T. Ganslandt

Towards integration of clinical decision support in commercial hospital information systems using distributed, reusable software and knowledge components

PROBLEMnClinicians acceptance of clinical decision support depends on its workflow-oriented, context-sensitive accessibility and availability at the point of care, integrated into the Electronic Patient Record (EPR). Commercially available Hospital Information Systems (HIS) often focus on administrative tasks and mostly do not provide additional knowledge based functionality. Their traditionally monolithic and closed software architecture encumbers integration of and interaction with external software modules. Our aim was to develop methods and interfaces to integrate knowledge sources into two different commercial hospital information systems to provide the best decision support possible within the context of available patient data.nnnMETHODSnAn existing, proven standalone scoring system for acute abdominal pain was supplemented by a communication interface. In both HIS we defined data entry forms and developed individual and reusable mechanisms for data exchange with external software modules. We designed an additional knowledge support frontend which controls data exchange between HIS and the knowledge modules. Finally, we added guidelines and algorithms to the knowledge library.nnnRESULTSnDespite some major drawbacks which resulted mainly from the HIS closed software architectures we showed exemplary, how external knowledge support can be integrated almost seamlessly into different commercial HIS. This paper describes the prototypical design and current implementation and discusses our experiences.

Experiences with an Interoperable Data Acquisition Platform for Multi-centric Research Networks Based on HL7 CDA

A remote data entry (RDE) module was successfully integrated within a Web-based telemedicine system in a German multi-centric research network for a rare disease called Epidermolysis Bullosa. The use of standards like XML and HL7 CDA (Clinical Document Architecture) for structured data storage, guarantees long-term accessibility and high level interoperability.

IT Infrastructure Components for Biobanking

OBJECTIVEnWithin translational research projects in the recent years large biobanks have been established, mostly supported by homegrown, proprietary software solutions. No general requirements for biobanking IT infrastructures have been published yet. This paper presents an exemplary biobanking IT architecture, a requirements specification for a biorepository management tool and exemplary illustrations of three major types of requirements.nnnMETHODSnWe have pursued a comprehensive literature review for biobanking IT solutions and established an interdisciplinary expert panel for creating the requirements specification. The exemplary illustrations were derived from a requirements analysis within two university hospitals.nnnRESULTSnThe requirements specification comprises a catalog with more than 130 detailed requirements grouped into 3 major categories and 20 subcategories. Special attention is given to multitenancy capabilities in order to support the project-specific definition of varying research and bio-banking contexts, the definition of workflows to track sample processing, sample transportation and sample storage and the automated integration of preanalytic handling and storage robots.nnnCONCLUSIONnIT support for biobanking projects can be based on a federated architectural framework comprising primary data sources for clinical annotations, a pseudonymization service, a clinical data warehouse with a flexible and user-friendly query interface and a biorepository management system. Flexibility and scalability of all such components are vital since large medical facilities such as university hospitals will have to support biobanking for varying monocentric and multicentric research scenarios and multiple medical clients.

Applicability of Lewin´s Change Management Model in a Hospital Setting

OBJECTIVESnTodays socio-economic developments in the healthcare area require continued optimization of processes and cost structures at hospitals, often associated with process changes for different occupational groups in the hospital. Formal methods for managing change have been established in other industries. The goal of this study was to assess the applicability of Kurt Lewins change management method to a health informatics-related project at a German university hospital.nnnMETHODSnA project at the University Hospital Erlangen introducing changed requirements in the documentation of costly material in the surgical area was conducted following the concept of Lewins approach based on field theory, group dynamics, action research and the three steps of change. A data warehouse contributed information to several steps in the change process.nnnRESULTSnThe model was successfully applied to the change project. Socio-dynamic forces relevant to the project goals were identified and considered in the design of the new documentation concept. The achieved documentation level met the new requirements and in some areas even exceeded them.nnnCONCLUSIONSnBased on the project experiences, we consider Kurt Lewins approach applicable to change management projects in the hospital sector without a requirement for substantial additional resources, however, specific hospital characteristics need to be taken into account. The data warehouse played an important role by providing essential contributions throughout the entire change process.

Concept and implementation of a study dashboard module for a continuous monitoring of trial recruitment and documentation

BACKGROUNDnThe difficulty of managing patient recruitment and documentation for clinical trials prompts a demand for instruments for closely monitoring these critical but unpredictable processes. Increasingly adopted Electronic Data Capture (EDC) applications provide novel opportunities to reutilize stored information for an efficient management of traceable trial workflows. In related clinical and administrative settings, so-called digital dashboards that continuously visualize time-dependent parameters have recently met a growing acceptance. To investigate the technical feasibility of a study dashboard for monitoring the progress of patient recruitment and trial documentation, we set out to develop a propositional prototype in the form of a separate software module.nnnMETHODSnAfter narrowing down functional requirements in semi-structured interviews with study coordinators, we analyzed available interfaces of a locally deployed EDC application, and designed the prototypical study dashboard based on previous findings. The module thereby leveraged a standardized export format in order to extract and import relevant trial data into a clinical data warehouse. Web-based reporting tools then facilitated the definition of diverse views, including diagrams of the progress of patient accrual and form completion at different granularity levels. To estimate the utility of the dashboard and its compatibility with current workflows, we interviewed study coordinators after a demonstration of sample outputs from ongoing trials.nnnRESULTSnThe employed tools promoted a rapid development. Displays of the implemented dashboard are organized around an entry page that integrates key metrics for available studies, and which links to more detailed information such as study-specific enrollment per center. The interviewed experts commented that the included graphical summaries appeared suitable for detecting that something was generally amiss, although practical remedies would mostly depend on additional information such as access to the original patient-specific data. The dependency on a separate application was seen as a downside. Interestingly, the prospective users warned that in some situations knowledge of specific accrual statistics might undermine blinding in a subtle yet intricate fashion, so ignorance of certain patient features was seen as sometimes preferable for reproducibility.nnnDISCUSSIONnOur proposed study dashboard graphically recaps key progress indicators of patient accrual and trial documentation. The modular implementation illustrates the technical feasibility of the approach. The use of a study dashboard might introduce certain technical requirements as well as subtle interpretative complexities, which may have to be weighed against potential efficiency gains.

Einführung eines Patientendatenmanagementsystems

BACKGROUNDnPatient data management systems (PDMS) enable digital documentation on intensive care units (ICU). A commercial PDMS was implemented in a 25-bed ICU replacing paper-based patient charting. The ICU electronic patient record is completely managed inside the PDMS. It compiles data from vital signs monitors, ventilators and further medical devices and facilitates some drug dose and fluid balance calculations as well as data reuse for administrative purposes. Ventilation time and patient severity scoring as well as coding of diagnoses and procedures is supported. Billing data transferred via interface to the central billing system of the hospital. Such benefits should show in measurable parameters, such as documented ventilator time, number of coded diagnoses and procedures and others. These parameters influence reimbursement in the German DRG system. Therefore, measurable changes in cost and reimbursement data of the ICU were expected.nnnMATERIAL AND METHODSnA retrospective analysis of documentation quality parameters, cost data and mortality rate of a 25-bed surgical ICU within a German university hospital 3 years before (2004-2006) and 5 years after (2007-2011) PDMS implementation. Selected parameters were documented electronically, consistently and reproducibly for the complete time span of 8 years including those years where no electronic patient recording was available. The following parameters were included: number of cleared DRG, cleared ventilator time, case mix (CM), case mix index (CMI), length of stay, number of coded diagnoses and procedures, detailed overview of a specific procedure code based on daily Apache II and TISS Core 10 scores, mortality, total ICU costs and revenues and partial profits for specific ICU procedures, such as renal replacement therapy and blood products.nnnRESULTSnSystematic shifts were detected over the study period, such as increasing case numbers and decreasing length of stay as well as annual fluctuations in severity of disease seen in the CM and CMI. After PDMS introduction, the total number of coded diagnoses increased but the proportion of DRG relevant diagnoses dropped significantly. The number of procedures increased (not significantly) and the number of procedures per case did not rise significantly. The procedure 8-980 showed a significant increase after PDMS introduction whereas the DRG-relevant proportion of those procedures dropped insignificantly. The number of ventilator-associated DRG cases as well as the total ventilator time increased but not significantly. Costs and revenues increased slightly but profit varied considerably from year to year in the 5 years after system implementation. A small increase was observed per case, per nursing day and per case mix point. Additional revenues for specific ICU procedures increased in the years before and dropped after PDMS implementation. There was an insignificant increase in ICU mortality rate from 7.4 % in the year 2006 (before) to 8.5 % in 2007 (after PDMS implementation). In the following years mortality dropped below the base level.nnnCONCLUSIONnThe implementation of the PDMS showed only small effects on documentation of reimbursement-relevant parameters which were too small to set off against the total investment. The method itself, a long-term follow-up of different parameters proved successful and can be adapted by other organizations. The quality of results depends on the availability of long-term parameters in good quality. No significant influence of PDMS on mortality was found.ZusammenfassungHintergrundDie elektronische Dokumentation hat nachgewiesene Effekte auf die Vollständigkeit, Quantität und Qualität der medizinischen Dokumentation. Diese Vorteile müssten in der aktuellen Abrechnungssystematik des deutschen „Diagnosis-Related-Groups“(DRG)-Systems auch ökonomische Auswirkungen in den Abrechnungsdaten einer Intensivstation (ITS) zeigen.Material und MethodenRetrospektive Auswertung verschiedener Parameter einer 25-Betten-ITS 3xa0Jahre vor und 5xa0Jahre nach Einführung eines PDMS. Bewertet wurden Parameter, die vollständig und qualitativ hochwertig über den gesamten 8-jährigen Auswertungszeitraum verfügbar waren. Dazu zählten: Zahl abgerechneter DRG und Beatmungs-DRG, „case mix (CM), „case mix index“ (CMI), Belegungstage, Beatmungsdauer, Zahl codierter Diagnosen mit und ohne „Comorbidity-and-complication-level“(CCL)-Relevanz, Zahl codierter Prozeduren insgesamt sowie des Operationen- und Prozedurenschlüssels (OPS) 8-980 intensivmedizinische Komplexbehandlung, des Weiteren Mortalität, Kosten, Erlöse und Zusatzentgelte.ErgebnisseDas Kollektiv veränderte sich hinsichtlich der Fallzahl, Liegezeit, des CM und CMI. Bei Einführung des PDMS ergaben sich folgende Effekte: Die Zahl codierter Diagnosen stieg, dagegen fiel der Anteil mit CCL-Relevanz. Die Zahl codierter Prozeduren pro Fall nahm nicht signifikant zu. Es konnte keine signifikante Änderung bei den OPS-Codes 8-980 beobachtet werden. Ebenfalls nichtsignifikant war der Anstieg der Beatmungsstunden und der abgerechneten Beatmungs-DRG. Bezogen auf Fälle, Belegungstage, Beatmungsstunden und CM-Punkte konnte ein monetärer Effekt des PDMS weitgehend ausgeschlossen werden. Die Zusatzentgelte stiegen bereits vor PDMS-Einführung; danach sanken sie. Die Mortalität auf der ITS stieg im Jahr nach PDMS-Einführung, der Anstieg war jedoch nicht signifikant und fiel im weiteren Verlauf unter das Niveau vor Systemeinführung.SchlussfolgerungDie PDMS-Einführung hatte auf die Dokumentation abrechnungsrelevanter Parameter nur wenig Einfluss und ist somit nicht in der Lage, das Abrechnungsergebnis der ITS wesentlich zu beeinflussen. Die retrospektive Betrachtung von Dokumentationsparametern über einen längeren Zeitraum erscheint prinzipiell geeignet, um auch in anderen Organisationen die Kosten-Nutzen-Bewertung eines Informationssystems durchzuführen. Die Qualität der Aussagen hängt stark von der Verfügbarkeit langfristig auswertbarer Parameter ab. Die Mortalität wird durch ein PDMS nicht signifikant beeinflusst.AbstractBackgroundPatient data management systems (PDMS) enable digital documentation on intensive care units (ICU) and have positive effects on completness, quality and quantity of documented information. A commercial PDMS was implemented in a 25-bed ICU replacing paper-based patient charting. The ICU electronic patient record is completely managed inside the PDMS. IT compiles data from vital signs monitors, ventilators and further medical devices and facilitates some drug dose and fluid balance calculations as well as data reuse for administrative purposes. Ventilation time and patient severity scoring as well as coding of diagnoses and procedures is supported. Billing data transferred via interface to the central billing system of the hospital. Such benefits should show in measurable parameters, such as documented ventilator time, number of coded diagnoses and procedures and others. These parameters influence reimbursement in the German DRG system. Therefore, measurable changes in cost and reimbursement data of the ICU were expected.Material and methodsA retrospective analysis of documentation quality parameters, cost data and mortality rate of a 25-bed surgical ICU within a German university hospital 3 years before (2004–2006) and 5 years after (2007–2011) PDMS implementation. Selected parameters were documented electronically, consistently and reproducibly for the complete time span of 8 years including those years where no electronic patient recording was available. The following parameters were included: number of cleared DRG, cleared ventilator time, case mix (CM), case mix index (CMI), length of stay, number of coded diagnoses and procedures, detailed overview of a specific procedure code based on daily Apache II and TISS Core 10 scores, mortality, total ICU costs and revenues and partial profits for specific ICU procedures, such as renal replacement therapy and blood products.ResultsSystematic shifts were detected over the study period, such as increasing case numbers and decreasing length of stay as well as annual fluctuations in severity of disease seen in the CM and CMI. After PDMS introduction, the total number of coded diagnoses increased but the proportion of DRG relevant diagnoses dropped significantly. The number of procedures increased (not significantly) and the number of procedures per case did not rise significantly. The procedure 8-980 showed a significant increase after PDMS introduction whereas the DRG-relevant proportion of those procedures dropped insignificantly. The number of ventilator-associated DRG cases as well as the total ventilator time increased but not significantly. Costs and revenues increased slightly but profit varied considerably from year to year in the 5 years after system implementation. A small increase was observed per case, per nursing day and per case mix point. Additional revenues for specific ICU procedures increased in the years before and dropped after PDMS implementation. There was an insignificant increase in ICU mortality rate from 7.4u2009% in the year 2006 (before) to 8.5u2009% in 2007 (after PDMS implementation). In the following years mortality dropped below the base level.ConclusionThe implementation of the PDMS showed only small effects on documentation of reimbursement-relevant parameters which were too small to set off against the total investment. The method itself, a long-term follow-up of different parameters proved successful and can be adapted by other organizations. The quality of results depends on the availability of long-term parameters in good quality. No significant influence of PDMS on mortality was found.

Implementation of a patient data management system. Effects on intensive care documentation

BACKGROUNDnPatient data management systems (PDMS) enable digital documentation on intensive care units (ICU). A commercial PDMS was implemented in a 25-bed ICU replacing paper-based patient charting. The ICU electronic patient record is completely managed inside the PDMS. It compiles data from vital signs monitors, ventilators and further medical devices and facilitates some drug dose and fluid balance calculations as well as data reuse for administrative purposes. Ventilation time and patient severity scoring as well as coding of diagnoses and procedures is supported. Billing data transferred via interface to the central billing system of the hospital. Such benefits should show in measurable parameters, such as documented ventilator time, number of coded diagnoses and procedures and others. These parameters influence reimbursement in the German DRG system. Therefore, measurable changes in cost and reimbursement data of the ICU were expected.nnnMATERIAL AND METHODSnA retrospective analysis of documentation quality parameters, cost data and mortality rate of a 25-bed surgical ICU within a German university hospital 3 years before (2004-2006) and 5 years after (2007-2011) PDMS implementation. Selected parameters were documented electronically, consistently and reproducibly for the complete time span of 8 years including those years where no electronic patient recording was available. The following parameters were included: number of cleared DRG, cleared ventilator time, case mix (CM), case mix index (CMI), length of stay, number of coded diagnoses and procedures, detailed overview of a specific procedure code based on daily Apache II and TISS Core 10 scores, mortality, total ICU costs and revenues and partial profits for specific ICU procedures, such as renal replacement therapy and blood products.nnnRESULTSnSystematic shifts were detected over the study period, such as increasing case numbers and decreasing length of stay as well as annual fluctuations in severity of disease seen in the CM and CMI. After PDMS introduction, the total number of coded diagnoses increased but the proportion of DRG relevant diagnoses dropped significantly. The number of procedures increased (not significantly) and the number of procedures per case did not rise significantly. The procedure 8-980 showed a significant increase after PDMS introduction whereas the DRG-relevant proportion of those procedures dropped insignificantly. The number of ventilator-associated DRG cases as well as the total ventilator time increased but not significantly. Costs and revenues increased slightly but profit varied considerably from year to year in the 5 years after system implementation. A small increase was observed per case, per nursing day and per case mix point. Additional revenues for specific ICU procedures increased in the years before and dropped after PDMS implementation. There was an insignificant increase in ICU mortality rate from 7.4 % in the year 2006 (before) to 8.5 % in 2007 (after PDMS implementation). In the following years mortality dropped below the base level.nnnCONCLUSIONnThe implementation of the PDMS showed only small effects on documentation of reimbursement-relevant parameters which were too small to set off against the total investment. The method itself, a long-term follow-up of different parameters proved successful and can be adapted by other organizations. The quality of results depends on the availability of long-term parameters in good quality. No significant influence of PDMS on mortality was found.ZusammenfassungHintergrundDie elektronische Dokumentation hat nachgewiesene Effekte auf die Vollständigkeit, Quantität und Qualität der medizinischen Dokumentation. Diese Vorteile müssten in der aktuellen Abrechnungssystematik des deutschen „Diagnosis-Related-Groups“(DRG)-Systems auch ökonomische Auswirkungen in den Abrechnungsdaten einer Intensivstation (ITS) zeigen.Material und MethodenRetrospektive Auswertung verschiedener Parameter einer 25-Betten-ITS 3xa0Jahre vor und 5xa0Jahre nach Einführung eines PDMS. Bewertet wurden Parameter, die vollständig und qualitativ hochwertig über den gesamten 8-jährigen Auswertungszeitraum verfügbar waren. Dazu zählten: Zahl abgerechneter DRG und Beatmungs-DRG, „case mix (CM), „case mix index“ (CMI), Belegungstage, Beatmungsdauer, Zahl codierter Diagnosen mit und ohne „Comorbidity-and-complication-level“(CCL)-Relevanz, Zahl codierter Prozeduren insgesamt sowie des Operationen- und Prozedurenschlüssels (OPS) 8-980 intensivmedizinische Komplexbehandlung, des Weiteren Mortalität, Kosten, Erlöse und Zusatzentgelte.ErgebnisseDas Kollektiv veränderte sich hinsichtlich der Fallzahl, Liegezeit, des CM und CMI. Bei Einführung des PDMS ergaben sich folgende Effekte: Die Zahl codierter Diagnosen stieg, dagegen fiel der Anteil mit CCL-Relevanz. Die Zahl codierter Prozeduren pro Fall nahm nicht signifikant zu. Es konnte keine signifikante Änderung bei den OPS-Codes 8-980 beobachtet werden. Ebenfalls nichtsignifikant war der Anstieg der Beatmungsstunden und der abgerechneten Beatmungs-DRG. Bezogen auf Fälle, Belegungstage, Beatmungsstunden und CM-Punkte konnte ein monetärer Effekt des PDMS weitgehend ausgeschlossen werden. Die Zusatzentgelte stiegen bereits vor PDMS-Einführung; danach sanken sie. Die Mortalität auf der ITS stieg im Jahr nach PDMS-Einführung, der Anstieg war jedoch nicht signifikant und fiel im weiteren Verlauf unter das Niveau vor Systemeinführung.SchlussfolgerungDie PDMS-Einführung hatte auf die Dokumentation abrechnungsrelevanter Parameter nur wenig Einfluss und ist somit nicht in der Lage, das Abrechnungsergebnis der ITS wesentlich zu beeinflussen. Die retrospektive Betrachtung von Dokumentationsparametern über einen längeren Zeitraum erscheint prinzipiell geeignet, um auch in anderen Organisationen die Kosten-Nutzen-Bewertung eines Informationssystems durchzuführen. Die Qualität der Aussagen hängt stark von der Verfügbarkeit langfristig auswertbarer Parameter ab. Die Mortalität wird durch ein PDMS nicht signifikant beeinflusst.AbstractBackgroundPatient data management systems (PDMS) enable digital documentation on intensive care units (ICU) and have positive effects on completness, quality and quantity of documented information. A commercial PDMS was implemented in a 25-bed ICU replacing paper-based patient charting. The ICU electronic patient record is completely managed inside the PDMS. IT compiles data from vital signs monitors, ventilators and further medical devices and facilitates some drug dose and fluid balance calculations as well as data reuse for administrative purposes. Ventilation time and patient severity scoring as well as coding of diagnoses and procedures is supported. Billing data transferred via interface to the central billing system of the hospital. Such benefits should show in measurable parameters, such as documented ventilator time, number of coded diagnoses and procedures and others. These parameters influence reimbursement in the German DRG system. Therefore, measurable changes in cost and reimbursement data of the ICU were expected.Material and methodsA retrospective analysis of documentation quality parameters, cost data and mortality rate of a 25-bed surgical ICU within a German university hospital 3 years before (2004–2006) and 5 years after (2007–2011) PDMS implementation. Selected parameters were documented electronically, consistently and reproducibly for the complete time span of 8 years including those years where no electronic patient recording was available. The following parameters were included: number of cleared DRG, cleared ventilator time, case mix (CM), case mix index (CMI), length of stay, number of coded diagnoses and procedures, detailed overview of a specific procedure code based on daily Apache II and TISS Core 10 scores, mortality, total ICU costs and revenues and partial profits for specific ICU procedures, such as renal replacement therapy and blood products.ResultsSystematic shifts were detected over the study period, such as increasing case numbers and decreasing length of stay as well as annual fluctuations in severity of disease seen in the CM and CMI. After PDMS introduction, the total number of coded diagnoses increased but the proportion of DRG relevant diagnoses dropped significantly. The number of procedures increased (not significantly) and the number of procedures per case did not rise significantly. The procedure 8-980 showed a significant increase after PDMS introduction whereas the DRG-relevant proportion of those procedures dropped insignificantly. The number of ventilator-associated DRG cases as well as the total ventilator time increased but not significantly. Costs and revenues increased slightly but profit varied considerably from year to year in the 5 years after system implementation. A small increase was observed per case, per nursing day and per case mix point. Additional revenues for specific ICU procedures increased in the years before and dropped after PDMS implementation. There was an insignificant increase in ICU mortality rate from 7.4u2009% in the year 2006 (before) to 8.5u2009% in 2007 (after PDMS implementation). In the following years mortality dropped below the base level.ConclusionThe implementation of the PDMS showed only small effects on documentation of reimbursement-relevant parameters which were too small to set off against the total investment. The method itself, a long-term follow-up of different parameters proved successful and can be adapted by other organizations. The quality of results depends on the availability of long-term parameters in good quality. No significant influence of PDMS on mortality was found.

Towards Implementation of OMOP in a German University Hospital Consortium

Background u2003In 2015, the German Federal Ministry of Education and Research initiated a large data integration and data sharing research initiative to improve the reuse of data from patient care and translational research. The Observational Medical Outcomes Partnership (OMOP) common data model and the Observational Health Data Sciences and Informatics (OHDSI) tools could be used as a core element in this initiative for harmonizing the terminologies used as well as facilitating the federation of research analyses across institutions. Objective u2003To realize an OMOP/OHDSI-based pilot implementation within a consortium of eight German university hospitals, evaluate the applicability to support data harmonization and sharing among them, and identify potential enhancement requirements. Methods u2003The vocabularies and terminological mapping required for importing the fact data were prepared, and the process for importing the data from the source files was designed. For eight German university hospitals, a virtual machine preconfigured with the OMOP database and the OHDSI tools as well as the jobs to import the data and conduct the analysis was provided. Last, a federated/distributed query to test the approach was executed. Results u2003While the mapping of ICD-10 German Modification succeeded with a rate of 98.8% of all terms for diagnoses, the procedures could not be mapped and hence an extension to the OMOP standard terminologies had to be made. Overall, the data of 3 million inpatients with approximately 26 million conditions, 21 million procedures, and 23 million observations have been imported. A federated query to identify a cohort of colorectal cancer patients was successfully executed and yielded 16,701 patient cases visualized in a Sunburst plot. Conclusion u2003OMOP/OHDSI is a viable open source solution for data integration in a German research consortium. Once the terminology problems can be solved, researchers can build on an active community for further development.

Einführung eines Patientendatenmanagementsystems@@@Implementation of a patient data management system: Auswirkungen auf die intensivmedizinische Dokumentation@@@Effects on intensive care documentation

BACKGROUNDnPatient data management systems (PDMS) enable digital documentation on intensive care units (ICU). A commercial PDMS was implemented in a 25-bed ICU replacing paper-based patient charting. The ICU electronic patient record is completely managed inside the PDMS. It compiles data from vital signs monitors, ventilators and further medical devices and facilitates some drug dose and fluid balance calculations as well as data reuse for administrative purposes. Ventilation time and patient severity scoring as well as coding of diagnoses and procedures is supported. Billing data transferred via interface to the central billing system of the hospital. Such benefits should show in measurable parameters, such as documented ventilator time, number of coded diagnoses and procedures and others. These parameters influence reimbursement in the German DRG system. Therefore, measurable changes in cost and reimbursement data of the ICU were expected.nnnMATERIAL AND METHODSnA retrospective analysis of documentation quality parameters, cost data and mortality rate of a 25-bed surgical ICU within a German university hospital 3 years before (2004-2006) and 5 years after (2007-2011) PDMS implementation. Selected parameters were documented electronically, consistently and reproducibly for the complete time span of 8 years including those years where no electronic patient recording was available. The following parameters were included: number of cleared DRG, cleared ventilator time, case mix (CM), case mix index (CMI), length of stay, number of coded diagnoses and procedures, detailed overview of a specific procedure code based on daily Apache II and TISS Core 10 scores, mortality, total ICU costs and revenues and partial profits for specific ICU procedures, such as renal replacement therapy and blood products.nnnRESULTSnSystematic shifts were detected over the study period, such as increasing case numbers and decreasing length of stay as well as annual fluctuations in severity of disease seen in the CM and CMI. After PDMS introduction, the total number of coded diagnoses increased but the proportion of DRG relevant diagnoses dropped significantly. The number of procedures increased (not significantly) and the number of procedures per case did not rise significantly. The procedure 8-980 showed a significant increase after PDMS introduction whereas the DRG-relevant proportion of those procedures dropped insignificantly. The number of ventilator-associated DRG cases as well as the total ventilator time increased but not significantly. Costs and revenues increased slightly but profit varied considerably from year to year in the 5 years after system implementation. A small increase was observed per case, per nursing day and per case mix point. Additional revenues for specific ICU procedures increased in the years before and dropped after PDMS implementation. There was an insignificant increase in ICU mortality rate from 7.4 % in the year 2006 (before) to 8.5 % in 2007 (after PDMS implementation). In the following years mortality dropped below the base level.nnnCONCLUSIONnThe implementation of the PDMS showed only small effects on documentation of reimbursement-relevant parameters which were too small to set off against the total investment. The method itself, a long-term follow-up of different parameters proved successful and can be adapted by other organizations. The quality of results depends on the availability of long-term parameters in good quality. No significant influence of PDMS on mortality was found.ZusammenfassungHintergrundDie elektronische Dokumentation hat nachgewiesene Effekte auf die Vollständigkeit, Quantität und Qualität der medizinischen Dokumentation. Diese Vorteile müssten in der aktuellen Abrechnungssystematik des deutschen „Diagnosis-Related-Groups“(DRG)-Systems auch ökonomische Auswirkungen in den Abrechnungsdaten einer Intensivstation (ITS) zeigen.Material und MethodenRetrospektive Auswertung verschiedener Parameter einer 25-Betten-ITS 3xa0Jahre vor und 5xa0Jahre nach Einführung eines PDMS. Bewertet wurden Parameter, die vollständig und qualitativ hochwertig über den gesamten 8-jährigen Auswertungszeitraum verfügbar waren. Dazu zählten: Zahl abgerechneter DRG und Beatmungs-DRG, „case mix (CM), „case mix index“ (CMI), Belegungstage, Beatmungsdauer, Zahl codierter Diagnosen mit und ohne „Comorbidity-and-complication-level“(CCL)-Relevanz, Zahl codierter Prozeduren insgesamt sowie des Operationen- und Prozedurenschlüssels (OPS) 8-980 intensivmedizinische Komplexbehandlung, des Weiteren Mortalität, Kosten, Erlöse und Zusatzentgelte.ErgebnisseDas Kollektiv veränderte sich hinsichtlich der Fallzahl, Liegezeit, des CM und CMI. Bei Einführung des PDMS ergaben sich folgende Effekte: Die Zahl codierter Diagnosen stieg, dagegen fiel der Anteil mit CCL-Relevanz. Die Zahl codierter Prozeduren pro Fall nahm nicht signifikant zu. Es konnte keine signifikante Änderung bei den OPS-Codes 8-980 beobachtet werden. Ebenfalls nichtsignifikant war der Anstieg der Beatmungsstunden und der abgerechneten Beatmungs-DRG. Bezogen auf Fälle, Belegungstage, Beatmungsstunden und CM-Punkte konnte ein monetärer Effekt des PDMS weitgehend ausgeschlossen werden. Die Zusatzentgelte stiegen bereits vor PDMS-Einführung; danach sanken sie. Die Mortalität auf der ITS stieg im Jahr nach PDMS-Einführung, der Anstieg war jedoch nicht signifikant und fiel im weiteren Verlauf unter das Niveau vor Systemeinführung.SchlussfolgerungDie PDMS-Einführung hatte auf die Dokumentation abrechnungsrelevanter Parameter nur wenig Einfluss und ist somit nicht in der Lage, das Abrechnungsergebnis der ITS wesentlich zu beeinflussen. Die retrospektive Betrachtung von Dokumentationsparametern über einen längeren Zeitraum erscheint prinzipiell geeignet, um auch in anderen Organisationen die Kosten-Nutzen-Bewertung eines Informationssystems durchzuführen. Die Qualität der Aussagen hängt stark von der Verfügbarkeit langfristig auswertbarer Parameter ab. Die Mortalität wird durch ein PDMS nicht signifikant beeinflusst.AbstractBackgroundPatient data management systems (PDMS) enable digital documentation on intensive care units (ICU) and have positive effects on completness, quality and quantity of documented information. A commercial PDMS was implemented in a 25-bed ICU replacing paper-based patient charting. The ICU electronic patient record is completely managed inside the PDMS. IT compiles data from vital signs monitors, ventilators and further medical devices and facilitates some drug dose and fluid balance calculations as well as data reuse for administrative purposes. Ventilation time and patient severity scoring as well as coding of diagnoses and procedures is supported. Billing data transferred via interface to the central billing system of the hospital. Such benefits should show in measurable parameters, such as documented ventilator time, number of coded diagnoses and procedures and others. These parameters influence reimbursement in the German DRG system. Therefore, measurable changes in cost and reimbursement data of the ICU were expected.Material and methodsA retrospective analysis of documentation quality parameters, cost data and mortality rate of a 25-bed surgical ICU within a German university hospital 3 years before (2004–2006) and 5 years after (2007–2011) PDMS implementation. Selected parameters were documented electronically, consistently and reproducibly for the complete time span of 8 years including those years where no electronic patient recording was available. The following parameters were included: number of cleared DRG, cleared ventilator time, case mix (CM), case mix index (CMI), length of stay, number of coded diagnoses and procedures, detailed overview of a specific procedure code based on daily Apache II and TISS Core 10 scores, mortality, total ICU costs and revenues and partial profits for specific ICU procedures, such as renal replacement therapy and blood products.ResultsSystematic shifts were detected over the study period, such as increasing case numbers and decreasing length of stay as well as annual fluctuations in severity of disease seen in the CM and CMI. After PDMS introduction, the total number of coded diagnoses increased but the proportion of DRG relevant diagnoses dropped significantly. The number of procedures increased (not significantly) and the number of procedures per case did not rise significantly. The procedure 8-980 showed a significant increase after PDMS introduction whereas the DRG-relevant proportion of those procedures dropped insignificantly. The number of ventilator-associated DRG cases as well as the total ventilator time increased but not significantly. Costs and revenues increased slightly but profit varied considerably from year to year in the 5 years after system implementation. A small increase was observed per case, per nursing day and per case mix point. Additional revenues for specific ICU procedures increased in the years before and dropped after PDMS implementation. There was an insignificant increase in ICU mortality rate from 7.4u2009% in the year 2006 (before) to 8.5u2009% in 2007 (after PDMS implementation). In the following years mortality dropped below the base level.ConclusionThe implementation of the PDMS showed only small effects on documentation of reimbursement-relevant parameters which were too small to set off against the total investment. The method itself, a long-term follow-up of different parameters proved successful and can be adapted by other organizations. The quality of results depends on the availability of long-term parameters in good quality. No significant influence of PDMS on mortality was found.