Uploaded byDr Neelesh Bhandari
Introduction To Medical Data
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.
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Introduction to Dr. Neelesh Bhandari and his expertise, highlighting his roles in Digital MedCom Solutions and RAKSHA.
The transformation from data to information to knowledge, emphasizing the hierarchy of medical data.
A brief overview of the healthcare process involving data gathering, interpretation, and decision-making.
Introduction to the process of hypothesis generation and refinement in medical research.
Decision-making strategies using etiology diagrams, decision trees, and the concept of 'Utilities' in evaluating quality versus length of life.
Definitions of medical datum vs. data, underlining the importance of proper data models with an example of blood pressure.
Four key elements of medical datum: patient, parameter, value, and time of observation.
Various types of medical data including narrative, textual, numeric, and visual inputs.
Challenges in interpreting medical data due to context-specific meanings of phrases.
Identifying weaknesses in traditional record-keeping methods, such as lack of linkage and inefficiencies.
Various stakeholders who utilize medical data, including clinical settings, research, and guideline creation.
Important medical terms for understanding data, such as sensitivity, specificity, prevalence, and risk.
Calculation methods for decisions involving likelihood ratios, predictive values, and decision evaluation.
Different sources of medical data, including clinic records, hospital records, and survey reports.
Importance of real-time collaboration in managing patient data among healthcare professionals.
Identifying the roles of various personnel like physicians, nurses, and administrative staff in data collection.
Comprehensive list of uses of medical data, from creating historical records to informing future health trends.
An overview of data agencies in India involved in health statistics and programs supporting medical data collection.
Contact information for Dr. Neelesh Bhandari and an emphasis on digital medicine.
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Introduction To Medical Data
- 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 hypothesisgeneration and refinement
- 5. Decision Taking • Decisiontaken 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 anddata • 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 ofmedical datum 1) Patient in Question 2) Parameter to be observed 3) Value 4) Time of observation
- 8. Various Types ofData • Narrative • Textual • Numeric • Device inputs • Drawings • Photographs
- 9. Peculiarities of Medicaldata • 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 TraditionalRecord Keeping •No Linkage •Difficult Chronology •Redundant •Inefficient
- 11. Medical Data usedby • 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 andreal time collaboration
- 16. Who are TheData Sharers/ Data Collectors • Physicians • Nurses • Lab personnel • Therapists • Pharmacy • Administrative staff
- 17. Uses Of Medicaldata • 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 inIndia • 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