Towards shared patient records: An architecture for using routine data for nationwide research

Knaup, Petra; Garde, Sebastian; Merzweiler, Angela; Graf, Norbert; Schilling, Freimut H.; Weber, R.; Haux, Reinhold

doi:10.1016/j.ijmedinf.2005.07.020

Cited by 22 publications

(14 citation statements)

References 20 publications

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“…The CAT research portal is an institute-specific data warehouse that can also be used to share data in a privacy-preserving and semantic-interoperable manner using internationally accepted data exchange standards and ontologies such as described in an accompanying study [28,29], addressing the growing need for standardized data exchange between medical centres [1,3,12]. Richesson and Krischer [30] describe that there are currently overlaps, challenges and gaps in the standards developed for research and clinical purposes for data retrieval at a local scale and data sharing at a global scale.…”

Section: Discussionmentioning

confidence: 99%

“…Faster and more accurate access to medical information is required to improve the data quality, shorten data-collection times and reduce cost. Furthermore, conducting trials in multiple centres and data-sharing are required in numerous research projects to validate trial results, enable the collection of larger datasets of trial patients with a rare disease or to conduct in silico trials [1,3–6]. Although the medical community has undertaken numerous efforts to digitize its patient and treatment documentation, data are still predominantly collected from paper charts.…”

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confidence: 99%

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Benefits of a clinical data warehouse with data mining tools to collect data for a radiotherapy trial

Roelofs

Persoon

Nijsten

et al. 2013

Radiotherapy and Oncology

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Introduction Collecting trial data in a medical environment is at present mostly performed manually and therefore time-consuming, prone to errors and often incomplete with the complex data considered. Faster and more accurate methods are needed to improve the data quality and to shorten data collection times where information is often scattered over multiple data sources. The purpose of this study is to investigate the possible benefit of modern data warehouse technology in the radiation oncology field. Material and methods In this study, a Computer Aided Theragnostics (CAT) data warehouse combined with automated tools for feature extraction was benchmarked against the regular manual data-collection processes. Two sets of clinical parameters were compiled for non-small cell lung cancer (NSCLC) and rectal cancer, using 27 patients per disease. Data collection times and inconsistencies were compared between the manual and the automated extraction method. Results The average time per case to collect the NSCLC data manually was 10.4 ± 2.1 min and 4.3 ± 1.1 min when using the automated method (p < 0.001). For rectal cancer, these times were 13.5 ± 4.1 and 6.8 ± 2.4 min, respectively (p < 0.001). In 3.2% of the data collected for NSCLC and 5.3% for rectal cancer, there was a discrepancy between the manual and automated method. Conclusions Aggregating multiple data sources in a data warehouse combined with tools for extraction of relevant parameters is beneficial for data collection times and offers the ability to improve data quality. The initial investments in digitizing the data are expected to be compensated due to the flexibility of the data analysis. Furthermore, successive investigations can easily select trial candidates and extract new parameters from the existing databases.

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Section: Discussionmentioning

confidence: 99%

mentioning

confidence: 99%

Benefits of a clinical data warehouse with data mining tools to collect data for a radiotherapy trial

Roelofs

Persoon

Nijsten

et al. 2013

Radiotherapy and Oncology

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“…In contrast to cross-institutional EPR systems [14] or shared patient records described in [16] our OpEN.SC approach is a research science center and so the requirements are somewhat different.…”

Section: Discussionmentioning

confidence: 99%

Integration of Decentralized Clinical Data in a Data Warehouse

Hanß

Schaaf²,

Wetzel³

et al. 2009

Methods Inf Med

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“…There are several other examples of successful integration of clinical decision support into CPRs, e.g. [49][50][51][52]. The structuring of CPR data entered by clinicians is essential for applications that are to process these data.…”

Section: Reuse Of Cpr Contentsmentioning

confidence: 99%

Section 2: Patient Records: The Computerized Patient Record: Where Do We Stand?

Jaspers¹,

Knaup²,

Schmidt³

2006

Yearb Med Inform

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SummaryTo provide an overview of trends in research, developments and implementations of the computerized patient record (CPR) of the last two years.We surveyed the medical informatics literature, spanning the years 2004-2005, focusing on publications on CPRs.The main trends revealed were: 1) the development of technologies to realize privacy and security goals or remote data entry and access to CPRs; 2) investigations into how to enhance the quality and reuse of CPR data; 3) the development and evaluation of decision support functions to be integrated with CPRs; 4) evaluations of the impact of CPRs on clinicians, patients, clinical work settings and patient outcomes; and 5) the further development and use of standards to move towards shared electronic health records (EHRs).The CPR is playing a growing part in medical informatics research and evaluation studies, but the goal of establishing a comprehensive lifelong EHR is still a long way off. In moving forward to EHRs, convergence of EHR standards seems required to realize true interoperability of health care applications. User acceptance of present-day CPRs (for all categories of users) and compatibility with work patterns has not been achieved yet, and can only be realized by giving these goals high priority. This will require substantial resources for in-depth work flow analysis, development and evaluation of CPRs. Besides this, the implementation of effective CPRs asks for health care organizations that are willing to invest in new developments and to contribute to evaluation studies, to further improve CPRs’ functionalities and enhance their use in practice.Haux R, Kulikowski C, editors. IMIA Yearbook of Medical Informatics 2006.

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Towards shared patient records: An architecture for using routine data for nationwide research

Cited by 22 publications

References 20 publications

Benefits of a clinical data warehouse with data mining tools to collect data for a radiotherapy trial

Benefits of a clinical data warehouse with data mining tools to collect data for a radiotherapy trial

Integration of Decentralized Clinical Data in a Data Warehouse

Section 2: Patient Records: The Computerized Patient Record: Where Do We Stand?

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