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Quality Check Essentials - Non-CE
Lesson 1
Lesson 1
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Video Transcription
Welcome to this learning activity titled Quality Check Essentials. Upon completion of this learning activity, the learner should be able to discuss the goal of the data quality program, identify and use available resources including the CDQR companion guide, and distinguish, differentiate, and interpret quality check messages. The data quality program's goal is to ensure the completeness, consistency, and accuracy of data submitted. The NCDR values quality and endeavors to ensure that the data used provides an accurate representation to allow for appropriate conclusions to be drawn. Data quality is important to the ACC and NCDR because the analyses and results from NCDR registry data are used for research and influence decision making, and for public reporting, risk models, and appropriate use criteria. The three key components of the data quality program includes completeness. All required elements are reported to the registry. This means if it appears on the data collection form, and if the information was available, it should be submitted to the registry. Consistency. Everyone who abstracts or codes shares a common understanding of the data and their definitions. The data dictionary guides data collection, and only data meeting the criteria specified in the data dictionary should be entered. The data entered is logical and consistent. As an example, the procedure date must be after the patient's date of birth. Accuracy. The data represents what is occurring at the facility. NCDR expects that the data submitted to the registry accurately reflects what occurred during the patient's episode of care and documented in the medical record. NCDR data quality activities vary by the data collection phase. We view this as three phases. Pre-data collection, data submission, post-data submission. Pre-data collection is the development and preparatory work to guide data collection. The data submission phase is when participating facilities actively submit their data to the registry. All data submissions are evaluated for errors, data assessment, and completeness, data completeness assessment. An automated summary report is sent to the participants after each data submission and participants may correct and resubmit their data as needed. The post-data submission phase is where evaluation of submitted data is done. Quality check occurs during the data submission phase. The data quality check allows for real-time assessment of the data submission and focus primarily on completion by setting thresholds for data entry and consistency by providing an evaluation of logic and internal consistency. What is a quality check? The quality check is a functionality within the ACC data collection tool or DCT. The quality check functionality provides the initial assessment of logic and accuracy of data entry. The quality check process identifies errors and outliers in data before it is sent to the data quality review process. An outlier is a warning generated by the quality check process and is designed to inform the abstractor of a value which has fallen outside of the usual range. Outlier warnings are helpful in assisting the abstractor in identifying keystroke errors and decimal misplacements. Outlier warnings will not prevent submitting to the DQR. Error messages must be reviewed. The data entered is not logical. Data must be corrected and passed the quality check. A quality check must be performed each time a patient record has been modified. Quality check must be performed on every patient data collection form. Every patient data collection form must pass through the data quality check before the DQR process will allow for data submission. The system alert informs the user of patient's data collection records that did not pass the quality check. All system alerts must be resolved in order to submit to the DQR. Every patient must pass the quality check before the DQR process will allow for data submission. All patient records included in the Porter must pass the quality check without receiving an error message to be accepted by the DQR. Locate the data elements involved in the error. Read the error message description and recode or correct the data to resolve the error message. Once the error message has been corrected, save the changes and perform the quality check. Once the quality check is completed and no outstanding error messages are received, the patient record is ready for submission to the DQR. This completes the learning activity titled Quality Check Essentials. Now that the learner has completed this lesson, they should be able to discuss the goal of the data quality program, identify and use available resources including the DQR Companion Guide, and distinguish, differentiate, and interpret quality check messages. Thank you for your participation.
Video Summary
The video titled "Quality Check Essentials" is a learning activity that aims to help learners understand the goal and importance of the data quality program. The video focuses on the three key components of the program: completeness, consistency, and accuracy. It explains that all required elements should be reported to the registry, and data entry should follow consistent definitions and logic. The video also introduces the concept of quality check, which is a functionality in the ACC data collection tool. Quality checks help identify errors, outliers, and logic inconsistencies in the data before it is submitted to the data quality review process. Learners are encouraged to resolve any error messages and perform quality checks to ensure data accuracy and completeness before submission to the DQR. The video concludes by reinforcing the objectives of the learning activity and thanking participants for their participation. No credits are mentioned in the transcript.
Keywords
Quality Check Essentials
data quality program
completeness
consistency
accuracy
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