IN THE NAME OF GOD Alireza Azizi Alireza Salehi Mohsen Rahmanian.
CDSS CLINICAL DECISION SUPPORT SYSTEMS By: Dr Alireza Kazemi.
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Transcript of CDSS CLINICAL DECISION SUPPORT SYSTEMS By: Dr Alireza Kazemi.
CDSSCLINICAL DECISION SUPPORT SYSTEMS
By: Dr Alireza Kazemi
2
Abbreviations• ME = Medication Errors
• Any preventable event that may cause or lead to inappropriate medication use or patient harm
• CPOE = Computerized Physician Order Entry• POE: Physician Order Entry • NOE: Nurse Order Entry
• DSS = Decision Support System• CDSS = Clinical Decision Support System
Definition of CDSS• Clinical decision support systems (CDSS) are computer
systems designed to impact clinician decision making about individual patients at the point in time that these decisions are made
Aim• make data about a patient easier to assess• foster optimal problem-solving, decision-making, and
action by the human•
History
Types of decision support systems• Knowledge-based CDSS
• Knowledge base• Clinical inference (inference model) (reasoning engine)• Interface
• non-knowledgebase CDSS1 )Trained
• Artificial neural networks• Neurodes (=neurons in human body)• weighted connections (=nerve synapses in human body)• 3 layers; input output and hidden• input -->receive data• output --> communicate results• hidden --> process incoming data and determine results• ANN process patterns in patient's data to derive associations between patient's signs,
symptom or lab tests and a diagnosis• learn from examples derived from large data• Advantages and disadvantages?
2) untrained • Genetic algorithms
• Recombination• components of random sets of solution are evaluated• best ones are kept (Fitness model)
6
Concept of Knowledge-based Decision Support System
Database Software UI
Knowledgebase
User ClientLisaInference engine
7
Background about medication errors• In USA 7000 deaths / year happen due to medication errors 1
• > 56% of medication errors happen in the prescription phase 2
• In newborns, dosing errors are the most frequent type of medication errors 3
• 10-fold and even greater dosing errors are frequently reported in neonates 4,5,6
• CPOE has been effective in reducing dosing errors in neonates 7,8
• No previous study has investigated the effect of CPOE on reducing dosing errors in middle-income countries
8
Aim• To find an appropriate model for adopting computerized provider order entry with clinical decision support functionalities in Iran, and evaluate the effect of the implemented model on patient safety
9
Project overview(Activities)
• Situational analysis
• Design• Implementation• Test• Adaptation
• Evaluation
POE vs. NOE (Study IV)
POE
Traditional system
Traditional vs. POE (Study II)
POE
NOE
NOE
Quantitative
Qualitative(Study I)
(Study III)
• Needs assessment
Project overview (structure)• Traditional vs. POE
• Qualitative• Study I
• Quantitative • Study II
• POE vs. NOE• Qualitative
• Study III• Quantitative
• Study IV
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No DSS
POE DSS1
DSS2
Traditional
Study II
Ext. Study II
Traditional
POE
NOE
POE
POE & NOE
DSS2
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Hamadan, North West Iran, 1,700,000 inhabitants.
General setting
300 Km
12
Study I•Aim
•To analyze the traditional prescription system•To assess prescribers’ needs prior to implementation of CPOE
and DSS
•Method (qualitative)•Setting: Ekbatan Hospital
•FGD, 8 experts Interview guideline•Semi-structured interviews ,
19 prescribers (interns, residents and attending) •On-looker observations 40 h
•Analysis method•Inductive thematic analysis
13
Study 1 – Results•Traditional prescription system
•Physician-centered, top-bottom hierarchy•No pharmacist is involved
•Reduction of dosing errors have priority
•CPOE and DSS?•Physicians are positive towards CPOE
•Feedback to physicians, not nurses (they preferred POE)•System should improve patient safety and prescription accuracy to
encourage physicians to continue performing order entry•Prescribers should not become DSS dependent for appropriate
calculation of dosages (not affordable everywhere in Iran)•Pilot in one of the most relevant wards for dosing errors
14
Studies II, III, IV - Setting•Besat, a 400-bed tertiary-care referral teaching hospital
•Besat's neonatal ward is a 17-bed clinical ward
15
Dosing DSS architecture
16
Wt= 3.25 Kg
3rd day of Life
35 q12h Amikacin
30 q12h
10 * 3.25 = 32.5 q12h
17
AsdhföashjAsdfla’sdflöaskAs’dlöfkAs’dlfka’slöA’sdölfk’asdölfk’aghjfghjfghjf
AsdhföashjAsdfla’sdflöaskAs’dlöfkAs’dlfka’slöA’sdölfk’asdölfk’aghjfghjfghjf
18
Study II• Aim
• To evaluate the effect of two interventions on reducing non-intercepted dosing errors:
I) Physician order entryII) Dose decision support system
19
Traditional(Period 1)
POE w/o DSS(Period 2)
POE+DSS1(Period 3)
No intervention
POE DSS1
Days
2007 (May - July) 2007 (July - Oct) 2007 (Oct - Dec)Time
Inter-vention
Order entry
DSS
Func.N/A N/A
E
vent
Study II (design)
Results – Study II(non-intercepted dosing errors)
20
0,0
10,0
20,0
30,0
40,0
50,0
60,0
Traditional(Period 1)
POE w/o DSS(Period 2)
POE+DSS1(Period 3)
POE+DSS2(Period 4)
NOE+DSS2(Period 5)
Erro
rs p
er 100
ord
ered
-med
icat
ions
Transcription Prescription
P<.001
95% CI
Extension of Study II• Aim
• To evaluate the effect of the DSS design on reducing non-intercepted dosing errors
21
22
POE+DSS1 (Period 3) POE + DSS2 (Period 4)
DSS1
2007 (Oct – Dec) Dec 2007 – Feb 2008Time
Inter-vention
Order entry
DSS
Func.
E
vent
Ext. Study II (design)
DSS2
Freq. First-time order + change in dosing criteria
All erroneous orders
Explanations
23
Results – Ext. Study II (non-intercepted dosing errors)
• Conclusion of Study II POE with dosing decision support functionalities is effective in reducing non-intercepted dosing errors, especially when explanations are available in the warning and alerts appear in every erroneous order.
0,0
10,0
20,0
30,0
40,0
50,0
60,0
Traditional(Period 1)
POE w/o DSS(Period 2)
POE+DSS1(Period 3)
POE+DSS2(Period 4)
NOE+DSS2(Period 5)
Erro
rs p
er 1
00 o
rder
ed-m
edic
atio
ns
Transcription Prescription
0,0
10,0
20,0
30,0
40,0
50,0
60,0
Traditional(Period 1)
POE w/o DSS(Period 2)
POE+DSS1(Period 3)
POE+DSS2(Period 4)
NOE+DSS2(Period 5)
Erro
rs p
er 100
ord
ered
-med
icat
ions
Transcription Prescription
P<.001P<.001 P<.001
95% CI
24
Duplications/redundancy
Dosing errors
Patient Safety
User Acceptability
AsdhföashjAsdfla’sdflöaskAs’dlöfkAs’dlfka’slöA’sdölfk’asdölfk’aghjfghjfghjf
AsdhföashjAsdfla’sdflöaskAs’dlöfkAs’dlfka’slöA’sdölfk’asdölfk’aghjfghjfghjf
25
Study III• Aim
• To investigate care providers’ perceptions about the advantages and disadvantages of the two implemented models
I) Physician Order Entry (POE)II) Nurse Order Entry (NOE)• Methods
• Semi-structured interviews attendings, residents and nurses • After establishment of the POE method (6 months after start)• After establishment of the NOE method (6 months after start)
• On-looker observations during the two periods• Analysis method
• Inductive thematic analysis
26
Study III - ResultsTheme POE NOE
Patient safety ( dosing errors) GOOD GOOD
Duplication / redundancy Exists (less) Exists
Spent time on order entry High for physicians and nurses
Less for both, especially physicians
Collaboration & communication Less More
Feasibility & continuity Less More
User acceptability Strong resistance Better acceptability
Transferability in Iran Very low High
Overall (Viability in the context) Less viable More viable
27
User acceptability
Continuity
Dosing medication errors
28
Study IV• Aim
• To investigate whether NOE is at least as effective as POE in reducing non-intercepted dosing errors
29
POE+DSS2 (Period 4) NOE + DSS2 (Period 5)
POE+DSS2
Dec 2007 – Feb 2008 2008 (July-Sep)Time
Inter-vention
Order entry
DSS
Func.
E
vent
Study IV (design)
NOE+DSS2
Freq. All erroneous orders All erroneous orders
Explanation
30
Results – Study IV (non-intercepted dosing errors)
0,0
10,0
20,0
30,0
40,0
50,0
60,0
Traditional(Period 1)
POE w/o DSS(Period 2)
POE+DSS1(Period 3)
POE+DSS2(Period 4)
NOE+DSS2(Period 5)
Erro
rs p
er 1
00 o
rder
ed-m
edic
atio
ns
Transcription Prescription
0,0
10,0
20,0
30,0
40,0
50,0
60,0
Traditional(Period 1)
POE w/o DSS(Period 2)
POE+DSS1(Period 3)
POE+DSS2(Period 4)
NOE+DSS2(Period 5)
Erro
rs p
er 1
00 o
rder
ed-m
edic
atio
ns
Transcription Prescription
P<.001 P<.001 P<.001
95% CI
31
Study IV – Results (severity)
0
100
200
300
400
500
600
Traditional (Period1)
POE w/o DSS(Period 2)
POE+DSS1(Period 3)
POE+DSS2(Period 4)
NOE+DSS2(Period 5)
Perc
ent o
verd
ose
Max registered dose
Number of two-fold or greater overdose errors
0
10
20
30
40
50
60
70
80
90
100
Traditional (Period 1)
POE w/o DSS(Period 2)
POE+DSS1(Period 3)
POE+DSS2(Period 4)
NOE+DSS2(Period 5)
Evaluation Period
Abs
olut
e nu
mbe
r of t
wo-
fold
or g
reat
er
over
dose
err
ors
95% CI
32
Conclusion - Study IV• NOE+DSS2 is as effective as or even more effective
than POE+DSS2 in reducing the rate and severity of non-intercepted medication dosing errors among neonates.
33
Thesis conclusion• Dosing decision support systems can improve patient
safety in neonatal wards. However, in order to successfully adopt a CPOE system, selection of order entry method and design of the DSS should be performed in close collaboration with care providers and with consideration for limitations in the local context.