Development and validation of a data dictionary for a feasibility analysis of emergency department key performance indicators

OBJECTIVES The primary study objective was to describe the development of a data dictionary for a feasibility analysis of 11 emergency department (ED) key performance indicators (KPIs). The secondary objective was to internally validate the data dictionary by measuring the inter-observer agreement between data abstractors at participating study sites. METHODS A list of data variables based on the minimum data set elements relevant to the KPIs was developed by a panel of emergency medicine (EM) specialists and from the EM literature. A summit involving the relevant stakeholders, including ED frontline staff, a health economist, an ED clinical data manager and a health care informatician, was convened. For the feasibility analysis project, each data abstractor was furnished with a copy of the data dictionary and attended a one-hour training session prior to commencing data abstraction. Data was independently abstracted for each KPI by two abstractors at each of 12 participating EDs. Inter-rater agreement between abstractors was calculated using Cohen's kappa and results were reported using the Landis and Koch criteria. RESULTS A data dictionary was developed by creating clear definitions and establishing abstraction instructions for each variable. A total of 43 data variables were included in the study data dictionary: 4 on patient demographics; 19 time variables; 5 outcome variables; 8 ED service and staffing units and 7 medical definitions. A clear definition and a set of data abstraction instructions including data sources were developed for each variable to aid data abstraction during the feasibility analysis. Overall 9,276 ED patient records were used for data abstraction to internally validate the data dictionary. The median Cohen kappa score ranged between 0.56 to 0.81. CONCLUSION There is a continued need to standardize definitions of KPIs for the purpose of comparing ED performance and for research purposes. This is a necessary first step in the implementation of valid and reliable ED performance measures. This study successfully developed an internally valid data dictionary that can be used for day-to-day ED operations and for research purposes.

[1]  Martin C. Were,et al.  Developing a National-Level Concept Dictionary for EHR Implementations in Kenya , 2015, MedInfo.

[2]  Alastair Baker,et al.  Crossing the Quality Chasm: A New Health System for the 21st Century , 2001, BMJ : British Medical Journal.

[3]  N. B. Anuar,et al.  The rise of "big data" on cloud computing: Review and open research issues , 2015, Inf. Syst..

[4]  Shari J. Welch,et al.  Emergency department performance measures updates: proceedings of the 2014 emergency department benchmarking alliance consensus summit. , 2015, Academic emergency medicine : official journal of the Society for Academic Emergency Medicine.

[5]  H. McKenna The Delphi technique: a worthwhile research approach for nursing? , 1994, Journal of advanced nursing.

[6]  J. Cimino Desiderata for Controlled Medical Vocabularies in the Twenty-First Century , 1998, Methods of Information in Medicine.

[7]  Variability in data: the Society of Thoracic Surgeons National Adult Cardiac Surgery Database. , 2010, The Journal of thoracic and cardiovascular surgery.

[8]  M. McHugh Interrater reliability: the kappa statistic , 2012, Biochemia medica.

[9]  J. R. Landis,et al.  The measurement of observer agreement for categorical data. , 1977, Biometrics.

[10]  A. Donabedian Evaluating the quality of medical care. 1966. , 1966, The Milbank quarterly.

[11]  Jacob Cohen,et al.  Weighted kappa: Nominal scale agreement provision for scaled disagreement or partial credit. , 1968 .

[12]  InSook Cho,et al.  Research Paper: Evaluation of the Expressiveness of an ICNP-based Nursing Data Dictionary in a Computerized Nursing Record System , 2006, J. Am. Medical Informatics Assoc..

[13]  Nabil Ahmed Sultan,et al.  Making use of cloud computing for healthcare provision: Opportunities and challenges , 2014, Int. J. Inf. Manag..

[14]  F. Hasson,et al.  A critical review of the Delphi technique as a research methodology for nursing. , 2001, International journal of nursing studies.

[15]  L. Given,et al.  The SAGE encyclopedia of qualitative research methods , 2011 .

[16]  Conor M. McWade,et al.  Implementing Data Definition Consistency for Emergency Department Operations Benchmarking and Research. , 2016, Academic emergency medicine : official journal of the Society for Academic Emergency Medicine.

[17]  Cathal Walsh,et al.  Development of key performance indicators for emergency departments in Ireland using an electronic modified-Delphi consensus approach , 2013, European journal of emergency medicine : official journal of the European Society for Emergency Medicine.

[18]  Jill Clark,et al.  Managing a data dictionary. , 2012, Journal of AHIMA.

[19]  Shari J. Welch,et al.  Emergency department performance measures and benchmarking summit. , 2006, Academic emergency medicine : official journal of the Society for Academic Emergency Medicine.

[20]  L. Morrison,et al.  Development of a data dictionary for the Strategies for Post Arrest Resuscitation Care (SPARC) network for post cardiac arrest research. , 2011, Resuscitation.

[21]  K. O'Brien,et al.  Data Management and Data Quality in PERCH, a Large International Case-Control Study of Severe Childhood Pneumonia , 2017, Clinical infectious diseases : an official publication of the Infectious Diseases Society of America.

[22]  Patricia S Wilson What mapping and modeling means to the HIM professional. , 2007, Perspectives in health information management.

[23]  Myung Kyung Lee,et al.  Evaluation of the Clinical Data Dictionary (CiDD) , 2010, Healthcare informatics research.

[24]  M. Schull,et al.  A framework for measuring quality in the emergency department , 2011, Emergency Medicine Journal.

[25]  Alisa Surkis,et al.  Improving data collection, documentation, and workflow in a dementia screening study , 2017, Journal of the Medical Library Association : JMLA.

[26]  J R Campbell,et al.  A framework for comprehensive health terminology systems in the United States: development guidelines, criteria for selection, and public policy implications. ANSI Healthcare Informatics Standards Board Vocabulary Working Group and the Computer-Based Patient Records Institute Working Group on Codes , 1998, Journal of the American Medical Informatics Association : JAMIA.

[27]  C M Goodman,et al.  The Delphi technique: a critique. , 1987, Journal of advanced nursing.

[28]  Shari J. Welch,et al.  Emergency department operations dictionary: results of the second performance measures and benchmarking summit. , 2011, Academic emergency medicine : official journal of the Society for Academic Emergency Medicine.

[29]  M. Gillam,et al.  Developing consensus in emergency medicine information technology. , 2004, Academic emergency medicine : official journal of the Society for Academic Emergency Medicine.