Assignment: Evaluation Plan Project: Select a Case Study and Model

Assignment: Evaluation Plan Project: Select a Case Study and Model

Assignment: Evaluation Plan Project: Select a Case Study and Model

Case studies are valuable tools in academics as well as in professional practice. Case studies illuminate how products or services can be applied, or how innovation or disruption can be managed. Case studies enable learners and practitioners to apply critical thinking while finding ways to develop solutions to problems.

Much like travelers might apply the lessons learned from previous visitors to their own plans to visit destinations, case studies can help researchers and practitioners to develop plans, either by applying lessons learned from past shared experiences or by practicing analysis skills necessary to develop effective plans. Similarly, case studies can help those developing health information technology (HIT) evaluation plans by guiding their application of a specific evaluation model to their own plans.

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In this Assignment, you reflect on Root cause analysis, usability, questionaires, and technology acceptance evaluation models and select one for application to the case study Early Implementation Problems of an Integrated Information System within the White Mountain University Health System , and compare this to the other applicable models.

In a 3- to 4-page paper, address the following:

Provide a brief, 1- to 2-paragraph summary of the case study.
Describe the model selected for your evaluation of the case study you selected.
Justify your choice by comparing your selected model to at least three of the other evaluative models .

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Evaluation Plan Project (Selecting a Case Study and Model): Early Implementation Problems of an Integrated Information System (IIS) within the White Mountain University Health System (WMUHS)  

            The report of the Institute of Medicine (IOM) in 1999 that was titled To Err Is Human was an eye opener to the healthcare provider fraternity because it revealed just how deep the problem of human errors in healthcare was (Palatnik, 2016). The report revealed that between 44,000 and 98,000 patient deaths annually could be attributed to preventable errors by healthcare personnel in US hospitals. The overwhelming recommendation after these damning findings was that technology should be embraced by the healthcare sector to help reduce unintentional human errors. Since then a lot of strides have been taken in terms of legislation and other policies to mandate the use of technology in healthcare. Of note here is the Health Information and Technology for Economic and Clinical Health Act or HITECH, signed into law in 2006 by President Barack Obama (Sweeney et al., 2017). This law began by mandating the use of certified electronic health record technology (CEHRT) systems through the meaningful use (MU) provision. Later on as the systems became better designed, vendors started selling health information management (HIM) systems that were better integrated than before. These new integrated systems had interfaces and components such as Computerized Decision Support (CDS), Computerized Provider Order Entry (CPOE), Bar-Code Medication Administration (BCMA), electronic Medication Administration Record (eMAR), and Patient Data Management Systems (PDMS) amongst others (Alotaibi & Federico, 2017; McGonigle & Mastrian, 2017). The purpose of this paper is to evaluate such an implementation program of an integrated information management system in a large healthcare organization, using the technology acceptance model (TAM).

Summary of the Case Study

            The case study in this paper is that of the White Mountain University Health System (WMUHS). This is a large tertiary healthcare organization that currently has many different and disconnected health information systems for different departments. This lack of internal interoperability has resulted inevitably to care fragmentation within the organization itself. For instance, one of the regular patients with multiple comorbidities and who is on polypharmacy comes for review of treatment but her medical records cannot be traced. This presents a challenge to the doctor seeing her as he cannot make any treatment decisions without knowing what the patient is on at the moment. She had earlier been referred to a cardiologist who also prescribed his own medications.

            This inconvenience and danger posed by having disparate systems for different departments had been noted by the organization’s end users and administrators and plans were already underway to purchase and implement an integrated information system (IIS). Doctors, nurses, and other end users at WMUHS had been involved in giving suggestions on clinical system requirements. In the end, a vendor was settled on to provide the system. However, the implementation was divided into 4 phases and it was to be completed after seven years. This did not go down well with the end users especially the doctors who insisted that their problems were current and needed urgent solutions. Some even suggested buying their own better systems as departments. This was however not going to be feasible since some departments were making more money than others.

Model Selected for the Evaluation of the Case Study

            The model selected for the evaluation of the case study is the technology acceptance model or TAM (Rahimi et al., 2018). The technology adoption willingness and buy-in of healthcare clinical staff as well as patients is usually assessed or evaluated by using one of several models. The technology acceptance model or TAM is one of the most used for this purpose. TAM was introduced in 1989 and has undergone many modifications to make it even better in terms of its predictive value for the adoption of technology in healthcare and other fields.

            The TAM model relies on the concept of perceived usefulness (U) and perceived ease of use (E). These two are influenced by different external variables or factors. Perceived usefulness may then lead directly to a behavioral intention to use (BI). Alternatively, it together with perceived ease of use may first just lead to the development of an attitude toward using (A). This may later lead to a behavioral intention to use. From a behavioral intention to use the last stage or step in this acceptance cascade is the actual system use (Rahimi et al., 2018). At the stage of actual system use, the stakeholder has already accepted the system and its implementation. By this time, all or most of their reservations will have already been addressed.

Justification of Choice

            The justification for the above choice of TAM for this organization in the case study (White Mountain University Health System) is that TAM is systematic and works well in its predictive value when used to evaluate technology acceptance in large organizations. The other reason is that it has also been around for several decades having been introduced in 1989. This has given it a chance to be refined over the years such that it is more reliable and valid in its results. The White Mountain University Health System is a large organization that has many stakeholders who are currently disgruntled with the slow pace of implementation of the integrated information system or IIS. This is why only a thorough and tried and tested model such as TAM is required for evaluation of level of acceptance.

Comparing TAM to Three Other Evaluative Models

            Lastly, this section presents a comparison of TAM and the other three evaluative models that can be used as alternatives to gauge the acceptance of innovative technologies in healthcare by stakeholders. These other three are root cause analysis, questionnaires, and usability evaluation.

            Root cause analysis works on the basis that systematically solving system issues is much better than merely waiting for a problem to occur then reacting to it (Tableau, 2022). In this case study, it differs with TAM in that it would have looked for the root causes of the system problems within WMUHS and solved them before they multiplied and became overwhelming as they are now. Usability evaluation on its part lays emphasis on the degree of efficiency of end users in learning and utilizing the innovative technology to achieve organizational and professional goals (Usability.gov, 2022). Lastly but not least, questionnaire evaluation involves designing some questions that the stakeholders will respond to then they get scored. As a rule, these are usually Likert-type questionnaires. All these three are however similar to AM in that they are all predictive models to technology acceptance in organizations.

Conclusion

            Technology in healthcare has had a profound impact in reducing human errors and facilitating the protection of patient safety. However, acceptance of these novel technologies is not always without problems. There are usually stakeholders who feel reluctant to accept the change for one reason or another. For this reason, there are models that have been tested that evaluate and predict the level of acceptance of such a technology by the organization’s stakeholders such as nurses, physicians, and patients. This paper has looked at the evaluation of acceptance of an integrated information system (IIS) by the technology acceptance model (TAM) in the tertiary healthcare organization named White Mountain University Health System or WMUHS.     

References

Alotaibi, Y., & Federico, F. (2017). The impact of health information technology on patient safety. Saudi Medical Journal, 38(12), 1173–1180. https://doi.org/10.15537/smj.2017.12.20631

McGonigle, D., & Mastrian, K.G. (2017). Nursing informatics and the foundation of knowledge, 4^th ed. Jones & Bartlett Learning.

Palatnik, A. (2016). To err is human. Nursing Critical Care, 11(5), 4. https://doi.org/10.1097/01.CCN.0000490961.44977.8d

Rahimi, B., Afshar, H.L., Timpka, T., & Nadri, H. (2018). A systematic review of the technology acceptance model in health informatics. Applied Clinical Informatics, 09(03), 604–634. https://doi.org/10.1055/s-0038-1668091 

Sweeney, J. (2017). Healthcare informatics. Online Journal of Nursing Informatics (OJNI), 21(1). https://www.himss.org/library/healthcare-informatics  

Tableau (2022). Root cause analysis explained: Definition, examples, and methods. https://www.tableau.com/learn/articles/root-cause-analysis#:~:text=Root%20cause%20analysis%20(RCA)%20is,symptoms%20and%20putting%20out%20fires

Usability.gov (March 17, 2022). Usability evaluation basics. https://www.usability.gov/what-and-why/usability-evaluation.html#:~:text=Usability%20Evaluation%20focuses%20on%20how,related%20to%20a%20new%20site