Sanjeev serves as the President and Chief Operating Officer for LeanTaaS, the leading AI / ML analytics company in healthcare operations. LeanTaaS’s predictive analytics software powers over 130 health systems and 500 hospitals to improve access and lower costs.

Sanjeev is also the co-author of the book “

”. Before LeanTaaS, Sanjeev was Google’s first Head of Product Marketing, and led three successful startups - CEO at Aloqa (acquired by Motorola), VP Products & Marketing at TellMe Networks (acquired by Microsoft) and Founder & CEO at Collegefeed (acquired by AfterCollege).

Sanjeev graduated with BS and MS degrees in Electrical Engineering and Computer Science from MIT. He started his career at McKinsey & Company and Cisco Systems before joining Google. Sanjeev has been named by Becker's Hospital Review as one of the top entrepreneurs innovating in Healthcare.

Sanjeev Agrawal

Physicians are experts in their vocation. They constantly manage complex medical challenges, diagnose patients, and address health maintenance all while providing the best counsel to patients on their care and overall well-being. But low-hanging administrative tasks prevent physicians from working at “the top of their license” and aggravate burnout that is already exacerbated by a workforce shortage.

AI-based data analytics can break through these operational barriers and provide physicians with time back in their day to focus on patient care, but health system leaders must prioritize physician buy-in to achieve a successful implementation. This starts with a trust-driven collaboration between health system leaders and physicians, and mutual agreement that data informs decision-making, improves operational efficiency, and strengthens care delivery.

A successful model for this method is the airline industry, where highly trained pilots are the equivalent of physicians. Pilots could not fly a plane without the proper automation, instruments, and real-time control feedback needed to make the plane function. Hospitals are learning that physicians cannot perform these analogous functions manually and by themselves and would benefit from technology to propel them to better performance. For hospitals to ‘fly right,’ they must implement the proper data and operational tools needed and wanted by physicians, letting them excel in the most important area – patient care.

Making it personal to engage stakeholders

Before large hospitals were established and health systems became the norm, individual physicians and smaller practices had their own approaches and “ways of doing things.” As practices came together under larger health systems, standard processes needed to be implemented to streamline operations in areas like scheduling OR blocks, placing referrals, or sending patients through the ED.

As hospitals and health systems emerge from the pandemic and struggle with high labor costs and rising patient volume, they face another operations tipping point – data-driven tools are critical to ensure efficient care delivery. Those in favor of implementing new technology may face resistance from physicians who have tech burnout or fear disruptive change management. To address this resistance, it’s critical to first understand root cause problems and then communicate the value and impact the technology will deliver.

The first question to ask physicians needs to be, “what is the underlying problem that you are trying to solve?” For example, health leaders should not rush to create dashboards on open OR block time and physicians should not request backlog reports before identifying and aligning on the root cause that needs to be solved. It’s helpful to begin by educating caregivers on waste and variation, identifying where their own pain points and frictions contribute to organizational operations issues, and how a data-driven approach can yield improvements.

When launching a new technology project, start small with specific and achievable first steps. Data transformation fails when systems try to “boil the ocean” and accomplish all their goals at the same time. Focus on delivering results that make an immediate impact on physician stakeholders and make their jobs easier and more rewarding. Does the new technology remove clicks rather than adding them? Does it make data easier to access when needed? Does it learn and predict patterns to eliminate guesswork? When project successes naturally engage stakeholders, it helps build a self-perpetuating, data-driven culture.

Demonstrating results to create champions

The nine-hospital system Community Health Network (CHN) experienced firsthand how important it was to engage physicians in its data analytics transformation. They faced a challenging operational problem: improving efficiency in the operating room. CHN leaders partnered closely with surgeons and surgical staff to identify pain points in the scheduling process. They worked with clinicians and stakeholders to frame their problems through an analytics lens. Leaders highlighted the value that could be gained by adopting a new analytics tool for the OR, including performing more OR cases, increasing surgeon access, and eliminating manual schedules by hospital staff.

This physician alignment helped lead to a successful implementation with an AI-based analytics company that had a proven track record in OR optimization. Two months after implementing a new analytics tool, the team at CHN unlocked an additional 1,250 hours of OR time beyond allocated blocks being requested and approved, maximizing physicians’ time and skillset, and driving better patient care. Clinicians experienced firsthand how analytics-driven scheduling relieved them of time-consuming operational tasks and helped them deliver care at the top of their license. This experience kept them continually engaged and created not just users of the tool, but champions.

When organizations step back and partner with physicians to discover the root of roadblocks and bring them on the transformation journey, they can identify opportunities to implement technology that helps physicians work more effectively, efficiently, and thoughtfully. This leads to not only physician buy-in for the current project, but helps create a forward-thinking, data-driven culture in the organization.

Patrick McGill, MD, EVP, is Chief Transformation Officer at Community Health Network

Sanjeev Agrawal is President and Chief Operating Officer of LeanTaaS

Articles

Low-hanging administrative tasks prevent physicians from working at “the top of their license” and aggravate burnout.

Advancing tech goals with physician buy-in

With all the useful information available on Physicians Practice, it is easy to become overwhelmed.

With this in mind, the tip of the week is a chance to reflect on some of the wisdom found all across the site.

the crucial capabilities missing from your EHR

“The EHR is excellent at doing what it was designed and chosen to do—harnessing all of the clinical, financial, operational, and patient-specific data in one place to create a single source of truth for the entire health system. It provides a unified view of all patient encounters across time and across all points of care, showing clinicians and staff a current view of the patient’s unique characteristics; however, the EHR cannot perform tasks it wasn’t built to perform.

There are three fundamental reasons why your EHR isn’t enough:

1). EHRs have a flawed concept of an appointment

2). EHRs encourage a first-come-first-scheduled mindset.

3). EHRs do not have capacities for probability theory or discrete event simulation.”

Come back next week for another tip of the week.

Your weekly dose of wisdom from the Physicians Practice experts.

Practice tip of the week: Why your EHR is just not enough

Health system leaders are increasingly looking to deploy sophisticated techniques to improve operational efficiency and mine the enormous amount of clinical, operational, and financial data that already exists within their electronic health records (EHRs). This begs the natural question—if the data mostly exists in the EHR, why can’t the EHR do these things for us?

Many EHR vendors will assert that their platform can perform these functions, or if not will soon be doing so in an upcoming release. The senior leadership in the health system would like to believe that the EHR they selected can deliver these capabilities. After all, they invested tens or hundreds of millions of dollars and a countless number of FTE-hours deploying the EHR.

The EHR is excellent at doing what it was designed and chosen to do—harnessing all of the clinical, financial, operational, and patient-specific data in one place to create a single source of truth for the entire health system. It provides a unified view of all patient encounters across time and across all points of care, showing clinicians and staff a current view of the patient’s unique characteristics; however, the EHR cannot perform tasks it wasn’t built to perform.

There are three fundamental reasons why your EHR isn’t enough:



The pros and cons of private practice versus hospital employment

1. EHRs have a flawed concept of an appointment

Every EHR treats an appointment as if it were a “reservation of the specific resource for the expected duration of the appointment.” Hence, when a two-hour infusion appointment is being scheduled, the EHR enables the scheduler to “reserve” an infusion chair from 9:00am to 11:00am on a specific day. This is an excellent way to schedule tennis courts or conference rooms because the 

exact start and end time of the reservation is known at the time of making the appointment. 

Unfortunatley, this is inadequate for scheduling a clinical encounter which will likely not start or end on time and, if it does run long, cannot be terminated midstream. This is why the scheduling grids displayed on the EHR look wonderful when the day begins and fall apart as soon as appointments start to deviate from the planned schedule.

2. EHRs encourage a first-come-first-scheduled mindset

Every EHR displays availability on each day into the future and encourages schedulers to “offer the patient their choice of available slots” believing that this is a patient-centric approach to scheduling. This is as helpful as attempting to solve a jigsaw puzzle by putting pieces on the table in the order they were handed to you. It also confuses the concept of scheduling with the concept of optimization. Scheduling is the act of putting an appointment on the calendar, whether on paper or online. 

Optimization is the method for determining the correct slot for that specific type of appointment—

 the appointment can be placed on the calendar with whatever scheduling mechanism is being used.

Displaying Empathy and Enthusiasm in Your Medical Practice

3. EHRs do not have capacities for probability theory or discrete event simulation

Complex scheduling environments rely extensively on advanced mathematical methods like probability theory and discrete event simulation. This is why airlines routinely overbook flights knowing that there will be cancelations and no-shows which will be offset by the extra standby and upgrade passengers. No EHR function accounts for these realities. You cannot book three appointments into two slots nor can you book a three-hour appointment into a two-hour slot. Instead, the EHR gives you a blunt “overbooking” instrument and leaves it to frontline staff to estimate the number of overbooked appointments and the placement of each one in a manner that would be minimally disruptive.

Understandably, health systems have challenged their EHR partners to help them solve some of these problems. In response, most EHRs have built robust dashboard and reporting capabilities and facilitated the smooth transfer of data into analytic tools like Tableau or Power BI. Dashboards are nice 

. Some health systems go a step further and provide future-looking predictions and alerts. Those can be helpful but only if they predict something unique or alert you to something unexpected.

Enabling the frontline to make rapid decisions based on 

 requires building predictive analytics, probability theory, constraint-based optimization, discrete event simulation, machine learning and AI algorithms at scale in order to fully leverage the data that exists in the EHR.

These capabilities simply do not exist in your EHR, which is why your EHR isn’t enough.

The crucial capabilities missing from your EHR.