Have you ever watched a movie in which the same scene was shown several times but as viewed by different individuals? Or, have you watched a detective show in which the witnesses all had differing accounts? The same can hold true for conducting an evaluation of a health information technology project. How you plan and conduct the evaluation is largely dependent on the viewpoint you assume and the perspective with which you approach the evaluation.
Consider a new patient discharge protocol at a small hospital. Do you want to know how the patient feels about the process? Do you want to gather the opinions of nurses who are using this process? Perhaps you want to determine if it is saving the hospital money by freeing up bed space in a more timely fashion. Obtaining each of these viewpoints would require a different approach. Depending on the goal of your evaluation, the model and viewpoint you opt to use will likely vary.
In this Discussion, determine which evaluation model would be most effective for evaluating the health information technology described in one of the scenarios below. Your Instructor will assign a specific scenario by Day 1 of this week.
- Scenario 1: You have recently provided a training program to help nurses and physicians become proficient in the use of a new bedside medication verification (BMV) system.
- Scenario 2: The Chief Medical Officer at your hospital is interested in finding out the impact of a new decision support system on the number of adverse events occurring in the past year.
- Scenario 3: You are helping with the design of a new outpatient surgery center to be built adjacent to the hospital. You are tasked with evaluating the opinions of physicians, nurses, and the general public toward this facility.
To prepare:
- Review the information on the types of evaluation models covered in this week’s Learning Resources.
- Determine which model would be most appropriate to use for evaluation in the scenario to which you were assigned.
- Consider why the viewpoint of the scenario or situation would impact the model used.
- View the scenario from a different viewpoint, and consider how a different model might be used.
- Reflect on the importance of basing an evaluation on a model.
By tomorrow 12/13/2016 at 9pm, post a minimum of 550 words in APA format with a minimum of 3 references from the list below, which include the level one headings as numbered below:
1) Post which scenario (1, 2, or 3) you were assigned and two different models that could be utilized to approach the evaluation.
2) Explain why you selected those models and how you would use them.
3) Explain why it is important to consider the intended goal of the evaluation and the viewpoint that is selected.
4) Finally, assess the importance of basing an evaluation on a model. Justify your response.
Required Readings
Technology Acceptance Model
Kowitlawakul, Y. (2011). The Technology Acceptance Model: Predicting nurses’ intention to use telemedicine technology (eICU). Computers, Informatics, Nursing, 29(7), 411–418.
Retrieved from the Walden Library databases.
Nurses encounter a variety of technological tools that are used in their field. This article explores the technology acceptance model and how it applies to nurses’ intention to use telemedicine technology.
Pai, F.-Y., & Huang, K. (2011). Applying the Technology Acceptance Model to the introduction of healthcare information systems. Technological Forecasting and Social Change, 78(4), 650–660.
Retrieved from the Walden Library databases.
This article focuses on the attempt to develop a model that will assist nurses in mastering the use of health information technology (HIT), thus enabling them to spend more time on patient care and less on clerical-type duties. The authors also studied how the use of HIT could increase patient safety.
Rippen, H. E., Pan, E. C., Russell, C., Byrne, C. M., & Swift, E. K. (2013). Organizational framework for health information technology. International Journal of Medical Informatics, 82(4), e1–e13.
Retrieved from the Walden Library databases.
In this article, the authors highlight results of a literature review on the implementation of health information technology and the related theories and models. Based on their research, the authors developed a framework of key areas that provides a structure to organize and capture information on the use of health IT.
Mohamed, A. H., Tawfik, H. M., Al-Jumeily, D., & Norton, L. (2011). MoHTAM: A Technology Acceptance Model for mobile health applications. Developments in E-systems Engineering (DeSE) Conference, 13–18.
Retrieved from the Walden Library databases.
In this article, the authors highlight a model they developed to determine how the decision to use a mobile health application is influenced by the design of the technology, the perceived ease of using it, and the perceived usefulness of the technology.
Diffusion of Innovations
Barnett, J., Vasileiou, K., Djemil, F., Brooks, L., & Young, T. (2011). Understanding innovators’ experiences of barriers and facilitators in implementation and diffusion of healthcare service innovations: A qualitative study. BMC Health Services Research, 11, 342.
Retrieved from the Walden Library databases
In this article, the authors describe the experiences of innovators in the medical field and the barriers that they have experienced in the implementation and diffusion of health care service innovations.
Kaissi, A. (2012). “Learning” from other industries: Lessons and challenges for health care organizations. Health Care Manager, 31(1), 65–74.
Retrieved from the Walden Library databases.
In this paper, the author explores how diffusion of innovations occurs in a variety of different industries and how these lessons can be adapted for use in the health care industries.
Thakur, R., Hsu, S. H. Y., & Fontenot, G. (2012). Innovation in healthcare: Issues and future trends. Journal of Business Research, 65(4), 562–569.
Retrieved from the Walden Library databases.
The medical field is a constantly evolving and improving. This article explores important innovations in the health care industry while highlighting certain issues and trends that may affect the future of the field.
Dickinson, A. D., & Scott, M. (2012). Diffusion of innovations in the National Health Service: A case study investigating the implementation of an electronic patient record system in a UK secondary care trust. In UK Academy for Information Systems (UKAIS) 17th Annual Conference, 27–28 March 2012, New College, Oxford. Retrieved from http://nrl.northumbria.ac.uk/6223/2/UKAIS_2012_paperDD_MS.pdf
This article examines a case study that focuses on the implementation of an electronic patient record system in a UK secondary care trust. In particular, the study highlights how new users adopt the system.
Valente, T. W., & Rogers, E. M. (1995). The origins and development of the diffusion of innovations paradigm as an example of scientific growth. Science Communication, 16(3), 242–273.
Copyright 1995 by Sage Publications Inc. Reprinted by permission of RISage Publications Inc. via the Copyright Clearance Center.
In this article, Valente and Rogers explore the origins and development of the diffusion of innovations paradigm. Through examining the different stages, it is possible to better understand how innovations are spread, accepted, and adopted within a health care organization.
Disruptive Innovation
Christensen, C. M., Bohmer, R., & Kenagy, J. (2000). Will disruptive innovations cure health care? Harvard Business Review, 78(5), 102–112.
Retrieved from the Walden Library databases
The health care field is constantly in need of new technologies to fill specific needs and niches. In this article, the authors discuss the role disruptive innovations could play in the development of the needed technologies.
Dhar, M., Griffin, M., Hollin, I., & Kachnowski, S. (2012). Innovation spaces: Six strategies to inform health care. Health Care Manager, 31(2), 166–177.
Retrieved from the Walden Library databases.
In this article, the authors use the disruptive innovation model as the framework to examine how innovation occurs in health care organizations. They determined six strategies to encourage innovation: dedicated times, formal teams, outside ideas, idea-sharing platforms, company/job goals, and incentives.
Poll, W. (2011). Derision is the sweet spot of adoption: Unleashing disruptive growth. Hospital Topics, 89(1), 23–25.
Retrieved from the Walden Library databases.
It is common that many people look at change and new technologies with a hint of disdain or distrust. The author of this article discusses how new ideas and disruptive innovations can be effectively presented to a somewhat hesitant organizations.
Sociotechnical Theory Models
Ancker, J. S., Kern, L. M., Abramson, E., & Kaushal, R. (2012). The Triangle Model for evaluating the effect of health information technology on healthcare quality and safety. Journal of American Medical Informatics Associations, 19(1), 61–65.
Retrieved from the Walden Library databases.
The authors of this article explain the Triangle Model for designing studies on the safety and quality outcomes of health information technology projects. The article focuses on the predictors of the model, including attributes of the technology in question, the technology provider, the organizational setting, and the population involved.
Currie, L., Sheehan, B., Graham, P., Stetson, P., Cato, K., & Wilcox, A. (2009). Sociotechnical analysis of a neonatal ICU. Studies In Health Technology and Informatics, (146), 258–262.
Retrieved from the Walden Library databases.
In this article, the authors provide a brief overview of sociotechnical theory. The authors also describe the results of a sociotechnical analysis of a neonatal intensive care unit.
Molleman, E., & Broekhuis, M. (2001). Sociotechnical systems: Towards an organizational learning approach. Journal of Engineering and Technology Management, 18(3), 271–294.
Retrieved from the Walden Library databases.
The authors of this article explore the application of sociotechnical systems (STS) theory for designing work processes to improve organizational performance. The authors examine the application of STS with four organizational performance indicators: price, quality, flexibility, and innovation.
Scott‐Findlay, S., & Estabrooks, C. A. (2006). Mapping the organizational culture research in nursing: A literature review. Journal of Advanced Nursing, 56(5), 498–513.
Retrieved from the Walden Library databases.
This article provides an empirical review of the nursing literature on organizational culture and its influence on practitioners.
