title: Can an online clinical data management service help in improving data collection and data quality in a developing country setting?
abstract: BACKGROUND
  Data collection by electronic medical record (EMR) systems have been proven to be helpful in data collection for scientific research and in improving healthcare. For a multi-centre trial in Indonesia and the Netherlands a web based system was selected to enable all participating centres to easily access data. This study assesses whether the introduction of a clinical trial data management service (CTDMS) composed of electronic case report forms (eCRF) can result in effective data collection and treatment monitoring.
  
  
  METHODS
  Data items entered were checked for inconsistencies automatically when submitted online. The data were divided into primary and secondary data items. We analysed both the total number of errors and the change in error rate, for both primary and secondary items, over the first five month of the trial.
  
  
  RESULTS
  In the first five months 51 patients were entered. The primary data error rate was 1.6%, whilst that for secondary data was 2.7% against acceptable error rates for analysis of 1% and 2.5% respectively.
  
  
  CONCLUSIONS
  The presented analysis shows that after five months since the introduction of the CTDMS the primary and secondary data error rates reflect acceptable levels of data quality. Furthermore, these error rates were decreasing over time. The digital nature of the CTDMS, as well as the online availability of that data, gives fast and easy insight in adherence to treatment protocols. As such, the CTDMS can serve as a tool to train and educate medical doctors and can improve treatment protocols.
authors.affiliation: Department of Head and Neck Oncology and Surgery, The Netherlands Cancer Institute- Antoni van Leeuwenhoek Hospital, Amsterdam, The Netherlands. m.wildeman@nki.nl
authors.forename: Maarten A
authors.initials: MA
authors.lastname: Wildeman
authors.forename: Jeroen
authors.initials: J
authors.lastname: Zandbergen
authors.forename: Andrew
authors.initials: A
authors.lastname: Vincent
authors.forename: Camelia
authors.initials: C
authors.lastname: Herdini
authors.forename: Jaap M
authors.initials: JM
authors.lastname: Middeldorp
authors.forename: Renske
authors.initials: R
authors.lastname: Fles
authors.forename: Otilia
authors.initials: O
authors.lastname: Dalesio
authors.forename: Emile
authors.initials: E
authors.lastname: van der Donk
authors.forename: I Bing
authors.initials: IB
authors.lastname: Tan
mesh_terms: D001331:Automation; D014408:Biomarkers, Tumor / Q000302:isolation & purification; D002277:Carcinoma; D002986:Clinical Trials as Topic / Q000379:methods* / Q000592:standards; D003906:Developing Countries; D057286:Electronic Health Records / Q000592:standards; D004854:Herpesvirus 4, Human / Q000302:isolation & purification; D006801:Humans; D007214:Indonesia; D019451:Information Management / Q000379:methods* / Q000592:standards; D020407:Internet; D015337:Multicenter Studies as Topic / Q000379:methods* / Q000592:standards; D000077274:Nasopharyngeal Carcinoma; D009303:Nasopharyngeal Neoplasms / Q000175:diagnosis / Q000628:therapy / Q000821:virology; D009426:Netherlands; D011237:Predictive Value of Tests; D011786:Quality Control; D012107:Research Design / Q000592:standards; D013997:Time Factors; D016896:Treatment Outcome
chemical_list: D014408:Biomarkers, Tumor