HIT Hazard Manager:

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HIT Hazard Manager: - Description

for Proactive Hazard Control. James Walker. . MD, Principal Investigator, Geisinger Health System. Andrea . Hassol MSPH, . Project Director, . Abt . Associates. September 10, . 2012. AHRQ . Contract. ID: 203956 Download Presentation

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HIT Hazard Manager:




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Presentations text content in HIT Hazard Manager:

Slide1

HIT Hazard Manager: for Proactive Hazard Control

James Walker

MD, Principal Investigator, Geisinger Health System

Andrea

Hassol MSPH,

Project Director,

Abt

Associates

September 10,

2012

AHRQ

Contract

: HHSA290200600011i

,#

14

Slide2

Accident Analysis

Most reporting systems concentrate on analyzing adverse events; this means that

injury has already occurred before any learning takes place.

DeRosier

, et al. (2002)

Using Health Care Failure Mode and Effect Analysis.

JC Journal on Quality Improvement.

28(5):248-269.

Slide3

Patient

Harm

Analysis

(e.g., RCA)

Accident Analysis

Slide4

Near-Miss Analysis

Most reporting systems concentrate on analyzing adverse events; this means that injury has already occurred before any learning takes place.

More progressive systems also concentrate on analyzing

close calls

, which affords the opportunity to learn from an event that did not result in a tragic outcome.

DeRosier

, et al. (2002)

Using Health Care Failure Mode and Effect Analysis.

JC Journal on Quality Improvement.

28(5):248-269.

Slide5

Patient

Harm

Near Miss

Analysis

(e.g., RCA)

Near-Miss Analysis

Slide6

Proactive Hazard Control

Most reporting systems concentrate on analyzing adverse events; this means that injury has already occurred before any learning takes place. More progressive systems also concentrate on analyzing close calls, which affords the opportunity to learn from an event that did not result in a tragic outcome.

Systems also exist that permit

proactive evaluation of vulnerabilities before close calls occur.

DeRosier

, et al. (2002)

Using Health Care Failure Mode and Effect Analysis.

JC Journal on Quality Improvement.

28(5):248-269.

Slide7

”Un-Forced”

HIT-Use Error

Error in

D

esign or Implementation

Interaction between HIT and other healthcare systems

Proactive Hazard Control

Care-Process

Compromise?

Identifiable Patient

Harm?

Patient

Harm

No Adverse Effect

Near Miss

Hazard

in

Production

No

Adverse Effect

Yes

Yes

HIT-Related Hazards

Yes

Yes

No

No

No

No

Use-Error Trap

Hazard Identified?

Hazard

Resolved?

HIT-Use-Error

Trap

Slide8

Proactive Hazard Control: A Case

Pre-implementation Analysis: New

CPOE

cannot interface safely with

the existing

best

-in

-

c

lass pharmacy system.

Replace

the pharmacy system with

the one that is integrated with the CPOE: Expensive 9

-month

delay

Years later, David

Classen

studied 62 HER implementations and concluded that

CPOE and pharmacy systems from different vendors can never be safely

interfaced.

Slide9

The Hazard Ontology

Why

a standard language (ontology) for HIT hazards?

To decrease the cost and increase the effectiveness of hazard control.

Example:

Much of the budget of the Aviation

Safety Information Analysis and Sharing (ASIAS) system

is devoted to normalizing data—because

every airline uses

a different ontology and can’t afford to change.

Slide10

Health It Hazard Manager – AHRQ ACTION Task Order

Design & Alpha-Test (266 hazards)

Geisinger

Beta-Test (Website)

Geisinger

Abt

Associates

ECRI PSO

Beta-Test Evaluation

Abt

Associates

Geisinger

Slide11

Hazard Manager Beta-Test

7

sites

: integrated delivery systems, large and small hospitals, urban and rural

Usability (individual interviews)

Inter-rater Scenario Testing (individual web or in-person sessions)

Ontology of hazard attributes (group conference)

Usefulness (group conference)

Automated Reports (group conference)

4 vendors offered critiques

All-Project meeting: 6 test sites, 4 vendors, AHRQ, ONC,

FDA

Slide12

HIT Hazard Manager 2.0

Demo

Slide13

Slide14

Hazard Ontology

Discovery:

when and how the hazard was discovered;

stage of discovery

Causation:

usability, data quality,

decision support, vendor factors, local implementation, other

organizational factors

Impact:

risk and impact of care process compromise; seriousness of patient harm

Hazard Control:

control steps; who will approve and implement the control plan

Slide15

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Slide19

Slide20

Slide21

Slide22

Beta-Test Analytic Methods

Content analysis of

495 Short Hazard Descriptions

Frequencies of hazard ontology factors: combinations often selected together; factors never selected

Inter-rater differences in entries of mock hazard scenarios/vignettes

Suggestions from testers to improve ontology clarity, comprehensiveness, mutual exclusivity

Content analysis of “Other Specify”

entries

Slide23

Example: Unforced User Error

Unforced User Error was the second most frequently chosen factor (79 hazards).In 55 instances, another factor was also chosen:

UsabilityData QualityCDSSoftware DesignOther Org. Factors229 12933

* Multiple selections possible

Inter-rater testing revealed differing attitudes about the role of health IT in

preventing

user errors.

Slide24

Ontology Revision: “Use Error”

Use

Error was often due to the absence of protections or safeguards to prevent

errors:

Added a new factor to Decision Support:

“Missing

Recommendation

or Safeguard”

Re-defined

“Unforced User Error” as “Use Error in the absence of other factors”

Slide25

Hazard Manager Benefits

Slide26

Value: Care-Delivery Organizations

Prior to an upgrade, learn about hazards others have

reported.

Identify hazards that occur at the interface of two vendors’ products.

Control hazards proactively.

E

stimate the risk hazards pose

and prioritize

hazard-control

efforts.

Inform user-group interactions with vendors.

Protect confidentiality.

Slide27

Value: HIT Vendors

Identify the

90% of hazards that their customers do not currently

report.

Learn which

products interact hazardously

with their own.

Prioritize hazard control efforts.

Identify

hazards early in the release

of

new versions.

Preserve confidentiality.

Slide28

Value: Policy Makers

Identify and categorize common hazards that occur at the interface of

specific types of products

(e.g

., pharmacy

and order entry).

Move hazard

identification earlier in the IT lifecycle

(especially prior

to production use

).

M

onitor

the success of

hazard control in

reducing health IT hazards and

decreasing their

impact on patients.

Slide29

For more information:andrea_hassol@abtassoc.com

Beta-Test Final Report

available on AHRQ

website:

healthit.ahrq.gov

/

HealthITHazardManagerFinalReport


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