Ronald Cornet | University of Amsterdam (original) (raw)

Papers by Ronald Cornet

This Data Management Plan (DMP) addresses the relevant aspects of making data FAIR – findable, ac... more This Data Management Plan (DMP) addresses the relevant aspects of making data FAIR – findable, accessible, interoperable and re-usable.

Studies in health technology and informatics, 2017

ArchMS is a framework that represents clinical information and knowledge using ontologies in OWL,... more ArchMS is a framework that represents clinical information and knowledge using ontologies in OWL, which facilitates semantic interoperability and thereby the exploitation and secondary use of clinical data. However, it does not yet support the automated assessment of quality of care. CLIF is a stepwise method to formalize quality indicators. The method has been implemented in the CLIF tool which supports its users in generating computable queries based on a patient data model which can be based on archetypes. To enable the automated computation of quality indicators using ontologies and archetypes, we tested whether ArchMS and the CLIF tool can be integrated. We successfully automated the process of generating SPARQL queries from quality indicators that have been formalized with CLIF and integrated them into ArchMS. Hence, ontologies and archetypes can be combined for the execution of formalized quality indicators.

Journal of innovation in health informatics, Jan 31, 2017

This article presents presentation and poster abstracts that were mistakenly omitted from the ori... more This article presents presentation and poster abstracts that were mistakenly omitted from the original publication.

These are the proceedings of KR-MED 2008, the Third International Conference on Formal Biomedical... more These are the proceedings of KR-MED 2008, the Third International Conference on Formal Biomedical Knowledge Representation, held in Phoenix, Arizona on May 31 – June 2, 2008. The conference is co-organized by the Working Group on Formal (Bio-)Medical Knowledge Representation of the American Medical Informatics Association (AMIA) and the International Health Terminology Standards Development Organisation (IHTSDO), and collocated with the 2008 AMIA Spring Congress.

INTRODUCTION Patients are sent to the intensive care unit (ICU) for several reasons, such as life... more INTRODUCTION Patients are sent to the intensive care unit (ICU) for several reasons, such as life-threatening medical problems or monitoring after an extensive surgery. The reason for ICU admission is registered in the electronic medical record (EMR) for direct patient care. Additionally, it is registered for the Acute Physiology and Chronic Health Evaluation IV (APACHE-IV) model to assess the severity of illness of patients at the intensive care, e.g. for quality improvement. This double registration creates an unnecessary administrative burden for ICU clinicians and may lead to suboptimal data quality. Another problem is that encoding diagnoses in a usable manner is challenging, and evidence to support guidelines for optimal user interface (UI) design to support this encoding is limited. PURPOSE The purpose of this scientific research project was to investigate how the APACHE-IV reason for ICU admission can be derived directly from data in the EMR and to gather evidence for guidelines to optimize the UI for medical data encoding. APACHE-IV DERIVATION METHOD We applied an existing four-step framework to update an existing SNOMED-APACHE mapping from the January 2011 version of SNOMED CT to the July 2015 version. We performed three additional steps to enable the derivation of the APACHE-IV classes from data in the EMR: (1) a migration and revision of the database, (2) the definition of classification rules; particularly for other, unknown and trauma classes, and (3) the design of the derivation process. RESULTS The update was carried out partially: we updated or removed 4 concepts and 7 relationships and revised the database to a new representation in line with SNOMED CT technical documentation. We developed classification rules which could replace the partially mapped other classes (n=49) and unknown classes (n=4) to fully mapped classes and allow the derivation of trauma classes based on traumatized body parts. DISCUSSION With these results we are one step closer to the APACHE-IV derivation from data in the EMR, but the mapping still needs to be revised and updated further. The derivation is hampered by the fact that the APACHE-IV classes are not defined explicitly. CONCLUSION The derivation of APACHE-IV classes requires an up to date SNOMED-APACHE mapping with classification rules, the encoding of admission diagnoses with SNOMED CT or SNOMED CT-based interface terminology and explicitly defined APACHE-IV classes. UI CONFIGURATION FOR DIAGNOSTIC DATA ENCODING METHOD We compared a guideline-compliant UI configuration for encoding diagnoses to one that resembles the configuration of an existing system, but is not guideline-compliant. Time, correctness, task completion, ease of use, user preference and motivations were the outcomes measures. We used a cross-over design in which we switched a randomly assigned initial configuration after half of the (n=20) cases. SETTING Residents, fellows and assistants (n=27) of the ICU of the Academic Medical Center Amsterdam completed the experiment. RESULTS We did not find a significant difference in correctness, task completion or ease of use, but participants were 19.3% (95% confidence interval: 6.38-33.7%, p-value<0.01) faster with the guideline-compliant UI configuration and had a clear preference for this configuration. Their motivations were in line with the guidelines. DISCUSSION Possibly, the sample size was too low to obtain significant differences in correctness, task completion and ease of use. CONCLUSION The time difference and clear user preference indicate the importance of UI design guidelines for encoding medical data. In order to find the influence on correctness, task completion and ease of use, and to evaluate more types of configurations, more research is required. CONCLUSION Deriving the APACHE-IV classification from the EMR is still hampered by an incomplete mapping between the interface terminology and SNOMED CT. We indicated that guideline-compliance of a UI to support medical data encoding can increase the speed of encoding and that participants prefer the UI that is compliant. The updated SNOMED-APACHE mapping needs to be implemented and evaluated in future research.

Studies in health technology and informatics, 2004

Evaluation of terminological systems has been demonstrated to be a complicated task. This is due ... more Evaluation of terminological systems has been demonstrated to be a complicated task. This is due to the broad range of terminological systems, their application, and the clinical contexts in which they can be applied. We propose an evaluation framework that explicitly distinguishes an application-independent description of terminological systems, methods to determine application-dependent requirements, and methods to assess the applicability. In order to support a systematic application-independent description of terminological systems, we present a categorization of characteristics, including explicit questions. The answers to these questions can be mapped to the requirements for a certain application of a terminological system. This framework aims at reducing the efforts for determining which terminological system is applicable for a certain clinical setting.

Structured and encoded information are important to maximize the meaningful (re)use of the Electr... more Structured and encoded information are important to maximize the meaningful (re)use of the Electronic Health Record (EHR). SNOMED CT is generally regarded as the preferred terminology system for encoding, but it has been shown that manual encoding (i.e., fully structured data entry) has issues with data quality and usability. Therefore, automated SNOMED CT encoding of free-text clinical narratives needs to be explored, which involves both post-hoc processing of yet unstructured records and ad-hoc processing of text being entered into a record.

Studies in health technology and informatics, 2012

In order to be able to automatically calculate clinical quality indicators, we have proposed CLIF... more In order to be able to automatically calculate clinical quality indicators, we have proposed CLIF, a stepwise method for clinical quality indicator formalisation. Quality indicators are used for external accountability and hospital comparison. As clinical quality indicators are computed in a decentralised manner by the hospitals themselves, reproducibility of the formalisation method is essential to ensure the comparability of calculated values. Thus, we performed a case study to investigate the reproducibility of CLIF. Eight participants formalised the same sample quality indicator with the help of a web-based indicator-authoring tool that facilitates the application of CLIF. We analysed the results per step and concluded that the method itself leads to reproducible results. To further improve reproducibility, ambiguities in the indicator text must be clarified and trained experts are needed to encode clinical concepts and to specify the relations between concepts.

Studies in health technology and informatics, 2004

The importance of terminological systems (TS) to support standardized and structured documentatio... more The importance of terminological systems (TS) to support standardized and structured documentation of medical data is commonly recognized. The usability of TS in real practice strongly depends on the completeness and the correctness of the content of the TS. We here present four different methods that can be applied to evaluate a TS' content. All four methods were applied in a case study. We make a comparison of 1) the results of two methods that focus on the completeness of the content and that differ in the application of the TS that they focus on and 2) the results of an automated and a manual evaluation of the correctness of the content. Finally we summarize the results of all four methods and analyze whether they overlap or complement each other.

Studies in health technology and informatics, 2018

Patient access to electronic health records (EHRs) is associated with improved efficiency, self-m... more Patient access to electronic health records (EHRs) is associated with improved efficiency, self-management, and patient engagement. However, the EHR contains medical language that can be difficult to comprehend by patients. In Dutch hospitals, the Diagnosethesaurus (DT) is used as an interface terminology to register diagnoses, but it does not contain patient-friendly terms. Fortunately, the DT is partly mapped to SNOMED CT and there is a proportionately small set of patient-friendly terms available in the Dutch SNOMED CT release. The purpose of this study was, therefore, to investigate if SNOMED CT can be used to generate clarifications of diagnoses for patients. Only 1.2% of the DT diagnoses that were already mapped to SNOMED CT had patient-friendly synonyms that were different from the diagnoses descriptions. However, by generalizing diagnoses to SNOMED CT concepts with patient-friendly terms, this number could be increased to 71%. In conclusion, we showed that a high percentage ...

Studies in health technology and informatics, 2017

Over 15 years, a broad spectrum of activities was undertaken to realize a health IT infrastructur... more Over 15 years, a broad spectrum of activities was undertaken to realize a health IT infrastructure in the Netherlands. In this paper we reflect on the history, challenges, accomplishments, changes, and the way forward. It shows that the infrastructure depends on technical, legal, and semantic aspects, which are frequently reciprocally related. It also highlights the fact that the role of health professionals and of patients is increasingly considered as a crucial element.

Studies in health technology and informatics, 2012

Automated encoding of free-text clinical narratives using concepts from terminological systems is... more Automated encoding of free-text clinical narratives using concepts from terminological systems is widely performed. However, the majority of natural language processing (NLP) tools and terminological systems involve the English language. As parts of the NLP process are language independent, and tools for various languages are available, an overview is needed to determine the applicability to performing NLP of Dutch medical texts. To this end an inventory of tools is created. A literature study and internet search were performed to describe available components for a Dutch NLP system, enabling to encode Dutch text as structured SNOMED CT output without the need to translate SNOMED CT in Dutch. We have found 31 papers, describing a variety of NLP frameworks and tools for the various NLP components for processing English and Dutch free text. Most of them are suitable for English free text, some of them are (also) usable for Dutch. To enable automated encoding of Dutch free text narrati...

Studies in health technology and informatics, 2016

Data in an Electronic Health Record must be recorded once, in a standardized and structured way a... more Data in an Electronic Health Record must be recorded once, in a standardized and structured way at the point of care to be reusable within the care process as well as for secondary purposes ('collect once, use many times' (COUMT) paradigm). COUMT has not yet been fully adopted by staff in every organization. Our study intends to identify concepts that underlie its adoption and describe its current status in Dutch academic hospitals. Based on literature we have constructed a model that describes these concepts and that guided the development of a questionnaire investigating COUMT adoption. The questionnaire was sent to staff working with patient data or records in seven out of eight Dutch university hospitals. Results show high willingness of end-users to comply to COUMT in the care process. End-users agree that COUMT is important, and that they want to work in a structured and standardized way. However, end-users indicate to not actually use terminology or information standa...

Studies in health technology and informatics, 2010

A crossmap between successive versions of classification systems is necessary to maintain the con... more A crossmap between successive versions of classification systems is necessary to maintain the continuity of health care documentation. A reference terminology can serve as an intermediary to support this task. Within this study we evaluated the use of SNOMED CT to create a crossmap between two versions of an intensive care classification system. Firstly, the SNOMED CT crossmap was compared with an expert-based and a data-driven crossmap. Next, the influence of these crossmap strategies on the health care outcome was evaluated. For 50% of the analyzed cases, the three mapping strategies resulted in the same crossmaps. In other cases, there was an overlap between the SNOMED CT crossmaps and the crossmaps provided by one of the two other strategies. Differences in the crossmap results had however no significant influence on the health care outcomes. SNOMED CT can be used as an intermediary to solve the problem of crossmapping between versions of classification systems.

The specialist field of rare diseases must connect its vast array of globally distributed disease... more The specialist field of rare diseases must connect its vast array of globally distributed disease and patient registries to maximise their value. Unfortunately, many registries are “boutique”, with few or no staff with formal informatics training. At a series of Bring Your Own Data workshops, we helped registry owners transform their data into formally structured triple stores following the Linked Data principles and demonstrated the potential of data linkage. We documented several useful approaches that we believe could be followed independently by other registry owners worldwide, including: that the transformation to Linked Data could be considered as passing through layers of increasing semantic complexity; that only a subset of ontologies are relevant at each layer; and that certain data transformation processes could be modelled as an “archetype”, and presented to registry staff to fill-in with their data. We propose that formally capturing these ontological layers and archetyp...

Dutch interface terminologies are needed to use SNOMED CT in the Netherlands. Machine translation... more Dutch interface terminologies are needed to use SNOMED CT in the Netherlands. Machine translation may support in their creation. The aim of our study is to compare different machine translations of procedures in SNOMED CT. Procedures were translated using Google Translate, Matecat, and Thot. Google Translate and Matecat are tools with large but general translation memories. The translation memory of Thot was trained and tuned with various configurations of a Dutch translation of parts of SNOMED CT, a medical dictionary and parts of the UMLS Metathesaurus. The configuration with the highest BLEU score, representing closeness to human translation, was selected. Similarity was determined between Thot translations and those by Google and Matecat. The validity of translations was assessed through random samples. Google and Matecat translated similarly in 85.4% of the cases and generally better than Thot. Whereas the quality of translations was considered acceptable, machine translations ...

The relation between an information entity and its referent can be described as a second-order st... more The relation between an information entity and its referent can be described as a second-order statement, as long as the referent is a type. This is typical for medical discourse such as diagnostic ...

It is widely agreed that rare disease patient registries should be international and follow the g... more It is widely agreed that rare disease patient registries should be international and follow the guiding principles of Findable, Accessible, Interoperable, Reusable (FAIR) for humans and computers. Furthermore, the procedures to collect and exchange data should be harmonised. Since 2014, the Bring Your Own Data (BYOD) annual workshop has been organised by and held at the National Centre for Rare Diseases Istituto Superiore di Sanitá (CNMR-ISS), Rome, Italy with the aim to promote the establishment of FAIR rare disease registries in compliance with IRDiRC and EU recommendations. The event has been arranged with the support of RD-Connect and ELIXIR, in particular, the Dutch Techcentre for Life Sciences representative of ELIXIR-NL. The general roadmap of the BYOD workshop contains at least a preparatory phase, an execution phase, and a follow-up phase to foster the results of the workshop by surveying and having phone conferences with participants. At the 4th edition of the BYOD this ye...

Studies in health technology and informatics, 2011

Multidisciplinary communication about patients with multiple and often interrelated diseases is o... more Multidisciplinary communication about patients with multiple and often interrelated diseases is of utmost importance to guarantee high quality of care. In this paper we focus on storing into the electronic medical record patients' disorders which are associated with each other, taking into account the role of SNOMED CT. The objectives of this paper are to design and discuss possibilities to appropriately record the associations between two disorders as defined in SNOMED CT and to get insight into the use of the relationship "associated with" in SNOMED CT and its consequences for data reuse. Our study showed that textual and concept-based reproducible recording of reusable data is hampered due to incorrect or incomplete modeling of associations between disorders in SNOMED CT. A possible solution for this is to record constituting characteristics of concepts directly into the record, instead of only being represented in the terminology. Further research on binding of inf...

Studies in health technology and informatics, 2017

Journal of innovation in health informatics, Jan 31, 2017

Studies in health technology and informatics, 2004

Studies in health technology and informatics, 2012

Studies in health technology and informatics, 2004

Studies in health technology and informatics, 2018

Studies in health technology and informatics, 2017

Studies in health technology and informatics, 2012

Studies in health technology and informatics, 2016

Studies in health technology and informatics, 2010

Studies in health technology and informatics, 2011

Terminology system-based data encoding for intensive care, 2016

INTRODUCTION Patients are sent to the intensive care unit (ICU) for several reasons, such as life... more INTRODUCTION Patients are sent to the intensive care unit (ICU) for several reasons, such as life-threatening medical problems or monitoring after an extensive surgery. The reason for ICU admission is registered in the electronic medical record (EMR) for direct patient care. Additionally, it is registered for the Acute Physiology and Chronic Health Evaluation IV (APACHE-IV) model to assess the severity of illness of patients at the intensive care, e.g. for quality improvement. This double registration creates an unnecessary administrative burden for ICU clinicians and may lead to suboptimal data quality. Another problem is that encoding diagnoses in a usable manner is challenging, and evidence to support guidelines for optimal user interface (UI) design to support this encoding is limited. PURPOSE The purpose of this scientific research project was to investigate how the APACHE-IV reason for ICU admission can be derived directly from data in the EMR and to gather evidence for guidelines to optimize the UI for medical data encoding.
APACHE-IV DERIVATION METHOD We applied an existing four-step framework to update an existing SNOMED-APACHE mapping from the January 2011 version of SNOMED CT to the July 2015 version. We performed three additional steps to enable the derivation of the APACHE-IV classes from data in the EMR: (1) a migration and revision of the database, (2) the definition of classification rules; particularly for other, unknown and trauma classes, and (3) the design of the derivation process. RESULTS The update was carried out partially: we updated or removed 4 concepts and 7 relationships and revised the database to a new representation in line with SNOMED CT technical documentation. We developed classification rules which could replace the partially mapped other classes (n=49) and unknown classes (n=4) to fully mapped classes and allow the derivation of trauma classes based on traumatized body parts. DISCUSSION With these results we are one step closer to the APACHE-IV derivation from data in the EMR, but the mapping still needs to be revised and updated further. The derivation is hampered by the fact that the APACHE-IV classes are not defined explicitly. CONCLUSION The derivation of APACHE-IV classes requires an up to date SNOMED-APACHE mapping with classification rules, the encoding of admission diagnoses with SNOMED CT or SNOMED CT-based interface terminology and explicitly defined APACHE-IV classes.
UI CONFIGURATION FOR DIAGNOSTIC DATA ENCODING METHOD We compared a guideline-compliant UI configuration for encoding diagnoses to one that resembles the configuration of an existing system, but is not guideline-compliant. Time, correctness, task completion, ease of use, user preference and motivations were the outcomes measures. We used a cross-over design in which we switched a randomly assigned initial configuration after half of the (n=20) cases. SETTING Residents, fellows and assistants (n=27) of the ICU of the Academic Medical Center Amsterdam completed the experiment. RESULTS We did not find a significant difference in correctness, task completion or ease of use, but participants were 19.3% (95% confidence interval: 6.38-33.7%, p-value<0.01) faster with the guideline-compliant UI configuration and had a clear preference for this configuration. Their motivations were in line with the guidelines. DISCUSSION Possibly, the sample size was too low to obtain significant differences in correctness, task completion and ease of use. CONCLUSION The time difference and clear user preference indicate the importance of UI design guidelines for encoding medical data. In order to find the influence on correctness, task completion and ease of use, and to evaluate more types of configurations, more research is required.
CONCLUSION Deriving the APACHE-IV classification from the EMR is still hampered by an incomplete mapping between the interface terminology and SNOMED CT. We indicated that guideline-compliance of a UI to support medical data encoding can increase the speed of encoding and that participants prefer the UI that is compliant. The updated SNOMED-APACHE mapping needs to be implemented and evaluated in future research.