Welcome to another HiQuiPS post!
Our series has aimed to present foundational topics in Health informatics, Quality Improvement and Patient Safety in a practical manner. In this new section – Expert’s Corner, we ask an expert some important questions to deepen our understanding of these sciences and improve our implementation. For our inaugural Expert’s Corner post, we invited Dr. Kaveh Shojania.
Dr. Shojania is the Vice Chair (Quality & Innovation) in the Department of Medicine at the University of Toronto. He is an Editor-in-Chief Emeritus for the BMJ Quality & Safety Journal (where he led the Journal’s astronomical rise in impact factor), and has had instrumental contributions to the field.1 We asked Dr. Shojania a simple question that has so many complex answers:
In your experience, what are the most common pitfalls that teams experience when conducting a QI initiative?
Inattention to change management
Healthcare is a complex environment that encompasses many different moving pieces, interconnected systems and diverse competing interests. Given this complexity, it is important to ensure that all relevant stakeholders are identified and properly engaged.
The first step is to identify anyone who has a stake in either the process as it stands and/or after possible changes will be implemented. It is unfortunately too common to forget ancillary and support staff such as technicians, environmental services, porters, and most importantly, patients. Moreover, if the process in question will affect other departments or groups, they would also need to be engaged.
Second, it is important to understand the different stakeholders’ involvement and motivations. There are different approaches to engaging stakeholders. Common things to consider are:
- What are the stakeholders’ beliefs, attitudes and knowledge (including perceived barriers) about possible changes?
- How affected are they (positively or negatively) by possible changes?
- How much influence do they have on the system or possible changes?
In one local QI initiative, a new technology was implemented to help decrease exposure to infectious agents in the ED. Engagement of the team was relatively low, especially the nursing team, which comprised a large proportion of the stakeholders. After several iterations of feedback through nursing huddles and surveys, barriers to uptake became apparent and were addressed. Moreover, a local nurse champion was designated to further facilitate uptake, and this led to successful results.2
Rushing to a solution
One of the most common pitfalls is starting a QI initiative with a solution in mind, for example a checklist, a pop-up reminder on the EHR, or performance report cards. Rushing to a solution skips over the steps involved in identifying the causes of the target quality problem and the rationale for applying the supposed solution. It may lead to a waste of resources and time. Taking time to truly understand the problem is an essential step in the QI approach.
Things to consider before determining the best solution(s) are:
- How well do you understand all relevant steps in the system or process?
- Have you engaged the relevant stakeholders?
- Have you conducted a proper root cause analysis or similar exercise?
- Have you considered the hierarchy of effectiveness in tailoring the right solution for the problem?
One local example to illustrate this is a QI team that aimed to decrease low-risk chest pain patients’ length of stay (LOS) in the ED. At the first team meeting, the “solution” was presented to update the chest pain algorithm so that a repeat troponin test would be done at the two hour mark instead of the previous three, based on the new high troponin sensitivities. However, a process map and root cause analysis session with trainees, nurses, physicians, clinical biochemists identified the following actual problems, which typically account for greater than one hour delay per patient:
- Delays between ordering tests on the electronic system and printing of labels
- Delays between physician orders of repeat troponin testing and nurse blood draws
- Delays between when blood work is resulted and physician reassessment of patients
Implementing an updated algorithm may have only solved one part of the problem, with other delays not attended to. Before putting resources and time into a prematurely chosen solution, make sure to understand the problem and contributing factors well.
Undertaking inauthentic PDSA cycles
The concept of plan-do-study-act cycles is one of iterative change based on continuous learning. One main pitfall is implementing several interventions without the iterative process. The intended output of PDSA cycles is learning and informed action.3 Moving too quickly (or superficial learning) removes the potential impact of PDSA cycles. Moreover, core principles of PDSA cycles are not usually executed in practice, with lack of small-scale changes, quantitative data collection and clear iterative approaches.4
Each implementation phase has potential challenges:3
- Failure to understand the problem fully
- Failure to implement the intended intervention
- Failure to collect the intended data
- Failure to capture unanticipated learning
- Failure to abandon the intervention despite negative results or side effects
- Failure to appropriately analyze or interpret the data collected
- Failure to communicate what has been learned with the team
- Moving too quickly from small to large scale change
To see how powerful the PDSA method can be when applied authentically, a primer on PDSA provides a detailed explanation of the many pivots and refinements to a project aiming to reduce for hospitalized patients.5 This primer presents the ‘back story’ for a successful intervention published as a short research paper in JAMA Internal Medicine, in which an intervention initially targeting busy nurses in the ED was quickly (and appropriately) abandoned in favour of a completely different approach involving empowering ward nurses to apply a decision algorithm and remove urinary catheters without needing to wait for a physician order.6 The whole project, from the initial idea through to the eventual evaluation published in JAMA Internal medicine showing a significant reduction in both duration of catheterization and catheter-associated UTIs, took only about 9 months. Gathering data at each intervention and subsequently improving each intervention before moving to the next may prove to be more beneficial without learning.
As seen here, implementing a successful QI initiative goes beyond a superficial series of steps. It requires a deeper dive into the QI paradigm than is sometimes taken. Common pitfalls include inattention to change management techniques and not optimizing engagement of relevant stakeholders; rushing to a proposed solution without a nuanced appreciation of the problem and its contributing factors; and undertaking quasi-PDSA cycles without learning from each intervention to inform the next. Before starting your next QI initiative. take some time to think through each phase and plan it out with your change team.
That is it for this Expert’s Corner. We would like to thank Dr. Kaveh Shojania for his input. Let us know what you think at @Hi_QuI_Ps on Twitter.
Junior Editor: Laura Pozobbon
Senior Editor: Lucas Chartier
- 1.C-QuIPS. Dr. Kaveh Shojania, MD. C-QuIPS. https://cquips.ca/dr-kaveh_shojania_md/
- 2.Taher A, Glazer P, Culligan C, et al. Improving safety and communication for healthcare providers caring for SARS-COV-2 patients. In Press. Published online 2021.
- 3.Reed JE, Card A. The problem with plan-do-study-act cycles. BMJ Quality & Safety. 2016;25(3):147-152.
- 4.Taylor M, McNicholas C, Nicolay C, Darzi A, Bell D, Reed J. Systematic review of the application of the plan–do–study–act method to improve quality in healthcare. BMJ quality & safety. 2014;23(4):290-298.
- 5.Leis J, Shojania kJ. A primer on PDSA: executing plan-do-study-act cycles in practice, not just in name. BMJ Qual Saf. 2017;26(7):572-577.
- 6.Leis J, Corpus C, Rahmani A, et al. Medical directive for urinary catheter removal by nurses on general medical wards. JAMA Intern Med . 2016;176:113-115.