A 15-facility healthcare organization utilized organizational change management techniques to aid with the adoption of a clinical information system to accomplish desired cultural transformation. The aim of this article was to provide a description of team member and physician attitudes toward change during conversion to a new clinical information system of electronic documentation. The tool developed and utilized was a change readiness survey to assess randomly selected team member and physician perceived readiness for the transition to an electronic documentation system. This article reviewed the rationale for using organizational change management techniques to facilitate adoption of a new clinical information system and discussed development of a change readiness survey tool. It explored the findings from the first 3 years of the survey.

Health care providers report several stressors related to the use of electronic healthrecord (EHR) systems to complete clinical documentation. These stressors include frustrations resulting from time-consuming and cumbersome interaction with the EHR. Speech recognition(SR) has been suggested as a way to help reduce this stress. Consensus is lacking in the research regarding the effect of SR on clinical documentation quality, and the research that has been conducted is primarily quantitative.The purpose of this study was to increase understanding of how the use of SR changes the work of completing clinical documentation and to identify strategies that would facilitate the implementation and use of SR for documentation. Additionally the study aimed to examine how the use of SR is perceived to impact clinical documentation quality. Qualitative methods were employed. Four physicians (three radiologists and one internist) with experience of using SR to complete documentation participated insemi-structured interviews. The results showed that an internist reported increased time spent on documentation due to the need to proofread and correct errors. Radiologists reported experiencing no significant change in the amount of time spent completing documentation. All physicians experienced an increased rate of errors and increased effort needed for proofreading documentation generated via SR. Physicians reported worries arising from the increased error rate to be a source of stress. A set of strategies to improve users’ experience of SR was developed based on physicians’ experiences, and issues to consider when healthcare organizations implement the use of SR for documentation were identified. Uncorrected SR errors, the ability to see the text while using SR and the immediacy that results from eliminating turn-around time were found to affect physicians’ perception of their documentation quality.

Access to information is fundamental in health care. This thesis presents research on Swedish medical records with the overall goal of building intelligent information access tools that can aid health personnel, researchers and other professions in their daily work, and, ultimately, improve health care in general. The issue of ethics and identifiable information is addressed by creating an annotated gold standard corpus and porting an existing de-identification system to Swedish from English. The aim is to move towards making textual resources available to researchers without risking exposure of patients’ confidential information. Results for the rule-based system are not encouraging, but results for the gold standard are fairly high. Affirmed, uncertain and negated information needs to be distinguished when building accurate information extraction tools. Annotation models are created, with the aim of building automated systems. One model distinguishes certain and uncertain sentences, and is applied on medical records from several clinical departments. In a second model, two polarities and three levels of certainty are applied on diagnostic statements from an emergency department. Overall results are promising. Differences are seen depending on clinical practice, annotation task and level of domain expertise among the annotators. Using annotated resources for automatic classification is studied. Encouraging overall results using local context information are obtained. The fine-grained certainty levels are used for building classifiers for real-world e-health scenarios. This thesis contributes two annotation models of certainty and one of identifiable information, applied on Swedish medical records. A deeper understanding of the language use linked to conveying certainty levels is gained. Three annotated resources that can be used for further research have been created, and implications for automated systems are presented.

Clinical documentation is at the center of a patient's medical record; this record contains all the information applicable to the care a patient receives in the hospital. The practice problem addressed in this project was the lack of clear, consistent, accurate, and complete patient medical records in a pediatric hospital. Although the occurrence of incomplete medical records has been a known issue for the project hospital, the issue was further intensified following the implementation of the 10th revision of International Classification of Diseases (ICD-10) standard for documentation, which resulted in gaps in provider documentation that needed to be filled. Based on this, the researcher recommended a quality improvement project and worked with a multidisciplinary team from the hospital to develop an evidence-based documentation guideline that incorporated ICD-10 standard for documenting pediatric diagnoses. Using data generated from the guideline, an artificial intelligence (AI) was developed in the form of best practice advisory alerts to engage providers at the point of documentation as well as augment provider efforts. Rosswurm and Larrabee's conceptual framework and Kotter's 8-step change model was used to develop the guideline and design the project. A descriptive data analysis using sample T-test significance indicated that financial reimbursement decreased by 25%, while case denials increased by 28% after ICD-10 implementation. This project promotes positive social change by improving safety, quality, and accountability at the project hospital.