SPIRIT: Systematic Planning of Intelligent Reuse of Integrated Clinical Routine Data. A Conceptual Best-practice Framework and Procedure Model.

BACKGROUND: Secondary use of clinical routine data is receiving an increasing amount of attention in biomedicine and healthcare. However, building and analysing integrated clinical routine data repositories are nontrivial, challenging tasks. As in most evolving fields, recognized standards, well-proven methodological frameworks, or accurately described best-practice approaches for the systematic planning of solutions for secondary use of routine medical record data are missing. OBJECTIVE: We propose a conceptual best-practice framework and procedure model for the systematic planning of intelligent reuse of integrated clinical routine data (SPIRIT). METHODS: SPIRIT was developed based on a broad literature overview and further refined in two case studies with different kinds of clinical routine data, including process-oriented nursing data from a large hospital group and high-volume multimodal clinical data from a neurologic intensive care unit. RESULTS: SPIRIT aims at tailoring secondary use solutions to specific needs of single departments without losing sight of the institution as a whole. It provides a general conceptual best-practice framework consisting of three parts: First, a secondary use strategy for the whole organization is determined. Second, comprehensive analyses are conducted from two different viewpoints to define the requirements regarding a clinical routine data reuse solution at the system level from the data perspective (BOTTOM UP) and at the strategic level from the future users perspective (TOP DOWN). An obligatory clinical context analysis (IN BETWEEN) facilitates refinement, combination, and integration of the different requirements. The third part of SPIRIT is dedicated to implementation, which comprises design and realization of clinical data integration and management as well as data analysis solutions. CONCLUSIONS: The SPIRIT framework is intended to be used to systematically plan the intelligent reuse of clinical routine data for multiple purposes, which often was not intended when the primary clinical documentation systems were implemented. SPIRIT helps to overcome this gap. It can be applied in healthcare institutions of any size or specialization and allows a stepwise setup and evolution of holistic clinical routine data reuse solutions.

From adverse drug event detection to prevention. A novel clinical decision support framework for medication safety.

BACKGROUND: Errors related to medication seriously affect patient safety and the quality of healthcare. It has been widely argued that various types of such errors may be prevented by introducing Clinical Decision Support Systems (CDSSs) at the point of care. OBJECTIVES: Although significant research has been conducted in the field, still medication safety is a crucial issue, while few research outcomes are mature enough to be considered for use in actual clinical settings. In this paper, we present a clinical decision support framework targeting medication safety with major focus on adverse drug event (ADE) prevention. METHODS: The novelty of the framework lies in its design that approaches the problem holistically, i.e., starting from knowledge discovery to provide reliable numbers about ADEs per hospital or medical unit to describe their consequences and probable causes, and next employing the acquired knowledge for decision support services development and deployment. Major design features of the framework's services are: a) their adaptation to the context of care (i.e. patient characteristics, place of care, and significance of ADEs), and b) their straightforward integration in the healthcare information technologies (IT) infrastructure thanks to the adoption of a service-oriented architecture (SOA) and relevant standards. RESULTS: Our results illustrate the successful interoperability of the framework with two commercially available IT products, i.e., a Computerized Physician Order Entry (CPOE) and an Electronic Health Record (EHR) system, respectively, along with a Web prototype that is independent of existing healthcare IT products. The conducted clinical validation with domain experts and test cases illustrates that the impact of the framework is expected to be major, with respect to patient safety, and towards introducing the CDSS functionality in practical use. CONCLUSIONS: This study illustrates an important potential for the applicability of the presented framework in delivering contextualized decision support services at the point of care and for making a substantial contribution towards ADE prevention. Nonetheless, further research is required in order to quantitatively and thoroughly assess its impact in medication safety.

Electronic health records. A systematic review on quality requirements.

OBJECTIVES: Since the first concepts for electronic health records (EHRs) in the 1990s, the content, structure, and technology of such records were frequently changed and adapted. The basic idea to support and enhance health care stayed the same over time. To reach these goals, it is crucial that EHRs themselves adhere to rigid quality requirements. The present review aims at describing the currently available, mainly non-functional, quality requirements with regard to electronic health records. METHODS: A combined approach - systematic literature analysis and expert interviews - was used. The literature analysis as well as the expert interviews included sources/experts from different domains such as standards and norms, scientific literature and guidelines, and best practice. The expert interviews were performed by using problem-centric qualitative computer-assisted telephone interviews (CATIs) or face-to-face interviews. All of the data that was obtained was analyzed using qualitative content analysis techniques. RESULTS: In total, more than 1200 requirements were identified of which 203 requirements were also mentioned during the expert interviews. The requirements are organized according to the ISO 9126 and the eEurope 2002 criteria. Categories with the highest number of requirements found include global requirements, (general) functional requirements and data security. The number of non-functional requirements found is by contrast lower. CONCLUSION: The manuscript gives comprehensive insight into the currently available, primarily non-functional, EHR requirements. To our knowledge, there are no other publications that have holistically reported on this topic. The requirements identified can be used in different ways, e.g. the conceptual design, the development of EHR systems, as a starting point for further refinement or as a basis for the development of specific sets of requirements.

Analysis and modelling of the multi-professional treatment process: preliminary results.

This paper presents first results of a research project aimed at improving co-operative work initiatives in hospitals. A holistic analysis of the treatment process is presented as a precondition for process reengineering, quality measurements and improvement of multi-professional co-operation. Treatment process modelling attempts within the last years have concentrated on specialised points of views, such as business process modelling or communication modelling. In contrast, we have developed a framework consisting of several views of the treatment process. We tested our framework in a broad system analysis within the Department of Child and Adolescent Psychiatry of the Heidelberg University Hospitals. Our preliminary results support the framework. Weaknesses were described precisely in both the field of organisational procedures and information management.