RescueNet® CaseReview - Module 6 How to trend CPR data

zollmedical
29 Jan 202105:17
EducationalLearning
32 Likes 10 Comments

TLDRThe video script discusses the process of tagging case files for efficient analysis and retrieval. It highlights the use of automatic and manual tagging, with examples of specific attributes like hospital departments and clinical details. The script further explains how to access and interpret CPR trend data through a user-friendly interface, allowing users to filter and refine information based on various parameters. The data is presented in both graphical and tabular formats, with options to track metrics over time for performance improvement and educational purposes. Users can also export this data into a comprehensive CSV file for further analysis.

Takeaways
  • 🏥 Tagging system: The script discusses an automatic and manual tagging system for categorizing and finding case files efficiently.
  • 📝 Consistent tagging: It is emphasized on creating a consistent list of tags with particular attributes to be followed over time for better organization.
  • 🏥 Case file example: The script provides an example of tagging a case file related to a hospital (designated as Zol H) and its specific areas like ICU with additional clinical attributes.
  • 📊 CPR trend analysis: The script explains how to access and interpret CPR trend data, which is displayed in both graphical and tabular formats.
  • ⚙️ Customizable filters: Users can refine the CPR trend data by adjusting interval parameters, patient age groups, and reviewing status for a more targeted analysis.
  • 🏷️ Tag-based filtering: The system allows users to filter trend data based on specific tags applied to the cases for a focused review.
  • 📈 Visualization of trends: The CPR trend graph uses colors to represent different metrics (e.g., rest in blue, ROSC in black), with the axes representing the selected interval and the number of arrests/ROSC.
  • 🔍 Interactive data points: Hovering over a point on the graph provides detailed information about that specific data point.
  • 📑 Aggregate data table: Below the graph, a table displays aggregate values for all selected cases, comparing actual metrics against target ranges set by the system administrator.
  • 💹 Performance tracking: Trending helps in tracking metrics over time, identifying areas for performance improvement, and guiding educational initiatives.
  • 📤 Exporting data: Users can generate a .csv file, which includes a zip file containing the trend data, advanced trend export, and filter options for further analysis.
Q & A

  • What is the primary purpose of adding tags to a case?

    -The primary purpose of adding tags to a case is to make them easier to find for further analysis.

  • What are the two types of tagging methods mentioned in the script?

    -The two types of tagging methods mentioned are automatic tagging and manual tagging.

  • How does automatic tagging work?

    -Automatic tagging applies a tag name to a newly uploaded case that matches the predefined search criteria.

  • In which part of the system can manual tags be added?

    -Manual tags can be added in the tag area on the case summary page.

  • What is an example of a tag attribute used in the script?

    -An example of a tag attribute used is designating a specific hospital, such as 'Zole Hospital' or 'Zoll Hospital 1', and a particular area within the hospital, like the ICU.

  • What additional information can be included as tags?

    -Additional information that can be included as tags are specific clinical attributes, rhythms displayed, waveforms, and personnel involved in the event.

  • How can a user access the CPR trend page?

    -The CPR trend page can be accessed by selecting 'CPR Trend' in the top banner of the system.

  • What format does the CPR trend data display?

    -The CPR trend data is displayed in both a graph and a table format.

  • What are some options available on the left side of the CPR trend page for refining the trended information?

    -Options on the left side of the page include interval parameters, patient age groups, and the selection of cases marked as reviewed.

  • What does the CPR trend graph represent?

    -The CPR trend graph represents trends in a resuscitation (CPR) event, with ROSC (Return of Spontaneous Circulation) in black and the number of arrests in blue.

  • How can users track metrics over time?

    -Users can track metrics over time by using the trending feature, which assists in identifying areas for performance improvement and educational initiatives.

  • What type of file can a user generate from the CPR trend page?

    -A user can generate a .csv file by selecting the blue box in the upper right corner of the page, which then generates a zip file containing three separate files: the trend export, the advanced trend export, and the filter options.

Outlines
00:00
🏥 Case Tagging and Analysis

This paragraph discusses the use of automatic and manual tagging in case files for easier analysis and retrieval. It explains the process of applying tags based on search criteria and the importance of maintaining a consistent list of tags over time. The example provided illustrates tagging a hospital case with specific attributes such as hospital name, department, and clinical details. The paragraph also introduces the use of the CPR trend page, which allows users to refine data through various filters and parameters, ultimately displaying trends in resuscitation efforts and spontaneous circulation in both graphical and tabular formats.

Mindmap
Keywords
💡transcript
A transcript is a written version of spoken words, such as in a video or audio recording. In the context of this video script, it serves as the primary source of information for understanding the content and message being conveyed. The transcript is essential for identifying key terms and concepts, as it provides a detailed account of the spoken material.
💡tags
Tags are labels or markers that are assigned to digital files, such as case files, to categorize and organize them efficiently. In the video, tags are used to make case files easier to find for further analysis. They can be applied automatically based on certain criteria or manually added by users to provide specific attributes to the case files.
💡automatic tagging
Automatic tagging is a process where a system automatically assigns tags to files based on predefined search criteria. This feature streamlines the organization and retrieval of information by reducing the need for manual input. In the context of the video, automatic tagging helps to quickly categorize newly uploaded case files that match specific conditions.
💡manual tags
Manual tags are user-defined labels that are added to files to provide additional context or classification. Unlike automatic tagging, manual tags require direct input from the user and can be customized based on individual needs or preferences. In the video, manual tags are added in the tag area on the case summary page, allowing for a more personalized organization of case files.
💡case file
A case file refers to a collection of documents, data, or information related to a specific instance or situation, such as a medical case or legal matter. In the context of the video, case files are the primary objects being managed and analyzed, with tags being used to organize and retrieve them efficiently.
💡clinical attributes
Clinical attributes are characteristics or features related to the medical and healthcare aspects of a case. These attributes provide important information about the patient's condition, treatment, and outcomes. In the video, clinical attributes such as 'rhythms displayed' and 'wave forms' are mentioned as examples of tags that can be added to a case file to capture specific details about the medical event.
💡CPR trend
CPR trend refers to the analysis of data related to cardiopulmonary resuscitation (CPR) over a period of time. This can include metrics such as the number of arrests, the success rate of CPR, and other related statistics. In the video, the CPR trend is accessed and displayed in both graphical and tabular formats to allow users to track and evaluate the effectiveness of CPR efforts.
💡interval parameters
Interval parameters are settings that define the time frame for data analysis or reporting. These parameters help to filter and display data according to specific intervals such as daily, weekly, monthly, quarterly, or yearly. In the context of the video, interval parameters are used to display data according to the selected time frame, allowing users to analyze trends over their desired period.
💡patient age group
Patient age group refers to the categorization of patients based on their age. This can include broad categories such as adult, pediatric, or infant. In the video, the patient age group is used as a filter to select cases that correspond to specific age ranges, which can be important for analyzing trends and outcomes in different patient populations.
💡filtering by tags
Filtering by tags is the process of narrowing down data or case files by applying specific tags as criteria. This feature allows users to view and analyze information that is relevant to their interests or needs. In the video, filtering by tags enables users to show trend data from cases that have specific tags applied, which can be useful for focusing on particular aspects of the data.
💡trending
Trending refers to the analysis and tracking of metrics over time to identify patterns, changes, or improvements. This process is crucial for performance evaluation and for guiding decision-making in various fields, including healthcare. In the video, trending is used to monitor the progress and effectiveness of CPR efforts, helping to identify areas for improvement and educational initiatives.
💡CSV file
A CSV (Comma-Separated Values) file is a type of data file that stores tabular data, where each row represents a record and each column represents a specific attribute or field. This format is widely used for data exchange and analysis because it is simple, straightforward, and compatible with various software applications. In the video, users can generate a CSV file containing the trended data, which can then be further analyzed or shared with others.
Highlights

Automatic tagging simplifies case file organization and retrieval for further analysis.

Manual tags can be added on the case summary page for more personalized categorization.

Creating a consistent list of tags with particular attributes ensures systematic data management.

Case files can be tagged by the enterprise as a whole, such as 'Zole Hospital' for clarity.

Specific hospital areas like 'Zoll Hospital 1 - ICU' can be designated for detailed case categorization.

Clinical attributes, such as rhythms and wave forms, can be used as tags for enhanced data specificity.

Involved personnel can be tagged to track involvement in specific events or cases.

The CPR trend page provides access to critical data through a simple selection process.

CPR trend data is presented in both graphical and tabular formats for comprehensive analysis.

Interval parameters allow users to filter data based on daily, weekly, monthly, quarterly, or yearly trends.

User can select specific patient age groups for a more targeted analysis.

Filtering by tags enables users to focus on trend data from cases with specific attributes.

The CPR trend graph visually represents trends in arrests and ROSC, with colors distinguishing between them.

Hovering over graph points provides detailed value insights for precise data analysis.

The table below the graph offers aggregate values, comparing them to target ranges with color-coding for performance evaluation.

Trending features allow tracking of metrics over time, aiding in performance improvement and educational initiatives.

Users can generate a .csv file for data export, including trend, advanced trend export, and filter options.

Transcripts

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Related Tags
Automated TaggingCase AnalysisData VisualizationPerformance TrendsHealthcare SystemZole HospitalICU MonitoringCPR TrendFilter OptionsEducational Insights