Hey, That’s my Parking Space!

We had a snowstom in the Northeast last week but as far as I’m concerned, the real storm is the one over parking that immediately follows the one with the snow.  Few local customs generate as much controversy as the tradition of “space savers.”  These are objects such as broken lawn chairs or traffic cones people use to “reserve” their parking spaces after spending time and energy to dig their car out of the snow.  People who remove a space saver to park there have been known to have their car vandalized in retaliation.

Some people consider the right to temporarily own a public parking spot the legitimate reward for investing time to dig out their car.  Others feel street parking is a shared public resource allocated on a first-come, first-served basis and there is no justification for even temporary ownership.  Local government had historically stayed out of the controversy, but in 2015 Boston Mayor Thomas Menino instructed garbage crews to remove space savers 48 hours after a storm ended.  This essentially enshrined a policy of two-day holds on parking.

From a resource allocation perspective, this is a terrible use of shared property. This hoarding behavior reduces utilization for everyone.  Hoarding happens when there is unregulated scarcity and cooperation breaks down. 

This issue is not unlike what we sometimes see in the perioperative suite.  Tenured surgeons claim ownership of OR blocks because they’ve historically used those blocks and have come to rely on them being available at their convenience.  Management is often reluctant to alienate those long-time surgeons and impose policy that would improve utilization of blocks by re-allocating them to someone with a larger caseload.  Newer surgeons are forced to “drive around in circles” looking for OR blocks, while prime time goes unutilized.

The following anecdote illustrates an alternative path forward.  I got my haircut this morning and was making small talk with my barber about the space savers and he told me about the time he took someone’s space saver when he arrived at his shop in the morning.  I was shocked to hear him admit to such a blatant violation of street rules.  But instead of just tossing the space saver aside, he placed it on top of his car with a note on his windshield saying:  “I took your space.  Please call me at 617… and I will give it back to you.”

Around 4:30 PM his phone rang from an unfamiliar number.  He answered and said: “You want your space back?”  Sure enough, it was the original parker.  The barber went out to move his car, prepared to apologize, but instead of being upset, the parker was grateful to him for keeping her space with an actual car.  She was nervous someone would take her space and she admitted she was unwilling to do anything to retaliate.

She then said, “I actually have something to ask you … can you do this again tomorrow?”  For the rest of the week, they arranged over text messages to share the space, allowing the barber the space during the day when he was at work and her the space overnight when she was home.

I share this story because it illustrates how cooperative behavior can lead to optimal utilization of resources.  Both parkers had the peace of mind to know their space would be available, and the space was also fully utilized.  Neither parker had to waste time looking for parking.  Hospital ORs can also benefit from this sort of shared behavior where, instead of competing for scarce resources, users coordinate to maximize utilization.

For more on space savers: http://lmgtfy.com/?t=i&q=space+savers+boston

Trailblazing a Path to the Future of Healthcare Operations

Photo by wildpixel/iStock / Getty Images
Photo by wildpixel/iStock / Getty Images

Joining Hospital IQ has allowed me to return to my roots: tapping the power of data and business intelligence to improve healthcare. Through the years, I’ve seen healthcare pioneers transform their operations through data.  Until recently this type of work only took place at a handful of healthcare systems, ones with access to specialized resources. Today, we find ourselves at an exciting crossroads where the combination of people, processes and technology can transform every health system, not just the fortunate few.   

At Hospital IQ, we have tools to make this operational transformation possible.  As we set out on this journey, it’s important to keep in mind three basic tenets:

1.    If you can’t measure it, you can’t improve it.

Most hospitals and health systems today stuggle to understand critical performance metrics. And if they can’t undertand the metrics, they can’t optimize them to improve patient care. This is not the fault of the leaderhip. Technology has failed them.  Many vendors have created point solutions providing moderate assistance for managers trying to improve operations. Enterprise business intelligence projects have also attempted to ease the burden, but there is an endless queue of work to serve an organization.  Both solutions fail to meet the mark and leave managers trying to pull together insights from multiple IT systems.  They often rely on their own Microsoft Excel skills or overworked analysts to get the ball rolling.   This leaves a manager living in a queue – hoping to one day receive their information to efficiently and effectively run their part of the organization. 

2.    To understand the future, you must understand the past.

When data is hard to come by, day-to-day activities easily consume the ability to look ahead.  Managers struggle to deliver their monthly performance reports.    The goal of being predictive, or even optimized, seems impossible to reach.  The technology exists to automate the routine activities, analyze past performance, and proactively share what lies ahead. Our platform will enable healthcare providers to understand their performance and have the proper decision support tools to affect future performance.  

3.    Statistics are no substitute for judgment.

It is easy to become fascinated with data, visualization and advanced analytics.  The real magic happens when healthcare professionals use the the information to make better decisions.  This is the power that we’re unlocking for our customers everyday at Hospital IQ. They  can use the data, combine it with their expertise and improve the quality and efficiency of care delivered to their patients. 

“Statistics and Compassion”

Photo by sindlera/iStock / Getty Images
Photo by sindlera/iStock / Getty Images

I watched the “Lego Batman” movie over the weekend.  And yes, this is highly relevant to healthcare analytics.  But first some background.  In the movie, Batman’s one-man crime-fighting prowess is thrown off balance when a new young police commissioner takes over from a retiring commissioner Gordon.   Instead of simply activating the bat-signal every time Gotham is in trouble, she wants to actually partner with Batman to get at the roots of crime instead of just reacting to the symptoms. The new commissioner gives a Powerpoint of where she reports on her adoption of “statistics and compassion” to effectively fight crime. 

At Hospital IQ, we also use “statistics and compassion” to fight waste and inefficiency at hospitals.  We don’t show up to clients in tights and a cape, but we do have a toolbelt of sophisticated waste-fighting operations planning and management software worthy of the bat-cave.  And like the new commissioner, we don’t just churn through data – we also have a deep appreciation and respect for the mission of healthcare.

In a fully logical world run by computers without emotions, the numbers would speak for themselves.  We would blindly apply the lessons of modern management research to hospital operations and call it a day.  In fact, we’ve seen academics present the results of “ideal hospital” simulators and then express befuddlement when their perfectly balanced OR schedule or inpatient bed layout is not immediately implemented by the hospital.  This bull-in-the-china-shop approach is not only strategically and politically unwise, it also misses the bigger picture of what healthcare is about.  Unlike many business that are fundamentally transactional in nature, healthcare is different.  At its core, it’s driven by doctors, nurses, and other providers with a genuine desire to help people.

When we at Hospital IQ help a hospital run more efficiently, it not only pleases the CFO because we’re treating more patients at a lower cost, it pleases the doctors and nurses because they can get services to their patients quicker.  We’re helping hospitals implement their mission by ensuring the best patient care with the least amount of waste.  It’s not just about saving money and it’s not just about adding more services.  It’s about true efficiencies by smarter allocation of finite resources.

“Statistics and Compassion” for Hospital IQ means using data to combine “solvency with humanity.”  We help hospitals meet their financial targets by getting patients the treatment they need faster.  It’s a textbook win-win situation where the only losers are the “bad guys” of waste.

At Hospital IQ, we’re not just a bunch of MIT-trained data wonks blindly chugging through simulations.  We have a deep respect for the mission of healthcare and want to use our talents and experience to help hospitals reach efficiencies that provide better care for patients, and better resources for doctors, nurses, and other providers.

Industry News: February 2017

It’s not easy to keep up with the endless cycle of industry news. In case you missed it, we’ve compiled the key issues and trends discussed during the past month regarding hospitals, health systems and hospital operations and management.

The role of software and big data continue to take center stage, with a great deal of attention given to the role both will play in the transformation of healthcare.

Driving operational efficiency continues to be a critical need for hospitals and health systems around the world.

And of course, HiMSS generated plenty of chatter around the progress that’s been made within health IT, as well as the struggles remaining around the practical use of technology

Found an interesting article?  Have an interesting perspective or insight? Share it with us.


Only a Holistic Approach Can Fix Patient Flow

When working to improve patient flow, it is vital to recognize that the different parts of a hospital are deeply interconnected. The nursing units where overcrowding is most evident may not be the units where the mismatch between demand and capacity is causing the problem. Further, patients have complex journeys through their hospital stays, and do not simply move “downstream” from ED to ICU to the floor. In order to improve patient flow in hospitals, sophisticated data analytics are needed to guide decisions on beds and staffing, and to target efforts on length of stay. And to deliver meaningful, actionable information, such analytics must be “holistic”. By holistic, I mean that analytics must encompass the entire interconnected picture of a hospital or even a system, as well as the full complexity of patient movements.

Those of us who work in patient flow have long realized that we cannot address any one part of the hospital in isolation. When tasked with “fixing the ED” to reduce crowding, walkouts, and ambulance diversion, and to improve door-to-doctor time, we know that process changes in the emergency department alone won’t get us to where we need to be. In most cases, emergency departments with significant crowding and delays are that way because beds in the emergency department during peak hours are filled with patients who are admitted and who are waiting to be moved to inpatient beds. Thus, freeing up inpatient capacity is key to unblocking the emergency department.

The same things hold true for other parts of the hospital. We cannot address problems in intensive care units without addressing the floor. We cannot address the PACU without addressing the intensive care units.

We also know that to fix problems in one part of the hospital we have to look both “upstream” and “downstream” to ensure we are actually addressing the real problem and not a symptom. The ICUs may be full because there aren’t enough telemetry beds for patients to move out to, not because there are too few ICU beds.

However, the picture is far more complicated than words like “upstream” and “downstream” can convey. Patients may move from the floor up to the ICU or go from the ICU to the OR, and sometimes they are directly discharged home from the ICU.

The true complexity of all the different patient journeys between different parts of the hospital has to be adequately represented if we are to target our true goals: namely, how often do we want to be able to place patients in the right level of care and the right nursing unit and how much of a delay are we willing to tolerate.

Nineteenth century approaches cannot yield the quantitative answers needed to fix flow. Walking around and looking at units that are full or at beds that are empty does not adequately explain what actions are required. Midnight and noon census, basic arithmetic and spreadsheets all fall short, as does queuing theory alone, which simplifies patients’ journeys into flow between compartments based on formulas and probability distributions.

We need computationally intensive advanced data modeling, such as discrete event simulation and what-if scenario testing, if we are to make the best use of our beds. Truly holistic models represent all the different parts of the hospital, including the ED, the OR, PACU, ICUs, floor; they take into account multiple sites across health systems; they factor in real-life constraints from hospital policies; and they represent the full complexity of patient journeys which crisscross throughout institutions. Only such holistic approaches can accurately represent the complexity we wish to manage. And only such approaches can provide us the operational clarity we need to improve patient access, and to better align staffing structure for overall financial performance.

In the broader culture, when the word holistic comes up, it can come across as a throw away adjective, used to sell everything from skin care products to dog food. But in hospital administration, a 21st century data analytics platform that offers a holistic view for operational planning and management is far from being a consumer luxury. It is an essential requirement for delivering efficient, effective patient care.

HiMSS 2017: Bringing Reality to the Table

The Hospital IQ team participated in last week’s HiMSS, the largest healthcare conference held annually in Orlando with close to 40,000 attendees.  We were there to support our two key strategic partners, TeleTracking and Allscripts, on the show floor. Much of the show’s focus this year was geared toward demonstrating a practical use of technology within the healthcare system, and less about the next cool app. 

Innovation occurs from within.
HiMSS’ focus on practicality underscores the need to work closely with your customers.  Who better understands the intricacies of a problem than the customer dealing with it?  Our customers deal with problems day in, day out, and many have found home-grown ‘work-arounds’ solutions that are quite impressive.  For example, a CMIO demonstrated an ED dashboard that had been internally developed at his hospital and talked about how he frequently met with his ED team to receive feedback on how to improve it. There was an icon of a patient sleeping on the screen and he proudly said that one colleague had asked for this in order to show when a patient is anesthetized because this requires additional staff and monitoring. It reminds us that if we want to build solutions that truly benefit our customers, we need to do the same as that CMIO. Don’t build a solution around what you think the problem is. Dig into the problem, with the customer, and develop a solution that addresses the complexity of a problem, and works in a real-life setting.

Disparate points of view are just as bad as disparate systems.
Our favorite quote of the conference came from a CMO and former surgeon. He said, “There is surgeon time and then there is real time.” He was referring to the fact that many surgeons often have an inaccurate assessment of how long a surgery takes to complete. And it’s not just surgeons. There are many roles, business units, and services in the hospital, all of which create a unique, and sometimes contradictory view of the patient experience.  When we think about practicality, we must remember that the people on the front lines don’t have time to analyze data to figure out what actions can or should be taken to optimize overall hospital performance.  The solutions we put at their fingertips must provide clear, accurate insights as well as offer actionable recommendations that can be easily understood and implemented.  

Hospitals and health systems need an operations planning and management system that creates a transparent and accessible view of the entire patient flow which can unite these differing points of view and get them focused on driving efficiency and not on defining terms.

Most hospitals and health systems believe they have unique challenges, while in reality most are striving to achieve the same outcomes:

  • Better and greater patient care
  • Stronger and happier staff
  • Improved financial performance

Practicality at Hospital IQ always means working closely with our customers so that we not only help that particular hospital or health system, but so that we also help bring about critical change to the healthcare industry as a whole.

“Stone Soup” Data Gathering

Data is the raw material that powers the growing industry of hospital analytics.  However, many well-meaning quality improvement and operational efficiency projects die simply because they cannot get the necessary data.  Given that most hospital IT departments have far more on their plate than hours in the day, overcoming this barrier has become a skill unto itself when Hospital IQ engages with clients.

We start by sharing our published data specification.   But “real-life” hospital data is rarely presented in that clean tabular normalized format.  Furthermore, because our specification is general-purpose for all hospitals we work with, it can be overly-detailed in some areas, while missing important subtlety in others.  We see the specification not as a demand, but simply the start of a collaboration between a hospital’s IT department and Hospital IQ.

This collaborative process often makes me think of the story of “Stone Soup.”  This refers to the tale of a traveler who shows up in a village with nothing more than a cooking pot.  The villagers are reluctant to share any of their food, so the traveler declares he has a soup recipe that requires nothing more than a stone.  The curious villagers gather round while the traveler heats the stone in a pot of water, all the while talking about how tasty the soup will be.  At one point, the traveler says the soup would really be helped by some seasoning, so one adventurous villager parts with a small satchel of spice.  The spice does indeed make the broth smell appetizing.  The traveler then asks for a carrot or two to give the soup some heft.  Another villager steps forward.  This goes on and the traveler eventually persuades the villagers to contribute more vegetables and even some meat.  Eventually the traveler cooks a soup that indeed lives up to its expectations and the village celebrates.

In Hospital IQ’s effort to gather data to help a client solve its operational challenges, the stone is the demo and the recipe are mathematical tools from modern operations research.  We start by showing our capabilities using anonymized data from another fictitious hospital.  That data arouses curiosity, but data from another hospital can’t necessarily help new and potential clients make better decisions about their own hospitals and healthcare systems.  However, the demo is usually enough to pique interest in importing some of their own “easier to get” data into our platform such as perioperative in/out times and a block schedule.  This allows us to show some more basic analytics around perioperative flow and demonstrate the speed, fidelity, and verifiability of our platform.  This first view is the “satchel of spice.”

While presenting this aromatic first pass of data, someone will typically ask “Can your platform show how perioperative flow impacts inpatient bed demand?” or “How I should arrange my ICU beds to make sure I can handle peak flow from both the PACU and ED?” 

To this we answer, “We can absolutely do this, but we will need more data”.  Now that we’ve shown value and gained credibility, barriers to data quickly fall.  Phone calls are made and we’re put in touch with the right people who can provide the necessary patient movement and visit data for these more sophisticated analysis and simulation modeling.

This iterative cycle goes on where we
(1)   Show value,
(2)   Questions are asked,
(3)   More data is obtained. 

This data often grows to include extracts including block releases, staff rosters, vacation schedules, clinic locations, medical and surgical scheduling, equipment requirements, anticipated discharges, anticipated post-surgical nursing requirements, ICD codes, and more.  Furthermore, multi-site hospitals start asking about our ability to model consolidation and centers of excellence scenarios, which means gathering data from peer facilities.  Where we encountered resistance when we first arrived, we are now welcomed.

Some people think of Stone Soup as a story about a clever traveler tricking the village into handing over food.  We see it as a skilled chef finding a way to demonstrate his talent to a skeptical audience.  At the end of the story the village enjoys a well-prepared communal soup they would not have otherwise enjoyed.  The hospital industry faces a similar challenge – sharing the ingredients and best practices they already have to make a data soup far more appetizing than would have happened if each individual prepared their meal separately.  This aligns with our mission to create tools that allow hospitals to benefit from modern management science in the same way as every other 21st century industry.

Hospitals have the data they need to get powerful predictive analytics that inform key decisions about resource allocation.  We realize that predictive analytics are new to most hospitals -- but the “Stone Soup” approach to data gathering shows one way for hospitals and third parties like Hospital IQ can work with IT to launch more projects that drive better operations.  IT departments are often overworked and understaffed so projects that show the most potential will naturally move to the front of the line.  Incrementally gathering the “easiest” data and showing results has been effective in building momentum and eventually drilling for the more elusive data.

Best of Both Worlds

Photo by Jirsak/iStock / Getty Images
Photo by Jirsak/iStock / Getty Images

While abhorrent to some, the idea that hospitals are, at least operationally, a lot like factories isn’t a new idea. It was first presented in a famous McKinsey paper in 2001.  There has been a small dedicated group of thought leaders who have been proselytizing the idea that, just as we have done in manufacturing, the inefficiency of healthcare could be dramatically improved by the application of time-tested mathematics.

This week’s announcement of the relationship between TeleTracking and Hospital IQ brings together TeleTracking’s industry leading patient flow technologies with Hospital IQ’s next generation operations planning and management platform for hospitals.  The relationship will allow health systems across the country to now realize the benefit of workflow automation, advanced analytics and simulation-based modeling for their organization. This combination of technologies creates an environment to better manage, analyze, and optimize health systems much like manufacturing has done for decades.   

To achieve this transformation, the partnership is based on two primary principles. First, it is time to innovate the way real-time operations are managed by various stakeholders across our health systems.  TeleTracking is an industry leader that brings visibility, workflow and communication to over 900 customers across the globe.  Hospital IQ will strategically help TeleTracking and its customers see into the future by predicting census and OR volumes so they can make better, data-driven decisions throughout their days.    Healthcare employees in various roles can now experience a world where understanding your future census is as simple as checking the weather. 

Secondly, long-term strategic decisions are being made without a full understanding of the consequences on the entire operations, financials and general well-being of health system.  Hospital IQ’s capacity planning capabilities will help shape business cases and guide decision-making through the optimization of existing facilities and acquisition of new facilities during this transformative era of healthcare. 

Given TeleTracking’s significant install base and 25 years of expertise helping to drive efficiency with their customers, the relationship with Hospital IQ provides the next natural step to mature and optimize their organizations.  Hospital IQ is excited to bring our solutions, mathematical expertise and future innovations to help transform the industry - just as manufacturing did many decades ago. 

Recapping the OR Business Management Conference 2017

The Hospital IQ team attended the OR Business Management Conference last week in New Orleans.  The conference was well attended and the team had a number of interesting conversations with attendees over the two and half day event.  Here are three notable observations we took away with us.

Hospitals have more in common than they may realize.
Every hospital feels like they have a unique set of challenges they’re working to address.  And while hospitals may have different policies and level of resources with which to work, the reality is that the challenges they face in driving efficiency in the operating room are not all that different. They include things such as OR block time governance, effective staffing, applying lean six sigma principles, etc. The real challenge seems to be finding solutions that actually help solve for these issues.  One attendee shared that they have been working on Preference Cards for more than eight years now. Small wonder that progress can sometimes be frustratingly slow in the hospital industry.

Change management is difficult.
One of the biggest challenges with implementing change in any organization is managing the expectations and modifying the behavior of the people involved.  And hospitals, by nature, tend to be conservative cultures with many key stakeholders vying to have their voices heard.  And as a result, change can be hard to affect and often takes a long time. On top of the human instinct to resist change, there are other factors attendees shared with us that hospitals often take into consideration. These include:

  • Legacy promises – “There are a lot of legacy promises made to nursing staff who have worked at the hospital for years.”
  • Sacred cow – “There are ‘sacred cow’ surgeons whose block time we can’t touch. One surgeon literally has his name above the operating room.”
  • Tribal knowledge – “There is a tribal knowledge culture where we have been doing the same thing for years, we have always done it that way, and we will always do it that way.”

Change management is something that MUST be driven from the C-suite.  There must be full alignment and support across hospital leadership so those who want to resist the new state of the union understand it’s a get-onboard-or-move-on-out proposition.

Eating the elephant one bite at a time.
The requirement for hospitals to implement electronic health record systems, as well as a number of other system initiatives, has left many IT and operations teams overwhelmed.  Many feel like they “can’t possibly take on another thing.”  One attendee talked about the importance of being able “to eat the elephant one bite at a time.”  They stressed that effective forward thinkers must evaluate and prioritize all the issues and take a leadership role in helping others to focus on a roadmap and process for tackling one issue at a time.

Having these sorts of conversations with people on the frontlines is critical to understanding how the industry can collectively come together to improve operations while focusing on the core mission of patient care. Hospital IQ will next be at HIMSS 17 (Feb. 19-23) and we’ll look forward to sharing our takeaways in our blog from one of the industry’s largest and most well-attended annual events. 

2017: Calling on all healthcare innovators and forward thinkers

Photo by SIphotography/iStock / Getty Images
Photo by SIphotography/iStock / Getty Images

The healthcare delivery system is on the forefront of significant change in the year ahead.  And not necessarily because of who’s in office or that hospitals and health systems really want to embrace change, but because they must simply to survive. As one of the last major industries to leverage data to drive operational efficiency, hospital and health systems will increasingly look to achieve a level operational clarity that will ultimately allow them to improve their financial performance and focus on their core mission: providing safe, quality care to their patients.

So what will these changes mean for Hospital IQ, its customers and partners? We hope it will mean a year of significant growth and success.

In 2016, we engaged in strategic partnerships with two of the significant players in the healthcare space: Allscripts and another marquee partner we’ll be announcing in the weeks to come (watch this space to learn more).  These partnerships are significant because one of the biggest challenges for hospitals and health systems is the ability to generate accurate insights and actionable recommendations from the data these companies’ solutions provide.  The billions in healthcare incentives over the past few years has helped to generate a wealth of information; however, this valuable data is too often siloed, which introduces the hurdle of system integration. Strategic collaboration with these partner organizations takes the burden of system integration off our customers’ plates and not only maximizes the investment they’ve already made in their existing systems, but also provides investment protection for the future.

This past year, we worked with several hospitals that truly understand the value of data and that are leading the pursuit to capitalize on the opportunities that a modern, robust operations management platform can deliver.  Hospitals are struggling to maintain single-digit margins, so even small improvements or cost reductions can represent millions of dollars to their bottom line.  At Hospital IQ, we feel strongly that for a hospital to gain real operational clarity, they must start with a holistic view. Otherwise how will you understand the impact a proposed change or series of changes will have upstream or downstream -- and how will you know if you’re focused on the true source of the problem and not just a symptom?  It’s also critical that hospitals stop reacting and constantly working in crisis mode.  They must be able to see what’s going to happen far enough in advance to proactively solve problems before they happen.  But that brings us back to the challenge at hand…access to data in a way that informs these decisions and actions.  Using manual spreadsheets, back of napkin calculations, “management by walking around” or floor-level meetings, or even consultant recommendations often means the data isn’t the most recent available and you can’t address questions at the time they are asked… when everyone is in the room.  As a result, the validity of the data comes into question and can often extend the decision to take action indefinitely.  We’ve learned that our customers need the ability to quickly and transparently drill down into each critical input associated with a recommendation.  And the ability to answer any question when asked, in real time.

Yes, this past year we’ve seen success.  We saw a Midwest Medical Center increase its orthopedic cases by 44% per week without needing to increase its bed capacity.  A two-million-dollar annual revenue increase from just that one service line.  We helped an East Coast Safety Net improve its on-time first-starts from 35% to 85%, grow its surgical volume 2.7% and improve its OR utilization from 80-85%, which added an annual operating margin of over a million dollars.  We’re also helping a Midwest System reduce its LWBS rate from 8% to its target goal of 3% while also accepting two additional high-acuity transfers per week to increase its annual revenue by $18 million.

So this year we hope to find and work with even more industry innovators that know what they want to accomplish or can envision what’s possible with the right investment.  If you are one of these hospital innovators and forward thinkers, please reach out. We are here to help make your operational goals happen in 2017. It’s going to be an exciting year for us all. 

Performance Excellence Summit Welcome Address

Photo by razihusin/iStock / Getty Images
Photo by razihusin/iStock / Getty Images

Last week Hospital IQ was invited to chair the Healthcare Focus day of the 2016 Performance Excellence Summit in San Francisco.  We were honored to present in front of so many quality improvement and business process leaders.  Below is the speech given by Ben Resner, VP Solutions of Hospital IQ to open the day.

We’re here today to talk about making healthcare better through improved processes that create efficiencies and reduce errors.  I’m really looking forward to this conference because it’s a group of like-minded people where I don’t have to explain myself.  Part of my job at Hospital IQ is demoing our product, and for a lot of hospitals, we’ll spend the first 20 minutes just giving a background on operations research and process improvement.  Yes, it’s a “thing” and yes it can help your hospital.  And yes, I’m flattered that you think I invented this but I really can’t take credit.  Today you will meet a group of innovative people who have all drunk the kool-aid and are fully committed to using data to improve healthcare.

And I use the word “innovative” deliberately because for many in the healthcare landscape, “innovation” simply means new ways of extracting payment from insurers.  What we’re talking about today is true innovation through operational efficiency and process improvement – doing more healing and wellness with less waste, fewer resources, and fewer mistakes.  We’re not simply sloshing cost from one bucket to another bucket with shenanigans that don’t actually improve quality.

For those of us here today, "innovation" means developing tools and culture to identify and execute on opportunities for care coordination that removes bottlenecks.  It means doing more surgeries with fewer complications, using less staff overtime and less patient waiting.  It means getting patients to the right bed at the right time with a distraction-free handoff.  It means looking at the hospital holistically so the effect of resource allocations in one part of the hospital can be understood to impact other parts of the hospital.

This type of true innovation is much more challenging than revenue cycle management.  It's not an invisible back-room process that can be plugged into an existing patient flow with no change to the clinical staff.  The change we’re talking about requires leadership that can cross departmental boundaries and supervise cultural change in how hospitals operate.   For operational efficiency to be realized, hospital staff from surgeons to CNAs need to adapt their behavior.

While true operational efficiency is hard to achieve in practice, it’s fundamentally a collaborative endeavor.  It doesn’t pit healthcare stakeholders against each other.  There’s no intrinsic us versus them.  It’s not payers versus providers or industry consolidation versus regional competition.  Nobody is rooting for more hospital acquired infections or greater ED wait times.  We don’t need to give one story to the CFO and a different story to the CMO. 

This is not to say process improvement is a hand-holding kumbaya moment – people certainly disagree about whether a program helps or hurts patients or, as one client put it, “is the juice worth the squeeze”?  But everyone wants the same outcome; we’re just arguing about how to get there.  As programs are demonstrated to work and are cost-effective, there’s rarely credible non-political pushback against widespread implementation.  (Political pushback is another story and nobody denies it exists.)

Many of us come from industry and look to companies like Toyota and Amazon to inspire models of efficiency.  How many of us have read an article or blog talking about how hospitals would be better if run more like a hotel, theme park, air traffic control tower, aircraft carrier, automotive factory, etc?  How many of us have written one?  At a minimum, we all come from hospitals that give lip service to moving in this direction.  At best, there are true leaders who are pushing hospitals to be run efficiently.

Any quality improvement project must show a return on investment in order to move out of the trial phase.  This is the only way to get the sustained attention of hospital leadership.  Our job is to not just socialize these changes but to show hard ROI.  Until that happens, we might be more correctly classified as part of a hospital’s marketing and outreach than the core infrastructure.  It’s a great challenge but every other modern industry has been totally transformed by operation science.  Now it is healthcare’s turn.

A cornerstone of ROI-driven cultural change is a robust data operation.  The good news on this front is that data has gone from non-existent paper records to awful electronic ones.  We’ve finally gotten to awful.  Yeah!  But we can work with awful.  We’ve been able to find signal in this noise.  And I believe that as we demonstrate the value of this data the quality will improve.  As clinicians feeding electronic health records see the utility and impact of accurate data, these clinicians will become more engaged.  Clinicians will be more diligent about raw data entry and leadership will be more demanding of tools that support accuracy over box-checking.

What has taken healthcare so long?  Is it just because of how we consume and pay for healthcare?  Or is there something else?  Is healthcare somehow different than a factory or hotel?  When I’ve done a good job describing what I do to people outside healthcare, their reaction is almost universally “you mean hospitals don’t already do that?”  Most people are surprised to learn that future inpatient elective admissions are not routinely reconciled against anticipated census to make sure there’s a bed for the patient after surgery is completed.  If an inpatient case can fit into the surgical schedule, it gets booked – no questions asked.  In all fairness, airlines and hotels also overbook but they use historical data to specifically calculate how many overbooks to accept in order to achieve a targeted rate of actual bumped customers.  Most hospitals treat bumped cases and overcrowding as a random external event totally out of their control – kinda like the weather. 

I don't think anyone can deny that healthcare is different.  For example, unlike cars and iPhones, humans were not designed for serviceability.  Healthcare is more like expecting Toyota to build a facility for repairing iPhones but not having any access to the people who actually built the iPhone.  A key part of factory process improvement is feedback and unless I’m mistaken, there’s no process where front-line clinicians can impact the fundamental design of humans.  We all see failure-prone plumbing and infected vestigial appendages and there’s nothing we can do about it.  Hospitals are basically tasked with servicing a product they did not design or build and had to reverse-engineer all the operating parameters.

That said, much of healthcare is like a factory.  Research consistently shows correlations between procedural volume and outcome.  Aggregating similar patients to high volume shops produces better results at lower cost.  Results improve even more when throughput is steady and predictable.  Nobody would expect iPhones to maintain their quality if managers forced workers to produce twice as many on Monday than Friday.  But somehow we expect this with hospitals and act surprised when variability impacts quality.

We need to take the right lessons from factory automation and logistics.  When the Wright brothers were developing the airplane, like so many other inventors, they looked to birds for inspiration.  But unlike previous attempts at controlled flight, the Wright brothers correctly understood flapping of wings to be about propulsion and not lift.  Flapping made birds go forward but it didn’t make them fly.  The lesson they took from birds was the airfoil -- the wing's cross section.  And they wisely kept the airfoil but replaced flapping with a propeller.  In healthcare, we need to apply the same thoughtful diligence and sensitivity to our work.  We need to know what is flapping and what is geometry.  Blindly copying every lesson from factory logistics will wind up looking like those black & white movies of failed frantically flapping flying machines we saw in junior high that are supposed to illustrate the irrepressible scrappy spirit of innovation based on a deeply flawed premise.  I don’t think any of us want to be that.

There is so much opportunity for hospitals to catch up to every other modern data-driven professionally managed industry.  How many of you are six-sigma black belts?  Six sigma means 3.4 defect per million.  For so many aspects of hospital operations, just getting to two or three sigmas is an accomplishment.  Wait time in the ED under 4 hours?  Discharge boarding under 8 hours?  Where do we start?

Healthcare is also unique because for so many – I think most –  of its participants, it is a mission-driven industry.  By this I mean doctors and nurses go into healthcare for a genuine desire to provide healing and care.  Yes, the salaries and status are appealing but I believe that fundamentally the majority of clinicians are in it to help people. By contrast, if I were to assert that investment bankers are truly motivated by a genuine desire to help humanity by efficiently allocating capital to the most worth enterprise, most would laugh.  Investment bankers are about the money and there’s absolutely nothing wrong with that.  But here healthcare is also different and our programs and products need to reflect that core value.  The goal of data-driven operational efficiency and quality improvement is to make it easier for hard-working and well-meaning clinicians to practice their craft with the best infrastructure and processes to lead to the best possible outcomes.


Nudging Surgical Departments Towards Systems Thinking

Photo by Carlos_bcn/iStock / Getty Images
Photo by Carlos_bcn/iStock / Getty Images

A client we've been working with asked us to help his Cardiothoracic service increase throughput without adding inpatient beds.  For this cardiothoracic service, patients go to a specialized unit that currently has a wide variation in census.  In extreme situations, elective surgeries are cancelled if one of the beds in this unit cannot be guaranteed on the morning of surgery.  Other weeks, this unit has empty beds and underutilized staff with far fewer surgical patients coming into the unit.  This variation in census angers surgeons when surgeries are cancelled, costs the hospital overtime dollars when the unit is overcrowded, and frustrates the nursing staff.  

We discovered a small but measurable number of these patients account for over half the bed days because they have a length of stay significantly longer than average. Furthermore, these patients are responsible for the majority of variation in census.  In fact, if you removed these patients from the population, the census would be relatively level with minimal variability.  Stable patient census makes staffing the unit much more predictable and safely allows more patients to flow through.

Upon further analysis by clinical staff, it became clear that these long-stay postsurgical patients can be identified beforehand by factors such as age and co-morbidity.  In other words, it’s not a surprise that these patients have a significantly higher LOS and account for a disproportionate number of bed days.  Experienced clinicians can look at the medial record and classify patients as likely to be a long-stay patient before the surgery occurs.

Our modelling software is showing staff how this historical pattern of scheduling multiples of these long-stay patients in a single week, followed by a few weeks of no long-stay patients quickly fills this inpatient unit and can block additional patients.  We then model scenarios where these patients are evenly scheduled and show how this helps smooth the census in this unit.  Like all our simulations and forecasts, we take variation into account and include in the model the understanding that some patients with fewer risk factors might stay more than seven days, and that some patients predicted for long stays in fact only spend two or three nights in this unit.

Because of these predictive simulations, this department is now building a process to identify these long-stay patients and schedule them more evenly.  This will help stabilize the census and hopefully enable the service to add patients while reducing the incidence of cancelled surgeries and/or staff overtime.

This might have been the end of the project but the staff kept going.  Seeing the disproportionate impact of this small complex population on census, clinical leaders asked why these patients needed to stay so long in the first place.  They started looking at the entire care plan for each patient with the goal of determining if they could sequence their CT surgery such that the patient would have a shorter stay.  For example, patients going into surgery with stable medication regimes and other therapies & supports in place might not need to stay in this specialized unit as long.  The conversation now includes the optimal time to do surgery so the patient has the best chance of an average length of stay.  Our software then modeled the effect of reducing the length of stay of this patient population and illustrated the impact on census demand and variation.

This is very exciting to our client.  He asked us to accomplish a specific task and now his staff is taking a modern systems approach to healthcare and realizing CT surgery is one stop in an arc of surgical and medical interventions each patient undergoes.  This is the type of thinking hospitals leaders need to inspire in their staff.  It’s a win to schedule long-stay patients at a regular cadence instead of bunched up.  But it’s an even bigger win to convert long-stay patients into more average-stay patients.

The tools and process our platform provides is giving staff and leadership the confidence to embark on a path of improvement.  Change didn’t come from a top-down powerpoint extolling departments to work together – change is coming from a bottom-up approach of looking at data in detail and then forecasting how different clinical and scheduling policies will impact their ability to care for surgical patients.

Obviously Obvious

The value of obvious, especially when it's not

Photo by victor zastol`skiy/iStock / Getty Images
Photo by victor zastol`skiy/iStock / Getty Images

As clients learn more about what we do, the braver ones ask "Isn't this all kinda obvious"?  A variant of this question is: "We know what our issues are, we don't need software to tell us what we already know".  I'm reminded of the joke that a consultant is a person who borrows your watch and then charges you to tell you the time.  When our analysis shows the ICU is crowded, how does it help if everyone already knows the ICU is crowded? Nobody needs to pay for a photo of an elephant if we all know one is in the room.

For example, our elective smoothing module shows that if hospitals do the same number of surgeries each day of the week instead of bunching them up on one or two days, peak inpatient bed census will usually go down. Furthermore, consider an orthopedic department that aggregates knee replacements as a "joint camp", where a cluster of elective patients all have surgery on Monday and then move through PACU, inpatient recovery, and then physical therapy.  It doesn't take fancy math to see that doing two cases a day instead of ten in a single day will reduce peak demand on inpatient beds and other post-surgical resources.  

The value of our software is the ability to quantify the opportunity by moving from joint camp to a smoother schedule.  Given how disruptive it is to change around surgeon schedules, leadership must do everything possible to make sure that the benefits are worth the costs.  It's not easy to make a cost - benefit decision if the costs and benefits are vague.  We can model the savings and reduction in peak staff workload from a smooth schedule, and this can be weighed against the cost of adding weekend services and changes to surgeon schedules.  This change may not make sense. Or the opportunity may be so big, even skeptics are forced to agree.  

In any hospital, there may be at least half a dozen operational changes that could improve efficiency through OR optimizationre-assigning beds, or updating staff schedules.  Which one is the biggest opportunity?  Where does one start?  Again, by quantifying the benefits of each scenario, leadership can use data to assist in the decision instead of guessing.  

And the obvious is not always obvious.  For example, we're often asked to study how moving cases to Saturday will affect inpatient bed crowding.  If variation in length of stay is large, it turns out that moving cases to Saturday doesn't make much of a difference to peak census.  This surprising result is a consequence of units with high unpredictability -- scheduling two days with no surgeries is statistically the same as one day without surgery.  What's becomes obvious is not disrupting schedules for a change that won't yield operational improvements.

We can also show the value of incremental change spread over months or even years.  For example, a service that crowds procedures to one or two days won't smooth overnight.  In fact, we've found it's a counterproductive academic exercise to present an "ideal" schedule that disregards historical work patterns.  Our simulations show how small changes produce small results and how over time this accumulation of small results winds up making a big difference.  Every time a surgeon retires and a new surgeon is hired, there's an opportunity to design blocks that will create the smoothest schedule.  We don't present a one-time analysis from a snapshot of data, we run continuously in the cloud so clients can always have the most updated view of their hospital.

The analogy is like a person on a diet.  Everyone knows eating fewer calories leads to weight loss.  It's calories in versus calories out.  But telling someone to "eat less" rarely works.   Hospital IQ is like the dietitian who says "You currently eat five doughnuts a week.  Cut this down to two a week and you'll lose 1 pound every three weeks for the next six months".  If this is too much of a sacrifice, the dieter can opt for a smaller reduction with smaller gains.  If the dieter wants to see faster results, they can cut out more donuts to know what to expect in terms of results.  Dieters know what they need to do to lose weight.  But the goals are much more manageable if they're put on a plan that's backed up by data and allow the change to be incremental.

Finally, the obvious is what some clients are actually looking for.  They have a good idea what they need to do, they just need data for the precision necessary to get to the finish line.  We can turn a strategic vision into tactical steps that can be incrementally executed and adjusted to real-world feedback.  By showing multiple scenarios with various degrees of cost and opportunity, leadership can build consensus around the best path forward.

The Cost of Taking Reservations

Why hospital leadership should eat out more often.

During college I worked at a hip local restaurant.  A staff pet peeve was when walk-in customers would respond to a long wait time by smugly pointing to an empty table and declaring “what about that, why can’t we sit there”?  We would have to resist the sarcastic response of “Oh, I failed to see that table.  Of course you can sit there.  Thank you for being so much better at my job than I am!”  What we had to say instead, very politely, was “That table is for someone with a reservation”.

This local restaurant had sales under $1 million but was doing something that many billion dollar hospitals seem to have difficulty with – setting aside resources for anticipated scheduled demand. 

Hospitals know weeks in advance about inpatient elective surgeries, yet as these patients are being wheeled out of the OR, they often have to wait for beds in the same queue as patients in the ED.  These patients are boarded in the PACU, or worse, they are boarded in the actual OR with the surgical team administering post-operative care instead of prepping the next patient.  These elective patients are not a surprise visit.

Let us be reasonable about this metaphor – hungry walk-in diners are not harmed if their wait time is increased because an empty table is set aside to honor a reservation.  Restaurants also operate in a first-come first-serve basis – they don’t triage really really really hungry people to the front of the line (but there are times this would really be nice).

But the metaphor is also instructive.  The restaurant business is extremely competitive and operates on very thin margins.  The cost of food, rent, and staff is only a sliver behind income.  Even popular crowded restaurants can lose money if not well-managed.  Therefore, it must have taken fortitude for the restaurant owner to look at that empty table on a busy night and not fill it.  Maybe the last three nights were slow?  The temptation to fill that table was very real.  What if the reservation doesn’t show?  When should the table finally be released?

Hospitals are operating in a similarly competitive environment with growing patient choice for elective surgical procedures.  A hospital has the opportunity to provide a consumer-friendly service by streamlining the care of elective patients.  This means understanding demand patterns in the ED and implementing strong management of elective OR resources.  It is impossible to eliminate edge cases where ED demand causes elective surgeries to be cancelled or EDs to be diverted.  But with proper understanding of historical demand patterns, hospitals can plan for this to happen a certain number of times each year and be ready when an elective case does have to be bumped or the ED does have to be closed. These events will happen with regularity that can be mathematically modeled and forecasted. 

Finally, we have seen client hospitals that are disciplined about setting aside ICU beds for major surgeries that will require ICU care after surgery.  These surgeries are more likely to be cancelled if an ICU bed cannot be guaranteed after surgery, and a reserved ICU bed is less likely to be opened for an ED patient.  We're heartened to see this precedent and hope to see this behavior for all beds not just the most acute.

Excel is Dead. Long live Excel!

How I learned to stop worrying and love the spreadsheet.

Excel is a wonderful tool for quickly modeling business and scientific data.  Those of us familiar with Excel and especially the pivot table functionality know how easy it can be to investigate data and identify meaningful patterns in a complex hospital extract.  Add in some knowledge of commands such as VLOOKUP and MATCH, and impressively powerful analytics can be performed with this well-known tool.

Many hospital strategy departments rely heavily on Excel and hire staff already familiar with Excel.  Typically raw data is imported into a spreadsheet and after several intermediate worksheets with varying levels of complex mappings, an aggregated output is presented.  With some additional effort, some basic interactive drilldown and configuration can be added.

So far, so good.  However, we start to see Excel’s shortcomings when repeating a given analysis with a new month or quarter of data.  We’ve met analysts who spend up to 1/4 or more of their time simply refreshing custom views of data.  For example, a new data pull arrives on the 15th of the month and then it’s a tricky 37-step manual process to convert this raw data to the intended output. 

These shortcomings are exacerbated once this process is transferred to another person.  Excel has no easy way to automate the complex steps that transform raw data into an output.  And each time this process is handed off to another person, more error and uncertainty is introduced.  Meanwhile the underlying data may also change and unless the analyst is paying close attention, these discrepancies can easily go unnoticed and the results suffer quality fatigue.

Even at its best, Excel is typically a tool just for analysts.  In practice, we rarely see the spreadsheets generated by an analyst used by anyone other than that analyst.  The spreadsheet may be distributed by email or placed on a server, but if there's a question that can be answered by data, the user-interface is a phone call to the analyst, not a peek at a spreadsheet.

The uncompromising solution is to use purpose-built software powered by relational databases and modern functional programming languages. This is the most reliable system for ensuring the same source data consistently produces the same output.  Data can be reliably processed month after month with sensitive alerts configured to raise alarms if anything in the source data changes.

Functional programming languages can also model block utilization metrics that are simply too complex and have too many configuration options to be managed by a database query or report writing engine.  Purpose-built cloud software can do so much more than just reports and dashboards once hospital data is loaded.

Excel is a victim of its own success -- it is so good at so many things, it's hard to know where to draw the line and recognize when the innovation it enables becomes a burden to maintain.  We think that Excel is a wonderful prototyping tool but not something that is appropriate for regular enterprise-grade reporting or complex modelling of the impact of various changes on hospital operations.

Some of Hospital IQ’s most successful collaborations are when a hospital analyst or clinician with deep institutional knowledge works with us to operationalize an Excel spreadsheet in our cloud-based software.  Excel is a prototyping platform for defining the data requirements and desired output.  In the early phases of rollout, it is also used to validate results.  But once the results are proven to be useful, we make sure this process can be repeated month after month.

Excel is where analysts can experiment with new ways of cutting data.  Relational databases and modern functional programming languages are where analysts can get reliable performance month after month, allowing them to discover new dimensions of hospital data that in turn become new operationalized features on our platform.

The Electric GOMER Block Utilization Policy

“The House of God”, Hospital Analytics & Strategy.

Samuel Shems’ 1978 book “The House of God” is a cynical semi-autobiographical expose of medical residency training.  In the book, the chief resident known as “The Fat Man” is showing the new interns “The electric GOMER bed”.   The purpose of this bed is to get patients to present any blood pressure the residents need in order to either discharge or admit the patient.  By changing the tilt and height of the bed, residents can essentially control the outcome of blood pressure measurements.

We sometimes see similar behavior with surgical block metrics.  There are so many different policies to evaluate how well surgeons are using their assigned blocks and each hospital seems to have a few new ones.  The most common policy is “room agnostic” – this means the scheduled room assigned a surgeon on the day of surgery is not the actual room the surgeon operates.  So if a surgeon is assigned room 15 and they operate in room 18, the surgeon should still get credit for having used room 15.  At most hospitals, most rooms, or groups of rooms, are interchangeable, so this policy makes sense.

From here, policies go in many different directions.  Adding in block release policy as well as variations in turnover time policy can produce wide variations in surgical utilization.  Double-booked, flipped rooms, multiple cases, and multi-surgeon surgeries further complicate a clear narrative of how well surgeons are using blocks.

Similar to the electric GOMER bed, cynical use of block policy can produce any block utilization a surgeon or service desires. Services that need more block time can usually find a consultancy or analyst who can navigate a path through the thicket of policy options to the desired outcome.  OR Executive committees that make block policy decisions can be faced with different reports from different services and practice groups, each showing the need for more surgical block.

Hospital IQ cloud-based block metrics platform has no magic that makes it immune to this manipulation.  But by applying the same policy to all services and surgeons, it makes sure all comparisons are on a level playing field.  Individual practice managers have full control to experiment with different policy selections and this is a good thing – correctly used, the policy should reflect the shared cultural and clinical expectations of an institution.  These policies are then shared with OR Executive committees with full transparency.  A policy configuration that shows a service needs more time might show another service needs even more time.  OR Executive committees are not forced to make apples-to-oranges comparisons when different groups apply different metrics to achieve departmental block allocation goals.  

There will always be actors who play by the rules to game the system.  By providing data-backed transparency, everyone can see how the sausages are being made.

The Importance of Reporting Variation in Hospital Data

Calling attention to the neglected stepchild of hospital analytics.

Hospital metrics typically present averages front and center.  Average length of stay, average admissions per day, average surgeries per week and so on.  But unless variation is included on equal footing, these metrics are only showing half the story and can actually be misleading.

Consider two hospitals.  Both hospitals admit an average of ten patients a day and each patient stays an average of four days.  This means both hospitals have an average inpatient census of 10 x 4 = 40 beds. 

Consider further the first hospital only performs routine elective procedures and admits exactly ten patients a day and they stay for exactly four days.  In this case, the hospital needs exactly 40 inpatient beds.  Not 41 beds or 42 beds but 40 beds.  And those 40 beds are 100% full.

The second hospital is a trauma center.  It may admit as few as five patients and as many as 40 patients in day.  And these patients may stay for as little as a day and as long as 8 days.  This hospital will need many more than 40 beds.  In fact, unless this hospital has 40 x 8 = 320 beds, it risks rejecting patients.  But if it actually had 320 beds, most of the beds would be unused.  This hurts the bottom line.

Modern operations science has developed mature statistical methods to characterize this variation and forecast the number of patients likely to be rejected given a set number of beds.  These methods replace qualitative words like “many” and “most” with a more precise statement such as “with 60 beds, 93% of all patients will be admitted within three hours”.  This isn’t a crystal ball into the future but it prepares hospital staff to expect that 7% of the time patients will have to wait more than three hours for a bed.  Instead of this being a crisis, it is can be an anticipated event.  If this wait time is unacceptable, the same analysis can find the number of beds required to meet hospital policy.

In this thought experiment, both hospitals have the same averages for admission and length of stay.  But for one hospital 40 beds is adequate while the other hospital needs far more beds to manage an acceptable percentage of the population.  The difference is variation.  And it matters.

This is one reason why ICU units can be harder to manage.  ICUs typically have the largest variation in length of stay of all hospital units.  A few patients with 30 days length of stay can take up half or more of an ICU’s capacity.  It is harder to find a balance between enough beds to avoid long wait times and not so many beds that they are often empty or filled with boarders from other parts of the hospital.

On the other end of the spectrum was a unit for pediatric otolaryngology in one of our client hospitals.  This unit had an average length of stay of 1.8 days with a variation in the hours.  Properly sized, this unit will rarely have an empty bed AND patients will rarely have to wait for a bed. 

When looking at averages, do not assume variation is low.  Planning based on averages runs the risk of resource scarcity during peak utilization.  Given this understanding of variation, low census in pediatric otolaryngology can be a sign of overcapacity but low census in the ICU is simply an expected part of natural variation in ICU demand.