotten in qualitative research can be used to get anecdotal evidence although neither point estimates nor values of confidence intervals can be used for this kind of result (Lewis-Beck, Bryman & Liao, 2013).

What to be measured and measurement method

Parameters to be measured include EMR quality, system efficiency, effectiveness, accuracy, reliability. Quality is to be measured in terms of data content, information quality,, data model and knowledge quality. All these parameters are to be looked at in terms of measurement of patient reported outcome (PRA) using electronic evaluation system within the setting of clinical care.

Benefit of one data collection tool to use

Questionnaires can be better for requirements gathering in this case. This is because questionnaires can be structured with simple and straight forward questions. The questions in this case can be structured for direct answers from the respondent thus avoiding double standard or complicated responses. Questionnaires are also more convenient as compared to other methods like interviews. This is because they can be distributed to respondents and collected later at will without interfering with respondents during their work sessions. They can also be used for large coverage by receiving responses from as many respondents as possible which is very difficult with interviews.

How to analyze the data gathered

The data gathered will be analyzed statistically by arranging the data collected into tables. The data graphs or charts can then be created from the tabulated data. The summary computation statistics can also be carried out for the data such as total frequency and other relevant statistical parameters.

How to draw conclusions

Conclusions will be drawn based on the accuracy and quality of the existing system based on collected data. The data collected can be used to determine data content quality, data model quality, information quality and knowledge quality of the system. If these qualities do not meet the expected standard, then conclusion can be drawn to recommend the upgrade of the system or develop a fresh system for the organization, else the current system is maintained.

References

Lau, F., Price, M., Boyd, J., Partridge, C., Bell, H., & Raworth, R. (2012). Impact of automated medical record on Office setting for the physician practice: a systematic review. BMC medical informatics and decision making, 12(1), 10.
Gottesman, O., Kuivaniemi, H., Tromp, G., Faucett, W. A., Li, R., Manolio, T. A., & eMERGE Network, T. (2013). The Electronic Medical Records and Genomics (eMERGE) network: past, present, and future. Genetics in Medicine, 15(10), 761-771.
Cebul, R. D., Love, T. E., Jain, A. K., & Hebert, C. J. (2011). Electronic health records and quality of diabetes care. New England Journal of Medicine, 365(9), 825-833.
Mitchell, P., Wynia, M., Golden, R., McNellis, B., Okun, S., Webb, C. E., & Von Kohorn, I. (2012). Core principles & values of effective team-based health care. Washington, DC: Institute of Medicine.
Bennett, A. V., Jensen, R. E., & Basch, E. (2012). Electronic patient‐reported outcome systems in oncology clinical practice. CA: a cancer journal for clinicians, 62(5), 336-347.
Persons, J. B. (2012). The case formulation approach to cognitive-behavior therapy. Guilford Press.
Lewis-Beck, M. S., Bryman, A., & Liao, T. F. (2013). Encyclopedia of Social Science Research Methods.