How to determine the critical medication prescribing alerts to include in a hospital EMM system Natalie Page

Pharmacist – Clinical Lead (Informatics), Children’s Health QLD

Former Lead Pharmacist, EMM, ACT Health

Master of Philosophy candidate, CHSSR, AIHI, Macquarie University

Supervisors

Professor Johanna Westbrook, Director, CHSSR, AIHI, Macquarie University

Dr Melissa Baysari, Senior Research Fellow, CHSSR, AIHI, Macquarie University

Background

• Interruptive medication prescribing alerts

• Alert categories

• Configuration options

• Safety benefits vs. alert fatigue

Objectives

• Current research gap

• Thesis aim

To identify critical alerts to include in hospital EMM systems based on evidence and the Australian experience and to develop guidance for implementers

Aims:

1. What is the evidence of the effectiveness of

a) an individual EMM interruptive prescribing alert category, or

b) an alert suite

to change prescriber behaviour and/or improve patient outcomes in the acute hospital inpatient setting?

2. Is there evidence to support the inclusion of an individual medication alert category or alert suite over others in hospital EMM systems?

Systematic Review

Methods

• PubMed, Embase, CINAHL and the Cochrane Library were searched for relevant articles published between January 2000 and February 2016

• Studies were included if they compared the outcomes of automatic, interruptive medication prescribing alert to a control/comparison group to determine alert effectiveness

• 23 studies

• 29 alerts categorised into 11 alert categories

• All 23 studies investigated the impact on prescriber behavior

• One study investigated the impact on patient outcomes

Results

Impact of alert categories on prescriber behaviour

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Condition DDI DRC Formulary Allergy Duplicate Corollary Adjustment Lab IV compat

Number of studies investigating the impact of alert category on prescriber behaviour

Number of studies reporting significant beneficial effect from alert

Number of studies reporting no significant change from alert

Number of studies reporting significant detrimental effect from alert

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Corollary DDI Adjustment DRC Allergy Condition Lab Duplicate Formulary IV compat IV/po

Number of studies investigating the impact of alert category on patient outcomes

Number of studies reporting significant beneficial effect from alert

Number of studies reporting no significant change from alert

Number of studies reporting significant detrimental effect from alert

Impact of alert categories on patient outcomes

Outcomes

• No clear association between alert category and a beneficial outcome

• Outcomes specific to the impact of an individual alert category (no alert suites)

• No comparison of the relative effectiveness of different alert categories

Conclusion

Current evidence does not support the inclusion of any individual prescribing alert category (or suite of alerts) over others in hospital EMM systems

Continued research is required in demonstrating the effectiveness of interruptive medication alert categories and alert suites

Aim: To determine what interruptive prescribing alert categories are being used in Australian hospital EMM systems, and to explore the experiences and opinions of implementers and the governance processes in place surrounding alert selection.

• Standardised semi-structured survey administered via telephone

• Participants identified via the investigators’ existing networks

• Consent process

• Ethics approval

Australian EMM Alerts Survey

• 15 responders • 14 Pharmacists; 1 Health Information Manager

• Representing EMM implementations at 26 hospitals

• Varying levels of system maturity

Preliminary Survey Results: Demographics

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7

2004 2005 2007 2009 2010 2011 2012 2013 2014 2015 2016

Year first introduced, including pilots

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State/territory of EMM implementation

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7

8

NSW Vic NT SA ACT Qld

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7

8

Principal referralhospitals

Children'shospitals

Public acute groupA hospitals

Public acute groupB hospitals

Public acute groupC hospitals

Publicrehabilitation

hospitals

Private acutegroup D hospitals

Psychiatrichospitals

Hospital type (AIHW Classification) N

um

ber

of

ho

spit

als

EMM System Implemented

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4

6

8

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12

14

MedChart, CSC Millennium, Cerner Sunrise, Allscripts Trakcare, Intersystems Willow Inpatient, EPICSystems

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Implementation scope • 1 hospital about to go-live

• 25 hospitals implemented at least in one ward • 12 hospitals have completed implemented hospital-wide in all eligible

inpatient areas • 8 have implemented hospital-wide but have hybrid medication management (i.e. paper charts or a specialty

EMM system) in some areas

• 13 hospitals have not yet implemented hospital-wide • 5 have hybrid medication management (i.e. paper charts or a specialty EMM system) in some areas

• Hybrid systems most frequently in

Operating theatres 11

Chemotherapy treatment 5

Haemodialysis 3

Intensive care 3

Hospital in the home 2

Paediatrics 2

Emergency department 1

Community Health 1

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10

15

20

25

Current Locations Fully Electronic

Hybrid

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5

10

15

20

25

Future Locations Fully Electronic

Hybrid

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Governance

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8

EMM Governance Group QUM/DTC Governance Group CDS Governance Group EMR Governance Group

Governance Models

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Alert Feedback

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9

10

Yes No

Solicit Feedback?

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Surveys User Groups During go-liveperiod only

FeedAackprocess via

EMM system

Forums

Feedback process

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Yes No

Alerts Evaluated?

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7

Alert rate Alert overriderate

Impact onprescriberoutcomes

Impact on patientoutcomes

Alert Evaluation Process

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Alert Evaluation

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25

30

Alert Categories in use in Australian EMM systems

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Beliefs of implementers

• Beliefs about evidence • To support the use of each alert category

• To improve prescriber behavior

• To improve patient outcomes

• Beliefs about the impact of each alert category at their hospital • To improve prescriber behavior

• To improve patient outcomes

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14

Agree Neither Disagree

Believe evidence to support alert category

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14

Agree Neither Disagree

Believe evidence alert category changes prescriber behaviour

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14

Agree Neither Disagree

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Believe evidence alert category improves patient outcomes

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12

Agree Neither Disagree

Believe alert category has changed prescriber behaviour at my institution

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Agree Neither Disagree

Believe alert category has improved patient outcomes at my institution

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Lessons learned

• Start small • No alert better than poorly designed alert

• Difficult to regain trust if have excessive alert generation • Explore other CDS options before interruptive alerts • Condier who, when why, what, how • Prioritise alerts of benefit to your casemix • Carefully design each alert considering the sensitivity, specificity and user-interface

(informatics and clinician collaboration)

• Transparency of alerts • If you evaluate the impact of your alerts you will refine them No evaluation = No improvement • Refine in response to alert fatigue

1. Continue survey recruitment

2. Complete survey analysis

3. Develop an evidence briefing for implementers on the critical medication prescribing alert/s to include in a hospital EMMS system • Evidence from the literature (results of Systematic Review)

• Experiences and advice of Australian implementers (results of Survey)

• Factors to consider when deciding which individual alert category or alert suite to include in a hospital EMMS system

• Expected completion end 2017

Next Steps

Acknowledgements

• Thank you to all the survey respondents for graciously sharing their time!

For further information

• To contribute to the survey, or receive a copy of the final survey and/or evidence briefing, contact

Natalie.Page@hdr.mq.edu.au or Natalie.Page@health.qld.gov.au,

or via www.linkedin.com/in/natalie-page-14031191