M MR Software

  • Office 2086 Al Tawar, Al Qusais 2 Dubai, United Arab Emirates
Menu
Visit Us
Menu
Visit Us

Query Management

Track

Track problems and solve root cause

We customize your system to optimize query resolution processes, ensuring swift resolutions. You have the flexibility to adjust most rules, enabling ongoing enhancements in query management.Experience benefits such as:

  1. Unlimited intelligent work-lists
  2. Seamless collaboration for all involved parties
  3. Powerful, customizable work-lists for in-depth analysis
 

Visibility

Visibility Flexible and
powerful

We customize your Credica system to streamline query resolution processes for swift resolutions. Most rules are adaptable by you, fostering continuous improvement in query management.

Enjoy these benefits:

  • Unlimited intelligent work-lists
  • Seamless involvement of all stakeholders in query resolution
  • Powerful, drillable work-lists for comprehensive analysis
  • Automated SLA breach notifications
  • Convenient top 10 reports revealing payment delays and reasons behind them.

Framework of Query and Data Management

Framework of Query and Data Management

 Step-1

Problem identification

Identifying specific problems to address through query management enables organizations to develop targeted solutions that are both cost-effective and time-sensitive.

 Step-2

Creating goals and KPIs

Once problems are identified, companies should define clear goals to address them. Establishing business metrics or Key Performance Indicators (KPIs) allows tracking of goal progress throughout the process.

 Step-3

Defining Strategy

A clear roadmap is essential to guide stakeholders in achieving defined goals. It serves as the strategy that stakeholders will follow to navigate toward successful outcomes.

 Step-4

Target Operating Model

The TOM, or Target Operating Model, outlines how an organization will execute its strategy. It identifies the required processes, technologies, people, culture, and other elements necessary to align with the defined strategy.

 Step-5

Assigning Responsibilities

After determining the Target Operating Model (TOM), organizations should allocate responsibilities to relevant stakeholders who will execute the data management effort. Each stakeholder should have clear roles and accountability throughout the process.

 Step-6

Creating glossaries

Collaboration hinges on mutual understanding among teams. Therefore, a management framework should include a glossary of technical terms accessible to all team members as a reference.

Frequently asked
questions about

Query Management

A query serves as a communication tool within the clinical trial process, aiming to address any discrepancies or inconsistencies detected in the data. Ultimately, the quality of data produced determines the value of clinical trials in advancing scientific discovery.

The primary characteristic of a query is clarity. It should be easily understandable for site staff, outlining the clarification needed and why. An ideal query identifies the type of issue, locates potential data errors, and prompts action with clear instructions.

However, queries should not provide specific answers to resolve discrepancies. For instance, if a blood pressure entry is recorded as 4000/1000, a query should flag the inconsistency and instruct staff to verify the data through manual re-checks and calibration. It should refrain from directing staff to change the measure to a specific value like 120/80.

Key objectives in clinical trial management include:

  1. Ensuring compliance with the protocol: Adhering to the defined procedures and guidelines outlined in the trial protocol.
  2. Completing data collection: Collecting all required data accurately and comprehensively.
  3. Assessing validity and quality of data: Regularly evaluating the accuracy and reliability of collected data at each trial site.
  4. Ensuring patient safety: Prioritizing the safety and well-being of trial participants throughout the study.
  5. Proactively addressing errors: Identifying and addressing any errors or discrepancies promptly to prevent further issues.
  6. Preparing for regulatory audits: Ensuring all data and processes are in compliance with regulatory requirements to facilitate successful audits.
 
 

Queries should request specific information for prompt resolution or response. However, they cannot fully replace site visits and manual checks, especially those generated through auto-checks. Query resolution often relies on site staff, necessitating clear and frequent communication between the data management team and trial sites.

In organizational settings, technologies like data lakes and warehouses leverage data sources such as Enterprise Resource Planning (ERP) systems to provide pertinent information to relevant teams. However, extracting accurate data from these sources can be challenging, often requiring the composition of lengthy queries.

To streamline this process, organizations should establish a centralized repository where developers can securely store and share queries with team members. This practice enhances efficiency, saves time and resources, and promotes data accessibility across different domains.

Similar to managing code, organizations should implement techniques for managing queries as data becomes increasingly crucial in modern enterprises.

Furthermore, complex queries often require updates. However, these queries typically have extensive documentation histories, making it difficult for new developers to locate the source and understand the purpose and significance of updates. Therefore, establishing clear documentation practices is essential for maintaining query integrity and facilitating seamless updates.