Introducing Electronic Patient Records to Hospitals

Healthcare is on of the industries that is currently fast adopting information technology (IT) into use. Electronic patient records (EPRs) are at the hearth of healthcare information technology applications. However, patient data is seldom efficiently organized even within one organization, and when patient data is needed in applications covering several organizations, the situation becomes even more complicated. We draw some lessons on how EPR systems should look like from the customer relationship management literature point of view: After all, patients are the customers of healthcare institutions. As a guiding framework for this analysis we use the concepts developed by (Winter, Ammenwerth, et al,. 2001). Then we proceed to discuss how EPR systems diffuse in the healthcare industry and use the Internet standards adoption (ISA) model presented by (Hovav, Patnayakuni, et al., 2004) as a starting point. We apply this model to the diffusion of EPR systems in the healthcare industry. We found big differences between customer relationship management and EPRs management. Customer relationship management aims at long-term relationships and customer profitability, which are not strong goals for EPR systems. Our analysis too resulted to the conclusion that the practical innovation adoption bath for EPRs over paper-based patient records is that of adoption through coexistence.

Computer and Stress in Social Healthcare Industries

Social and healthcare industries offer demanding occupations, as they are very human-contact intensive workplaces and, moreover, the customers are usually met in critical and not-wished-for situations. Possible actions are many, and seldom are there clear procedures on how to continue: Each customer contact is a place for genuine decisions. Add to this deliberate service situation a computer, and you can count on difficulties. Our focus is on how information systems affect the stress levels of health and social-care workers. Our empirical study shows–among many other factors–strong correlation between the use of computers and stress levels in the healthcare professions: The more computer use, the more stress. Wediscuss what could be done to manage stress levels in relationship to computer use in health and social-care industries. In conclusion, we wrap the research findings together and propose our extensions to the current knowledge on the relationship between stress and information systems in health care. Our most important finding is that when users understand the total collaborative work setting, computer work obtains meaning, and stress levels reduce.

Predicting Internet Use

The technology acceptance model (TAM; Davis, 1989) has been widely used by information technology researchers to gain a better understanding of information technology (IT) adoption and its use in organizations. While TAM has been applied and tested in academic and corporate settings, involving students, business managers, and clerical and administrative types as participants, few studies have evaluated TAM in the healthcare environment. This chapter examines the applicability of the extended technology acceptance model (TAM2; Ventkatesh & Davis, 2000) in the context of physicians’ intention to adopt Internet-based health applications. Data was collected in a survey of pediatricians to see how well the extended model fits in the medical sector. This chapterdiscusses the implications, limitations, and possible explanations for the inconsistent results found within the model when applied to such professional users as physicians.

Evaluation of Health Information Systems

This chapter summarizes the problems and challenges that occur when health information systems are evaluated. The main problem areas presented are the complexity of the evaluation object, the complexity of an evaluation project, and the motivation for evaluation. Based on the analysis of those problem areas, the chapter then presents recommendations of how to address them. In particular, it discusses in more detail what benefits can be obtained from applying triangulation in evaluation studies. Based on the example of the evaluation of a nursing documentation system, it shows how both the validation of results and the completeness of results can be supported by triangulation. The authors hope to contribute to a better understanding of the peculiarities of evaluation in healthcare, and to provide information how to overcome them.

The Evaluation Roadmap

(Extracted from Ammenwerth. E., Brender, J., Nykänen, P., Prokosch, H., Rigby, M., & Talmon, J. [2004]). Visions and strategies to improve evaluation of health information systems Reflections and lessons based on the HIS-EVAL workshop in Innsbruck. International Journal of Medical Informatics, 73, 479-491.) Results from the European Science Foundation sponsored Workshop on Systematic Evaluation of Health information Systems (HIS-EVAL), April 4-6th, 2003. Participants: Jos Aarts, Elske Ammenwerth, Andrea Berghold, Marie-Catherine Beuscart-Zéphir, Jytte Brender, Thomas Bürkle, Martina Deibl, Martin Denz, Nina Eminovic, Rolf Holle, Mathew Jones, Joe Liu, Christian Nøhr, Pirkko Nykänen, Ulrich Prokosch, Michael Rigby, Cornelia Ruland, Heike Sander, Nikki Shaw, Arjen Stoop, Jan Talmon, Vivian Vimarlund, Jeremy Wyatt. Initiator and contact point: Elske Ammenwerth, MIT-University for Health Sciences, Medical Informatics and Technology, [email protected]

Quantitative and Qualitative Method

Contrary to what would be expected, the increasing application of patient care information systems hardly resulted in well-defined, methodical purchase or development and implementation trajectories. Together with the lack of thorough evaluations in daily practice, this was an important motivation to the development, implementation and evaluation of the studied electronic patient record. It is a problem that both successful and failed electronic patient record projects are seldom evaluated. This is a problem, because failures and successes can provide relevant information about system qualities, system requirements, important aspects of implementations, and so forth. A second problem is that the methods to evaluate are not yet fully developed as well as the content of evaluations. Clearly, this impedes evaluation practices. To contribute to solutions for both problems we did a case study in the field of neurology. We developed, implemented and evaluated an electronic patient record for stroke with qualitative and quantitative methods. The evaluation started before the development phase and ended after a trial period in daily practice. It was based on an evaluation framework (van der Meijden, Tange, Troost, & Hasman, 2003). The results of the evaluation showed that the previously described framework was applicable in evaluating electronic patient records. It was possible to assess attributes that represented the quality of record keeping, the impact on daily work, the opinions of nurses and physicians about electronic record keeping and the experiences of management. The analysis of these attributes provides insight in why the electronic patient record was successful in some aspects and was less successful in others. They also showed that the combination of questionnaires, interviews, chart reviews and observations in an evaluation provided deeper insight in reasons for use or non-use of an electronic patient record than one single method would have. Results collected with one method can supplement result– regarding the same subject–collected with another method.

USE IT

This chapter is the heart of the book and reflects five years of research on diffusion of e-health systems. The resulting USE IT model has four determinants that have to be balanced in assessing the diffusion and use of information systems. Resistance is defined as the degree to which the surroundings and locality negatively influences the users of IT and the degree to which IT-users themselves are opposing or postponing the IT change. The result of this study was that opposite to what was hypothesized,

USE IT Interview-Protocol

Interview questions.

The Dynamics of IT Adoption in a Major Change Process in Healthcare Delivery

This chapter deals with the qualitative theory of information systems success. First, the definition of success used in this research will be given. Then, the theory on diffusion of innovations and success of information systems will be discussed to reveal what factors determine the successful implementation of information systems as far as the product and the user are involved. The outcome of this part of the literature study will be used in the construction of the USE IT model, in Chapter IX.

Assessing E-Health

While healthcare is the biggest service industry on the globe, it has yet to realize the full potential of the e-business revolution in the form of e-health. This is due to many reasons, including the fact that the healthcare industry is faced with many complex challenges in trying to deliver cost-effective, high-value, accessible healthcare and has traditionally been slow to embrace new business techniques and technologies. Given that e-health to a great extent is a macro-level concern that has far reaching micro-level implications, this chapter first develops a framework to assess a country’s preparedness with respect to embracing e-health (i.e., the application of e-commerce to healthcare) and from this, an e-health preparedness grid to facilitate the assessment of any e-health initiative. Taken together, the integrative framework and preparedness grid provide useful and necessary tools to enable successful e-health initiatives to ensue by helping country and/or organization within a country to identify and thus address areas that require further attention in order for it to undertake a successful e-health initiative.