This document discusses medical data and its importance. It defines key terms like data, information and knowledge. It explains how medical data is collected and used by various stakeholders in healthcare. It also outlines the peculiarities of medical data and challenges with traditional record keeping. Finally, it discusses important data sources, users, and agencies involved in medical data in India.

1. Introduction To Medical
Data
Dr. Neelesh Bhandari
MBBS (AFMC), MD (Pathology),
PGP Human Rights
• CEO, Digital MedCom Solutions
• Director, RAKSHA

2. Data  Knowledge
• Data
• Information
• Knowledge

3. The Healthcare Process:
• Gather Data
• Interpret Meaning
• Make decision

4. Process of hypothesis generation and refinement

5. Decision Taking
• Decision taken via etiology
diagrams, Decision trees or
expert computer systems.
• Use of the quantifiable notion of
‘Utilities’.
• Quality v/s Length of Life

6. Medical datum and data
• Medical datum is any single
observation of a patient, data is plural
of datum.
• A number of datum make up data.
BP:120/80 mm of Hg (data or datum?)
• Importance of having a sound data
model.

7. 4 Elements of medical datum
1) Patient in Question
2) Parameter to be observed
3) Value
4) Time of observation

8. Various Types of Data
• Narrative
• Textual
• Numeric
• Device inputs
• Drawings
• Photographs

9. Peculiarities of Medical data
• Typical phrases like RRR / TWNL /
NAD
• Different meanings in different
contexts
eg: M.I may mean different things
in different cases/ contexts

10. Weakness of Traditional Record Keeping
•No Linkage
•Difficult Chronology
•Redundant
•Inefficient

11. Medical Data used by
• All Stakeholders in the healthcare
delivery in clinical settings (admin/
physicians/ finance, etc)
• Research and analysis/ New eHealth
Products
• helps create Guidelines for EBM
• Governments, NGOs
• Clinical research

12. Important Terms
• Sensitivity
• Specificity
• Incidence
• Prevalence
• Odds, Risk
• Likelihood ratios

13. Calculating decisions
LR= Likelihood Ratio
• LR+ = TPR/FPR
• LR- = FNR/TNR
• Predictive value of tests
• Calculating value of decision at each
fork

14. Data Sources
• Clinic records
• Hospital records
• Disease registers
• Medical literature
• Web based databases
• Survey reports
• …..

15. Patient data and real time
collaboration

16. Who are The Data Sharers/
Data Collectors
• Physicians
• Nurses
• Lab personnel
• Therapists
• Pharmacy
• Administrative staff

17. Uses Of Medical data
• Create historical record, compliance
• Communication between stakeholders
• Anticipate future health problems/ trends
• Support basic research
• Create guidelines for good clinical
practice
• Quality studies
• Fuel eHealth startups

18. Data Agencies in India
• National sample surveys
• NRHM units
• CGHS
• National and state programs
• Teaching Hospitals
• Private sector
• NGOs

19. Dr. Neelesh Bhandari
http://about.me/edrneelesh
http://linkedin.com/in/neeleshbhandari
Digital Medicine