Sign up to save your podcasts
Or
Share EP45 - AMDIS Roundtable - Data Governance at the Point of Care
Share to email
Share to Facebook
Share to X
Share to email
Share to Facebook
Share to X
Or
EP45 - AMDIS Roundtable - Data Governance at the Point of Care
In this AMDIS collaboration, Dr. Mark Pierce (former Parkview Health), Dr. Howard Landa (Adventist Health), and Dr. John Lee (HIT Peak Advisors) examine why data governance is ultimately a patient-care issue, not just an IT function. Drawing on real bedside decisions, EHR transitions, and conflicting metrics, they show how unclear definitions and hidden data create hesitation, workarounds, and loss of clinician trust. Together, they discuss the leadership commitment and investment required to improve data quality, and why clean data is the prerequisite for safe and meaningful AI in healthcare.
Key Takeaways- Unclear data definitions slow care — clinicians pause, double-check, or guess at the bedside.
- Data governance is a patient-safety function, not an IT committee exercise.
- Most data problems are silent — staff create workarounds instead of reporting issues.
- Different departments define the same metric differently, eroding organizational trust.
- Leadership wants fast ROI, but governance requires long-term investment and persistence.
- AI magnifies bad data — clean inputs matter more than advanced algorithms.
- Use AI first to clean and structure data before deploying clinical AI tools.
- Start governance with visible problems (e.g., length-of-stay definitions, data sharing).
- Tie governance efforts to active initiatives to gain momentum and participation.
- Organizations rarely advertise good governance — you see it in outcomes, not org charts.
- Clinician trust is fragile; one bad data-driven decision can last for years.
- Accessible, synthesized data enables faster decisions and real improvement cycles.
00:00 | Why Data Governance Gets Ignored 02:01 | Data Governance as a Patient-Safety Issue 04:25 | When Data Helps — and When It Slows Care 06:29 | Too Much Information, Not Enough Clarity 09:14 | The "Raiders of the Lost Ark" Data Warehouse Problem 11:04 | Why Leaders Delay Governance Work 13:06 | The Real Investment Required 14:28 | The PD-Not-PDSA Cycle in Healthcare 15:16 | AI Fails Without Clean Data 16:55 | What Breaks When Definitions Differ 18:05 | Bad Data at the Bedside: A Stroke Decision 20:19 | How Trust in Data Is Lost 23:13 | Silent Workarounds Across Hospitals 25:18 | Where Organizations Should Start 27:15 | Making Data Actionable for Clinicians 29:26 | Governance as Organizational DNA 31:24 | Aligning AI Governance With Data Governance 32:13 | Use AI to Clean Data First 34:15 | Bias, Training Data, and Clinical Risk 36:29 | Final Message: When Rules Are Unclear, Care Suffers
Guests: Dr. Mark Pierce, Dr. Howard Landa, Dr. John Lee Host: Gregg Malkary - Lighthouse Healthtech Cohost: Keith Washington - Companions in Courage Foundation Sponsored by: Simplifi Medical & Storage Systems Unlimited Audio/Video: Tim Jones - Health Nuts Media Marketing: Josh Troop - Troop-Creative Learn More at: www.beyond-blueprint.com
View all episodes
By Beyond the Blueprint - Health SeriesIn this AMDIS collaboration, Dr. Mark Pierce (former Parkview Health), Dr. Howard Landa (Adventist Health), and Dr. John Lee (HIT Peak Advisors) examine why data governance is ultimately a patient-care issue, not just an IT function. Drawing on real bedside decisions, EHR transitions, and conflicting metrics, they show how unclear definitions and hidden data create hesitation, workarounds, and loss of clinician trust. Together, they discuss the leadership commitment and investment required to improve data quality, and why clean data is the prerequisite for safe and meaningful AI in healthcare.
Key Takeaways- Unclear data definitions slow care — clinicians pause, double-check, or guess at the bedside.
- Data governance is a patient-safety function, not an IT committee exercise.
- Most data problems are silent — staff create workarounds instead of reporting issues.
- Different departments define the same metric differently, eroding organizational trust.
- Leadership wants fast ROI, but governance requires long-term investment and persistence.
- AI magnifies bad data — clean inputs matter more than advanced algorithms.
- Use AI first to clean and structure data before deploying clinical AI tools.
- Start governance with visible problems (e.g., length-of-stay definitions, data sharing).
- Tie governance efforts to active initiatives to gain momentum and participation.
- Organizations rarely advertise good governance — you see it in outcomes, not org charts.
- Clinician trust is fragile; one bad data-driven decision can last for years.
- Accessible, synthesized data enables faster decisions and real improvement cycles.
00:00 | Why Data Governance Gets Ignored 02:01 | Data Governance as a Patient-Safety Issue 04:25 | When Data Helps — and When It Slows Care 06:29 | Too Much Information, Not Enough Clarity 09:14 | The "Raiders of the Lost Ark" Data Warehouse Problem 11:04 | Why Leaders Delay Governance Work 13:06 | The Real Investment Required 14:28 | The PD-Not-PDSA Cycle in Healthcare 15:16 | AI Fails Without Clean Data 16:55 | What Breaks When Definitions Differ 18:05 | Bad Data at the Bedside: A Stroke Decision 20:19 | How Trust in Data Is Lost 23:13 | Silent Workarounds Across Hospitals 25:18 | Where Organizations Should Start 27:15 | Making Data Actionable for Clinicians 29:26 | Governance as Organizational DNA 31:24 | Aligning AI Governance With Data Governance 32:13 | Use AI to Clean Data First 34:15 | Bias, Training Data, and Clinical Risk 36:29 | Final Message: When Rules Are Unclear, Care Suffers
Guests: Dr. Mark Pierce, Dr. Howard Landa, Dr. John Lee Host: Gregg Malkary - Lighthouse Healthtech Cohost: Keith Washington - Companions in Courage Foundation Sponsored by: Simplifi Medical & Storage Systems Unlimited Audio/Video: Tim Jones - Health Nuts Media Marketing: Josh Troop - Troop-Creative Learn More at: www.beyond-blueprint.com