A Review of Data Quality Assessment in Emergency Medical Services

Introduction: Data quality is an important issue in emergency medicine. The unique characteristics of emergency care services, such as high turn-over and the speed of work may increase the possibility of making errors in the related settings. Therefore, regular data quality assessment is necessary to avoid the consequences of low quality data. This study aimed to identify the main dimensions of data quality which had been assessed, the assessment approaches, and generally, the status of data quality in the emergency medical services. Methods: The review was conducted in 2016. Related articles were identified by searching databases, including Scopus, Science Direct, PubMed and Web of Science. All of the review and research papers related to data quality assessment in the emergency care services and published between 2000 and 2015 (n=34) were included in the study. Results: The findings showed that the five dimensions of data quality; namely, data completeness, accuracy, consistency, accessibility, and timeliness had been investigated in the field of emergency medical services. Regarding the assessment methods, quantitative research methods were used more than the qualitative or the mixed methods. Overall, the results of these studies showed that data completeness and data accuracy requires more attention to be improved. Conclusion: In the future studies, choosing a clear and a consistent definition of data quality is required. Moreover, the use of qualitative research methods or the mixed methods is suggested, as data users’ perspectives can provide a broader picture of the reasons for poor quality data.

[1]  Michael J Ward,et al.  Effects of Common Data Errors in Electronic Health Records on Emergency Department Operational Performance Metrics: A Monte Carlo Simulation. , 2015, Academic emergency medicine : official journal of the Society for Academic Emergency Medicine.

[2]  Laura Sebastian-Coleman,et al.  Measuring Data Quality for Ongoing Improvement: A Data Quality Assessment Framework , 2012 .

[3]  Nicholas Genes,et al.  Quality and safety implications of emergency department information systems. , 2013, Annals of emergency medicine.

[4]  Richard Y. Wang,et al.  Data Quality Assessment , 2002 .

[5]  David F.M. Brown,et al.  The accuracy and completeness of data collected by prospective and retrospective methods. , 2005, Academic emergency medicine : official journal of the Society for Academic Emergency Medicine.

[6]  Jane Taggart,et al.  Health reform: Is routinely collected electronic information fit for purpose? , 2012, Emergency medicine Australasia : EMA.

[7]  Jane Taggart,et al.  The Quality of Routinely Collected Data: Using the "Principal Diagnosis" in Emergency Department Databases as an Example , 2011 .

[8]  Anders Haug,et al.  The costs of poor data quality , 2011 .

[10]  J. Kanegaye,et al.  Improved documentation of wound care with a structured encounter form in the pediatric emergency department. , 2005, Ambulatory pediatrics : the official journal of the Ambulatory Pediatric Association.

[11]  Small rural emergency services can electronically collect accurate episode-level data: A cross-sectional study. , 2015, The Australian journal of rural health.

[12]  Matthew Cooke,et al.  Linkage of ambulance service and accident and emergency department data: a study of assault patients in the west midlands region of the UK. , 2005, Injury.

[13]  Nathan Kuppermann,et al.  Lack of agreement in pediatric emergency department discharge diagnoses from clinical and administrative data sources. , 2007, Academic emergency medicine : official journal of the Society for Academic Emergency Medicine.

[14]  Pradeep Kumar Ray,et al.  Towards an ontology for data quality in integrated chronic disease management: A realist review of the literature , 2013, Int. J. Medical Informatics.

[15]  A. Forster,et al.  Prevalence of information gaps for seniors transferred from nursing homes to the emergency department. , 2009, CJEM.

[16]  G Berenholz,et al.  Completeness and accuracy of International Classification of Disease (ICD) external cause of injury codes in emergency department electronic data , 2007, Injury Prevention.

[17]  Abdulelah Alwabel,et al.  Toward a framework for data quality in cloud-based health information system , 2013, International Conference on Information Society (i-Society 2013).

[18]  Madhu C. Reddy,et al.  Identification and Management of Information Problems by Emergency Department Staff , 2014, AMIA.

[19]  Michael J Ward,et al.  Operational data integrity during electronic health record implementation in the ED. , 2013, The American journal of emergency medicine.

[20]  Peter J. Haug,et al.  Research Paper: Assessing the Quality of Clinical Data in a Computer-based Record for Calculating the Pneumonia Severity Index , 2000, J. Am. Medical Informatics Assoc..

[21]  Samuel M. Galvagno,et al.  Identification of dynamic prehospital changes with continuous vital signs acquisition. , 2014, Air medical journal.

[22]  Lachlan MacKinnon,et al.  Assessing Data Quality of Integrated Data by Quality Aggregation of its Ancestors , 2010 .

[23]  Ping Yu,et al.  A Review of Data Quality Assessment Methods for Public Health Information Systems , 2014, International journal of environmental research and public health.

[24]  Hong Chen,et al.  Do We Have the Reliable Data? An Exploration of Data Quality for AIDS Information System in China , 2013, MedInfo.

[25]  Gholamreza Faridaalaee,et al.  Evaluating the quality of multiple trauma patient records in the emergency department of Imam Khomeini Hospital in Urmia , 2015 .

[26]  P. Bath,et al.  Accessibility versus confidentiality of information in the emergency department , 2009, Emergency Medicine Journal.

[27]  Andy Koronios,et al.  Data Quality for Emergency Department BI Dashboard , 2010, ICE-B 2010.

[28]  George Hripcsak,et al.  Emergency Department Access to a Longitudinal Medical Record , 2007, J. Am. Medical Informatics Assoc..

[29]  A. Stiell,et al.  Prevalence of information gaps in the emergency department and the effect on patient outcomes. , 2003, CMAJ : Canadian Medical Association journal = journal de l'Association medicale canadienne.

[30]  Thomas C. Redman,et al.  Measuring Data Accuracy: A Framework and Review , 2014 .

[31]  P. Dalawari,et al.  Patient transfer forms enhance key information between nursing homes and emergency department. , 2011, Geriatric nursing.

[32]  R A Lyons,et al.  Routine narrative analysis as a screening tool to improve data quality , 2003, Injury prevention : journal of the International Society for Child and Adolescent Injury Prevention.

[33]  Reinhold Haux,et al.  Health information systems - past, present, future , 2006, Int. J. Medical Informatics.

[34]  Adir Even,et al.  Data quality assessment in context: A cognitive perspective , 2009, Decis. Support Syst..

[35]  Haleh Ayatollahi,et al.  Information needs of clinicians and non-clinicians in the Emergency Department: a qualitative study. , 2013, Health information and libraries journal.

[36]  J. Marc Overhage,et al.  In Support of Emergency Department Health Information Technology , 2005, AMIA.

[37]  Siti Asma Mohammed,et al.  Towards an evaluation framework for information quality management (IQM) practices for health information systems--evaluation criteria for effective IQM practices. , 2013, Journal of evaluation in clinical practice.

[38]  Anders Grimsmo,et al.  Closing information gaps with shared electronic patient summaries--How much will it matter? , 2011, Int. J. Medical Informatics.

[39]  David D. Salcido,et al.  Inaccuracy of patient care reports for identification of critical resuscitation events during out-of-hospital cardiac arrest. , 2015, The American journal of emergency medicine.

[40]  Dennis Wollersheim,et al.  Geocoding Coronial Data: Tools and Techniques to Improve Data Quality , 2012, Health information management : journal of the Health Information Management Association of Australia.

[41]  Erin C. Smith,et al.  The Development of a Quality Assessment Tool for Ambulance Patient Care Records , 2004, Health information management : journal of the Health Information Management Association of Australia.

[42]  Mei-Chen Lo,et al.  The assessment of the information quality with the aid of multiple criteria analysis , 2009, Eur. J. Oper. Res..

[43]  Debbie A. Travers,et al.  Timeliness of Emergency Department Diagnoses for Syndromic Surveillance , 2006, AMIA.

[44]  Jonathan Groner,et al.  A comparison of paper documentation to electronic documentation for trauma resuscitations at a level I pediatric trauma center. , 2015, Journal of emergency nursing: JEN : official publication of the Emergency Department Nurses Association.

[45]  Shannon Manzi,et al.  Patients providing the answers: narrowing the gap in data quality for emergency care , 2010, Quality and Safety in Health Care.

[46]  David L. Banks,et al.  Data quality: A statistical perspective , 2006 .

[47]  J. Considine,et al.  Can written nursing practice standards improve documentation of initial assessment of ED patients , 2006 .

[48]  Accuracy of the medication history at admission to hospital in Saudi Arabia. , 2011, Saudi pharmaceutical journal : SPJ : the official publication of the Saudi Pharmaceutical Society.

[49]  S. Manzi,et al.  Getting the data right: information accuracy in pediatric emergency medicine , 2006, Quality and Safety in Health Care.

[50]  Markus Helfert,et al.  Assessing information quality deficiencies in emergency medical service performance , 2010, ICIQ.

[51]  Shortfalls in residents' transfer documentation: challenges for emergency department staff. , 2014, Australasian emergency nursing journal : AENJ.

[52]  G. Mears,et al.  A link to improve stroke patient care: a successful linkage between a statewide emergency medical services data system and a stroke registry. , 2010, Academic emergency medicine : official journal of the Society for Academic Emergency Medicine.

[53]  Z. Obermeyer,et al.  Emergency care in 59 low- and middle-income countries: a systematic review , 2015, Bulletin of the World Health Organization.

[54]  Nathan Kuppermann,et al.  Availability of pediatric emergency visit data from existing data sources. , 2005, Academic emergency medicine : official journal of the Society for Academic Emergency Medicine.

[55]  Bart Baesens,et al.  A multidimensional analysis of data quality for credit risk management: New insights and challenges , 2013, Inf. Manag..

[56]  Laura Sebastian-Coleman.  Introduction: Measuring Data Quality for Ongoing Improvement , 2013 .

[57]  Richard Y. Wang,et al.  Developing Measurement Scales for Data-Quality Dimensions , 2014 .

[58]  Carlo Batini,et al.  Methodologies for data quality assessment and improvement , 2009, CSUR.

[59]  J. Brice,et al.  Accuracy of EMS-Recorded Patient Demographic Data , 2008, Prehospital emergency care : official journal of the National Association of EMS Physicians and the National Association of State EMS Directors.

[60]  Kirsten McKenzie,et al.  Assessing the Concordance of Trauma Registry Data and Hospital Records , 2005, Health information management : journal of the Health Information Management Association of Australia.