Your browser doesn't support javascript.
loading
Show: 20 | 50 | 100
Results 1 - 2 de 2
Filter
Add more filters










Database
Language
Publication year range
1.
Artif Intell Med ; 92: 88-94, 2018 11.
Article in English | MEDLINE | ID: mdl-26603750

ABSTRACT

OBJECTIVE: Most practically deployed Arden-Syntax-based clinical decision support (CDS) modules process data from individual patients. The specification of Arden Syntax, however, would in principle also support multi-patient CDS. The patient data management system (PDMS) at our local intensive care units does not natively support patient overviews from customizable CDS routines, but local physicians indicated a demand for multi-patient tabular overviews of important clinical parameters such as key laboratory measurements. As our PDMS installation provides Arden Syntax support, we set out to explore the capability of Arden Syntax for multi-patient CDS by implementing a prototypical dashboard for visualizing laboratory findings from patient sets. METHODS AND MATERIAL: Our implementation leveraged the object data type, supported by later versions of Arden, which turned out to be serviceable for representing complex input data from several patients. For our prototype, we designed a modularized architecture that separates the definition of technical operations, in particular the control of the patient context, from the actual clinical knowledge. Individual Medical Logic Modules (MLMs) for processing single patient attributes could then be developed according to well-tried Arden Syntax conventions. RESULTS: We successfully implemented a working dashboard prototype entirely in Arden Syntax. The architecture consists of a controller MLM to handle the patient context, a presenter MLM to generate a dashboard view, and a set of traditional MLMs containing the clinical decision logic. Our prototype could be integrated into the graphical user interface of the local PDMS. We observed that with realistic input data the average execution time of about 200ms for generating dashboard views attained applicable performance. CONCLUSION: Our study demonstrated the general feasibility of creating multi-patient CDS routines in Arden Syntax. We believe that our prototypical dashboard also suggests that such implementations can be relatively easy, and may simultaneously hold promise for sharing dashboards between institutions and reusing elementary components for additional dashboards.


Subject(s)
Decision Support Systems, Clinical/organization & administration , Expert Systems , Hospital Information Systems/organization & administration , Artificial Intelligence , Decision Support Systems, Clinical/standards , Hospital Information Systems/standards , Humans , Medical Informatics , Programming Languages , Tertiary Care Centers
2.
Stud Health Technol Inform ; 228: 532-6, 2016.
Article in English | MEDLINE | ID: mdl-27577440

ABSTRACT

Automated perioperative measurements such as cardiovascular monitoring data are commonly compared to established upper and lower thresholds, but could also allow for more complex interpretations. Analyzing such time series in extensive electronic medical records for research purposes may itself require customized automation, so we developed a set of algorithms for quantifying different aspects of temporal fluctuations. We implemented conventional measures of dispersion, summaries of absolute gradients between successive values, and Poincaré plots. We aggregated the severity and duration of hypotensive episodes by calculating the average area under different mean arterial pressure (MAP) thresholds. We applied these methods to 30,452 de-identified MAP series, and analyzed the similarity between alternative indices via hierarchical clustering. To explore the potential utility of these propositional metrics, we computed their statistical association with presumed complications due to cardiovascular instability. We observed that hierarchical clustering reliably segregated features that had been designed to quantify dissimilar aspects. Summaries of temporary hypotension turned out to be significantly increased among patient subgroups with subsequent signs of a complicated recovery. These associations were even stronger for measures that were specifically geared to capturing short-term MAP variability. These observations suggest the potential capability of our proposed algorithms for quantifying heterogeneous aspects of short-term MAP fluctuations. Future research might also target a wider selection of outcomes and other attributes that may be subject to intraoperative variability.


Subject(s)
Algorithms , Blood Pressure/physiology , Monitoring, Physiologic , Patient Outcome Assessment , Arterial Pressure/physiology , Electronic Health Records , Germany , Humans , Perioperative Period , Time Factors
SELECTION OF CITATIONS
SEARCH DETAIL
...