Nic k Baker

1

A Clinical and a Pharmaceutical
Events Query Dashboard
Nelson Marlborough District Health Board
Nick Baker...
Information Needed for
Intelligent Behaviour
• Learning from experience
– modify services to meet needs
– improve effectiv...
What is Clinically Useful?
• Personal health objectives
• right care, right place, right time,
• shared information, teams...
First Attempt 1996
• data from each admission stored in Orocare
• 95 fields of data for every admission

• data extracted ...
Data Selection

Nick Baker

5
Leading Causes of Hospitalisation
Nelson Marlborough March 94 - March 99 < 18 yrs
ICD9 Title
Tally
Days
1 DENTAL CARIES
11...
Blenheim Asthma

Nick Baker

7
Asthma Annual Trends

8

Nick Baker
2013
•
•
•
•
•

proliferating information systems – collaborative?
a large amount of data is collected
the data used for f...
2013 Tableau Reader Based System
From Data to Information

Multiple, Fragmented
Data Sources

Actionable
Information
Has New Clinical
Pathway Changed
Prescribing?
• Select Data
• Age group
• Medication
• Very complex queries possible
• Cli...
Pathway + Education Sessions!
Where Might Further Targeted
Interventions Occur?
Costs of Oxycodone

• Includes direct medicine cost
• Numbers of patients treated
• Cost and claims per patient
Graphical Trends - Oxycodone
All Pharmaceuticals for < 5yrs

Five Slides for Graham
Disease Example
Admissions Over 75yrs
Admissions Over 75yrs
Clinical Uses So Far
• Reality check data
– look at coding, does result make clinical sense

• Answer Quick Queries
• Hosp...
Problems
• rubbish in rubbish out
– constantly refined
– test validity

• need knowledge of limitations
“out of sight out ...
Conclusions
• The system can
– allow rapid analysis of trends
– answer quick queries
– evaluate interventions
– be used fo...
Conclusion
• Information alone

“blind idiocy”

• Clinical judgement alone

anecdote

• Information + clinical judgement

...
Acknowledgements
• Donald Hudson – Clinical Intelligence
• Graham Parton – Chief Pharmacist
• Chip Felton - Principal Cons...
28

Nick Baker
A Clinical and a Pharmaceutical Events Query Dashboard
A Clinical and a Pharmaceutical Events Query Dashboard
A Clinical and a Pharmaceutical Events Query Dashboard
A Clinical and a Pharmaceutical Events Query Dashboard
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A Clinical and a Pharmaceutical Events Query Dashboard

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Presented by Nick Baker
General and Community Paediatrician
Executive Clinical Director for Community Based Services, Nelson Marlborough District Health Board.

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Transcript of "A Clinical and a Pharmaceutical Events Query Dashboard"

  1. 1. Nic k Baker 1 A Clinical and a Pharmaceutical Events Query Dashboard Nelson Marlborough District Health Board Nick Baker, Community Paediatrician Donald Hudson, Business and Clinical Intelligence Graham Parton, Chief Pharmacist Montage Ltd. Chip Felton, Principal Consultant, Visualisations
  2. 2. Information Needed for Intelligent Behaviour • Learning from experience – modify services to meet needs – improve effectiveness and outcomes – enhancing quality and consistency • Data is stored in many places – is often inadequate – collected in incongruent ways – difficult to link to individual programmes of care
  3. 3. What is Clinically Useful? • Personal health objectives • right care, right place, right time, • shared information, teams thrive • Service level objectives • audit, trends, effectiveness, planning, staffing • Population health objectives – target prevention • age group, season, practitioners, regions – evaluate interventions – surveillance of trends 3 Nick Baker
  4. 4. First Attempt 1996 • data from each admission stored in Orocare • 95 fields of data for every admission • data extracted from oracle based system as a spreadsheet • imported directly into Access • daily downloads possible • database used to analyse data • dataset filtered to extract a subset of admissions • any fields can be used to control to data selected – standard formats to view data graphs, tables. 4 Nick Baker
  5. 5. Data Selection Nick Baker 5
  6. 6. Leading Causes of Hospitalisation Nelson Marlborough March 94 - March 99 < 18 yrs ICD9 Title Tally Days 1 DENTAL CARIES 1185 21 2 OTITIS MEDIA 1064 358 3 ASTHMA 635 1811 4 GASTRO-ENTERITIS 347 937 5 PREMATURITY 280 4334 6 HEAD INJURY 216 586 7 CHRONIC TONSILLITIS 178 224 8 ACUTE BRONCHIOLITIS 169 562 9 CONVULSIONS 153 347 10 URINARY TRACT INF. 138 315 11 ACUTE APPENDICITIS 129 652 12 VIRAL INFECT 122 177 13 PNEUMONIA 115 409 14 UPPER RESP. INF. 114 184 15 REDUNDANT PREPUCE AND PHIMOSIS 102 12 95 14 Nick 16 PERIAPICAL ABSCESS Baker 6
  7. 7. Blenheim Asthma Nick Baker 7
  8. 8. Asthma Annual Trends 8 Nick Baker
  9. 9. 2013 • • • • • proliferating information systems – collaborative? a large amount of data is collected the data used for funding and reporting purposes rarely converted into clinically useful information lack of checks against clinical reality mean errors can go unchallenged • Information visualisation – “The use of computer-supported, interactive, visual representations of abstract data to amplify cognition.” (Card, Mackinlay, Shneiderman, 1999) 9
  10. 10. 2013 Tableau Reader Based System From Data to Information Multiple, Fragmented Data Sources Actionable Information
  11. 11. Has New Clinical Pathway Changed Prescribing? • Select Data • Age group • Medication • Very complex queries possible • Clinician driven hypothesis testing
  12. 12. Pathway + Education Sessions!
  13. 13. Where Might Further Targeted Interventions Occur?
  14. 14. Costs of Oxycodone • Includes direct medicine cost • Numbers of patients treated • Cost and claims per patient
  15. 15. Graphical Trends - Oxycodone
  16. 16. All Pharmaceuticals for < 5yrs Five Slides for Graham
  17. 17. Disease Example
  18. 18. Admissions Over 75yrs
  19. 19. Admissions Over 75yrs
  20. 20. Clinical Uses So Far • Reality check data – look at coding, does result make clinical sense • Answer Quick Queries • Hospitalisation, pharmaceutical usage – Emerging trends, identify variation, patterns • Identify outliers provide focus for discussion – Hypothesis generation/validation – Identify at risk groups 23 • Target interventions – falls, event management • Prioritise • Seasonal and temporal trends for conditions allow Nick Baker targeting of community interventions
  21. 21. Problems • rubbish in rubbish out – constantly refined – test validity • need knowledge of limitations “out of sight out of mind a blind idiot!” – enormously powerful tool – to jump to wrong conclusions and upset people – best to let clinicians explain information 24 Nick Baker
  22. 22. Conclusions • The system can – allow rapid analysis of trends – answer quick queries – evaluate interventions – be used for service planning – be used to target population health interventions. – useful addition to standard processes of clinical audit • Extreme care is needed in using data collected by non-clinical staff for non-clinical purposes to draw epidemiological conclusions. 25 Nick Baker
  23. 23. Conclusion • Information alone “blind idiocy” • Clinical judgement alone anecdote • Information + clinical judgement clarification • Clinically driven information selection and visualisation enlightenment and wisdom?
  24. 24. Acknowledgements • Donald Hudson – Clinical Intelligence • Graham Parton – Chief Pharmacist • Chip Felton - Principal Consultant, Visualisations, Montage Ltd.
  25. 25. 28 Nick Baker

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