Upload
sitra-hyvinvointi
View
743
Download
1
Tags:
Embed Size (px)
DESCRIPTION
Computers can improve the quality of healthcare, and save healthcare professionals' time for patient care. Ilkka Kunnamo, MD, PhD and Chief Editor at Duodecim, gave a talk at Health Tuesday, 6 May 2014, explaining the benefits and logic of EBmEDS decision support service.
Citation preview
Virtual health check and
computer based decision
support
Ilkka Kunnamo, MD, PhD, Chief Editor
Disclosure: I am a salaried employee of Duodecim Medical
Publications Ltd., the company that develops and and licenses the
EBMeDS decision support service
6.5.2014
How could computers
• Improve the quality of care – make sure
that everyone gets the right care at the
right time
• Prevent medical errors
• Save time of health care professionals
to be used on patient care
Case history
• A 40-year-old man visits the doctor because
of a hernia.
• The decision support system automatically
shows a reminder that the latest data on
blood pressure was from 3 years ago:
185/100.
• The doctor measures the blood pressure,
which is now 220/110.
• Without the reminder the high blood pressure
would have remained undetected, and the
patient would not have received treatment
How many health data items?
Future: millions (billions?) Now: about 100 000
Nigam Shah (Stanford)2013
Drugs Diseases Tests Devides Procedures
Diabetes (E11.9)
Coronary Disease (I20.8)
BP: 145/90 mmHg Potassium: 6.1 mmol/l
EBMeDS
Decision
support
Clinical decision support
Electronic
health
record
Rule
library
Interactive algorithms are automatically populated by patient data
(diagnoses, medications, lab test results) from the EHR
The patient’s path and
the best choice is shown
Patient and System Data
Decision Support
Database
Web Server
• Demographics • Problems and Risks • Measurements • Interventions
Work Station
Data filter
EBMeDS architecture
Electronic Health Record
Trig
ger
Feed
ba
ck
EBMeDS
Client Component
Intra/Internet
Reminders are shown in the user
interface of the electronic health
record
EBMeDS decision support service:
statistics
• Developed by Duodecim (medical society and
publishing company) since 2003
• Multilingual: messages in 11 languages
• 800 rules in a rules library
• Integrated with ~ 20 EHR systems (including
Effica, Pegasos, Mediatri, Uranus, Dynamic
Health in Finland)
• > 40 % of Finnish primary care physicians and
> 50 % of hospital physicians use at least
some component of EBMeDS
EBMeDS messages
General reminders by complex rules 1324
Guideline links 6191
Drug Interactions 12583
Drug and Renal Malfunction 5028
Drug Contraindications 3387
Drug Indications 3124
Total Number of Reminders 31 637
If 200 000 comprehensive medication
reviews were performed in Finland
manually by clinical pharmacists reading
electronic health records and checking all
drug information from databases, the cost
would be 44 million euros at the lowest
market price of 218 €/review
EU-funded study on the effects of reducing
polypharmacy using the EBMeDS tool will
start in 2014
Fundus photography
Using a computer-generated
diagnosis-specific summary
• reduced the time needed to retrieve all
relevant data from the electronic health
record from 5.5 to 1.7 minutes
• saved 57 mouse clicks
Richelle J. Koopman et al. Annals of Family Medicine
2011;9 (no 5)
In a virtual health check all
decision support rules are
executed in a population of
patients, and resulting
reminders are listed.
Implementing evidence-based care on
populations
Examples of reminders triggered in a Virtual
Health Check for a population of 16 000 from a
set of 100 rules
• Blood-pressure lowering drug not used in moderately
high BP and high cardiovascular risk 396
• All beneficial drugs not in use in heart failure 143
• LDL cholesterol > 2.5 mmol/l in type 2 diabetes 69
• Metformin not in use in type 2 diabetes 61
• No visits for a patient with diabetes during last 13 months 58
The comprehensive medication review tool
can be applied to patient populations
Example: drug dosing suggestions based on
kidney function in a population of 16 000
• Check dosing (may be too high) 1164
• Drug not recommended/forbidden 28
Prioritization for health benefit
• The population is listed and sorted by care gap and potential health benefit
• For each patient, the most important interventions are put on top
• A general practitioner who knows the patient is the best coordinator of care
Patients recording their own data
and checking their
• Symptom history and monitoring
• Family history
• Blood pressure, weight, height
• Peak expiratory flow
• Blood glucose
• ECG
• Pain intensity
• Functioning
• current medication list
• diagnosis list
Patients performing their own health checks
… and getting individualized advice
Decision support for patients and
professionals
Data in
professional
health record
Data in
personal health
record
Interactive
care plan
Decision
support
rules
Personalized
advice
Personalized
advice
Data
hub