course material

1. Common Models in Health Informatics Evaluation
Common Models in Health Informatics EvaluationHave 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

2. 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 databasesIn 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.pdfThis article examines a

3. 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 databasesThe 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

4. 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.