| 1. |
- Joukes, Erik, et al.
(author)
-
Collect Once, Use Many Times: End-Users Dont Practice What They Preach
- 2016
-
In: EXPLORING COMPLEXITY IN HEALTH: AN INTERDISCIPLINARY SYSTEMS APPROACH. - : IOS PRESS. - 9781614996781 - 9781614996774 ; , s. 252-256
-
Conference paper (peer-reviewed)abstract
- 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 standards, but often register diagnoses and procedures in free text, and experience repeated recording of data. In conclusion, we found that COUMT is currently well adopted in mind, but not yet in practice.
|
|
| 2. |
- Joukes, Erik, et al.
(author)
-
Eliciting end-user expectations to guide the implementation process of a new electronic health record: A case study using concept mapping
- 2016
-
In: International Journal of Medical Informatics. - : ELSEVIER IRELAND LTD. - 1386-5056 .- 1872-8243. ; 87, s. 111-117
-
Journal article (peer-reviewed)abstract
- Objective: To evaluate the usability of concept mapping to elicit the expectations of healthcare professionals regarding the implementation of a new electronic health record (EHR). These expectations need to be taken into account during the implementation process to maximize the chance of success of the EHR. Setting: Two university hospitals in Amsterdam, The Netherlands, in the preparation phase of jointly implementing a new EHR. During this study the hospitals had different methods of documenting patient information (legacy EHR vs. paper-based records). Method: Concept mapping was used to determine and classify the expectations of healthcare professionals regarding the implementation of a new EHR. A multidisciplinary group of 46 healthcare professionals from both university hospitals participated in this study. Expectations were elicited in focus groups, their relevance and feasibility were assessed through a web-questionnaire. Nonmetric multidimensional scaling and clustering methods were used to identify clusters of expectations. Results: We found nine clusters of expectations, each covering an important topic to enable the healthcare professionals to work properly with the new EHR once implemented: usability, data use and reuse, facility conditions, data registration, support, training, internal communication, patients, and collaboration. Average importance and feasibility of each of the clusters was high. Conclusion: Concept mapping is an effective method to find topics that, according to healthcare professionals, are important to consider during the implementation of a new EHR. The method helps to combine the input of a large group of stakeholders at limited efforts. (C) 2016 Elsevier Ireland Ltd. All rights reserved.
|
|
| 3. |
- Burger, Gerard, et al.
(author)
-
Natural language processing in pathology: a scoping review
- 2016
-
In: Journal of Clinical Pathology. - : BMJ PUBLISHING GROUP. - 0021-9746 .- 1472-4146. ; 69:11, s. 949-955
-
Research review (peer-reviewed)abstract
- Background Encoded pathology data are key for medical registries and analyses, but pathology information is often expressed as free text. Objective We reviewed and assessed the use of NLP (natural language processing) for encoding pathology documents. Materials and methods Papers addressing NLP in pathology were retrieved from PubMed, Association for Computing Machinery (ACM) Digital Library and Association for Computational Linguistics (ACL) Anthology. We reviewed and summarised the study objectives; NLP methods used and their validation; software implementations; the performance on the dataset used and any reported use in practice. Results The main objectives of the 38 included papers were encoding and extraction of clinically relevant information from pathology reports. Common approaches were word/phrase matching, probabilistic machine learning and rule-based systems. Five papers (13%) compared different methods on the same dataset. Four papers did not specify the method(s) used. 18 of the 26 studies that reported F-measure, recall or precision reported values of over 0.9. Proprietary software was the most frequently mentioned category (14 studies); General Architecture for Text Engineering (GATE) was the most applied architecture overall. Practical system use was reported in four papers. Most papers used expert annotation validation. Conclusions Different methods are used in NLP research in pathology, and good performances, that is, high precision and recall, high retrieval/removal rates, are reported for all of these. Lack of validation and of shared datasets precludes performance comparison. More comparative analysis and validation are needed to provide better insight into the performance and merits of these methods.
|
|
| 4. |
- Cornet, Ronald, et al.
(author)
-
Comparison of Three English-to-Dutch Machine Translations of SNOMED CT Procedures
- 2017
-
In: MEDINFO 2017: PRECISION HEALTHCARE THROUGH INFORMATICS. - : IOS PRESS. - 9781614998303 - 9781614998297 ; , s. 848-852
-
Conference paper (peer-reviewed)abstract
- 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 alone are yet insufficient.
|
|
| 5. |
- Dentler, Kathrin, et al.
(author)
-
Barriers to the reuse of routinely recorded clinical data : a field report
- 2013
-
In: Proceedings of Studies in Health Technology & Informatics, vol.192. - : IOS Press. - 9781614992882 - 9781614992899 ; , s. 313-317
-
Conference paper (peer-reviewed)abstract
- Today, clinical data is routinely recorded in vast amounts, but its reuse can be challenging. A secondary use that should ideally be based on previously collected clinical data is the computation of clinical quality indicators. In the present study, we attempted to retrieve all data from our hospital that is required to compute a set of quality indicators in the domain of colorectal cancer surgery. We categorised the barriers that we encountered in the scope of this project according to an existing framework, and provide recommendations on how to prevent or surmount these barriers. Assuming that our case is not unique, these recommendations might be applicable for the design, evaluation and optimisation of Electronic Health Records.
|
|
| 6. |
- Dentler, Kathrin, et al.
(author)
-
Formalization and computation of quality measures based on electronic medical records
- 2014
-
In: JAMIA Journal of the American Medical Informatics Association. - : BMJ Publishing Group / Elsevier. - 1067-5027 .- 1527-974X. ; 21:2, s. 285-291
-
Journal article (peer-reviewed)abstract
- Objective Ambiguous definitions of quality measures in natural language impede their automated computability and also the reproducibility, validity, timeliness, traceability, comparability, and interpretability of computed results. Therefore, quality measures should be formalized before their release. We have previously developed and successfully applied a method for clinical indicator formalization (CLIF). The objective of our present study is to test whether CLIF is generalizablethat is, applicable to a large set of heterogeneous measures of different types and from various domains. Materials and methods We formalized the entire set of 159 Dutch quality measures for general practice, which contains structure, process, and outcome measures and covers seven domains. We relied on a web-based tool to facilitate the application of our method. Subsequently, we computed the measures on the basis of a large database of real patient data. Results Our CLIF method enabled us to fully formalize 100% of the measures. Owing to missing functionality, the accompanying tool could support full formalization of only 86% of the quality measures into Structured Query Language (SQL) queries. The remaining 14% of the measures required manual application of our CLIF method by directly translating the respective criteria into SQL. The results obtained by computing the measures show a strong correlation with results computed independently by two other parties. Conclusions The CLIF method covers all quality measures after having been extended by an additional step. Our web tool requires further refinement for CLIF to be applied completely automatically. We therefore conclude that CLIF is sufficiently generalizable to be able to formalize the entire set of Dutch quality measures for general practice.
|
|
| 7. |
- Dentler, Kathrin, et al.
(author)
-
Influence of data quality on computed Dutch hospital quality indicators: a case study in colorectal cancer surgery
- 2014
-
In: BMC Medical Informatics and Decision Making. - : BioMed Central. - 1472-6947. ; 14:32
-
Journal article (peer-reviewed)abstract
- Background: Our study aims to assess the influence of data quality on computed Dutch hospital quality indicators, and whether colorectal cancer surgery indicators can be computed reliably based on routinely recorded data from an electronic medical record (EMR). Methods: Cross-sectional study in a department of gastrointestinal oncology in a university hospital, in which a set of 10 indicators is computed (1) based on data abstracted manually for the national quality register Dutch Surgical Colorectal Audit (DSCA) as reference standard and (2) based on routinely collected data from an EMR. All 75 patients for whom data has been submitted to the DSCA for the reporting year 2011 and all 79 patients who underwent a resection of a primary colorectal carcinoma in 2011 according to structured data in the EMR were included. Comparison of results, investigating the causes for any differences based on data quality analysis. Main outcome measures are the computability of quality indicators, absolute percentages of indicator results, data quality in terms of availability in a structured format, completeness and correctness. Results: All indicators were fully computable based on the DSCA dataset, but only three based on EMR data, two of which were percentages. For both percentages, the difference in proportions computed based on the two datasets was significant. All required data items were available in a structured format in the DSCA dataset. Their average completeness was 86%, while the average completeness of these items in the EMR was 50%. Their average correctness was 87%. Conclusions: Our study showed that data quality can significantly influence indicator results, and that our EMR data was not suitable to reliably compute quality indicators. EMRs should be designed in a way so that the data required for audits can be entered directly in a structured and coded format.
|
|
| 8. |
- Huijben, Jilske A., et al.
(author)
-
Development of a quality indicator set to measure and improve quality of ICU care for patients with traumatic brain injury
- 2019
-
In: Critical Care. - : BioMed Central. - 1364-8535 .- 1466-609X. ; 23
-
Journal article (peer-reviewed)abstract
- Background: We aimed to develop a set of quality indicators for patients with traumatic brain injury (TBI) in intensive care units (ICUs) across Europe and to explore barriers and facilitators for implementation of these quality indicators.Methods: A preliminary list of 66 quality indicators was developed, based on current guidelines, existing practice variation, and clinical expertise in TBI management at the ICU. Eight TBI experts of the Advisory Committee preselected the quality indicators during a first Delphi round. A larger Europe-wide expert panel was recruited for the next two Delphi rounds. Quality indicator definitions were evaluated on four criteria: validity (better performance on the indicator reflects better processes of care and leads to better patient outcome), feasibility (data are available or easy to obtain), discriminability (variability in clinical practice), and actionability (professionals can act based on the indicator). Experts scored indicators on a 5-point Likert scale delivered by an electronic survey tool.Results. The expert panel consisted of 50 experts from 18 countries across Europe, mostly intensivists (N=24, 48%) and neurosurgeons (N=7, 14%). Experts agreed on a final set of 42 indicators to assess quality of ICU care: 17 structure indicators, 16 process indicators, and 9 outcome indicators. Experts are motivated to implement this finally proposed set (N=49, 98%) and indicated routine measurement in registries (N=41, 82%), benchmarking (N=42, 84%), and quality improvement programs (N=41, 82%) as future steps. Administrative burden was indicated as the most important barrier for implementation of the indicator set (N=48, 98%).Conclusions: This Delphi consensus study gives insight in which quality indicators have the potential to improve quality of TBI care at European ICUs. The proposed quality indicator set is recommended to be used across Europe for registry purposes to gain insight in current ICU practices and outcomes of patients with TBI. This indicator set may become an important tool to support benchmarking and quality improvement programs for patients with TBI in the future.
|
|
| 9. |
- Huijben, Jilske A, et al.
(author)
-
Quality indicators for patients with traumatic brain injury in European intensive care units : a CENTER-TBI study.
- 2020
-
In: Critical Care. - : Springer Science and Business Media LLC. - 1364-8535 .- 1466-609X. ; 24:1
-
Journal article (peer-reviewed)abstract
- BACKGROUND: The aim of this study is to validate a previously published consensus-based quality indicator set for the management of patients with traumatic brain injury (TBI) at intensive care units (ICUs) in Europe and to study its potential for quality measurement and improvement.METHODS: Our analysis was based on 2006 adult patients admitted to 54 ICUs between 2014 and 2018, enrolled in the CENTER-TBI study. Indicator scores were calculated as percentage adherence for structure and process indicators and as event rates or median scores for outcome indicators. Feasibility was quantified by the completeness of the variables. Discriminability was determined by the between-centre variation, estimated with a random effect regression model adjusted for case-mix severity and quantified by the median odds ratio (MOR). Statistical uncertainty of outcome indicators was determined by the median number of events per centre, using a cut-off of 10.RESULTS: A total of 26/42 indicators could be calculated from the CENTER-TBI database. Most quality indicators proved feasible to obtain with more than 70% completeness. Sub-optimal adherence was found for most quality indicators, ranging from 26 to 93% and 20 to 99% for structure and process indicators. Significant (p < 0.001) between-centre variation was found in seven process and five outcome indicators with MORs ranging from 1.51 to 4.14. Statistical uncertainty of outcome indicators was generally high; five out of seven had less than 10 events per centre.CONCLUSIONS: Overall, nine structures, five processes, but none of the outcome indicators showed potential for quality improvement purposes for TBI patients in the ICU. Future research should focus on implementation efforts and continuous reevaluation of quality indicators.TRIAL REGISTRATION: The core study was registered with ClinicalTrials.gov, number NCT02210221, registered on August 06, 2014, with Resource Identification Portal (RRID: SCR_015582).
|
|
| 10. |
- Joukes, Erik, et al.
(author)
-
Composite Quality of Care Scores, Electronic Health Record Maturity Models, and their Associations; Preliminary Literature Review Results.
- 2013
-
In: Proceedings of Studies in Health Technology & Informatics, vol. 192. - 9781614992882 - 9781614992899 ; , s. 981-981
-
Conference paper (peer-reviewed)abstract
- To accurately assess the association between the use of EHR systems and the quality of healthcare we need (composite) measures for quality of healthcare, and a model to measure the maturity of the EHR. This Medline-based literature study therefore focussed on three topics; (1) methods to compose a measure for quality of care based on individual quality indicators (QI), (2) models to measure EHR maturity, and (3) the association between the former two. Composite quality is most often measured using opportunity-based scores, maturity is measured in functionalities or levels. EHR maturity measures are not used extensively in biomedical literature. Most studies found a positive association between EHR use and the quality of care but almost none of them differentiate in maturity of EHR which hampers firm conclusions about this relation.
|
|
