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Table 2 Quality assessment of the CDSSs

From: Laboratory test ordering in inpatient hospitals: a systematic review on the effects and features of clinical decision support systems

References

CDSS design

Data entry source

Implementation characteristic

Is it integrated with CPOE?

Does it give real time feedback at point of care?

Does the CDS suggest a recommended course of action?

CDSS Classification*

Is it automated through EHR?

Does clinical staff enter data specifically for intervention?

Was it pilot tested or used an iterative process of development/ implementation?

Was there any user training/clinician education?

Are the authors also the developers and part of the user group for the CDS?

Was there use of audit and- feedback (or other internal incentive)?

Are there any other implementation components not already discussed?

Bates et al. [28]

Yes

Yes

No

C

Yes

No

NM**

NM

Yes

No

50% of the tests with a computer order were not screened for redundancy because they were ordered as part of an order set

BoonFalleur et al. [31]

No

No

No

B

No

No

Yes

NM

NM

No

No

Bridges et al. [34]

Yes

Yes

No

B

NM

No

Yes

NM

No

No

Clinicians likely experienced an “adjustment” period once they became familiar with the alert,

Dalal et al. [35]

Yes

Yes

No

D

Yes

No

Yes

Yes

Yes

No

No

Eaton et al. [36]

Yes

Yes

No

B

No

NM

No

NM

NM

No

No

Gottheil et al. [30]

Yes

Yes

No

C

NM

No

Yes

NM

Yes

Yes

The importance of stakeholder engagement prior to the intervention and having decision leaders in each department to champion our cause

Klatte et al. [37]

Yes

Yes

No

D

Yes

Yes

Yes

NM

NM

No

No

Levick et al. [38]

Yes

Yes

No

B

No

No

NM

NM

Yes

No

Use of alerts should be used judiciously and in the appropriate environment

Lippi et al. [32]

Yes

Yes

No

B

NM

No

NM

NM

Yes

Yes

No

Nicholson et al. [39]

Yes

Yes

No

C

NM

Yes

NM

NM

Yes

No

No

Niès et al. [33]

Yes

Yes

No

C

Yes

No

Yes

NM

Yes

No

Testing options were constrained by unbundling serum metabolic panel tests into single components and reducing the ease of repeating targeted tests

Quan et al. [40]

Yes

Yes

No

D

NM

No

NM

NM

NM

Yes

No

Procop et al. [41]

Yes

Yes

No

D

NM

No

Yes

Yes

No

Yes

No

Rosenbloom et al. [42]

Yes

Yes

No

C

NM

Yes

NM

NM

Yes

Yes

Designers of CDS interventions should take into account the paradoxical prompting that such interventions might generate

Rudolf et al. [43]

Yes

Yes

No

C

NM

Yes

NM

NM

NM

Yes

Providers could use workarounds to place daily orders, entering the orders in a manner that would not trigger the audits. For example, placing staggered sets of orders to occur every other day or writing in daily orders on templates could have circumvented our auditing process and accounting of daily testing for this analysis

Samuelson et al. [44]

Yes

Yes

No

C

NM

Yes

NM

NM

NM

NM

No

Sum

           

Yes

No

NM

15

1

0

15

1

0

0

16

0

A: 0

B: 5

C: 7

D: 4

4

3

9

5

10

1

8

1

7

2

0

14

8

2

6

6

9

1

 
  1. *Intervention Classification: “A” interventions provided information only; “B” interventions presented information on appropriateness or guidelines specifically tailored to the individual patient, often as a pop-up or alert. Some of these interventions also recommended alternative interventions, but did not include any barrier for the clinician to order the test; “C” interventions in general were similar to “B” interventions, but required the ordering clinician to justify with free text why they were overriding the decision support recommendation that a study was inappropriate (ie, a “soft stop”). “D” interventions included a “hard stop,” meaning the intervention prevented the clinician from ordering a test contrary to the CDS determination of inappropriateness, until additional discussion with or permission obtained from another clinician or pathologist
  2. **Not Mentioned