Data Quality Associated with Handwritten Laboratory Test Requests: Classification and Frequency of Data-Entry Errors for Outpatient Serology Tests

2015 ◽  
Vol 44 (3) ◽  
pp. 7-12 ◽  
Author(s):  
Elia Vecellio ◽  
Michael W. Maley ◽  
George Toouli ◽  
Andrew Georgiou ◽  
Johanna Westbrook
Keyword(s):  
Laboratory Test ◽  
Data Quality ◽  
Data Entry

Synoptic operative reports for spinal cord injury patients as a tool for data quality

2016 ◽  
Vol 22 (4) ◽  
pp. 984-991 ◽  
Author(s):  
Grace I Paterson ◽  
Sean Christie ◽  
Wilfred Bonney ◽  
Ginette Thibault-Halman
Keyword(s):  
Spinal Cord ◽  
Spinal Cord Injury ◽  
Data Quality ◽  
Accuracy Assessment ◽  
Data Entry ◽  
Secondary Data ◽  
Feedback Questionnaire ◽  
Data Feedback ◽  
Cord Injury ◽  
Operative Report

The advent of synoptic operative reports has revolutionized how clinical data are captured at the time of care. In this article, an electronic synoptic operative report for spinal cord injury was implemented using interoperable standards, HL7 and Systematized Nomenclature of Medicine–Clinical Terms. Subjects ( N = 10) recruited for a pilot study completed recruitment and feedback questionnaires, and produced both an electronic synoptic operative report for spinal cord injury report and a dictated narrative operative report for an actual patient case. Results indicated heterogeneity by subjects in access and use of electronic sources of patient data. Feedback questionnaire results confirmed that subjects were comfortable using both methods for data entry of operative reports, and that some were unable to find the diagnosis terms they needed in electronic synoptic operative report for spinal cord injury. Data quality improved. Electronic synoptic operative report for spinal cord injury reports were more complete (95.26%) than dictated (80%) for all subjects. An accuracy assessment, which considered usability for secondary data use, was conducted and the electronic synoptic operative report for spinal cord injury was demonstrated to improve accuracy.

scholarly journals Evaluation of National Injury Surveillance Centre, India, 2015-16

2020 ◽  
Vol 32 (1) ◽  
pp. 51-56
Author(s):  
Naveen Kumar Rastogi ◽  
Kapil Goel ◽  
Tanu Jain ◽  
Samir V Sodha ◽  
Rajesh Yadav ◽  
...  
Keyword(s):  
Data Quality ◽  
Data Entry ◽  
Cross Sectional Study ◽  
Injury Surveillance ◽  
New Delhi ◽  
Willingness To Participate ◽  
Cross Sectional ◽  
Key Informants ◽  
Annual Reporting ◽  
Reported Data

Background: Globally, injuries accounts for 9% of all deaths, but India account for 11%. Due to limited data on injury characteristics, National Injury Surveillance Centre (NISC) was established in 2014 in New Delhi. Aim & Objectives: To evaluate attributes of NISC and make evidence-based recommendations. Methods and Material: We conducted cross-sectional study and used US Centers for Disease Control and Prevention guidelines to assess simplicity, flexibility, acceptability, stability, timeliness, representativeness, usefulness, and data quality. We reviewed 2015 records and interviewed 20 key-informants. We used Epi-Info7 for analysis. Results: NISC captured 4043 injuries in 2015 from one hospital. Among five data entry operators, four reported lengthy format, but all reported it easy. Among ten relevant key-informants, all reported data-management software easy. System demonstrated flexibility in three variables. All 20 staff reported willingness to participate, and 90% felt quarterly reporting acceptable. Regarding stability, data was collected for 361/365 days. Quarterly reports were available but only submitted annually. Regarding usefulness, all WHO-recommended variables included. Regarding data quality, 17% data-fields were missing. Conclusion: NISC is simple, flexible, stable, acceptable and potentially useful based on data captured. Timeliness based on annual reporting is high, can be improved to quarterly. We recommend training to improve data quality and integration of additional hospitals to improve representativeness.

scholarly journals Overcoming challenges to data quality in the ASPREE clinical trial

Trials ◽  
2019 ◽  
Vol 20 (1) ◽  
Author(s):  
Jessica E. Lockery ◽  
◽  
Taya A. Collyer ◽  
Christopher M. Reid ◽  
Michael E. Ernst ◽  
...  
Keyword(s):  
Clinical Trials ◽  
Missing Data ◽  
Data Quality ◽  
Large Scale ◽  
Controlled Trial ◽  
Data Entry ◽  
Quality Data ◽  
Community Based ◽  
Data Set ◽  
The Impact

Abstract Background Large-scale studies risk generating inaccurate and missing data due to the complexity of data collection. Technology has the potential to improve data quality by providing operational support to data collectors. However, this potential is under-explored in community-based trials. The Aspirin in reducing events in the elderly (ASPREE) trial developed a data suite that was specifically designed to support data collectors: the ASPREE Web Accessible Relational Database (AWARD). This paper describes AWARD and the impact of system design on data quality. Methods AWARD’s operational requirements, conceptual design, key challenges and design solutions for data quality are presented. Impact of design features is assessed through comparison of baseline data collected prior to implementation of key functionality (n = 1000) with data collected post implementation (n = 18,114). Overall data quality is assessed according to data category. Results At baseline, implementation of user-driven functionality reduced staff error (from 0.3% to 0.01%), out-of-range data entry (from 0.14% to 0.04%) and protocol deviations (from 0.4% to 0.08%). In the longitudinal data set, which contained more than 39 million data values collected within AWARD, 96.6% of data values were entered within specified query range or found to be accurate upon querying. The remaining data were missing (3.4%). Participant non-attendance at scheduled study activity was the most common cause of missing data. Costs associated with cleaning data in ASPREE were lower than expected compared with reports from other trials. Conclusions Clinical trials undertake complex operational activity in order to collect data, but technology rarely provides sufficient support. We find the AWARD suite provides proof of principle that designing technology to support data collectors can mitigate known causes of poor data quality and produce higher-quality data. Health information technology (IT) products that support the conduct of scheduled activity in addition to traditional data entry will enhance community-based clinical trials. A standardised framework for reporting data quality would aid comparisons across clinical trials. Trial registration International Standard Randomized Controlled Trial Number Register, ISRCTN83772183. Registered on 3 March 2005.

Data entry design and data quality

1985 ◽  
Vol 6 (3) ◽  
pp. 229 ◽  
Author(s):  
M. Marvin Newhouse for the MPS Coor
Keyword(s):  
Data Quality ◽  
Data Entry

scholarly journals Healthcare-Associated Infection Decisions of Antibiotic-Resistant Organisms: A Data Quality Review

2020 ◽  
Vol 41 (S1) ◽  
pp. s246-s246
Author(s):  
Jennifer Ellison ◽  
Kathryn Bush ◽  
Blanda Chow ◽  
Kaitlin Hearn ◽  
Andrea Howatt ◽  
...  
Keyword(s):  
Data Quality ◽  
Tertiary Care ◽  
Data Entry ◽  
Infection Prevention And Control ◽  
Healthcare Associated Infection ◽  
Antibiotic Resistant ◽  
Predictive Values ◽  
Rehabilitation Care ◽  
Program Staff ◽  
Quality Review

Background: Infection Prevention and Control (IPC) for Alberta Health Services and Covenant Health in the province of Alberta, Canada conducts surveillance for methicillin-resistant Staphylococcus aureus (MRSA) and vancomycin-resistant enterococcus (VRE) on all individuals admitted to acute-care and acute tertiary-care rehabilitation care facilities. Objective: The objective of this study was to determine the consistency and accuracy of infection decisions for MRSA and VRE. Methods: Surveillance cases of antibiotic-resistant organisms (AROs) collected using the provincial data entry surveillance platform between April 1, 2015, and March 31, 2017, across the province were reabstracted by infection control professionals and physicians using the NHSN infection definitions and compared to the original case severity decisions. Interrater agreement (Cohen’s ) and validity (sensitivity, specificity and predictive values) were calculated to compare the original and reabstracted infection decisions. Results: Collectively, 97% (87 of 90) of the IPC program staff and physicians who were initially invited re-abstracted 264 MRSA cases and 103 VRE cases within the review period. Provincially, 20% of the ARO cases reviewed (74 of 367) differed from the original infection decision. Among these 74 cases, 46 cases (34 MRSA and 12 VRE cases) changed from infection (original decision) to colonization (reabstracted decision) and 28 cases (21 MRSA and 7 VRE cases) changed from colonization to infection. The Cohen values for MRSA and VRE were 0.55 and 0.56, respectively, suggesting a moderate level of agreement for decisions made among IPC program staff. The sensitivity of the infection decision was higher with MRSA (86.5%) than for VRE (74.1%), meaning that there were more MRSA cases than VRE cases classified as infection in the original decision that remained infection following the review. Conclusions: Observed discordances on infection decisions were identified and may be attributed (1) to variations in the interpretation of the NHSN definitions, (2) to additional information that may have been available in the re-abstracted review compared to the original review, or (3) a difference in the information that was accessed to perform the original review compared to the reabstraction. This data-quality review provided an opportunity for IPC staff and physicians to become more familiar with infection definitions and such reviews will continue to be a regular process used to assess data quality within the IPC department.Funding: NoneDisclosures: None

scholarly journals REPLICCAR II Study: Data Quality Audit in the Paulista Cardiovascular Surgery Registry

2019 ◽  
Author(s):  
Bianca Maria Maglia Orlandi ◽  
Omar Asdrubal VilcaMejia ◽  
Maxim Goncharov ◽  
Kenji Nakahara Rocha ◽  
Lucas Bassolli ◽  
...  
Keyword(s):  
Data Quality ◽  
Categorical Data ◽  
Cardiovascular Surgery ◽  
Data Entry ◽  
Sao Paulo ◽  
Study Data ◽  
São Paulo ◽  
Continuous Variables ◽  
Health Records

AbstractBackgroundElectronic health records databases are important sources of data for research and health practice. The aim of this study was to assess the quality of the data in REPLICCAR II, the Brazilian cardiovascular surgery database based in São Paulo State.Study DesignThe REPLICCAR II database contains data from 9 institutions in São Paulo, with more than 700 variables. We audited data entry at 6 months (n=107 records) and 1 year (n=2229 records) after the start of data collection. We present a modified Aggregate Data Quality Score (ADQ) for 30 variables in this analysis.ResultsThe agreement between the data independently entered by a database operator and a researcher was good for categorical data (Cohen κ = 0.70, 95%CI 059, 0.83). For continuous data, the intraclass coefficient was high for all variables, with only 2 of 15 continuous variables having an ICC of less than 0.90. In an indirect audit, 74% of the selected variables (n = 23) showed a good ADQ score, regarding completeness and reliability.ConclusionsData entry in the REPLICCAR II database is satisfactory and can provide accurate and reliable data for research in cardiovascular surgery in Brazil.

scholarly journals Design, Implementation and Management of an International Medical Device Registry

2021 ◽  
Author(s):  
Herbert Mauch ◽  
Jasmin Kaur ◽  
Colin Irwin ◽  
Josie Wyss
Keyword(s):  
Data Quality ◽  
Medical Device ◽  
Data Entry ◽  
Easy Access ◽  
Clinical Routine ◽  
International Registry ◽  
Site Monitoring ◽  
Patient Reported ◽  
Measurement Tools ◽  
The Cost

Abstract Background Registries are powerful clinical investigational tools. More challenging, however, is an international registry conducted by industry. That requires considerable planning, clear objectives and endpoints, resources and appropriate measurement tools. Methods This paper aims to summarize our learning from ten years of running a medical device registry monitoring patient-reported benefits from hearing implants. Results We enlisted 113 participating clinics globally, resulting in a total enrolment of more than 1500 hearing-implant users. We identify the stages in developing a registry specific to a sensory handicap such as hearing loss, its challenges and successes in design and implementation, and recommendations for future registries. Conclusions Data collection infrastructure needs to be maintained up to date throughout the defined registry lifetime and provide adequate oversight of data quality and completeness. Compliance at registry sites is important for data quality and needs to be weighed against the cost of site monitoring. To motivate sites to provide accurate and timely data entry we facilitated easy access to their own data which helped to support their clinical routine. Trial registration: ClinicalTrials.gov NCT02004353

scholarly journals CALIDAD DE DATOS Y SU EVALUACIÓN: UN CASO DE ESTUDIO. DATA QUALITY AND ITS EVALUATION: A STUDY CASE

2012 ◽  
Vol 3 (2) ◽  
pp. 33-49
Author(s):  
Lorena Zúñiga-Segura ◽  
Elisa Sánchez-Godínez
Keyword(s):  
Data Quality ◽  
Quality Assessment ◽  
Data Entry ◽  
Assessment Methodology ◽  
Data Quality Assessment ◽  
Palabras Clave ◽  
Organizational Information ◽  
Toma De Decisiones ◽  
Study Case

En los diferentes procesos que se llevan a cabo en una institución o empresa se utiliza información, es por ello que desde la recolección o captura de los datos debe contemplarse lacalidad de los mismos. El presente artículo describe una metodología para la evaluación de la calidad de los datospropuesta por el autor Arkady Maydanchik y su aplicación a una base de datos determinada.  Los resultados generales que se obtuvieron permiten señalar oportunidades de mejora, que contribuirán con la calidad de los datos, y por ende, en todos los procesos que hacen uso de ellos para la toma de decisiones. El análisis fue realizado en el año 2011, se evaluó información que pertenece a la Universidad Estatal a Distancia (UNED) de Costa Rica, la cual fue registrada entre los años 1980 al 2011.Palabras clave: evaluación de la calidad de datos, información, bases de datos.AbstractOrganizations perform different kinds of processes that use information. For this reason, the data quality must be taken into account from the data entry activities through organizational information systems. This article describes the data quality assessment methodology proposed by Arkady Maydanchick, which was applied in order to assess the data quality of an organizational database.  The findings show that there are opportunities for improvements, which will contribute to data quality and therefore all processes that use these data for decision making support. The analysis was conducted in 2011; information from the Universidad Estatal a Distancia (UNED) of CostaRica was evaluated, the database assessed contains information between the years 1980 to 2011.Keywords: data quality assessment, information, databases.

scholarly journals Applying Persuasive Design Techniques to Change Data Entry Behaviour in Primary Care (Preprint)

2017 ◽  
Author(s):  
Justin St-Maurice ◽  
Catherine Burns ◽  
Justin Wolting
Keyword(s):  
Primary Care ◽  
Data Quality ◽  
Systems Analysis ◽  
Data Entry ◽  
Systems Design ◽  
Statistical Process ◽  
Registry System ◽  
Viable Approach ◽  
Entry Behavior ◽  
Persuasive Systems

BACKGROUND Persuasive design (PD) is an approach that seeks to change the behaviours of users by using design and social influence. In primary care, clinician behaviours and attitudes are important precursors to structured data entry, and there is an impact on overall data quality. This research hypothesizes that PD could change data entry behaviours in clinicians and improve data quality. OBJECTIVE Our objective was to use PD principles to change clinician data-entry behaviours in a primary care environment and to increase data quality within a registry system. METHODS We performed a detailed systems analysis of the data-entry task by using cognitive work analysis (CWA). We used the results of this analysis with the Persuasive Systems Design (PSD) framework to describe the persuasion context. We identified several PD principles to be introduced in a new summary screen, which became part of the data entry workflow. As part of our experimental design, we defined three data quality measures (same-day entry, record completeness, and data validity) to measure changes in data quality and entry behaviour. We measured the impacts of the new screen with a paired pre/post t-test and generated XmR charts to contextualize the results. RESULTS 53 users were shown the new screen during their data entry over the course of 10 weeks. Based on a pre-post analysis, the new summary screen successfully encouraged users to enter more of their data on the same day as their encounter. The percentage of same-day entries increased by 10.34% (P < 0.001). During the first month of the new screen, users compensated by sacrificing aspects of data completeness, before returning to normal in the second month. Improvements to record validity were marginal over the study period (P = 0.045). Statistical process control techniques allowed us to study the XmR charts to contextualize our results and understand trends throughout the study period. CONCLUSIONS By conducting a detailed systems analysis and introducing new PD elements into a data entry system, we demonstrated it was possible to change data-entry behavior and influence data quality in a reporting system. The results show that using PD concepts may be effective at influencing data entry behaviours in clinicians. There may be opportunities to continue improving this approach, and further work is required to perfect and test additional designs. Persuasive design is a viable approach to encourage clinician user change and could support better data capture in the field of medical informatics.

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