Quick Summary

The AFMC, with its strategic role, partnerships, and access to data, is well-positioned to provide valuable insights on the key priorities of its stakeholders, including medical students, physicians, and other healthcare professionals in Canada.

The AFMC engaged Bronson.AI to conduct a Data Maturity Assessment to evaluate its current data capabilities, compare them against industry peers, and provide actionable recommendations for future improvements.

Bronson.AI reviewed existing AFMC data documentation, conducted stakeholder interviews, and performed benchmarking by engaging with similar organizations and analyzing publicly available data-related materials.

Project Overview

The Association of Faculties of Medicine of Canada (AFMC) oversees the national repository of information related to Canada’s medical faculties. Its mission is to “lead and deliver a highly responsive system of medical education and research,” with a focus on quality, excellence, and social accountability to address the healthcare needs of Canadians.

With its influential role, extensive partnerships, and access to critical data, the AFMC is in a unique position to offer strategic insights into the key issues facing its stakeholders, including members, medical students, physicians, and other healthcare professionals. To assess how effectively it can support this role, the AFMC enlisted Bronson.AI to conduct a Data Maturity Assessment as part of the renewal of its Strategic Plan. This assessment is designed to guide the optimization of data management, utilization, and governance within the organization. The primary aim of the assessment was to evaluate the AFMC’s current capacity to leverage its data assets, benchmark its performance against industry peers, and deliver actionable recommendations for future improvement.

The Challenge

Bronson.AI was tasked with conducting a comprehensive, end-to-end Data Maturity Assessment for the AFMC. This included a review of existing AFMC documentation to assess data literacy, interviews with both internal stakeholders and external industry peers, and an evaluation of the AFMC’s data maturity across key areas such as data governance, data quality and integration, and data privacy. The assessment concluded with the proposal of actionable recommendations to advance the AFMC’s data strategy and improve its overall data management capabilities.

Our Solution and Impact

To assess the data maturity of the AFMC, Bronson.AI performed three key tasks: a literacy and document review of the AFMC’s existing data-related documentation, stakeholder interviews with five individuals at the AFMC, and benchmarking against similar organizations through interviews and an analysis of publicly available data-related materials.

Literacy and Document Review
Bronson.AI reviewed AFMC documents that outline the organization’s current data holdings to understand how data is collected, its sources, its usage, and storage methods.

Stakeholder Interviews
Bronson.AI conducted interviews with five key AFMC stakeholders who are responsible for data usage or leadership within the organization. The DAMA-DMM data model, a widely recognized best-practice tool for Data Maturity Assessments, was used as the foundation for these interviews. This model evaluates ten key areas of data maturity:

  1. General Data Environment
  2. Data Governance
  3. Data Quality
  4. Data Architecture
  5. Metadata Management
  6. Data Operations
  7. Data Security
  8. Data Warehousing and Business Intelligence
  9. Document and Content Management
  10. Data Integration and Interoperability

Each area was assessed on a maturity scale from 0 (undefined) to 5 (optimizing), reflecting the organization’s level of maturity and capability. Bronson.AI provided the AFMC with an overall data maturity score based on the findings from the literacy review and stakeholder interviews.

Benchmarking
Bronson.AI also conducted benchmarking interviews with representatives from three organizations with similar data agendas to the AFMC: the Association of American Medical Colleges (AAMC), the Canadian Institute for Health Information (CIHI), and the Canadian Institute of Health Research (CIHR). By reviewing publicly available data-related information and engaging in conversations with these organizations, Bronson.AI gained a comprehensive understanding of their data practices, which were used to benchmark the AFMC’s data maturity.

Bronson.AI compiled the key findings from the assessment and benchmarking into a detailed report, providing actionable insights for the AFMC to advance its data strategy.

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