This document discusses quality improvement tools for analyzing health information technology (HIT) errors, including root cause analysis (RCA), failure mode and effects analysis (FMEA), and hazard analysis. RCA is a structured problem-solving process that considers all potential causal factors of an incident. FMEA prospectively predicts error modes by assessing the likelihood and impact of process failures. The document provides examples of using RCA and FMEA to analyze HIT-related errors and identifies key areas of focus for HIT safety measures.
Root cause Analysis (RCA) & Corrective and Preventive action (CAPA) in MRCT d...Bhaswat Chakraborty
This presentation describes Identification & differentiation of Protocol deviation & violation; Different methods of RCA & best suitable method for Multiregional Clinical Trial; CAPA management and CAPA application to other trial sites/CRO/SMO/ Country that is involved in same trial (Strategic Management and application of CAPA in MRCT)
Risk Assessment with “Actuarial Data”, George GrayOECD Governance
Presentation by Prof. George Gray, Director of the Centre for Risk Science and Public Health, George Washington University, at the Workshop on Risk Assessment in Regulatory Policy Analysis (RIA), Session 7, Mexico, 9-11 June 2014. Further information is available at http://www.oecd.org/gov/regulatory-policy/
Data Management: Alternative Models for Source Data VerificationKCR
KCR's presentation on alternative models for Source Data Verification (SDV) Risk Based Monitoring (RBM) is evolving into a standard expectation for SDV and study management in general.
Risk of bias assessment and different tools used to assess systematic review ...Pubrica
• The risk of bias is defined as the risk of systematic error or a deviation from reporting the truth or an appropriate evidence finding.
• It occurs when there is a systematic flaw or limitations in the study design or the conduct of the study.
• This article describes different assessment tools and the types of study designs for which the tool is applicable along with the flow of how to avoid the risk of bias.
For full informtion: https://bit.ly/2U4ibro
Reference: https://pubrica.com/services/research-services/systematic-review/
Why pubrica?
When you order our services, we promise you the following – Plagiarism free, always on Time, outstanding customer support, written to Standard, Unlimited Revisions support and High-quality Subject Matter Experts.
Contact us :
Web: https://pubrica.com/
Blog: https://pubrica.com/academy/
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WhatsApp : +91 9884350006
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Temporal relations in queries of ehr data for researchWolfgang Kuchinke
Temporal Relations in Queries of Electronic Patient Records. Our main scenario covers the patient identification and recruitment process for clinical trials. For this purpose an extension of the EHR4CR workbench to support patient recruitment was created. This workbench covers following requirements:
Need for built-in privacy protection.
Patient identification and recruitment tracking.
Availability at clinical sites in the form of a workbench with an user-friendly interface.
Each participating clinical site has its own installation only used locally.
Ability to generate queries with temporal relations and constraints for eligibility criteria to find candidate patients.
Our development is based on the fact that queries in EHRs often have a temporal component. But available user interfaces allow only the generation of simple queries with basic temporal relations. Time points and time intervals are therefore the main concepts that must be considered. Time points are related to instantaneous events (e.g. a single myocardial infarction), or to situations lasting for a span of time (e.g. a drug therapy for 2 weeks). Intervals can be represented using time points by their upper and lower temporal boundaries: the start and end. Temporal relations (e.g before, after) can be expressed via additional anchors. The dates of these anchor events can be retrieved and event dates relative to an anchor event can be calculated. EHR4CR decided to build its workbench upon a simple, time-stamp database concept. To each patient’s attribute a time-stamp, which corresponds to the time of the attribute’s occurrence was assigned. The processing of temporal intervals is necessary for EHR4CR since many questions dealing with inclusion / exclusion criteria often involve complex temporal periodes. A graphical interface to use boxes for querying with temporal relations was therefore created. The idea is that the easiest way to specify temporal operators is with an user interface based on the combination of boxes. Temporal operators based on Allen’s algebra were included. Expressions are displayed as graphic boxes and combined by
operators. Events are specified and a temporal operator selected from a predefined list.
Root cause Analysis (RCA) & Corrective and Preventive action (CAPA) in MRCT d...Bhaswat Chakraborty
This presentation describes Identification & differentiation of Protocol deviation & violation; Different methods of RCA & best suitable method for Multiregional Clinical Trial; CAPA management and CAPA application to other trial sites/CRO/SMO/ Country that is involved in same trial (Strategic Management and application of CAPA in MRCT)
Risk Assessment with “Actuarial Data”, George GrayOECD Governance
Presentation by Prof. George Gray, Director of the Centre for Risk Science and Public Health, George Washington University, at the Workshop on Risk Assessment in Regulatory Policy Analysis (RIA), Session 7, Mexico, 9-11 June 2014. Further information is available at http://www.oecd.org/gov/regulatory-policy/
Data Management: Alternative Models for Source Data VerificationKCR
KCR's presentation on alternative models for Source Data Verification (SDV) Risk Based Monitoring (RBM) is evolving into a standard expectation for SDV and study management in general.
Risk of bias assessment and different tools used to assess systematic review ...Pubrica
• The risk of bias is defined as the risk of systematic error or a deviation from reporting the truth or an appropriate evidence finding.
• It occurs when there is a systematic flaw or limitations in the study design or the conduct of the study.
• This article describes different assessment tools and the types of study designs for which the tool is applicable along with the flow of how to avoid the risk of bias.
For full informtion: https://bit.ly/2U4ibro
Reference: https://pubrica.com/services/research-services/systematic-review/
Why pubrica?
When you order our services, we promise you the following – Plagiarism free, always on Time, outstanding customer support, written to Standard, Unlimited Revisions support and High-quality Subject Matter Experts.
Contact us :
Web: https://pubrica.com/
Blog: https://pubrica.com/academy/
Email: sales@pubrica.com
WhatsApp : +91 9884350006
United Kingdom: +44- 74248 10299
Temporal relations in queries of ehr data for researchWolfgang Kuchinke
Temporal Relations in Queries of Electronic Patient Records. Our main scenario covers the patient identification and recruitment process for clinical trials. For this purpose an extension of the EHR4CR workbench to support patient recruitment was created. This workbench covers following requirements:
Need for built-in privacy protection.
Patient identification and recruitment tracking.
Availability at clinical sites in the form of a workbench with an user-friendly interface.
Each participating clinical site has its own installation only used locally.
Ability to generate queries with temporal relations and constraints for eligibility criteria to find candidate patients.
Our development is based on the fact that queries in EHRs often have a temporal component. But available user interfaces allow only the generation of simple queries with basic temporal relations. Time points and time intervals are therefore the main concepts that must be considered. Time points are related to instantaneous events (e.g. a single myocardial infarction), or to situations lasting for a span of time (e.g. a drug therapy for 2 weeks). Intervals can be represented using time points by their upper and lower temporal boundaries: the start and end. Temporal relations (e.g before, after) can be expressed via additional anchors. The dates of these anchor events can be retrieved and event dates relative to an anchor event can be calculated. EHR4CR decided to build its workbench upon a simple, time-stamp database concept. To each patient’s attribute a time-stamp, which corresponds to the time of the attribute’s occurrence was assigned. The processing of temporal intervals is necessary for EHR4CR since many questions dealing with inclusion / exclusion criteria often involve complex temporal periodes. A graphical interface to use boxes for querying with temporal relations was therefore created. The idea is that the easiest way to specify temporal operators is with an user interface based on the combination of boxes. Temporal operators based on Allen’s algebra were included. Expressions are displayed as graphic boxes and combined by
operators. Events are specified and a temporal operator selected from a predefined list.
The background, key features and main steps of the concise analysis method are described, discussed and applied in this module together with the main tools used during a concise analysis (timeline, guiding questions, constellation diagram, and statements of findings).
Test beyond the obvious- Root Cause AnalysisPractiTest
Kevin Wilkes - Senior Test Consultant at QualiTest and Richard Morgan - UK Delivery Manager at QualiTest, Co-present "Test beyond the obvious- Root Cause Analysis" at OnlineTestConf.com
Objectives:
By the end of this call, you will be able to:
•Describe the processes of Root-Cause Analysis (RCA) and Multi-Incident Analysis (MIA) and their role in quality improvement
•Compare and contrast the different approaches to collecting hospital-acquired VTE data
•Identify an approach suitable for improving patient safety at your institution
Operations Management A CEO Checklist for High-Value H.docxvannagoforth
Operations Management
A CEO Checklist for High-Value Health Care:
Ten Elements
Foundational elements
• Governance priority—visible and determined
leadership by CEO and board.
• Culture of continuous improvement—commitment
to ongoing, real-time learning.
Infrastructure fundamentals
• IT best practices—automated, reliable information to
and from the point of care.
• Evidence protocols—effective, efficient, and
consistent care.
• Resource utilization—optimized use of personnel,
physical space, and other resources.
Care delivery priorities
• Integrated care—right care, right setting, right
providers, right teamwork.
• Shared decision-making—patient-clinician
collaboration on care plans.
• Targeted services—tailored community and clinic
interventions for resource-intensive patients.
Reliability and feedback
• Embedded safeguards—supports and prompts to
reduce injury and infection.
• Internal transparency—visible progress in
performance, outcomes, and costs.
What is Operations Management?
• The design, operation, and improvement of
the processes that create and deliver the
organization’s services.
• The goal is to more effectively and efficiently
produce and deliver the organization’s
services.
Healthcare Management
• The management of processes or health systems
that provide care to patients.
• The use of decision tools to manage and
improve processes.
• Functional roles:
– CEO
– COO
– CXO
– Mid-level manager
– Department or function manager
Health Care Operations Management
– Process improvement.
– Quality control and outcomes .
– Patient satisfaction.
– Financial operations – cost, reimbursement.
– Supply chain management – procurement, medical supplies.
– Human resources management – productivity, motivating
employees.
– Information systems management.
– Population health.
– Physician alignment.
– Governance.
– Strategy and operations.
System Decisions
System Design
Capacity.
Location.
Proximity.
Service planning.
Acquisition and placement of
equipment.
System Operations
Personnel.
Inventory.
Scheduling.
Product management.
Quality measurement
and assurance.
There are two groups of decisions:
Applicability to Health Care
• Patient is a participant in the process.
• Production and consumption occur
simultaneously.
• Uncontrollable capacity.
• Site selection is dictated by patient location.
• Labor intensive.
INTRODUCTION TO PROCESS IMROVEMENT
Process or Performance Improvement
• Scientific management
– Mass production
• TQM, CQI, Six Sigma
• ISO 9000
• Lean
• Six Sigma
Background
• Scientific Management Techniques (1910s) – Frederic W. Taylor
• Standardization – Frank & Gillian Gilberth
• Psychological Effects of Work Conditions – Henry Gannt
• Quantitative Inventory Management (1915) – F.W. Harris
• Quality Control & Sampling (1930s) – W. Shewhart
• Operations ...
Microbiological Hazard and Risk Assessment of Fish and Fishery productsAsrafurTalha1
All the microbial hazard and risk assessment of fish and fishery products are described here for the advancement of fish and fishery products to cope up with the advancing and progressing world.
A 15-minutes oral presentation that was given in ISQua's 32nd International Conference, Doha, October 2015 by Dr. Yasser Amer under the track: "Quality and Safety in Developing Countries"
The background, key features and main steps of the concise analysis method are described, discussed and applied in this module together with the main tools used during a concise analysis (timeline, guiding questions, constellation diagram, and statements of findings).
Test beyond the obvious- Root Cause AnalysisPractiTest
Kevin Wilkes - Senior Test Consultant at QualiTest and Richard Morgan - UK Delivery Manager at QualiTest, Co-present "Test beyond the obvious- Root Cause Analysis" at OnlineTestConf.com
Objectives:
By the end of this call, you will be able to:
•Describe the processes of Root-Cause Analysis (RCA) and Multi-Incident Analysis (MIA) and their role in quality improvement
•Compare and contrast the different approaches to collecting hospital-acquired VTE data
•Identify an approach suitable for improving patient safety at your institution
Operations Management A CEO Checklist for High-Value H.docxvannagoforth
Operations Management
A CEO Checklist for High-Value Health Care:
Ten Elements
Foundational elements
• Governance priority—visible and determined
leadership by CEO and board.
• Culture of continuous improvement—commitment
to ongoing, real-time learning.
Infrastructure fundamentals
• IT best practices—automated, reliable information to
and from the point of care.
• Evidence protocols—effective, efficient, and
consistent care.
• Resource utilization—optimized use of personnel,
physical space, and other resources.
Care delivery priorities
• Integrated care—right care, right setting, right
providers, right teamwork.
• Shared decision-making—patient-clinician
collaboration on care plans.
• Targeted services—tailored community and clinic
interventions for resource-intensive patients.
Reliability and feedback
• Embedded safeguards—supports and prompts to
reduce injury and infection.
• Internal transparency—visible progress in
performance, outcomes, and costs.
What is Operations Management?
• The design, operation, and improvement of
the processes that create and deliver the
organization’s services.
• The goal is to more effectively and efficiently
produce and deliver the organization’s
services.
Healthcare Management
• The management of processes or health systems
that provide care to patients.
• The use of decision tools to manage and
improve processes.
• Functional roles:
– CEO
– COO
– CXO
– Mid-level manager
– Department or function manager
Health Care Operations Management
– Process improvement.
– Quality control and outcomes .
– Patient satisfaction.
– Financial operations – cost, reimbursement.
– Supply chain management – procurement, medical supplies.
– Human resources management – productivity, motivating
employees.
– Information systems management.
– Population health.
– Physician alignment.
– Governance.
– Strategy and operations.
System Decisions
System Design
Capacity.
Location.
Proximity.
Service planning.
Acquisition and placement of
equipment.
System Operations
Personnel.
Inventory.
Scheduling.
Product management.
Quality measurement
and assurance.
There are two groups of decisions:
Applicability to Health Care
• Patient is a participant in the process.
• Production and consumption occur
simultaneously.
• Uncontrollable capacity.
• Site selection is dictated by patient location.
• Labor intensive.
INTRODUCTION TO PROCESS IMROVEMENT
Process or Performance Improvement
• Scientific management
– Mass production
• TQM, CQI, Six Sigma
• ISO 9000
• Lean
• Six Sigma
Background
• Scientific Management Techniques (1910s) – Frederic W. Taylor
• Standardization – Frank & Gillian Gilberth
• Psychological Effects of Work Conditions – Henry Gannt
• Quantitative Inventory Management (1915) – F.W. Harris
• Quality Control & Sampling (1930s) – W. Shewhart
• Operations ...
Microbiological Hazard and Risk Assessment of Fish and Fishery productsAsrafurTalha1
All the microbial hazard and risk assessment of fish and fishery products are described here for the advancement of fish and fishery products to cope up with the advancing and progressing world.
A 15-minutes oral presentation that was given in ISQua's 32nd International Conference, Doha, October 2015 by Dr. Yasser Amer under the track: "Quality and Safety in Developing Countries"
Rate Controlled Drug Delivery Systems, Activation Modulated Drug Delivery Systems, Mechanically activated, pH activated, Enzyme activated, Osmotic activated Drug Delivery Systems, Feedback regulated Drug Delivery Systems systems are discussed here.
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Hypertension is a chronic condition of concern due to its role in the causation of coronary heart diseases. Hypertension is a worldwide epidemic and important risk factor for coronary artery disease, stroke and renal diseases. Blood pressure is the force exerted by the blood against the walls of the blood vessels and is sufficient to maintain tissue perfusion during activity and rest. Hypertension is sustained elevation of BP. In adults, HTN exists when systolic blood pressure is equal to or greater than 140mmHg or diastolic BP is equal to or greater than 90mmHg. The
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In this session, we will explore how a robust quality management solution can empower your organization to meet regulatory requirements and improve processes for MIPS reporting and internal quality programs. Learn how our MeasureAble application enables compliance and fosters continuous improvement.
Medical Technology Tackles New Health Care Demand - Research Report - March 2...pchutichetpong
M Capital Group (“MCG”) predicts that with, against, despite, and even without the global pandemic, the medical technology (MedTech) industry shows signs of continuous healthy growth, driven by smaller, faster, and cheaper devices, growing demand for home-based applications, technological innovation, strategic acquisitions, investments, and SPAC listings. MCG predicts that this should reflects itself in annual growth of over 6%, well beyond 2028.
According to Chris Mouchabhani, Managing Partner at M Capital Group, “Despite all economic scenarios that one may consider, beyond overall economic shocks, medical technology should remain one of the most promising and robust sectors over the short to medium term and well beyond 2028.”
There is a movement towards home-based care for the elderly, next generation scanning and MRI devices, wearable technology, artificial intelligence incorporation, and online connectivity. Experts also see a focus on predictive, preventive, personalized, participatory, and precision medicine, with rising levels of integration of home care and technological innovation.
The average cost of treatment has been rising across the board, creating additional financial burdens to governments, healthcare providers and insurance companies. According to MCG, cost-per-inpatient-stay in the United States alone rose on average annually by over 13% between 2014 to 2021, leading MedTech to focus research efforts on optimized medical equipment at lower price points, whilst emphasizing portability and ease of use. Namely, 46% of the 1,008 medical technology companies in the 2021 MedTech Innovator (“MTI”) database are focusing on prevention, wellness, detection, or diagnosis, signaling a clear push for preventive care to also tackle costs.
In addition, there has also been a lasting impact on consumer and medical demand for home care, supported by the pandemic. Lockdowns, closure of care facilities, and healthcare systems subjected to capacity pressure, accelerated demand away from traditional inpatient care. Now, outpatient care solutions are driving industry production, with nearly 70% of recent diagnostics start-up companies producing products in areas such as ambulatory clinics, at-home care, and self-administered diagnostics.
Navigating Challenges: Mental Health, Legislation, and the Prison System in B...Guillermo Rivera
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1. Quality Improvement
Learning From Mistakes: Error
Reporting and Analysis and HIT
Lecture c
This material (Comp 12 Unit 11) was developed by Johns Hopkins University, funded by the Department of
Health and Human Services, Office of the National Coordinator for Health Information Technology under
Award Number IU24OC000013. This material was updated in 2016 by Johns Hopkins University under
Award Number 90WT0005.
This work is licensed under the Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International
License. To view a copy of this license, visit http://creativecommons.org/licenses/by-nc-sa/4.0/.
2. Learning From Mistakes: Error
Reporting and Analysis and HIT
Learning Objectives — Lecture c
• Apply QI tools to analyze HIT errors.
2
4. Quality Improvement Tools:
Root Cause Analysis (RCA)
• Structured problem-solving process.
• Considers all potential causal or
contributing factors:
– Human factors.
– System factors.
• Detailed chronological list of events
surrounding incident.
• Premise: one can learn from one’s
mistakes.
4
6. RCA: Practical Example
• A17-year-old was taught how to do laundry,
in anticipation of her living in a college
dormitory.
• She returned home one weekend with a
total body rash and oily clothes.
• After taking her to the dermatologist and
getting prescriptions filled, the parent,
doctor, and teen wanted to try to uncover
what led to this situation.
6
7. RCA: Steps — 1
• Briefly describe event:
– Student arrived home with a total body rash and oily
jeans.
• Identify affected areas/services:
– Dorm laundry facilities.
– Home laundry facility.
– Use of laundry facilities.
• Assemble a team:
– Student.
– Parent.
– Dermatologist. 7
8. RCA: Steps — 2
• Diagram the process (flowchart):
– As it was designed.
– As it is usually done.
– As it was done when event occurred.
• Identify potential root causes:
– Size of washing machine (diminutive versus full-sized).
– Type of washing machine (front loader versus top loader).
– Type/amount of detergent (too much?).
– Length of rinse cycle (single versus double rinse).
– Following instructions given at home in the dorm
environment.
8
9. RCA: Steps — 3
• Develop action plan:
– Use less soap and double-rinse clothes after
washing.
– Responsibility: student.
– Implementation date: as soon as she returns
to school.
– Measurement strategy: skin assessment
when student returns home and assessment
of clothes for soap residue.
9
10. RCA: Health Care Example
• Mrs. A. received blood in the emergency department
(ED).
• Within 15 minutes, she experienced a bad reaction.
• Her nurse realized that she had received blood
intended for another patient.
• She was transferred to the intensive care unit to be
stabilized.
• The ED staff wanted to know how this could have
happened, so they assembled a team to identify
possible causes.
10
11. RCA: Steps for Health Care — 1
• Briefly describe event:
– Mrs. A. received blood intended for someone else.
• Identify affected areas/services:
– Blood transfusion service.
– Medical/nursing staff.
– Risk manager (RM)/quality improvement (QI) staff.
• Assemble a team:
– Manager, Transfusion Services.
– Physician Chair of QI Committee.
– Nurse managers, staff nurses.
– QI, RM, patient safety representatives.
– HIT representative.
11
12. RCA: Steps for Health Care — 2
• Diagram the process (flowchart):
– As it was designed.
– As it is usually done.
– As it was done when event occurred.
• Identify potential root causes:
– Flawed patient identification process.
– Faulty patient-blood product verification process.
– Inadequate staffing levels.
– Inadequate orientation, training, or competence
assessment.
12
13. RCA: Steps for Health Care — 3
• Prioritize root causes:
– Evaluate whether these factors will cause harm in the future.
– Design interventions that reduce this probability of harm and that
have a high probability of being implemented as intended, given
available resources (Pham et al, 2010).
• Develop action plan:
– Implement barcode blood product verification system.
– Responsibility: HIT Project Manager.
– Implementation date: November 2011.
– Measurement strategy: collect data on patient misidentification
errors related to blood product transfusion and compare to
implementation rates.
• Evaluate results!
13
14. Quality Improvement Tools: Failure
Modes and Effects Analysis (FMEA)
• Prospective attempt to predict error
modes.
• Combines the likelihood of a particular
process failure with an estimate of the
relative impact of that error.
• Produces a criticality index that allows for
the prioritization of specific processes as
QI targets.
14
16. FMEA: Event
• After reading several articles about
laboratory specimen errors that result in
lab tests being done on the wrong
patients, doctors at a community office
practice decide to examine the potential
for this problem to happen in their office
laboratory.
16
17. FMEA: Steps
• Select a high-risk process (patient identification):
– Affects a large number of patients.
– Carries a high risk for patients.
– Has known process problems identified by other
organizations (e.g., Joint Commission Sentinel Event
Alert!).
• Assemble a team:
– People closest to issue involved.
– People critical to implementation of potential changes.
– Respected, credible team leader.
– Someone with decision-making authority.
– People with diverse knowledge bases.
17
19. Conduct a Hazard Analysis
Frequency Catastrophic (4) Major (3) Moderate (2) Minor (1)
Frequent (4) 4 X 4 = 16 4 X 3 = 12 4 X 2 = 8 4 X 1 = 4
Occasional (3) 3 X 4= 12 3 X 3 = 9 3 X 2 = 6 3 X 1 = 3
Uncommon (2) 2 X 4 = 8 2 X 3 = 6 2 X 2 = 4 2 X 1 = 2
Remote (1) 1 X 4 = 4 1 X 3 = 3 1 X 2 = 2 1 X 1 = 1
• The higher the number, the more urgent the need to
prevent a failure.
11.15 Table.
19
20. Quality Improvement Tools:
Comparison
• RCA:
– Looks to the past.
– How? Why? Who?
– Retrospective.
– Usually retroactive.
– Dissects error.
– Identifies possible
failure causes.
– Subject to hindsight
bias.
• FMEA:
– Looks to the future.
– What if … ?
– Prospective.
– Proactive.
– Anticipates error.
– Identifies possible
failure modes.
– Not subject to
hindsight bias. 20
21. NQF HIT Safety Measures Project
• Conducted an environmental scan of relevant HIT measures
and measure concepts.
• Convened a multistakeholder committee to guide and provide
input on all phases of the project as well as engage NQF
members and public stakeholders at key points throughout
the project.
• Developed a conceptual framework for HIT safety as a way to
categorize measure concepts and gaps in measurement.
• Identified challenges to the measurement of HIT-related
safety events and adoption of best practices to strengthen
measurement efforts.
• Identified and prioritized key measurement areas and
potential measure concepts related to HIT safety.
21
22. NQF HIT Safety Measures
Committee Focus
1. Clinical decision support.
2. System interoperability.
3. Patient identification.
4. User-centered design and use of testing, evaluation, and
simulation to promote safety across the HIT lifecycle.
5. System downtime (data availability).
6. Feedback and information sharing.
7. Use of HIT to facilitate timely and high-quality
documentation.
8. Patient engagement.
9. HIT-focused risk management infrastructure.
Full report: http://www.qualityforum.org/ProjectMaterials.aspx?projectID=77689 22
23. Learning From Mistakes: Error
Reporting and Analysis and HIT
Summary — Lecture c
• Tools:
– Root Cause Analysis (RCA).
– Failure Mode and Effects Analysis (FMEA).
– Hazard analysis.
– Flowcharting.
– HIT-related safety measures.
23
24. Learning From Mistakes: Error
Reporting and Analysis and HIT
References — Lecture c
References
Agency for Healthcare Research and Quality. (2016). Failure mode and effects analysis.
Retrieved June 3, 2016, from https://healthit.ahrq.gov/health-it-tools-and-
resources/workflow-assessment-health-it-toolkit/all-workflow-tools/fmea-analysis
Agency for Healthcare Research and Quality, Patient Safety Network. (2016). Glossary.
Retrieved June 3, 2016, from https://psnet.ahrq.gov/glossary
Charts, Tables, Figures
11.11 Figure: Quality Improvement Tools. Dr. Stephanie Poe.
11.12 Figure: RCA Factors. Dr. Stephanie Poe.
11.13 Figure: FMEA Analysis and Premises. Dr. Stephanie Poe.
11.14 Figure: FMEA: Diagram the Process. Dr. Stephanie Poe.
11.15 Table: Conduct a Hazard Analysis.
24
25. Quality Improvement
Learning From Mistakes: Error
Reporting and Analysis and HIT
Lecture c
This material (Comp 12 Unit 11) was developed
by Johns Hopkins University, funded by the
Department of Health and Human Services,
Office of the National Coordinator for Health
Information Technology under Award Number
IU24OC000013. This material was updated in
2016 by Johns Hopkins University under Award
Number 90WT0005.
25
Editor's Notes
Welcome to Quality Improvement: Learning from Mistakes: Error Reporting and Analysis and HIT. This is Lecture c.
Our focus will be on several quality improvement tools that are used often in health care and may prove helpful in learning from mistakes.
By the end of Learning from Mistakes: Error Reporting and Analysis and HIT, you will be able to apply QI tools to the analysis of HIT errors.
This lecture will discuss quality improvement tools.
There are two quality improvement tools that are used in all organizations accredited by the Joint Commission. They are known as mantras of modern risk management because they have the power to transform patient safety through learning. Both are systematic and team based.
One is called RCA, or Root Cause Analysis, and it looks to the past to learn from mistakes.
The second, Failure Modes and Effects Analysis, or FMEA, takes the opposite approach and looks to the future by anticipating errors and putting processes in place to either prevent or mitigate potential harm.
However, there are additional tools that can be used to improve safety, such as flowchart analysis or cause-and-effect fishbone diagram.
Root cause analysis is a structured, problem-solving process used to identify the causal or contributing factors underlying adverse events. In a methodical way, team members consider all possible causes of events (both human and system factors) as potential contributors to the event, rather than attributing the event to the first cause they examine. The premise underlying RCA is that we can learn from our mistakes and the mistakes of others. According to the Agency for Healthcare Research and Quality, the single most important product of an RCA is the detailed account of the events that led up to the incident. The beauty of the RCA is that the tool is based on the premise that one can learn from one’s mistakes. Therefore, although the approach is predominantly retrospective (in that we are trying to find out what went wrong in something that really occurred), changes as a result of an RCA benefit from the prospective analysis of what could go wrong if we institute this fix.
Human factors to take into consideration include knowledge, skill, and abilities of those involved in the event, including adequacy of training.
Procedural factors include the complexity of the procedure itself and any dependencies that exist. For example, if use of a central line safety checklist is required, but the lists are paper based and cannot be found at the time they are needed, then this could have led to an adverse event under review. Use of a central line cart that is stocked with checklists, or the availability of an electronic checklist at the point of care, would be appropriate interventions.
Defects or failures in equipment or facilities, work conditions, and communication are also examined.
RCA, or Root Cause Analysis, is used whenever something really bad happens and we want to understand why so that we can prevent a similar event from occurring in the future. We know that if we dissect the error by developing a chronological description of the who, what, when, where, and how of the situation, we can find out the probable cause and put something in place to prevent the event from occurring again. RCA is based on the belief that we can learn from our mistakes.
Let’s take a practical example from everyday life. A 17-year-old was taught how to do laundry, in anticipation of her living in a college dormitory. She returned home one weekend with a total body rash and oily clothes. After taking her to the dermatologist and getting her prescriptions filled, her concerned parent wanted to try to uncover what led to this situation.
Obviously, something happened between the time the teenager lived at home and “practiced” doing laundry successfully and the time she returned in misery. She left for school with clear skin, a bottle of unscented Tide, and a suitcase filled with five pairs of jeans and a multitude of tops. What could be done in order to get to the root of this problem? The answer: an RCA.
Root cause analyses are very structured. In this case, the team assembled for the inquiry included the student, her concerned parent, and the teen’s dermatologist. First, they needed to describe what happened. The student had arrived home with a total-body rash and oily jeans in her suitcase. Next, they had to look at all areas that may have affected the problem. In our example, this included the college dorm’s laundry facilities, the student’s home laundry facilities, and how each of these were used by the teen.
A diagram was drawn of the steps that the daughter had been taught to use when doing laundry. Here it was important to look at the conditions in her home, with respect to the laundry room. Next, a second diagram was drawn about how she actually did laundry in her home. And finally, a diagram was drawn of the steps she took in the dorm. Again, it was important to also look at the dorm’s laundry facilities.
In examining these steps, it was discovered that the dorm washing machine was much smaller than the home machine, was a front loader versus a top loader, required much less detergent and a different concentration of detergent, and had only a single rinse cycle (while the machine at home had an automatic double rinse cycle). The teenager had followed her parent’s instructions to the letter; unfortunately, the equipment was different, and she did not know to alter her procedure in response to these differences. Her clothes retained soap, rubbed against her skin, and caused the rash.
So what plans could be made? Definitely use less soap, and use the kind that is made for use in front loaders. Set the rinse cycle so that the clothes could be double rinsed. Of course, the responsibility belonged to the daughter and not the parent. The new plan had to happen as soon as she returned to school. The concerned parent would be able to determine if the plan was effective when the student reported her skin status and by examining her clothes on her next visit home.
Now that we’ve had a practical example, let’s talk about a health care example that you may encounter as an HIT professional.
Mrs. A. received blood in the emergency room. Within 15 minutes, she experienced a bad reaction. Her nurse realized that she had received blood intended for another patient. Mrs. A. was transferred to the intensive care unit to be stabilized. The Emergency Department staff wanted to know how this could have happened, so they assembled a team to identify possible causes.
As you can see, the ramifications of patient identification errors can be catastrophic in the health care setting. It’s essential that the health care team work together to understand the root causes of errors such as these so that similar events can be decreased in the future.
So let’s walk through the steps of an RCA for this event.
As soon as clinical leaders became aware of the event, they would discuss what happened. Since this is a very serious event, they would decide to do a Root Cause Analysis. To start, they would identify the affected areas or services. In this case, clinicians and blood transfusion services, as well as quality improvement staff or the risk manager would be selected to join the RCA team. In addition, since HIT has shown promise in helping to prevent patient identification errors, as an HIT professional, you might be requested to contribute to this analysis.
Early on, the team will take a “deep dive” into the details of the event. They will develop flowcharts on how the blood product transfusion patient identification process was designed, how it is usually done in this particular Emergency Department, and how it was done on the day that this event occurred. Invariably, we would find that these three workflow processes differ in some way or another.
The team might uncover flawed processes for patient identification. They might also find something wrong with the patient verification process against the blood product. They may uncover that inadequate staffing levels led to workarounds because nurses were too busy to do the usual safety checks. Or that nurses who were managing the blood transfusion were not fully trained in the facility’s blood product transfusion practices.
The team may find several root causes. Here we can learn lessons from the aviation industry. We can increase the potential for success by prioritizing each cause and selecting interventions, based on their ability to prevent future harm as well as our ability to successfully implement these interventions, given our available resources.
Luckily, the team thought to add you, an HIT professional. You might point out the merits of barcode technology for blood product verification. This technology interfaces with both the electronic health record and the transfusion medicine information system. You might be assigned responsibility and a timeline to develop a project plan. As a team, you would all determine a measurement strategy that would show that you have improved the ability to accurately identify patients who receive blood transfusions.
As you can see, this is a very effective strategy for learning from our mistakes. But we don’t have to wait for mistakes to happen before we take action. There are other quality improvement tools that anticipate events and try to either stop them from happening or minimize harm if they do happen.
Failure Modes and Effects Analysis looks to the future in a prospective attempt to predict where errors could possibly, potentially occur. FMEA combines the likelihood of a particular process failure with an estimate of the relative impact of that error to produce a "criticality index." By combining the probability of failure with the consequences of failure, this index allows for the prioritization of specific processes as quality improvement targets. This is one of the tools that is used in the third phase of reliability work.
During an FMEA, the team analyzes ways in which a process or design can fail, why it might fail, and how it can be made safer or better. The FMEA is based on the premise that we do not have to wait for errors to happen. We can anticipate errors and adverse events, and we can do things to reduce the risk of harm.
Let’s look at a health care example. After reading several articles about laboratory specimen errors that result in lab tests being done on the wrong patients, doctors at a community office practice decide to examine the potential for this problem to happen in their office laboratory. Let’s walk through the steps of an FMEA.
The first thing to do is to select a high-risk process. In this instance, it is patient identification but could be any process that affects large numbers of patients, carries a high risk for patients, or has known process problems identified by other organizations.
Here, the provider members of this group practice are alerted to a high-risk process by reading articles written by other doctors. They wonder about the risk of this particular problem occurring in their office lab and decide to do a Failure Modes and Effects Analysis. They also wonder whether there is an IT solution that would minimize the risk of laboratory patient misidentification errors in their practice.
When assembling the team, you want to include people who are closest to the issue involved, those who are critical to implementing potential changes. You want to have a respected, credible leader, someone with decision-making authority, and people with diverse knowledge bases. So our hypothetical provider group would ask you, as an HIT professional, to participate in this FMEA. They also include the lab supervisor, an office nurse, and two lab technicians.
The flow diagram starts with CPOE orders entered. It is connected to “labels print in lab area.” This one is connected to “phlebotomist asks patient to state name and birthdate.” This one is connected to “phlebotomist checks patient labels with patient's response.” This is connected to a diamond that reads “correct patient.” If the answer is “yes,” it connects to a box that reads “perform collection.” If the answer is “no,” it connects to a box that reads “follow clinic procedure.”
Together, they diagram the process and look for ways in which the process could potentially fail. They identify three places that the process could fail: there could be a problem with the label printing; the phlebotomist could forget to ask the patient to state his name and birthdate, or the phlebotomist could lead the patient to affirm an incorrect identity by phrasing the question to include the incorrect name, “Mr. Jones, right?”; finally, the phlebotomist could fail to check the patient’s lab requisition label with the patient’s response.
During the hazard analysis, the team may find that most often, phlebotomists forget to request the patient’s name and birthdate. This could lead to inappropriate or missed lab draws. On your advice, they decide to investigate barcode technology as a method to increase the safety of the laboratory specimen identification process in their office lab.
Both RCA and FMEA are powerful quality improvement tools that can assist teams in understanding errors and implementing improvement actions.
RCA looks to past errors for answers, while FMEA anticipates error.
RCA asks the questions: how, why, and who; FMEA asks: what if?
RCA is predominantly a retrospective dissecting of events that have occurred, while FMEA is a prospective, proactive anticipation of error that could occur in the future.
RCA looks for causes and contributors; FMEA looks for possible failure modes.
While RCA is subject to hindsight bias, this is not the case with FMEA.
Another area of interest at the intersection of HIT and patient safety is that of measurement. The National Quality Forum (NQF) led a project to develop a set of recommendations around the measurement of HIT-related safety issues. To accomplish this task, NQF:
Conducted an environmental scan of relevant HIT measures and measure concepts;
Convened a multi-stakeholder committee to guide and provide input on all phases of the project as well as engage NQF members and public stakeholders at key points throughout the project;
Developed a conceptual framework for HIT safety as a way to categorize measure concepts and gaps in measurement;
Identified challenges to the measurement of HIT-related safety events and adoption of best practices to strengthen measurement efforts; and
Identified and prioritized key measurement areas and potential measure concepts related to HIT safety.
In addition, the NQF convened a national HIT Safety Committee. Expert members of the committee identified nine key measurement areas for HIT safety, each of which include several measure concepts that could potentially reflect performance in that area, possible data sources or data collection strategies for each measurement topic, as well as the entities that could potentially be held accountable for performance in each area. The final list of key measurement areas is as follows:
Clinical decision support.
System interoperability.
Patient identification.
User-centered design and use of testing, evaluation, and simulation to promote safety across the HIT lifecycle.
System downtime (data availability).
Feedback and information sharing.
Use of HIT to facilitate timely and high-quality documentation.
Patient engagement.
HIT-focused risk management infrastructure.
Additional details on each measurement area are available in the full report, which was finalized in February 2016 and is available on the NQF website.
This concludes Lecture c of Learning From Mistakes: Error Reporting and Analysis and HIT.
In summary, we covered two quality improvement tools that can be used to detect and analyze HIT errors — the Root Cause Analysis and the Failure Modes and Effects Analysis.
We discussed the Root Cause Analysis as an effective QI tool that looks to the past for the cause of adverse events and seeks to prevent these causes from resurfacing in the future.
Failure Modes and Effects Analysis was presented as another equally effective QI tool that uses a different approach; it anticipates adverse events, conducts a hazard analysis, and looks to the future to prevent failure modes with the highest criticality.
We did a deeper dive into some of the dimensions of these two analytic methods — discussing the concept of a hazards analysis and aspects of flowcharting. We made the point that the ability to construct and use flow diagrams is an important skill for professionals involved in these processes. With an understanding of QI tools such as RCA and FMEA, health IT professionals can be key contributors to improvement efforts.