Tools and Methods

The jbara way
We love tools and methods.
We take great pride in choosing the right approach and tools to manage your organizational improvement projects. Successful project delivery depends on knowing when to apply the best tools to address the right questions. The way we manage a project is defined by techniques that we use, offering your organization practice-informed tools to make care safer and more reliable in your health care settings.
As health care consultants, we utilize many qualitative and quantitative methods that have been successfully applied in the scientific and social science disciplines. Our methods specifically focus on:
- Improving leadership and communications skills;
- Reducing errors and improving patient safety;
- Decreasing length of stay and treatment durations;
- Reducing costs and/or increasing revenue; and,
- increasing patient satisfaction

A Multi-Disciplinary Tool Kit
We address a wide range of topics of structure, processes, systems, and organization of health care services; their use and people’s access to services; efficiency and effectiveness of health care services; the quality of healthcare services and its relationship to health status; and, the optimal use of medical knowledge.
Our training and staff development includes a range of modalities from online annotated PowerPoints to more traditional in-person classroom instruction. The training is designed to match current participant knowledge and skill levels and it is delivered “just-in-time.”
The tools are applied in the framework of the DMAIC or PDSA problem solving models. Basically, problems are defined, teams are formed, data is collected and analyzed, improvements are suggested and tested, and progress is maintained.

our tool kit
Qualitative Tools
We define artefacts as the implements, notes, or materials that are used in the daily workflow of patient care. Artefact analysis is the study of these implements. Cognitive artefacts are man-made implements that seem to aid or enhance our cognitive abilities. Some examples include calendars, to-do lists, electronic mails, phone texts, phone messages, computer screen printouts, or simply tying a string around your finger as a reminder.
Cognitive artefacts are widely used in healthcare and include items such as an operating theatre whiteboard, end-of-shift sign-out sheet, surgery schedule or a written sign-out that are used as reminders of what needs to be completed for patient care. Study artefacts can help one better understand how clinicians perceive and actually do their work.
Ref: Johnson, J, Arora V, Barach P. What can artefact analysis tell us about patient transitions between the hospital and primary care? Lessons from the HANDOVER project. European Journal of General Practice, 2013; 19: 185–193.
The Aristotle risk assessment scoring system stratifies patient risk based on the potential for morbidity, mortality and the anticipated technical difficulty of a given procedure. Assessing quality of care by assigning surgical operations a risk score or grouping operations of similar risk into categories. The Aristotle Basic Complexity (ABC) score methodologic details of developed the ABC score. The score includes potential for mortality, potential for morbidity, and technical difficulty for each operation contribute up to 5 points each to this continuous score (range 1.5 to 15). The score was used by its authors to group the procedures as follows: level 1, scores 1.5 to 5.9; level 2, scores 6 to 7.9; level 3, scores 8 to 9.9; and level 4, scores 10 to 15.
Ref: Karamichalis J, Barach P, Henaine R, Nido del P. Bacha E. Assessment of Surgical Competency in Pediatric cardiac surgery. Progress in Pediatric Cardiology – January 2012;Vol. 33; 1 15-20, DOI: 20110.1016/j.ppedcard.2011.12.003.
Barach, P., Johnson, J., Ahmed, A., Galvan, C., Bognar, A., Duncan, R., Starr, J., Bacha, E. Intraoperative Adverse Events and their impact on Pediatric Cardiac Surgery: A Prospective Observational Study. Journal of Thoracic and Cardiovascular Surgery 2008 Dec; 136 (6): 1422-1428.
Cognitive task analysis (CTA) is used to explore complex decision making in healthcare. Cognitive task analysis focuses on the operator’s mental representation of the knowledge and skills required to perform tasks and is also a tool for exploring how operators’ cognitive processes come into play during task performance. Probes are used to explore cues, goals, strategies, and information needs during each step of the work action being studied.
Ref: Militello L, Gordon H, Flanagan M, Rattray N, Frankel R, Rehman S, Franks Z, Barach P. “Workin’ on Our Night Moves”: How residents prepare for shift handoffs. The Joint Commission Journal on Quality and Patient Safety, 2018, https://doi.org/10.1016/j.jcjq.2018.02.005
Rattray N, Militello L, Gordon H, Flanagan M,, Barach P Frankel R, Rehman S, Franks Z. Content Counts, but the Context Makes a Difference in Developing Expertise: A Qualitative Study of How Residents Learn End of Shift Handoffs. BMC Medial Educat, 2018.doi.org/10.1186/s12909-018-1350-8.
Aviation distinguishes between ‘normal’, ‘non-normal’ and ‘emergency’ checklists. ‘Normal’ checklists are used as part of standard operating procedures. They include lists used for preparation of a flight or technical checks by maintenance staff. Emergency’ checklists deal with uncommon, and unexpected crisis situations likely to have catastrophic outcomes.
Ref: Subbe, C, Kellet J, Barach P. et al. Crisis checklists for in-hospital emergencies: expert consensus, simulation testing and recommendations for a template determined by a multi-institutional and multi- disciplinary learning collaborative. BMC Health Services Research (2017) 17:334 DOI 10.1186/s12913-017-2288-y.
Ethnography is a qualitative research study looking at the social interaction of users in a given environment. This research provides an in-depth insight into the user’s views and actions along with the sights and sounds they encounter during their day. It provides the researcher with an understanding of how those users see the world and how they interact with everything around them.
Ethnography methods include direct observation, diary studies, video recordings, photography and artefact analysis such as devices that a person uses throughout the day. Observations can be made anywhere from the user’s workplace, their home or while they are out with family and friends. The length of the studies can vary depending on the research that is being conducted. They can range from a couple of hours of observation, to studies that last several months.
Ethnographic studies are a good way to really understand your users and the challenges they may face while going about their everyday lives. The research will give you insights to your users that you may not have seen if they were in a lab being asked to complete a task.
Ref: Schraagen JM, Schouten A, Smit M, van der Beek D, Van de Ven J. Barach P. Improving methods for studying teamwork in cardiac surgery. Qual Saf Health Care 2010;19:1-6 doi:10.1136/qshc.2009.040105
Barach, P., Johnson, J., Ahmed, A., Galvan, C., Bognar, A., Duncan, R., Starr, J., Bacha, E. Intraoperative Adverse Events and their impact on Pediatric Cardiac Surgery: A Prospective Observational Study. Journal of Thoracic and Cardiovascular Surgery 2008 Dec; 136 (6): 1422-1428.
Galvan, C., Bacha, B., Mohr, J., Barach, P. A Human Factors Approach to Understanding Patient Safety during Pediatric Cardiac Surgery. Progress in Pediatric Cardiology 2005;20:13– 20.
GCM is an integrated mixed method, including both qualitative and quantitative measures. It uses a structured approach to identify an expert group’s understanding about the types, methods and characteristics of healthcare work and
Multivariate statistical techniques of multidimensional scaling and hierarchical cluster analysis (HCA) are used to translate complex qualitative data into conceptual maps. A group concept map shows all the specific ideas about a particular topic (eg, handover educational interventions). The map also indicates how ideas are related to other ideas. In addition, the map indicates how much emphasis should be placed on a particular idea or cluster relative to other ideas (eg, how relatively important or feasible to implement a given intervention is, vis-a-vis other proposed approaches).
Ref: Stoyanov S, Bouschizen E, Groene O, M, W Hendrick H, Barach P. Mapping handover educational interventions. British Medical Journal Quality and Safety, 10.1136/bmjqs-2012-001169.
The method of Human Reliability Analysis aims to identify and surface the potential failures of the system resulting from human errors, analyze causes and identify appropriate countermeasures to prevent and reduce the linked risk and resultant patient harm. These methods are well-accepted and integrated into the safety management process in most industries. These methods allow the investigation of medical error and patient harm and to develop the applications of these methods to the problem of adverse reactions to treatment and other associated risks in healthcare.
Ref: Barach P, Levashenko V, Zaitseva E. Application of Fuzzy Decision Trees in Medical Decision-Making Support Systems, Human Factors and Ergonomics Society, March 21-24, Chicago, 2019.
The Influence Diagram demonstrates how the interplay of some of the issues associated with human characteristics and work context, and help explore the factors that can contribute to the tendency for a false assumption by providers. The arrows in this diagram represent influences, these diagrams are often referred to as influence diagrams, which represent a type of modeling framework. Similarly, influence diagrams could also be constructed to model omissions in the communication of patient information during sign-out reporting (for example, stemming from interruptions during work activities).
Ref: Sharit J, McCane L, Thevenin DM, Barach P. Examining Links Between Sign-Out Reporting During Shift Changeovers and Patient Management Risks. Risk Anal. 2008;28(4):983-1001.
IM is a systematic, iterative six-step process that helps to develop an intervention, based on theoretical, empirical and practical information
Step 1: Problem analysis
Structure the problem analysis by using the PRECEDE PROCEED model to analyse and describe the scale, causes, and consequences of the health problem and to identify the target population.
Step 2: Identify intervention outcomes, performance objectives and change objectives
Identify the desired outcomes of the intervention and formulated specific performance objectives for the target population, such as writing a complete, accurate and timely discharge letter by the hospital physician.
It is important to identify what steps need to be tweaked in order to affect the performance objective, and ultimately the intervention outcome. We identified the most important determinants (e.g., lack of knowledge and understanding between hospital and primary care providers) that need to be changed and combined these with performance objectives to formulate our change objectives. These change objectives specified who and what will change as a result of the intervention.
Step 3: Selection of theory-based methods and strategies
Selecte theory-based methods that relate to the change objectives in step 2. These methods are required to change the behavioural and environmental determinants of ineffective hospital discharge. Subsequently, these methods were translated into practical strategies.
Step 4: Develop an intervention
Provide suggestions for the design of the intervention by considering the target group and local setting.
Steps 5 and 6: Implementation and Evaluation
Make suggestions for developing an implementation plan for accomplishing program adoption, and for evaluating the effects and feasibility of the intervention program. The suggestions were based on literature regarding effective implementation strategies, existing implementation toolboxes, and a literature review on methods to evaluate complex interventions in health care.
Ref: Hesselink G, Zegers M, Vernooij-Dassen M, Barach P, et al: European HANDOVER Research Collaborative. Improving patient discharge and reducing hospital readmissions by using Intervention Mapping. BMC Health Services Research 2014 Sep 13;14:389. doi: 10.1186/1472-6963-14-389.
Ref: Johnson, Barach P, Vernooij-Dassen, M, Conducting a multicenter and multinational qualitative study on patient transitions, BMJ Qual & Safety 2012;0:1–7. doi:10.1136/bmjqs-2012-001197.
Sharit J, McCane L, Thevenin DM, Barach P. Examining Links Between Sign-Out Reporting During Shift Changeovers and Patient Management Risks. Risk Anal. 2008;28(4):983-1001.
The clinical Microsystems is centered around the needs of the patient and provides a service. To succeed, the microsystem must: (1) do the work; (2) meet both patient and staff needs; and, (3) maintain themselves as a functioning clinical unit.
The clinical microsystem, as an organizational construct, is a systems approach for
providing healthcare based on theories from organizational development, leadership,
and improvement. The success characteristics reflect what people working in high-performing practices say about their work and how they go about achieving their work. The characteristics of a clinical microsystem are summarized below. The MAT Survey tool assesses all critical aspects of the processes with targeted questions and with open-ended questions.
Ref:
Göbel B, Zwart D, Hesselink G, Pijnenborg L, Barach P, Kalkman C, Johnson JK. Stakeholder perspectives on handovers between hospital staff and general practitioners: an evaluation through the microsystems lens. BMJ Qual Saf. 2012 Dec;21 Suppl 1:i106-13. doi: 10.1136/bmjqs-2012-001192. Epub 2012 Nov 1.
Mohr, J., Barach, P., Cravero, J., Blike, G., Godfrey, M., Batalden, P., & Nelson, E. Microsystems in Health Care. Joint Commission Journal on Quality and Safety 2003;29:401-408.
A process map or flowchart is a visual representation of the care process that is created with information provided by team members. The process mapping exercise can help clinicians clarify through visualization what they know about their environment and determine what they want to improve about it. The process maps use common flowchart symbols and can describe the current state or baseline, the improved state in transition, and the optimal state. The exercise helps clinicians make assumptions and expectations explicit and can provide insights into reflecting on their current state and, importantly, into how to improve the process of care or
to overcome barriers they perceive to its improvement. Visualizing the process can also help identify inefficiencies (e.g., parallel or redundant processes that have emerged for whatever reason), clarify roles, and reduce ambiguity among team members, all of which can help coordinate patient care.
Ref:
Johnson J, Barach P. Tools and Strategies for Continuous Quality Improvement and Patient Safety. In Sanchez J, Barach P, Johnson H, Jacobs J (eds.). Perioperative Patient Safety and Quality: Principles and Practice, Springer, 2017, ISBN 978-3-319-44010-1.
Ref: Barach, P., Johnson, J., Ahmed, A., Galvan, C., Bognar, A., Duncan, R., Starr, J., Bacha, E. Intraoperative Adverse Events and their impact on Pediatric Cardiac Surgery: A Prospective Observational Study. Journal of Thoracic and Cardiovascular Surgery 2008 Dec; 136 (6): 1422-1428
Root cause analysis (RCA) is a systematic process for identifying “root causes” of problems or events and an approach for responding to them. RCA is based on the basic idea that effective management requires more than merely “putting out fires” for problems that develop, but finding a way to prevent them.
A root cause is defined as a factor that caused a nonconformance and should be permanently eliminated through process improvement. The root cause is the core issue—the highest-level cause—that sets in motion the entire cause-and-effect reaction that ultimately leads to the problem(s).
Root cause analysis (RCA) is defined as a collective term that describes a wide range of approaches, tools, and techniques used to uncover causes of problems. Some RCA approaches are geared more toward identifying true root causes than others, some are more general problem-solving techniques, and others simply offer support for the core activity of root cause analysis.
APPROACHES TO ROOT CAUSE ANALYSIS
There are many methodologies, approaches, and techniques for conducting root cause analysis, including:
- Events and causal factor analysis:Widely used for major, single-event problems, such as a refinery explosion, this process uses evidence gathered quickly and methodically to establish a timeline for the activities leading up to the accident. Once the timeline has been established, the causal and contributing factors can be identified.
- Change analysis:This approach is applicable to situations where a system’s performance has shifted significantly. It explores changes made in people, equipment, information, and more that may have contributed to the change in performance.
- Barrier analysis:This technique focuses on what controls are in place in the process to either prevent or detect a problem, and which might have failed.
- Management oversight and risk tree analysis:One aspect of this approach is the use of a tree diagram to look at what occurred and why it might have occurred.
- Kepner-Tregoe Problem Solving and Decision Making:This model provides four distinct phases for resolving problems:
- Situation analysis
- Problem analysis
- Solution analysis
- Potential problem analysis
Ref:
Cassin B, Barach P. Making sense of root cause analysis investigations of surgery-related adverse events. Surg Clin North Am. 2012;92:101-15.
Culture can be defined as the collection of individual and group values, attitudes, and practices that guide the behavior of group members. Characteristics of a strong safety culture include a commitment to discuss and learn from errors, recognition of the inevitability of errors, proactive identification of latent threats, and incorporating nonpunitive systems for reporting and analyzing adverse events. Studies of safety culture have focused mainly on discovering deficits in organization, communications, or personal skills.
We designed a Questionnaire based on scaled questions e taken from validated studies to explore areas of known importance described in the safety culture literature. In addition, new areas were described, and scaled questions were formulated based on the clinical experience of our research team members. A clinical scenario and a set of open-ended questions were added to the scaled questions to increase the validity and interpretability of the study.
Ref: Bognar A, Barach P, Johnson J, Duncan R. Woods D, Holl J, Birnbach D, Bacha E. Errors and the Burden of Errors: Attitudes, Perceptions and the Culture of Safety in Pediatric Cardiac Surgical Teams. Ann Thoracic Surgery 2008;(4);1374-1381.
A scoping literature review can be used to identify the gaps in research. Scoping reviews are a traceable method of ‘mapping’ areas of research and highlighting gaps in the literature for future research. Scoping reviews are a useful tool to identify gaps in evidence synthesis approaches and require rigorous and transparent methods to ensure that the results are trustworthy. This methodology summarizes the evidence available on a topic in order to convey the breadth and depth of that topic by mapping the existing literature in a field of interest in terms of the volume, nature and characteristics of the primary research and identify gaps in the existing literature.
Ref:
Subbe C, Barach P. Impact of Electronic Health Records on Pre-defined Safety Outcomes in Patients Admitted to Hospital. A Scoping Review, BMJ Open, 2021;11:e047446. doi:10.1136/bmjopen-2020-047446
The pre-surgial miniSTAR consisted of the following questions:
- Did you receive, in your opinion, sufficient information about the child scheduled for the operation?
- Did you sleep well last night?
- Are you troubled or distracted by any physical or mental stress that could possibly affect your performance during the operation?
- Are you concerned about the performance of other team members during this operation?
The scores of the four questions were collapsed into one score, with a minimum of 0 (indicating optimal preparation) and a maximum of 7 (indicating serious concerns about team preparedness and readiness).
The post-operation miniSTAR was completed immediately after the operation. It consisted of the following questions:
- Did you do anything that should not have been done or done differently, even though this may not at all have led to patient harm?
- Did you notice that other team members did something that had better not been done or done differently, even though this may not at all have led to patient harm?
- Did you notice that you or others had done anything that should not have been done or done differently, and which has occurred before?
- Was the operation carried out in a pleasant and harmonious atmosphere?
- Did you notice any conflicts among team members and how were they resolved?
Ref: Schraagen JM, Schouten A, Smit M, van der Beek D, Van de Ven J. Barach P. A prospective study of paediatric cardiac surgical microsystems: assessing the relationships between non-routine events, teamwork and patient outcomes. BMJ Qual Saf 2011. doi:10.1136/ bmjqs .2010.048983.
Non technical skills (NTS) encompass a range of competencies, including communication, teamwork, leadership, decision making, situational awareness, managing stress, and coping with fatigue. In contrast to methods of evaluating technical skills, the assessment of NTS almost exclusively relies on rating scales and checklists that include specific definitions and examples of behaviors representing superior or substandard performance at each measured NTS.
These tools can be used in both the simulated and actual clinical environment, and rely on direct observation of subjects. Several instruments have been created to evaluate NTS with considerable overlap, demonstrating the importance of some of these competencies to a number of academic surgical teams. Some of these instruments are discussed below.
To achieve high reliability and consistent performance, each team member must be able to (1) anticipate the needs of the others; (2) adjust to each other’s actions and to the changing environment; (3) monitor each other’s activities and distribute workload dynamically; and (4) have a shared understanding of accepted processes, and how events and actions should proceed (shared mental model).
Ref: Schraagen JM, Schouten T Barach P. Assessing and improving teamwork in cardiac surgery. Qual Saf Health Care. 2010;19:e29.
Baker, D. Battles J, King H, Salas, E., Barach, P. The Role of Teamwork in the Professional Education of Physicians: Current Status and Assessment Recommendations. Joint Commission Journal on Quality and Safety 2005; 31:4:185-202.
Schraagen JM, Schouten A, Smit M, van der Beek D, Van de Ven J. Barach P. A prospective study of paediatric cardiac surgical microsystems: assessing the relationships between non-routine events, teamwork and patient outcomes. BMJ Qual Saf 2011. doi:10.1136/ bmjqs 2010.048983.
The Electronic Team Survey (ETS) is designed to collect information about the roleof the patient and the culture of reporting that might influence team members’ dailywork and subsequent outcomes. It is a mixed methods survey, combining qualitative and quantitative methods.
The first section of the ETS asks participants to: “Briefly describe ONE event from today that stands out in your mind from your work related to patients. Describe your feelings about this work, your experience of this work, or your team’s experience of this work. The event you describe can be positive, negative, or neutral.”
The ETS gives participants the opportunity to reflect, in real time, on their role in creating value, and upon the work culture process by which safety is created or undermined.
High-reliability organizational theory posits that organizational features including psychological safety, leadership involvement and a relentless culture of quality measurement are needed to sustain reliable improvements in care. We defined the work system to include the persons,
organization, tools and technologies, tasks and their work environment. Work environment is the physical and organizational culture under which healthcare professionals perform their tasks.
Ref: Brubakk K, Svendsen MV, Hofoss D, Barach P, Tjomsland O. Associations between work satisfaction, engagement and 7-day patient mortality: a cross-sectional survey. BMJ Open 2019;9:e031704. doi:10.1136/
Quantitative Tools
The nuclear power industry calls near misses “accident precursors”. This analysis proceeds prospectively, in a direction opposite to that of root cause analysis. Given the precursor, the analysis identifies the events that prevented the precursor from leading to an undesirable consequence. This is achieved by “mapping” the event onto the event and fault trees of the plant’s probabilistic risk assessment (PRA) model. The purpose of the accident sequence precursor (ASP) analysis is to determine how close the precursor came to being an accident with undesirable consequences. Human recovery-the ability of operators to detect, localize, and correct system faults caused by either human error or technical failure-is critical to understanding how to improve both systems and training perspectives.
The three primary steps of precursor analysis are as follows. After a precursor event occurs, the first step is to gather relevant information about the event. The information that is gathered includes items such as what components failed, which human actions were in error, what was the chronology of events, and what were the complicating factors. Then, after the information-gathering step, one maps the event onto the PRA model, that is, onto the event and fault trees that depict the potential accident sequences.
Ref: Apostolakis, G. Barach, P. Lessons learned from nuclear power. Patient Safety, International Textbook, Hatlie, M. & Tavill, K. (Eds), Aspen Publications, pp. 205-225, 2003
A Bayesian approach is characterized as a means of rational learning from experience in the face of uncertainty, and since advances in healthcare typically happen through incremental gains in knowledge rather than paradigm-shifting breakthroughs, this domain appears particularly amenable to a Bayesian perspective. This approach acknowledges that judgments about the benefits for example of a new technology will rarely be based solely on the results of a single study but should synthesize evidence from multiple sources—for example, pilot studies, trials of similar interventions, and even subjective judgments about the generalizability of the study’s results. A Bayesian perspective leads to an approach to clinical trials that is claimed to be more flexible and ethical than traditional methods,1 and to elegant ways of handling multiple substudies—for example, when simultaneously estimating the effects of a treatment on many subgroups. Proponents have also argued that a Bayesian approach allows conclusions to be provided in a form that is most suitable for decisions specific to patients and decisions affecting public policy.
Ref: Lilford R, Chilton PJ, Hemming K, Brown C, Girling A, Barach P. Evaluating policy and service interventions: framework to guide selection and interpretation of study end points. BMJ 2010; 341:c4413.
A Failure mode and effects analysis (FMEA) is a very popular Lean Six Sigma method for identifying likely breakdowns in processes or work systems and developing strategies to mitigate risks. Failure mode and effects analysis (FMEA) is a method for engaging local staff in identifying real or potential breakdowns in processes or work systems and to develop strategies to mitigate risks that can impact clinical performance.
FMEA includes reviewing of the following:
- Steps in the process
- Failure modes (What could go wrong?)
- Failure causes (Why would the failure happen?)
- Failure effects (What would be the consequences of each failure?)
It is often applied after waste analysis because it can help identify and prioritize the most serious potential “failures.” Not every non-value-added activity needs to be remediated.
A session facilitator will map the group discussion graphically for using a FMEA form is used to first list the process steps and the failures. Each step can have multiple failures. Then staff must identify the effects or negative results such as delays, extra costs and dis-satisfied patients). Next you must identify the causes and existing process controls. These can be gauges on equipment, inspections or reviews of metrics.
In Summary, the steps are:
- Identification of process problems or breakdowns that contribute to failure to achieve the desired outcome.
- Develop interventions to directly mitigate those potential breakdowns/ failures.
- We will be looking at a Simplified FMEA. You could also collect data to identify the frequency and level of importance of each problem.
The assessment of risk involves the ratings of failure severity, frequency of occurrence, and the likelihood of detection of the failure. The staff subject matter experts on the team rate each of these items to calculate the Risk Priority Number (RPN). The higher the number; the greater the risk. The priority failures can lead to counter measures or improvement projects.
Ref: Popovich, E, Wiggins, H, Barach P. The Patient Flow Physics Framework. In: Sollecito, W and Johnson, J (eds). Continuous Quality Improvement in Health Care: Theory, Implementations, and Applications. pp.143-174, 5th edition. Jones and Bartlett, 2019, ISBN 978-1-284-12695-4.
Fault tree analysis (FTA) is one type of PRA. Fault trees begin with a careful description of a system—i.e., its components, its intended and unintended modes of operation. Unlike some PRAs, however, this method generates a mathematical model. This model represents the probability of an adverse event as a function of the probabilities of basic events. For example, in this study we tested whether it is feasible to apply fault tree models to explain and predict preventable adverse events in medicine.
Ref: Wilwerding, J., White, A., Apostolakis, G., Barach, P., Fillipo, B., & Graham, L. Modeling Techniques and Patient Safety. In, Spitzer C, Schmocker U, Dang, VN (ed.) Probabilistic Safety Assessment and Management 2004. Berlin, Springer 2004, vol. 4.
Human factors engineering is the application of knowledge about human behaviour, abilities,
limitations, and other characteristics of medical device users to the design of medical
devices/drugs including mechanical and software-driven user interfaces, systems, tasks, user
documentation, and user training to enhance and demonstrate safe and effective use. The
operating room is a complex technical environment in which highly trained sub-specialists
interact with each other using sophisticated equipment to care for patients with a wide range
of diseases and significant co-morbidities. Clinicians work under human factor
constraints in complex, technology-infused, rapidly changing, time-constrained, and stressful
work environments where effective performance demands expert knowledge, appropriate
problem-solving strategies, and fine motor skills.
Ref: Galvan, C., Bacha, B., Mohr, J., Barach, P. A Human Factors Approach to Understanding Patient Safety during Pediatric Cardiac Surgery. Progress in Pediatric Cardiology 2005;20:13– 20.
Jensen, P.F., Barach, P. The Role of Human Factors in the Intensive Care Unit. Quality Safety Health Care 2003;12(2):147-148.
McNeer, R, Bohorquez, J, Varon, A, Ozdamar, O, Barach, P. Human Factors Engineering of Urgency-Encoded Audible Alarm Signals, Journal of Clinical Monitoring and Computing. J Clin Monit Comput 2007; 21(6): 353-63.
Wang A; Ahmed, R; Ray J; Hughes P; Eric McCoy E; Marc A. Auerbach, A, Barach P. Supporting the Quadruple Aim Using Simulation and Human Factors During COVID-19 Care. American Journal of Quality, AJMQ-20-289.R1. Accepted, Dec 30, 2020.
Probabilistic risk assessment is an engineering tool developed in the 1970s to quantify risks and identify threats to the safety of nuclear power plants. Subsequently, it has been applied in settings ranging from aerospace to manufacturing to natural disasters. PRA is a systematic tool that prospectively identifies a system’s risk points. It utilizes quantitative and qualitative data to “map” the risks associated with adverse outcomes. PRA is thus a hybrid between qualitative process analysis techniques and quantitative decision-support models. PRA involves a detailed deductive method that utilizes logical relationships and probability theory to construct a model (“fault tree”) of how risk points interact with one another and either individually or collectively combine to contribute to the adverse outcome. Once specific target risks are identified, intervention strategies can be identified or designed using a risk-informed approach to design of intervention strategies.
Ref: Jonathan Wilwerding, Ph.D., Alan White, Ph.D., Austin Frakt, Ph.D., Donna Hurd, R.N. Laura Graham, Paul Barach, MD, MPH. Probabilistic Risk Assessment and Medical Errors Associated with Transitions of Care, Modeling Techniques for Transitions of Care in Integrated Delivery Systems, AHRQ, 2004 Contract # 290-00-0003.
This process and tool assesses the current maintenance and reliability practices and processes and compares against internal perceptions and industry best practices. It also facilitates the development of recommendations to improve performance. The outcome of performing a Reliability Maturity Assessment is an action plan with recommendations to close identified gaps and proposed solutions that will help to deliver value in the short, medium, and long term.
The goal is to establish what is actually happening on-site as opposed to what should be happening. The audit process determines the current state from analysis of data, conducting interviews, and mapping work flows. The emphasis is on analyzing what are the driving elements for performing work, what barriers exist in preventing continuous improvement, and what extent risk and reliability is taken into account in the management process. These elements are compared to best practice, their interaction is mapped, and the benefits to closing the gap is estimated. A plan to close the gap by developing a road map for improvements is the final step in completing the assessment.
Ref: The more I know, the less I sleep, Global perspectives on clinical governance. Lead author Marc Berg, Paul Barach co-author, KPMG Global Health Practice. 2013.
Ref: Sanchez J, Barach P. High Reliability Organizations and Surgical Microsystems: Re-engineering Surgical Care. Surgical Clinics of North America, 02/2012; 92(1):1-14DOI: 10.1016/j.suc.2011.12.005
Two of the most powerful CQI tools are run charts and control charts. These tools are valuable for analyzing variability in clinical processes. The run chart is a simple plot of a measurement over time with a line drawn at the median value. The data can be related to patients, organizations, or clinical units. Run charts are particularly useful because they can reveal subtle changes over time that would otherwise go noticed. A run chart is a graphic representation of process performance data tracked over time and represents continuous data. Important uses of the run chart for improvement are to:
- Display data to make process performance visible
- Determine whether tested changes improve the process or endpoints
- Determine whether the changes are lasting
- Allow for a temporal view of data versus a static view
Statistical process control (SPC) methods have the potential to complement traditional feedback by facilitating data interpretation and improving reaction times. By combining time series, statistical and graphical analysis of data in near real time, control charts help determine whether data exhibit natural (eg, within probabilistic thresholds) versus unnatural (eg, statistically significant increase or decrease) variation.
Ref:
Popovich, E, Wiggins, H, Barach P. The Patient Flow Physics Framework. In: Sollecito, W and Johnson, J (eds). Continuous Quality Improvement in Health Care: Theory, Implementations, and Applications. pp.143-174, 5th edition. Jones and Bartlett, 2019, ISBN 978-1-284-12695-4.
Johnson J, Barach P. Quality improvement methods to study and improve the process and outcomes of pediatric cardiac surgery. Prog Pediatr Cardiol. 2011;32(2):147–53.
We use autoregressive integrated moving average (ARIMA) time series intervention models to evaluate the effects of the changes due to public policies such as assessing the impact from raising speed limits on fatalities, serious injuries, or the impact of new infection control efforts on the rate of surgical infections.
ARIMA models are more appropriate for describing the effect of policy changes when using time series data rather than linear regression models or simple before and after comparisons.
These models are fitted to time series data either to better understand the data or to predict future points in the series.
Ref:
Ben Micheal, E , Barach, P., Richter E. Increase Speed Limits, Case Fatality and Road Deaths in Israel: A Time Series Analysis. Injury Prevention, 2007;13:156-161.
Lean Six-Sigma Tools
Ishikawa diagrams, also known as “cause-and effect diagrams,” “fishbone diagrams,” and “root- cause analyses,” are visual representations of the sources of variation in a process. The diagram is often created by brainstorming with key stakeholders to identify the causes of the effects of a process. The causes are generally allocated to five general main headers/categories: place (environment), equipment, procedures and methods (processes), people (patients and providers), and policies. Routine root cause analysis with Ishikawa diagrams can be very powerful in analyzing surgical adverse events. These diagrams help identify potential improvements and which improvements might be transferable to another
setting.
Ref: Warm E, Ahmad Y, Benjamin Kinnear B, Kelleher M, Sall D, Wells A, Barach P. A Dynamic Risk Management Approach for Reducing Harm from Invasive Bedside Procedures for Internal Medicine Residency Programs, accepted Academic Medicine, Dec 7, 2020, AcadMed-D-20-00684R2
Pareto Analysis is a statistical technique in decision-making used for the selection of a limited number of tasks that produce significant overall effect. It uses the Pareto Principle (also known as the 80/20 rule) the idea that by doing 20% of the work you can generate 80% of the benefit of doing the entire job.
WHEN TO USE A PARETO CHART
- When analyzing data about the frequency of problems or causes in a process
- When there are many problems or causes and you want to focus on the most significant
- When analyzing broad causes by looking at their specific components
- When communicating with others about your data
PARETO CHART PROCEDURE
- Decide what categories you will use to group items.
- Decide what measurement is appropriate. Common measurements are frequency, quantity, cost and time.
- Decide what period of time the Pareto chart will cover: One work cycle? One full day? A week?
- Collect the data, recording the category each time, or assemble data that already exist.
- Subtotal the measurements for each category.
- Determine the appropriate scale for the measurements you have collected. The maximum value will be the largest subtotal from step 5. (If you will do optional steps 8 and 9 below, the maximum value will be the sum of all subtotals from step 5.) Mark the scale on the left side of the chart.
- Construct and label bars for each category. Place the tallest at the far left, then the next tallest to its right, and so on. If there are many categories with small measurements, they can be grouped as “other.”
Note: Steps 8 and 9 are optional but are useful for analysis and communication.
- Calculate the percentage for each category: the subtotal for that category divided by the total for all categories. Draw a right vertical axis and label it with percentages. Be sure the two scales match. For example, the left measurement that corresponds to one-half should be exactly opposite 50% on the right scale.
- Calculate and draw cumulative sums: add the subtotals for the first and second categories, and place a dot above the second bar indicating that sum. To that sum add the subtotal for the third category, and place a dot above the third bar for that new sum. Continue the process for all the bars. Connect the dots, starting at the top of the first bar. The last dot should reach 100% on the right scale.
Ref: Popovich, E, Wiggins, H, Barach P. The Patient Flow Physics Framework. In: Sollecito, W and Johnson, J (eds). Continuous Quality Improvement in Health Care: Theory, Implementations, and Applications. pp.143-174, 5th edition. Jones and Bartlett, 2019, ISBN 978-1-284-12695-4.
There is nothing more exciting than gathering a group of people together to discuss improvement ideas, especially in a company that is maturing through the Lean Journey and team engagement is spreading. One of the challenges often faced early on is how we decide on the “right” improvement ideas to focus on?
We have found using a PICK chart is a great way to encourage team discussion and provide timely feedback to the team as to how the group views their ideas, how easy they are to implement, and their likely impact once they are implemented. There is nothing more discouraging to a team than offering suggestions through a “Suggestion Scheme” and never hearing any thing about your idea or seeing it completed. Utilising a PICK chart makes feedback timely and reduces the management burden of sifting through ideas.
What is a PICK Chart?
The PICK chart is borrowed from the Lean Six Sigma set of tools and is used to categorise process improvement ideas generated by a work group. This could happen at any stage while implementing the Lean Enterprise tools. The purpose of the chart is to help classify the ideas into useful sectors. A standard 2×2 grid is designed.
The two axes are labelled “Difficulty”, ranging from easy to hard, and “Payoff”, which ranges from low to high. Difficulty describes how easy or difficult the improvement idea is to implement and is based on the knowledge within the group. Payoff refers to the benefit or opportunity once the idea is implemented, and, again, is based on the knowledge of the team. If an idea is too far outside of the current knowledge, add a question mark on the Post-it note as a reminder that more information is required.
Each quadrant of a PICK chart labelled as Possible, Implement, Challenge and Kill (PICK), where:
- Possible includes the ideas that are easy to implement and with a low payoff
- Implement for projects that are easy to implement, with a potential high payoff
- Challenge, which includes projects with technology that is new to the company and may be hard to implement. However the payoff can be high
- Kill that eliminates ideas that are hard to implement and with a low return
PICK charts are a method to prioritize a number of action items or problem solving ideas. A pick chart allows visual comparison of action items relative to their impact to the problem being addressed vs. the ease/cost of implementation. In VERY rudimentary terms, PICK charts are a Return On Investment (ROI) method.
When faced with multiple improvement ideas a PICK chart may be used to determine the most useful. There are four categories on a 2*2 matrix; horizontal is scale of payoff (or benefits), vertical is ease of implementation. By deciding where an idea falls on the pick chart four proposed project actions are provided; Possible, Implement,
The vertical axis, representing ease of implementation would typically include some assessment of cost to implement as well. More expensive actions can be said to be more difficult to implement.
Quality function deployment combines quality assurance and quality control with function deployment in value engineering. Quality function deployment helps to focus improvement efforts on the customer’s needs by attending to and respecting the voice of the customer (VOC) and by translating these needs into design and engineering characteristics for a product or service. QFD is a process of developing customer needs into actionable responses.
Ref: Omachonu V, Barach, P. Quality Function Development (QFD) in a Managed Care Organization. Quality Progress, 2005: 36-41.
Culture can be defined as the collection of individual and group values, attitudes, and practices that guide the behavior of group members. Characteristics of a strong safety culture include a commitment to discuss and learn from errors, recognition of the inevitability of errors, proactive identification of latent threats, and incorporating nonpunitive systems for reporting and analyzing adverse events. Studies of safety culture have focused mainly on discovering deficits in organization, communications, or personal skills.
We designed a Questionnaire based on scaled questions e taken from validated studies to explore areas of known importance described in the safety culture literature. In addition, new areas were described, and scaled questions were formulated based on the clinical experience of our research team members. A clinical scenario and a set of open-ended questions were added to the scaled questions to increase the validity and interpretability of the study.
Ref: Bognar A, Barach P, Johnson J, Duncan R. Woods D, Holl J, Birnbach D, Bacha E. Errors and the Burden of Errors: Attitudes, Perceptions and the Culture of Safety in Pediatric Cardiac Surgical Teams. Ann Thoracic Surgery 2008;(4);1374-1381.
We use Lean Six Sigma (LSS) frameworks, which is a quality improvement methodology described as a systematic approach to identifying and eliminating waste or non-value add activities in a process through continuous improvement. Lean Six Sigma is a data-driven process, the methodology of which is used to realize stable and predictable results, decreasing process variation and defects to desired levels.
The SIPOC-R is a high-level Lean Six Sigma (LSS) process mapping tool. Its name is an acronym for Suppliers, Inputs, Process Activities, Outputs, Customers, and Requirements. Early identification of all relevant stakeholders is facilitated through a Suppliers, Inputs, Process, Outputs and Customers (SIPOC) diagram. LSS methods place a strong emphasis on team-building tools, including the SIPOC, that help the team collaborate, engage and negotiate with a variety of disciplines. This provokes greater buy-in from staff to the initiative and helps to create sustainable change.
Teams that create this tool start by identifying several, general phases of a process including the beginning and ending boundaries, such as hospital admission and discharge. Then they identify the outputs and customers for each phase (e.g., H&P and patient). Next, they identify the suppliers and the inputs for each process phase. The internal customers (i.e., staff, clinicians) work in the process and they have specific requirements for the inputs. For example, do they arrive to the hospital on time, are the surgical equipment items readily available and reliable, and are they easy to use. The external customers can be the patients or other stakeholders (such as staff at the next process phase) that have an interest in the outputs. (services or products).
Ideally, only the most important inputs and outputs are identified, and customer requirements can be converted to metrics to help manage the process. The SIPOC-R phases can launch the more micro or detailed swimlane maps. The phases can be sub-divided into several more detailed steps.
Ref: Popovich, E, Wiggin, H, Barach P. Lean and Six Sigma Management: Building a Foundation for Optimal Patient Care Using Patient Flow Physics. In: Sollecito, W and Johnson, J (eds). Continuous Quality Improvement in Health Care: Theory, Implementations, and Applications. pp.143-174, 5th edition. Jones and Bartlett, 2019, ISBN 978-1-284-12695-4.
A swim lane map is similar to a flowchart in that it maps out a process, decisions, and loops; however, a swim lane map places events and actions in “lanes” to delineate a person/group responsible, or a specific subprocess. A swim lane map has three elements: time, people (or job functions), and tasks/processes.
It gets its name from the rows that are used to separate the patient and different types of staff that do the work. The maps contain beginning and end points, activity steps, decisions, and arrows for direction.
The activities can include things like the “nurse started an IV” or the “surgeon introduced herself to the patient.” Decisions always have a “yes or no” and an example could be “doctor discharges the patient.”
You can measure the total or cycle time of the whole process; the time, quality, and cost of each step; and, the space in between the steps. Those transitions or handoffs are important because it is easy to forget them.
Swimlane maps help us “see” and analyze the process and only the people who work in the process can identify the details.
How to Build a Swim Lane Map
Place your people, departments, or job functions in one column, and draw lanes next to each area. Start from the beginning, and document the process to the end:
Walk the Process
Questions to ask:
- Where does this information come from?
- Is the process completed with or without interruption?
- Do you ever miss information or have incorrect information?
- Where does the information go from here?
- Is there more than one place the information goes?
- Is there new information or is it being translated into another form?
- Characterize the Process
- What forms, screens, or programs does each step use?
- How long does each step take?
- Are there handoffs, where the task travels from one person to another? How does it happen?
- Is there consistently missing information, duplication, multiple locations for the same data, etc.?
- Where do you wait for someone to make a decision, or for information to be placed in (for example) an inbox?
- Does inspection/approval happen at any point(s) during the process?
- Are there points where you need to enter data for the sole purpose of making the business system work (AKA system requirements)?
Ref: Popovich, E, Wiggins, H, Barach P. The Patient Flow Physics Framework. In: Sollecito, W and Johnson, J (eds). Continuous Quality Improvement in Health Care: Theory, Implementations, and Applications. pp.143-174, 5th edition. Jones and Bartlett, 2019, ISBN 978-1-284-12695-4.
A Waste Analysis and Improvement Tool provides a systematic method for hospital frontline clinical staff, members of the financial team, and leaders to identify clinical and operational waste and subsequently prioritize and implement waste reduction initiatives that will result in cost savings for the organization. Process waste are the non-value-added activities or fail points that can severely diminish process efficiency and effectiveness. Waste will decrease “flow” or how quickly the process operates. Slow clinical processes can lead to bad patient outcomes. This waste needs to be identified and eliminated.
This Tool is designed to provide a snapshot of potential areas of waste within a hospital, as identified by frontline clinical staff. Once this snapshot is obtained, representatives of the hospital’s frontline clinical staff, finance department, and leadership engage in a process of enriched review and analysis of the findings to prioritize and implement waste reduction initiatives.
There are eight basic types of waste and they are: defects (errors), over-production, waiting (delays), not utilizing staff, long or in-effective transitions (hand-offs), excess or insufficient inventory, unnecessary movement/transportation, or extra processing.
Defects, delays and movement are the most prevalent kinds of waste, but the other types can also be found. An improvement team will systematically examine each step in the process to find these unwelcome fail points.
Hospitals can use the Waste Analysis and Improvement Tool as one key strategy in an ongoing process of identifying, assessing the impact of, and reducing waste by engaging both frontline staff and leadership. The tool may be adapted by Monument Health to maximize its effectiveness within their clinical environments.
Ref: Popovich, E, Wiggins, H, Barach P. The Patient Flow Physics Framework. In: Sollecito, W and Johnson, J (eds). Continuous Quality Improvement in Health Care: Theory, Implementations, and Applications. pp.143-174, 5th edition. Jones and Bartlett, 2019, ISBN 978-1-284-12695-4.