Deinnovation ≠ Denervation:

How We Use Healthcare Delivery Science To Deimplement Lower Value Interventions and Expand Higher Value Ones

Becker’s recently had an interesting article titled de-innovation, sharing examples from a few health systems about what is chosen to be eliminated or removed. David Asch, who leads UPenn’s Center for Health Care Innovation had a nice quote:

“There’s a resistance to innovation and it’s a term I like to call ‘de-innovation’” Dr. Asch said. “It’s hard for some clinicians to adopt new practices, but it’s even harder to give up old practices that no longer serve or benefit health systems.”

I think it’s very true… change brings uncertainty and stress. But, generally, once we become accustomed to a way of doing things, or a particular program, we are apt to continue it. The familiarity breeds a certain type of acceptance. We instinctively resist new changes, but also resist taking away older processes, even if they don’t deliver desired value. And this results in accumulations of tasks, documentation, rules and regulations, and even EHR features (when was the last time you can think of where an EHR feature that wasn’t overall very useful was taken away to reduce the cognitive load of a user?). But what to cut, and how?

Enter Healthcare Delivery Science

Healthcare delivery science is a newer field that integrates research-quality methods into operations to help guide how we manage our resources and efforts. Teams, like ours at MCW, Froedtert, and Children’s, are arising more frequently across academic medical centers across the country.

To me, deinnovation sounds a lot like denervation (the cutting of a nerve, resulting in atrophy or loss of downstream muscles). Denervation removes any connection between the coordination centers (brain) and the doers (muscles). Some programs in healthcare probably wither by denervation (feedback loops fray, and eventually a practice isn’t working well but is still on the books). This must be avoided.

Simply, deinnovation or deimplementation is not denervation.

Simply, deinnovation or deimplementation is not denervation. Deimplementation should be intentional, a result precisely of the well-working nerve giving feedback to the coordination center and reallocating resources (effort, people, amino acids, ATP) to other areas that are more valuable. Deinnovation or deimplementation is not denervation precisely because the sensing through the nerve is a key part of the process. Healthcare delivery science adds an additional layer of higher reasoning that critically evaluates processes, helps determine value, and supports a case for either program expansion or deimplementation. And as science, the system and society overall may learn from the experience, generating and sharing knowledge for others.

Healthcare delivery science adds an additional layer of higher reasoning that critically evaluates processes, helps determine value, and supports a case for either program expansion or deimplementation.

Let me share an example of something that we studied, and decided to change course.

A Feedback Loop Example

Our parent health system implemented an early warning system to track physiologic parameters and other electronic data for hospitalized patients, generate a composite score, and alert teams if the score changed beyond a threshold. The goal was to reduce avoidable in-hospital cardiac arrest. Through Inception Health’s Virtual Care Team, nurses experienced with critical care monitored for alerts and then called the bedside nurse through their vocera communicator to share information about the alert and support the local care team. This was a resource-intensive intervention, beyond EHR-integration and service costs, as centralized nurses and, when called, bedside nurses, devoted substantial time to reviewing and addressing alerts. Were we getting the desired benefits?

To answer that, MCW’s Collaborative for Healthcare Delivery Science began an evaluation, looking both at mortality data, rapid responses, and ICU transfers. The team also looked at qualitative data — how was this intervention impacting local nurses? How do such systems, which are being created by EHR vendors, as well as companies as integrated solutions, intersect with workflow? And how do they provide value to care teams?

Over the weekend, we published the first of two articles taking a deep look at the outcomes and experience in BMJ Quality and Safety (with a special acknowledgement to Emilie Braun, the first-author and CHDS/Inception Labs medical student at MCW).

Through a qualitative assessment of bedside nurses, the evaluation team identified six principle themes that healthcare systems should consider when implementing an early warning system

• Timeliness
  Nurses were often aware of the patient’s decline and began or completed the appropriate intervention before the EWS triggers and the VCT calls
• Workflow Interruption
  Nurses were often called about an EWS alert while they were busy implementing the appropriate medical interventions.
• Accuracy
  Nurses perceived the EWS algorithm to be inaccurate, citing many anecdotes of false positives and false negatives, especially with the EWS’s inclusion of subjective nursing assessment data, such as urine colour and patient mood.
• Actionability
  Nurses felt the overall program rarely offered actionable, novel suggestions, however, some nurses appreciated the EWS and VCT as a safety net.
• Underappreciation of core nursing skills
  Nurses emphasised the value of in-person assessments and were concerned with the reliance on technology by a hands-on profession.
• Opportunity cost
  Nurses cited the need for additional hands-on support and criticized spending on the EWS during a time of hospital financial stress.

Through formal, scientific methods, including the rigorous qualitative research above and quantitative methods under peer review, we identified that the overall program as implemented was not adding the desired value.

And as we were gathering these lessons and making sense of our data, the COVID-19 pandemic was just beginning.

Shifting Resources

Inception’s VCT was busy! But they were also about to be even more in demand. The coming pandemic, in late February and early March of 2020, was already requiring centralized resources, including experienced nurses to help triage patients, provide for remote monitoring, and support the filling ICUs.

Simply put, we couldn’t keep doing everything.

It was this pivotal time where we needed to step back, take a look at what our data were telling us, and deimplement a program that was not delivering enough value to local care teams and shift resources to other needs. Simply put, we couldn’t keep doing everything. Fortunately, we had the data that helped us feel more confident that we were making the right choices and investments.

We implemented several programs, but the two main digital initiatives that vastly supported our ambulatory care services, and then by direct extension our inpatient services, were led and supported by our Virtual Care Team.

The VCT pivoted to be able to handle asynchronous care requests for testing and triage, running sometimes almost half of our testing requests through their services. Secondly, then ran our COVID-19 remote monitoring program, where we cared for upwards of 4,000 patients with COVID-19 at home. Our remote monitoring program, also rigorously assessed, is under peer review, but we believe that our program was able to avoid some hospital admissions and provide a sense of safety for our patients at home. Our VCT nurses commented that this work was some of the most rewarding of their careers.

Our VCT also supported our bedside nurses and ICU nurses, helping provide an additional set of eyes monitoring our sickest patients and also supporting transitions from ICU to the medical floors, a transition point where patients may require more monitoring.

Summary or TL;DR

• We often resist parting with familiar practices, processes, or features even though they may not provide desired value.
• Deimplementing processes can return value to people as much as implementation of new processes.
• Healthcare delivery science, rigorous looks at operational problems, can identify areas where value may be maximized
• We have had experience with deimplementing an exciting program that did not deliver desired value to bedside nurses, and then shifting resources to a new high needs area (COVID-19 RPM) where healthcare delivery science identified higher value per resources.