AACC 2017 Brown Bag: Case Studies: Acceptability of Patient Risk at Monthly/Regular QC Review

AACC 2017 Brown Bag: Case Studies: Acceptability of Patient Risk at Monthly/Regular QC Review

Evaluate acceptability of patient risk at monthly/regular QC review 44119/54219

Speaker: Zoe Brooks, ART AWEsome Numbers Inc., Sudbury, Ontario, Canada

Date: Wednesday, August 2, 2017 at 7:30 am – 8:30 am and 12:30 pm – 1:30 pm.

Primary Topic: Quality Assurance
Secondary Topic: Patient Safety
Presentation Level: Intermediate

Session Overview:

These surveys and case studies are open to the laboratory community now! Results will be presented first at the round-table, then at a webinar for all participants.

How do you manage risk?

How much risk exists in your methods?

Take the surveys now!

This session is 100% case study based. Take the QC practice survey and send monthly QC summary data. Look at quality differently – with mathematical algorithms that include patient volume, laboratory-approved medical goals and acceptable risk levels. Discover the impact of your mathematical choices in terms of patient risk and cost.

Target Audience: This session brings NEW knowledge to Lab Directors, Clinical Chemists, Technologists, Quality managers, IVD Industry Scientists, administrators and CFOs

What are the problems/issues that will be addressed in this session?
1. Laboratory errors waste precious time and resources in the laboratory and add billions of dollars in clinical care in the USA.
2. The practice of IQCP and risk management add new requirements that cannot be met with existing QC metrics: CLSI EP 23-A recommends
a. “Risk evaluation – process of comparing the estimated risk against given risk criteria to determine the acceptability of the risk.”
b. ”Evaluate the potential costs both in terms of the patient’s well-being and in terms of financial liability of the treating parties vs known benefits to the patient.”
c. “At the least, the ability of the QC procedures to detect medically allowable error should be evaluated.”
3. There is a huge opportunity to quickly improve quality
a. many QC processes are not effective to detect medically allowable error
b. many analytical processes show opportunities to reduce risk

Who is affected by the problems?
1. Medical laboratory director: CLIA requires that he/she “ensure that the test methodologies selected have the capability of providing the quality of results required for patient care.” and “ensure the establishment and maintenance of acceptable levels of analytical performance for each test system.”
2. Institution paying the cost of unnecessary laboratory tests and avoidable clinical costs.
3. Laboratory managers who want the assurance that their QC are indeed effective to maintain the quality standards set by the laboratory director
4. Patients who lives are impacted by tumors and kidney disease are diagnosed too late by false negative results, plus the cost and risk of follow-up tests from a false positive result.

What has been done to fix the problems in the past?
a. Laboratory quality control practices have not changed significantly in 30 years.
b. Statistics produce only statistical metrics that are interpreted inconsistently.
c. Some statistical formulae are based on unproven or outdated assumptions.
d. Some statistical formulae are mathematically incorrect.
e. Both quality control design and front line QC practice are inconsistent.
f. The same set of measured facts can produce fourteen different sigma values.

Why was it successful or unsuccessful?

Statistical QC fails because people are not good at statistics.
The effectiveness of QC processes is not typically evaluated.

How will my presentation effectively address the problems and provide solutions?
Participants will be able to compare mathematically-calculated risk metrics for prepared case studies and their QC results to the numbers, assumptions and action from their original statistical interpretations. They will be challenged to agree on evaluation of the acceptability of risk with sigma metrics, margin for error and risk graphics.

Learning Objectives:
After this session, participants will be able to:
1. Set medical goals and acceptable risk level for case studies.
2. Describe a process to determine the acceptability of current risk at monthly/regular review
3. Critically examine the effectiveness of existing monthly/regular review process.

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