To continue our FLOW Hacks series, Dr. Shawn Dowling of Calgary, AB writes about his team’s innovation: Reducing Coagulation Studies in the Emergency Department.
FLOW Hacks: The Concept
The FLOW (Featured Leadership & Organizational Workplace) Hacks Series highlights innovative strategies for increasing patient flow in the emergency department (ED). This series is unique given its focus on the administrative aspect of emergency medicine. We are interested in small or large interventions that increase patient flow from an input, throughput, and output perspective. Our goal is to provide ED leaders a forum to highlight the successes and challenges they have faced. Send us interventions from your ED and we will showcase it on our site.
Four adult EDs in Calgary, AB which receive a total of 320,000 visits per year, combined.
Description of the Innovation
Rationale: In light of escalating health care costs, initiatives such as Choosing Wisely have been advocating the need to “reduce unnecessary or wasteful medical tests, treatments and procedures”. Thus, we have identified coagulation studies as one of those low cost, but frequently ordered items, where we can decrease unnecessary testing and costs by leveraging our Computerized Practitioner Order Entry (CPOE) system. Additionally, considerable evidence exists to suggest a low yield of doing coagulation studies (herein defined as PTT/INR’s) in suspected cardiac chest pain patients.
Background: In Calgary, we have a Computerized Order Entry System in the ED and numerous established Nurse Initiated Order Sets. RN’s and MD’s develop these NIOS and zone-wide departmental leaders approve them. Also, a protocol exists to outline rationale, details and scope of each of the NIOS.
Phase 1 (completed):
- Firstly, we removed the “pre-selected” INR/PTT from the Nurse Initiated Order Set (NIOS).
- We embedded recommendations in the order sets which advised when to order PTT/INR.
- Finally, nurses and physicians were provided with an educational resource documenting the rationale, methodology, impact and evidence for our project.
Phase 2 (underway):
- Prioritizing highest impact order sets, we will, when appropriate, unbundle PTT and INR and remove PTT in all our ED order sets.
Was a quality improvement methodology used?
We used a Plan, Do, Study, Act (PDSA) model to develop and implement this project.
What data were used?
We obtained data from our Computer Information System (Sunrise Emergency Care/Sunrise Clinical Manager) which was monitored over time using a dashboard (using a Tableau platform).
Who was on the team?
- Kathy Yiu, RNBN (Registered Nurse, Bachelor of Nursing, Manager, SCM Clinical Content/Order Sets)
- Alexis Mageau, RN, BNSc, MN – Clinical Nurse Specialist, Emergency
- Heather Hair, RN, MBA – Executive Director, Emergency Strategic Clinical Network (ESCN)
- Dr. Eddy Lang – Academic and Clinical Department Head for Emergency Medicine, Cumming School of Medicine, Alberta Health Services, Calgary Zone
- Dr. Tom Rich – Clinical IT Lead, AHS
What did you use as performance measures?
- Number of PTT/INR pre-post intervention from the Nurse Initiated Suspected Cardiac Chest Pain Order Set.
- Rates of MD “add-ons” for PTT/INR.
- Total number of coags (PTT and INR) across all order sets.
Additionally, we used a before/after study design collecting data 90 days pre/post-intervention. Furthermore, we also reassessed the data at 180 days to monitor the changes for sustainability.
How did you implement the intervention?
- The intervention involved modifying the nurse initiated cardiac chest pain order set to remove the pre-selected coagulation studies.
- Distributed an educational document to MD’s and RN’s around appropriate usage of coagulation studies.
- We created a dashboard to follow coagulation usage post-intervention.
How did you get buy-in from physicians, nurses, administrators and other allied professionals?
- We had tremendous buy-in due to having a multi-disciplinary team. As a result, each team member could communicate with their team in a way that resonated with them. It also allowed for better two-way communication since the respective team leads could illicit feedback, suggestions and concerns and bring them back to the project team.
- Focusing on reducing unnecessary tests, rather than “cost savings”, increased engagement. The reality is that determining the cost of lab tests is complex and site-dependent because of factors such as fixed (lab tech, tourniquet, etc.) vs. variable costs (e.g. reagents) and volume averaging (reagent prices are dependent on volume so as volume goes down, price can actually increase). One of the key aspects is to communicate with your individual lab services, both in terms of the costing- and process-related issues (i.e., is the lab willing to have a “draw and hold” policy to minimize the need for re-drawing labs).
What impact has it had on your department?
- Primary Outcome
- Pre-intervention – 9964 PTT or INR’s via NIOS
- Post-intervention – 1552 PTT or INR’s via NIOS
- Reduction of 8412 tests
- Secondary Outcomes
- No change in MD lab “add-ons” – 219 pre- and 218 post-intervention.
- We performed an additional 2704 fewer PTT or INR in the post-intervention.
- % of abnormal INR increased in the post phase.
- We sustained the reduction in PTT/INR reduction at 180 days.
What were some of the barriers to success?
- Firstly, this is an ED only project (at this time), as a result, we selected the cardiac chest pain population because we know most of those patients are discharged home. Thus, as we expand this to other order sets and to patients who are admitted, our efforts to “minimize unnecessary testing” can be negated by admitting services.
- Secondly, IT is a finite resource. Thus, we need to be selective of the “interventions” we do.
If you could do it all over again what changes would you make?
In conclusion, we need to better track the financial impact of this intervention in the future. Especially to justify a “gain-sharing” approach where we can increase our IT and analytical capacity to develop, implement and measure future interventions.
Copyedited by Michael Bravo (@bravbro).