---
_id: '9356'
abstract:
- lang: eng
  text: In today’s manufacturing industry, enterprise-resource-planning (ERP) systems
    reach their limit when planning and scheduling production subject to multiple
    objectives and constraints. Advanced planning and scheduling (APS) systems provide
    these capabilities and are an extension for ERP systems. However, when integrating
    an APS and ERP system, the ERP data frequently lacks quality, hindering the APS
    system from working as required. This paper introduces a data quality (DQ) assessment
    framework that employs a Bayesian Network (BN) to perform quick DQ assessments
    based on expert interviews and DQ measurements with actual ERP data. We explain
    the BN’s functionality, design, and validation and show how using the perceived
    DQ of experts and a semi-supervised learning algorithm improves the BN’s predictions
    over time. We discuss applying our framework in an APS system implementation project
    involving an APS system provider and a medium-sized manufacturer of hydraulic
    cylinders. Despite considering the DQ assessment framework in such a specific
    context, it is not restricted to a particular domain. We close by discussing the
    framework’s limits, particularly the BN as a DQ assessment methodology and future
    works to improve its performance.
author:
- first_name: Jan-Phillip
  full_name: Herrmann, Jan-Phillip
  id: '75846'
  last_name: Herrmann
- first_name: Sven
  full_name: Tackenberg, Sven
  id: '71470'
  last_name: Tackenberg
- first_name: Elio
  full_name: Padoano, Elio
  last_name: Padoano
- first_name: Jörg
  full_name: Hartlief, Jörg
  last_name: Hartlief
- first_name: Jens
  full_name: ' Rautenstengel, Jens'
  last_name: ' Rautenstengel'
- first_name: Christine
  full_name: Loeser, Christine
  last_name: Loeser
- first_name: 'Jörg '
  full_name: 'Böhme, Jörg '
  last_name: Böhme
citation:
  ama: Herrmann JP, Tackenberg S, Padoano E, et al. An ERP Data Quality Assessment
    Framework for the Implementation of an APS system using Bayesian Networks. <i>Procedia
    Computer Science</i>. 2022;200:194-204. doi:<a href="https://doi.org/10.1016/j.procs.2022.01.218">https://doi.org/10.1016/j.procs.2022.01.218</a>
  apa: Herrmann, J.-P., Tackenberg, S., Padoano, E., Hartlief, J.,  Rautenstengel,
    J., Loeser, C., &#38; Böhme, J. (2022). An ERP Data Quality Assessment Framework
    for the Implementation of an APS system using Bayesian Networks. <i>Procedia Computer
    Science</i>, <i>200</i>, 194–204. <a href="https://doi.org/10.1016/j.procs.2022.01.218">https://doi.org/10.1016/j.procs.2022.01.218</a>
  bjps: <b>Herrmann J-P <i>et al.</i></b> (2022) An ERP Data Quality Assessment Framework
    for the Implementation of an APS System Using Bayesian Networks. <i>Procedia Computer
    Science</i> <b>200</b>, 194–204.
  chicago: 'Herrmann, Jan-Phillip, Sven Tackenberg, Elio Padoano, Jörg Hartlief, Jens  Rautenstengel,
    Christine Loeser, and Jörg  Böhme. “An ERP Data Quality Assessment Framework for
    the Implementation of an APS System Using Bayesian Networks.” <i>Procedia Computer
    Science</i> 200 (2022): 194–204. <a href="https://doi.org/10.1016/j.procs.2022.01.218">https://doi.org/10.1016/j.procs.2022.01.218</a>.'
  chicago-de: 'Herrmann, Jan-Phillip, Sven Tackenberg, Elio Padoano, Jörg Hartlief,
    Jens  Rautenstengel, Christine Loeser und Jörg  Böhme. 2022. An ERP Data Quality
    Assessment Framework for the Implementation of an APS system using Bayesian Networks.
    <i>Procedia Computer Science</i> 200: 194–204. doi:<a href="https://doi.org/10.1016/j.procs.2022.01.218">https://doi.org/10.1016/j.procs.2022.01.218</a>,
    .'
  din1505-2-1: '<span style="font-variant:small-caps;">Herrmann, Jan-Phillip</span>
    ; <span style="font-variant:small-caps;">Tackenberg, Sven</span> ; <span style="font-variant:small-caps;">Padoano,
    Elio</span> ; <span style="font-variant:small-caps;">Hartlief, Jörg</span> ; <span
    style="font-variant:small-caps;"> Rautenstengel, Jens</span> ; <span style="font-variant:small-caps;">Loeser,
    Christine</span> ; <span style="font-variant:small-caps;">Böhme, Jörg </span>:
    An ERP Data Quality Assessment Framework for the Implementation of an APS system
    using Bayesian Networks. In: <i>Procedia Computer Science</i> Bd. 200, Elsevier
    (2022), S. 194–204'
  havard: J.-P. Herrmann, S. Tackenberg, E. Padoano, J. Hartlief, J.  Rautenstengel,
    C. Loeser, J. Böhme, An ERP Data Quality Assessment Framework for the Implementation
    of an APS system using Bayesian Networks, Procedia Computer Science. 200 (2022)
    194–204.
  ieee: 'J.-P. Herrmann <i>et al.</i>, “An ERP Data Quality Assessment Framework for
    the Implementation of an APS system using Bayesian Networks,” <i>Procedia Computer
    Science</i>, vol. 200, pp. 194–204, 2022, doi: <a href="https://doi.org/10.1016/j.procs.2022.01.218">https://doi.org/10.1016/j.procs.2022.01.218</a>.'
  mla: Herrmann, Jan-Phillip, et al. “An ERP Data Quality Assessment Framework for
    the Implementation of an APS System Using Bayesian Networks.” <i>Procedia Computer
    Science</i>, vol. 200, 2022, pp. 194–204, <a href="https://doi.org/10.1016/j.procs.2022.01.218">https://doi.org/10.1016/j.procs.2022.01.218</a>.
  short: J.-P. Herrmann, S. Tackenberg, E. Padoano, J. Hartlief, J.  Rautenstengel,
    C. Loeser, J. Böhme, Procedia Computer Science 200 (2022) 194–204.
  ufg: '<b>Herrmann, Jan-Phillip u. a.</b>: An ERP Data Quality Assessment Framework
    for the Implementation of an APS system using Bayesian Networks, in: <i>Procedia
    Computer Science</i> 200 (2022),  S. 194–204.'
  van: Herrmann JP, Tackenberg S, Padoano E, Hartlief J,  Rautenstengel J, Loeser
    C, et al. An ERP Data Quality Assessment Framework for the Implementation of an
    APS system using Bayesian Networks. Procedia Computer Science. 2022;200:194–204.
date_created: 2023-01-25T12:00:32Z
date_updated: 2024-08-06T11:45:41Z
department:
- _id: DEP7020
doi: https://doi.org/10.1016/j.procs.2022.01.218
intvolume: '       200'
keyword:
- Data Quality Assessment
- Advanced Planning
- Scheduling
- Bayesian Network
- Enterprise Resource Planning
language:
- iso: eng
main_file_link:
- open_access: '1'
  url: https://www.sciencedirect.com/science/article/pii/S1877050922002277
oa: '1'
page: 194-204
publication: Procedia Computer Science
publication_identifier:
  issn:
  - '1877-0509 '
publication_status: published
publisher: Elsevier
quality_controlled: '1'
status: public
title: An ERP Data Quality Assessment Framework for the Implementation of an APS system
  using Bayesian Networks
type: journal_article
user_id: '83781'
volume: 200
year: '2022'
...
---
_id: '11745'
abstract:
- lang: eng
  text: "Background: Data capture is one of the most expensive phases during the conduct
    of a clinical trial and the increasing use of electronic health records (EHR)
    offers significant savings to clinical research. To facilitate these secondary
    uses of routinely collected patient data, it is beneficial to know what data elements
    are captured in clinical trials. Therefore our aim here is to determine the most
    commonly used data elements in clinical trials and their availability in hospital
    EHR systems.\r\n\r\nMethods: Case report forms for 23 clinical trials in differing
    disease areas were analyzed. Through an iterative and consensus-based process
    of medical informatics professionals from academia and trial experts from the
    European pharmaceutical industry, data elements were compiled for all disease
    areas and with special focus on the reporting of adverse events. Afterwards, data
    elements were identified and statistics acquired from hospital sites providing
    data to the EHR4CR project.\r\n\r\nResults: The analysis identified 133 unique
    data elements. Fifty elements were congruent with a published data inventory for
    patient recruitment and 83 new elements were identified for clinical trial execution,
    including adverse event reporting. Demographic and laboratory elements lead the
    list of available elements in hospitals EHR systems. For the reporting of serious
    adverse events only very few elements could be identified in the patient records.\r\n\r\nConclusions:
    Common data elements in clinical trials have been identified and their availability
    in hospital systems elucidated. Several elements, often those related to reimbursement,
    are frequently available whereas more specialized elements are ranked at the bottom
    of the data inventory list. Hospitals that want to obtain the benefits of reusing
    data for research from their EHR are now able to prioritize their efforts based
    on this common data element list."
article_number: '159'
author:
- first_name: Philipp
  full_name: Bruland, Philipp
  id: '75847'
  last_name: Bruland
  orcid: 0000-0001-6939-7630
- first_name: Mark
  full_name: McGilchrist, Mark
  last_name: McGilchrist
- first_name: Eric
  full_name: Zapletal, Eric
  last_name: Zapletal
- first_name: Dionisio
  full_name: Acosta, Dionisio
  last_name: Acosta
- first_name: Johann
  full_name: Proeve, Johann
  last_name: Proeve
- first_name: Scott
  full_name: Askin, Scott
  last_name: Askin
- first_name: Thomas
  full_name: Ganslandt, Thomas
  last_name: Ganslandt
- first_name: Justin
  full_name: Doods, Justin
  last_name: Doods
- first_name: Martin
  full_name: Dugas, Martin
  last_name: Dugas
citation:
  ama: Bruland P, McGilchrist M, Zapletal E, et al. Common data elements for secondary
    use of electronic health record data for clinical trial execution and serious
    adverse event reporting. <i>BMC Medical Research Methodology</i>. 2016;16(1).
    doi:<a href="https://doi.org/10.1186/s12874-016-0259-3">10.1186/s12874-016-0259-3</a>
  apa: Bruland, P., McGilchrist, M., Zapletal, E., Acosta, D., Proeve, J., Askin,
    S., Ganslandt, T., Doods, J., &#38; Dugas, M. (2016). Common data elements for
    secondary use of electronic health record data for clinical trial execution and
    serious adverse event reporting. <i>BMC Medical Research Methodology</i>, <i>16</i>(1),
    Article 159. <a href="https://doi.org/10.1186/s12874-016-0259-3">https://doi.org/10.1186/s12874-016-0259-3</a>
  bjps: <b>Bruland P <i>et al.</i></b> (2016) Common Data Elements for Secondary Use
    of Electronic Health Record Data for Clinical Trial Execution and Serious Adverse
    Event Reporting. <i>BMC Medical Research Methodology</i> <b>16</b>.
  chicago: Bruland, Philipp, Mark McGilchrist, Eric Zapletal, Dionisio Acosta, Johann
    Proeve, Scott Askin, Thomas Ganslandt, Justin Doods, and Martin Dugas. “Common
    Data Elements for Secondary Use of Electronic Health Record Data for Clinical
    Trial Execution and Serious Adverse Event Reporting.” <i>BMC Medical Research
    Methodology</i> 16, no. 1 (2016). <a href="https://doi.org/10.1186/s12874-016-0259-3">https://doi.org/10.1186/s12874-016-0259-3</a>.
  chicago-de: Bruland, Philipp, Mark McGilchrist, Eric Zapletal, Dionisio Acosta,
    Johann Proeve, Scott Askin, Thomas Ganslandt, Justin Doods und Martin Dugas. 2016.
    Common data elements for secondary use of electronic health record data for clinical
    trial execution and serious adverse event reporting. <i>BMC Medical Research Methodology</i>
    16, Nr. 1. doi:<a href="https://doi.org/10.1186/s12874-016-0259-3">10.1186/s12874-016-0259-3</a>,
    .
  din1505-2-1: '<span style="font-variant:small-caps;"><span style="font-variant:small-caps;">Bruland,
    Philipp</span> ; <span style="font-variant:small-caps;">McGilchrist, Mark</span>
    ; <span style="font-variant:small-caps;">Zapletal, Eric</span> ; <span style="font-variant:small-caps;">Acosta,
    Dionisio</span> ; <span style="font-variant:small-caps;">Proeve, Johann</span>
    ; <span style="font-variant:small-caps;">Askin, Scott</span> ; <span style="font-variant:small-caps;">Ganslandt,
    Thomas</span> ; <span style="font-variant:small-caps;">Doods, Justin</span> ;
    u. a.</span>: Common data elements for secondary use of electronic health record
    data for clinical trial execution and serious adverse event reporting. In: <i>BMC
    Medical Research Methodology</i> Bd. 16. London, Springer Science and Business
    Media LLC (2016), Nr. 1'
  havard: P. Bruland, M. McGilchrist, E. Zapletal, D. Acosta, J. Proeve, S. Askin,
    T. Ganslandt, J. Doods, M. Dugas, Common data elements for secondary use of electronic
    health record data for clinical trial execution and serious adverse event reporting,
    BMC Medical Research Methodology. 16 (2016).
  ieee: 'P. Bruland <i>et al.</i>, “Common data elements for secondary use of electronic
    health record data for clinical trial execution and serious adverse event reporting,”
    <i>BMC Medical Research Methodology</i>, vol. 16, no. 1, Art. no. 159, 2016, doi:
    <a href="https://doi.org/10.1186/s12874-016-0259-3">10.1186/s12874-016-0259-3</a>.'
  mla: Bruland, Philipp, et al. “Common Data Elements for Secondary Use of Electronic
    Health Record Data for Clinical Trial Execution and Serious Adverse Event Reporting.”
    <i>BMC Medical Research Methodology</i>, vol. 16, no. 1, 159, 2016, <a href="https://doi.org/10.1186/s12874-016-0259-3">https://doi.org/10.1186/s12874-016-0259-3</a>.
  short: P. Bruland, M. McGilchrist, E. Zapletal, D. Acosta, J. Proeve, S. Askin,
    T. Ganslandt, J. Doods, M. Dugas, BMC Medical Research Methodology 16 (2016).
  ufg: '<b>Bruland, Philipp u. a.</b>: Common data elements for secondary use of electronic
    health record data for clinical trial execution and serious adverse event reporting,
    in: <i>BMC Medical Research Methodology</i> 16 (2016), H. 1.'
  van: Bruland P, McGilchrist M, Zapletal E, Acosta D, Proeve J, Askin S, et al. Common
    data elements for secondary use of electronic health record data for clinical
    trial execution and serious adverse event reporting. BMC Medical Research Methodology.
    2016;16(1).
date_created: 2024-07-18T13:31:36Z
date_updated: 2024-07-18T13:33:42Z
department:
- _id: DEP5024
doi: 10.1186/s12874-016-0259-3
extern: '1'
intvolume: '        16'
issue: '1'
keyword:
- Clinical trials
- Common data elements
- Data quality
- Electronic health records
- Metadata
- Secondary use
language:
- iso: eng
place: London
publication: BMC Medical Research Methodology
publication_identifier:
  issn:
  - 1471-2288
publication_status: published
publisher: Springer Science and Business Media LLC
status: public
title: Common data elements for secondary use of electronic health record data for
  clinical trial execution and serious adverse event reporting
type: scientific_journal_article
user_id: '83781'
volume: 16
year: '2016'
...