cdss clinical decision support systems by: dr alireza kazemi

CDSSCLINICAL DECISION SUPPORT SYSTEMS

By: Dr Alireza Kazemi

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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)

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Concept of Knowledge-based Decision Support System

Database Software UI

Knowledgebase

User ClientLisaInference engine

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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

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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

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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

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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

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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

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Studies II, III, IV - Setting•Besat, a 400-bed tertiary-care referral teaching hospital

•Besat's neonatal ward is a 17-bed clinical ward

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Dosing DSS architecture

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Wt= 3.25 Kg

3rd day of Life

35 q12h Amikacin

30 q12h

10 * 3.25 = 32.5 q12h

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AsdhföashjAsdfla’sdflöaskAs’dlöfkAs’dlfka’slöA’sdölfk’asdölfk’aghjfghjfghjf

AsdhföashjAsdfla’sdflöaskAs’dlöfkAs’dlfka’slöA’sdölfk’asdölfk’aghjfghjfghjf

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Study II• Aim

• To evaluate the effect of two interventions on reducing non-intercepted dosing errors:

I) Physician order entryII) Dose decision support system

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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)

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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

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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

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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

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Duplications/redundancy

Dosing errors

Patient Safety

User Acceptability

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AsdhföashjAsdfla’sdflöaskAs’dlöfkAs’dlfka’slöA’sdölfk’asdölfk’aghjfghjfghjf

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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

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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

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User acceptability

Continuity

Dosing medication errors

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Study IV• Aim

• To investigate whether NOE is at least as effective as POE in reducing non-intercepted dosing errors

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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

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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

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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

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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.

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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.