Tag Archives: operational cost

On Air Traffic Control and Health Costs

Explosion of data volumes. Interoperability of systems. Large servers in the sky that can analyze enormous amounts of data, compute complex algorithms in real time and communicate in microseconds. Mobile communication through devices that patients, providers and staff all carry all the time.

What does this all mean for hospital operations?

Based on our work with dozens of hospitals and conversations with 100-plus others, we think the near future of hospital operations is quite exciting. Call it what you will—“Hospital 2.0,” “No Waiting Rooms,” “Hospital Operations Center”—the basic building blocks to enable the future of hospital operations are already here.

Today, two major shifts are putting pressure on hospitals to rethink how they deliver care: (a) increased demand for care from the Affordable Care Act and the growing number of people with chronic illnesses and (b) the move toward value-based care.

See Also: 5 Trends in Health IT

These shifts have big implications across the board but, most importantly, in operations. Hospitals are under constant pressure to do more with less. Every day, they face an operational paradox: Scarce resources are both overbooked and underutilized within the same day. This leads to several undesirable outcomes: long patient waiting times, overworked staff, millions of dollars of unnecessary operational costs and an insatiable appetite for expanding existing facilities or constructing entirely new ones. For specialty services like chemotherapy, it could take days or weeks for a new patient to be given a slot, yet the typical infusion chair is occupied less than 60% of the time between 7 a.m. and 7 p.m. The same is true of operating rooms; study after study shows that hospitals don’t utilize their resources optimally.

Historically, process improvement efforts in hospitals worked with small, historical snapshots of data from which the core operational issues were identified. From this, strategies were developed, implementation plans were executed and disciplines for continuous improvement were established. This was the best approach when all that was available were rear-view mirror data snapshots and Microsoft Excel as the analytic engine of choice. Today, there’s a lot more data to learn from. On average, health systems produce as much as two terabytes of data per patient every year. Combined with the explosion of smart devices, computational power in the cloud and the growing pervasiveness of data science and machine learning algorithms, an entirely different realm of operational optimization has suddenly become possible. It is similar to the realization that, decades ago, general surgeons did the best they could with the insight they gleaned from grainy X-ray images. Today, armed with high-resolution MRI/PET images and fiber-optic cameras, the same surgeons can execute surgeries an order of magnitude more complex than those they could have imagined being able to do when they were surgical residents a few decades ago.

Consider the following scenarios on how predictive analytics is already optimizing patient pathways within hospitals:
  • Hospitals are working on optimizing access to treatments such as chemotherapy. By looking at historical demand patterns and operational constraints, sophisticated forecasting algorithms can predict the daily volume and mix of patient volume and can orchestrate appointment slots so there are no “gaps” between treatments. This radically improves chair utilization, lowers patient waiting times and reduces the overall cost of operations. Doing this without sophisticated data science is hard — for example, just arranging the order in which 70 patients can be slotted for their treatments in a 35-chair infusion center is a number exceeding 10^100, as this analysis shows. Trying to solve this problem with pen, paper or Excel is a pointless exercise.
  • Operating rooms are key resources within the hospital. Study after study shows that the OR utilization at most large hospitals is, at best, 50-60%. In most hospitals, operating rooms are allocated to surgeons using “blocks.” (For simplicity, the blocks are often either half-day or full-day blocks.) Even the most prolific and productive surgeons often don’t fully utilize the blocks they are given, and the process for reallocating blocks on a monthly basis—or even for last-minute block swaps—is cumbersome and manual. Using data science and machine learning, hospitals can monitor utilization, identify pockets for improvement, automatically reallocate underutilized blocks and improve overall operating room utilization. A three to five point improvement in block utilization is worth $2 million per year for a surgical suite with just four operating rooms.
  • In-patient bed capacity is a constraining bottleneck in most hospitals, yet virtually every hospital solves this problem with an arithmetic-based “huddle” approach that reviews the patient census from the overnight stay in each unit, adds known incoming patients, subtracts known discharges and then decides if the unit is flirting with the limits of its available capacity. This cycle repeats itself, often several times a day, with a planning horizon of the day at hand. On the other hand, Google completes the search bar while we are typing because it has analyzed millions of search terms similar to the one you are entering, and it automatically presents the four or five highest probability queries you intend to submit. Imagine looking at each overnight patient, finding the 1,000 patients over the last two years who entered the hospital with a similar diagnostic or procedure code and then reviewing their “flight path” through the hospital (i.e., number of days spent in each of the units prior to discharge). Then, an aggregate probabilistic assessment of the likely occupancy of each unit could be developed. Not only would it provide a better answer for today, it would help anticipate the evolving unit capacity situation over the next five to seven days, thereby leading to smarter operational decisions on transfers, elective surgery rescheduling, etc.
  • A similar machine-learning approach can help orchestrate patient flows at clinics, labs, the pharmacy and any unit within the hospital network that struggles with the operational paradox of being overbooked and underutilized at the same time.

An interesting metaphor for the future of hospital operations is how airport operations, air traffic control and sophisticated scheduling have transformed air travel for passengers. They, too, have enormous complexity and the mission-critical requirement of passenger safety in the face of challenging external conditions.

Three direct parallels:

  • For a single flight to transport passengers safely from point A to point B, it requires the “above the wing” services (boarding, food, crew) and “below the wing” services (baggage, fuel, tire check, other inspections) to come together seamlessly. Similarly, to perform even a routine surgery, services like labs, pharmacy, the clinician, the surgeon and the supporting team all need to come together to be able to safely and successfully treat the patient.
  • Every day, at any busy airport, tens of thousands of passengers  navigate their personal journey across connecting flights while relying on “invisible supporting services” such as bag transfers and re-bookings in the case of delays, weather systems, etc. Similarly, on any given day in a busy hospital, thousands of patients navigate their personal journey across a continuum of care while relying on the supporting services of labs, pharmacy, etc. to be timely and accurate.
  • The volume of airline passengers has grown from a few thousand to a few million per day, and airports and airlines have been forced to do “more with less.” Similarly, the Affordable Care Act and a growing and aging population combined with the increased incidence of chronic disease will require hospitals to do “more with less.”

The aviation industry has diligently invested in the required technology, systems and processes to monitor, measure, collaborate and orchestrate. Similarly, hospitals are beginning to invest in the technology, systems and processes to maximize patient access at each “node” and to streamline the linkages across nodes.

Just as the advent of air traffic control and fine-grained scheduling transformed airports like JFK from handling only a few hundred flights each day in the 1960s to managing thousands of takeoffs and landings a day within the same airspace, modern technologies and predictive analytics will lead to the creation of a similar air-traffic-control capability for hospitals. Assets like the OR, inpatient beds, clinics, infusion chairs and MRI machines will be far better utilized throughout the day. Many more patients will be treated within the same facilities, and they will need to wait far less between the “legs of their flight” across the continuum of care.

This post was written by Mohan Giridharadas, the CEO of LeanTaaS. 

Customer Perception Is Your Reality!

The quote in the headline — “The customer’s perception is your reality” — is from the renowned business trainer Kate Zabriskie, and I hope you agree it is absolutely true. No matter how excellent you think you are, or your company is, at service delivery, your future success as an enterprise depends principally upon how good you are in your customers’ minds when responding to their ever-changing needs. Or, as John Mackey (CEO, Whole Foods) put it, “For us, our most important stakeholder is not our stockholders, it is our customers. We’re in business to serve the needs and desires of our core customer base.”

But what are those needs? Are they those that you may have already identified, based on your experience? Has your considerable operational expenditure, in people and systems, really met what your customers need? Or is our thinking unconsciously restricted by our knowledge of what we can and cannot easily achieve?

There are many publications, a plethora of business processes ideas and of course the Internet itself, all crammed with customer relationship management theories. I don’t suggest that these are wrong, but what I do believe is that most financial services customers want something better than the superficial contact often delivered regularly by mailshots or e-mails. The “relationship” they require is more like that of their general medical practitioner! Namely a service that is accessible, resulting in knowledgeable and courteous attention, one that is effective, on call always but available only when needed.

This article focuses on customer perception and service delivery for existing insurance customers and associated stakeholders. More specifically about how appropriately the enterprise responds to customers’ post-sales questions, claims and changes about personal lines policies.

It might first be helpful to consider, in general terms, the prime means of post-sales service delivery in the UK currently deployed by insurance companies, brokers, claims service companies, etc.

These channels are principally face-to-face in offices; via the Internet; over the telephone, including SMS texting; and, to an under-developed extent, through mobile service platforms.

Branch contact used to be normal, but face-to-face customer contact seems on the decline. No doubt the cost of staff, the use of alternative technologies and the need to drive down costs have all contributed to the demise of the branch office. The challenge then is how to achieve the goal that Sam Walton (founder of Wal-Mart) described as “customer service that is not just the best but legendary.”

Well, I imagine that the words “call center” do not spring immediately to your mind as “legendary.”

At their best, call centers provide a good and necessary service, but I do not believe that the sophisticated telephony statistics and in-house customer surveys yield an entirely accurate picture of customer perception.

In the main, customer perception is that call centers are a dismal fact of life. They often describe their experience as an endless series of numerical options and pre-recorded messages. These are followed by an interminable wait brought to an unsatisfactory climax by what they perceive as a “factory service,” so often a conversation with an underpowered and strictly timed operator, who seems in a hurry to deal with the next call.

Is this the sort of post-sales service your customers deserve? Does it really surprise and delight your customer with “legendary” service?

From an enterprise point of view, call centers are generally sub-optimal. Staff turnover can be high, recruitment and training costs significant, with onerous levels of supervisory oversight. Management often experiences prolonged stress, justifying service delays and fretting how to improve service without incurring more costs. Most call center staff cannot make significant changes to policy records, or handle customers’ resulting needs themselves; instructions have to be prepared for other processing technical staff.

Is there a better or additional way, other than a call center, in which the increasing expectations of existing insurance customers can be met and exceeded? Is it possible to achieve this and at the same time drive a huge chunk of operational costs out of the business?

The answer is emphatically yes! In fact these benefits can be achieved quickly and cheaply compared with traditional legacy and Internet technology. The solution is to deploy the latest and powerful mobile technology directly to customers, to empower them to access their own records and to make self-service changes, raise claims and initiate inquiries directly to a database or a secure copy.

Today’s customer is never far from a smartphone or tablet. The expectation from an enterprise is that of mobile technology being available to post-sales and post-renewal. Customers do not want to be pinned down to call center hours or a static location from which to call to make changes or to deal with claims.

Any company that offers a post-sales insurance service that suits the time and place of their choice must surely have a significant and differentiated product. If that same company, as a result, is able to eliminate a huge percentage of its operational costs, then it also will derive a massive commercial advantage. Let’s see how this can be achieved.

To explain and to avoid confusion with traditional legacy solutions, I will briefly describe the provenance of modern mobile technology platforms.

It was not long ago that mobile phones were used solely for voice calls and texts. Today’s smart phones and tablets are multifunctional devices that can insert themselves into the very DNA of the customer-enterprise relationship.

This is possible by means of developing intelligent mobile processes. Operating systems for smart phones such as Mac iOS, Android, Windows and RIM are now fully mature and open a window of opportunity for the development of third-party software.

But quality matters, too, and development needs to be easy and intuitive to use because mobile users demand more choice, more ways to use their phones more functionally.

The Internet just allowed us to connect with anyone in the whole world. But with mobile technology we will connect anytime and anywhere with everything through “the Internet of Things” (IoT). Manufacturers and retailers are investing immense amounts of money in intelligent appliances, and very soon your home will be as smart as your car. This technology offers a unique chance for insurance enterprises to integrate intelligent mobile devices in their post-sales service delivery.

For example:

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How would this work in practice? Mobile and tablet applications are limited only by vision and imagination, and space in this article permits only a brief summary. There are two principal post-sales areas where advantage can be gained, namely policy changes/inquiries and claims reporting/progress.

Imagine your home and contents policyholder receiving a renewal notice and reviewing the cover. This might show that the sums assured need revision and that a newly acquired item of jewelry should be added; perhaps an optional extra such as legal expenses cover is to be considered. By means of an appropriate mobile phone or tablet, the policyholder “logs in” and views current policy details. No doubt this will include a reminder that renewal is almost due.

Using the form of graphic display the policyholder is used to (sliders and check boxes on smart phones for example) the cost of changes are modeled. More information about the legal expenses cover is requested, received and possibly some questions answered. Mid-term changes are frequent, too, so any relevant date and details of change may subsequently be selected once the policy records are accessed from the mobile. When the customer is satisfied with the modeled changes, the new risk profile is sent to the insurer and a new premium generated. If accepted (or remodeled), payment details are collected, and no doubt certain questions required by the insurer are “check-boxed,” instant confirmation is given and promptly afterward updated documents e-mailed to the policyholder.

All of these events take place at a time, day and location of the customer’s choice. Unless the customer chooses otherwise, no call center conversation is required; no staff are needed to manually process the changes. In this example, all the requested changes were within the insurer’s underwriting and rating rules; had they not been, then an appropriate message would be generated ensuring, that a call center contact is focused upon more specialized and justified issues, requiring a smaller number of trained and empowered people. In effect, the call center becomes a skill center, a quite different entity.

Reporting claims and dealing with claims progress issues can easily be imagined, and again the limit is process appetite and creativity. Mobile technology has the advantage of a camera, GPS and verifiable date and time. So this data can be assured and becomes invaluable within the claims oversight process.

Photographs can be taken, with assured dates/times/locations of loss-related events, damage, articles etc. These can be attached to a mobile claims notification, with appropriate inbuilt guidance, and sent to the claims department to initiate the process. The mobile can be used to receive calls, texts and e-mails. Even voice messages or videos from the customer can be attached. Adjusters can be appointed automatically subject to a “rules engine”; replacement goods can be selected and offered via the mobile connection; estimates and invoices can be generated or photographed for sending on to the claims department.

The effect of these customer processes upon service delivery is abundantly clear. But what of the opportunity to save costs? In my experience, between 25% and 50% of inbound customer calls are of a standard, non-exceptional nature. Conservatively, once fully operational, I would expect mobile technology for post-sales activities to drive out 30% of staff and call center costs of the enterprise. For those who also use call center or technical staff to actually manually process changes, as well, similar levels of savings could be achieved in that part of the operation.

At this stage it is reasonable to ask, if the technology is available now, the advantages so attractive and already being employed by other enterprises, why have insurers, generally, not yet filled this space?

I speculate that there are five reasons:

– The skills required to build mobile technology platforms are not generally available in most insurers’ computer departments.

Mobile process development is new and different, and simply importing legacy or internet systems on mobiles produces ugly, cumbersome customer applications. The solution is the careful selection of a third-party provider, working with staff, to introduce these new skills into the computer department.

– Core processes and enterprise data is jealously guarded by departments. Security is also of paramount importance.

They are right to be careful! These assets must not be put in harm’s way. Until complete confidence is established, the safe solution is to use replicated rules engines and validate changed data outside the core processes. The use of the latest and most secure encryption technology is paramount.

– Most IT departments have a tremendous backlog of legacy system updates. It’s essential but difficult to focus on a new mobile future when you are trapped in the technology of the past developments.

By using a third-party provider to quickly develop applications and train existing staff, an enterprise can begin to move forward and avoid being left behind by newer competitors.

– Development is seen as possibly expensive and probably protracted.

In fact, the opposite is true. It is surprisingly quick and relatively inexpensive to develop the latest generation of applications for mobile platforms compared with legacy systems. Payback can often be achieved within months of launch.

– There may be a lack of imagination or strategic understanding of what mobile applications can achieve.

It is, in my opinion, dismally true that some of the few mobile insurance “apps” available download little more than contact details, or a claim form. Recreating on a mobile what an enterprise already does on the Internet misses the point entirely and wastes a unique opportunity.

In conclusion, mobile technology has rendered the call center, in its current form, obsolete. The only question is how long the process will take. It will be fascinating to see the more agile and visionary insurance enterprises seize the opportunities presented by mobile technology.