Posts Tagged ‘workflow’

Electronic Health Records: Where they should be Going but aren’t

January 9, 2015

The past few years, mostly because of the Affordable Care Act, the adoption of Electronic Health Record (EHR) systems in the USA has seen a dramatic growth. Because of the rapid climb, EHR vendors have been trousering some pretty large amounts of revenue, billions of dollars, in fact. This is not a bad thing per se’, but as Congress suddenly realized this year, all that cash didn’t translate into giant leaps in innovation, as they predicted. Some of this is the result of a captive market, some because of psychosocial artifacts of clinicians, and some to do with that markets aren’t necessarily innovative.

One of the ways in which one can see the lack of innovation, or even basic maturity, is the degree to which clinicians have to type the same data over and over in different electronic forms. Not only do the EHR systems not interoperate very well between vendors, some don’t even interoperate with themselves! So it is a common sight to see a nurse type in records from a sheet of paper, then if they are lucky, copy and paste them into another form. If they are unlucky, they get to retype the same data multiple times in different EHR screens. If they are doubly unlucky, the system is also somewhat fragile, which isn’t unusual, and it aborts the session before the data is saved. In that case, they get to retype it all again when the system comes back to life. Sometimes this happens several times a day – in one case that I encountered, the clinician had to try fourteen times before the system recorded the data!

This is obviously a pretty abominable situation, and to get even the most basic degree of workflow into this is going to take a lot of effort and money. Luckily, the EHR vendors are flush and positively glowing pink with all that Meaningful Use cash in their fists.

The Goal

What I want to see isn’t beyond current technology or in the realm of science fiction, and not even where we ultimately want to be, but it shows where the thinking needs to head (In my opinion, that is).

What I want to see is the removal of the human from any data capture that doesn’t actually require their expertise.
Not really a big ask, given that we can put intelligence in spectacles and the average smartphone has more brains than it knows what to do with.

So let’s say a patient arrives for a consultation.

When they enter the waiting room, I want them to get a transponder sticker. These are dirt cheap, pretty reliable, and can be scanned without actual contact. At the reception desk, the clerk reads the sticker and associates it with the patient record. Now I can tally who left without being registered (elopement), how long it took (primary wait time), and at which stage of the encounter all the patients are (census).

When the patient is called, they are read leaving the waiting room, and again when they enter the examination room. The nurse or nurse practitioner scans them, and the patient record is already onscreen in the room when the nurse scans their ID on the workstation. Each vital sign collected goes directly into the patient record because the instruments are vaguely intelligent. Blood pressure, pulse-oximetry, weight, height, respirations, temperature, etc. are all directed from the device to the EHR simply by using them on the patient. These are all time-stamped, have the ID of who was using them, the ID of the device, and are shown as machine entries in the patient record.

Verbal notes can already be captured through speech recognition, but let’s say that the nurse actually has to enter this themselves. They don’t have to search for the patient record or the screen, those are already there, and they simply need to verify that the patient record is correct. (Although unless the patient swapped armbands with somebody, we are pretty sure who they are).

When the process has reached a certain point, the EHR can buzz the physician that the patient is close to ready. So no long wait while the nurse has to write things down or type in much, and no need for them to go find the physician.

A similar scenario unfolds when the physician enters: the room, patient, and physician are associated in an entry event because all three have transponder identities. Relevant patient data is already displayed when the physician scans their ID at the workstation to login, and again, any use of instruments captures data. Listening to the patients lungs with an intelligent stethoscope can capture the sounds, timestamp them, and put them into the correct place in the patient’s record. Even more wonderful, if the patient has any electronic records pertinent to the encounter, these can be transmitted from a smartphone Personal Health Record (PHR) app.

The only parts the physician play in capturing data is when expertise is required or when the machines can’t (yet) do it themselves. There is no reason on earth why a scale, blood pressure cuff, or pulse-oximetry device can’t transfer the data to the EHR themselves. Only the most antiquarian of medical offices don’t already have devices that display the data digitally, it’s just that we then typically ask a human to write it down or type it into the EHR manually. That is a bad use of resources, and opens up opportunities to get it wrong.

With time stamped machine data, the practice can start monitoring movement and wait times, and would be enabled to make adjustments to their workflow to optimize patient flow, and reduce unnecessary steps or waits. Staffing rosters and equipment placement can be evidence based rather than rely on guesswork, and bottlenecks in the processes will be far more visible.

Conclusion

The basic theory is similar to industrial engineering – don’t ask a human to do something that the machine can do. Free up clinician time, reduce transcription errors, and allow the clinician to focus on where their expertise lies – not in being low-level data capture clerks.

We should be demanding that equipment manufacturers and EHR vendors get their act together, and stop making clinicians do their dirty work.

That’s my story, and I’m sticking to it!

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The HealthCare Blockbuster Trio: Workflow + EHR + Activity-Based KM

November 19, 2013

The Emergency Room (ER) is a dangerous place to be, and the less time a patient spends in one, the better their chances of an optimal outcome.

This is a simple unpleasant fact, and one reason is a simple truism – people who really need to be in the ER tend to be very ill and if you are one of them, your odds are already sub-optimal.
Other than the rare hypochondriac with Munchausen’s syndrome, most patients in the ER are not in a good way – otherwise they would have fixed it themselves or gone to their general practitioner.
The other reason is both more sinister and complex: ERs tend to get crowded, chaotic, and triaged. The chaos is a result of a combination of crowding, acuity, variation, and stressed processes. Many ER patients really should be treated by a primary care physician, but go to the ER instead because they lack health insurance, don’t know how to gauge their condition, or their primary care provider is not open after hours or on weekends. The ER increasingly supports primary care by performing complex diagnostic workups not provided by primary care facilities, handling primary care overflow, and after hours care. (1)

The fact that ER triage’s patients is a frank (and normal) admission that demand has outstripped supply of services, but ER crowding is mainly a function of idiot politicians and a Gordian knot of infrastructure, policies, processes, technology, and people.

Let’s deal with the simplest but most unappetizing part first

Idiot Politicians

Politicians are those kinds of people who are vaguely of the opinion that laws can reduce the duration of gestation, change the behavior of pathogens, or turn aside hurricanes, typhoons, and tornadoes. I am not sure if this is the result of repeated head injuries on their part, bad genes, or just a lack of scientific training. The problem is that they will enact silly laws to satisfy donors, and these laws will tend to cut funding to primary care, education, nutrition, environment, safety, and a host of other epidemiological causes of injury, disease, and ill health. This not only increases the burden of sickness in the net number of patients, but also means that they will tend to have more serious health incidents, not address illness early on, and present in greater numbers, with more complex conditions, more often than would be the case in the null hypothesis in which there was no stupid politician making these laws.

Simply put, politicians as a class are a health hazard, and sadly, there is no cure for them.

Infrastructure and policies

Somewhat caused by idiot politicians, a sub-optimal infrastructure is often the result of policies that shape themselves to the laws that exist (see above).
Often the policies serve people with money rather than those with need, and as a result the infrastructure caters to heroic and epic conditions rather than those that cause the most harm and suffering to patients. This is somewhat because the people who get sickest and sicker more often tend to live lives that do this to them. They live in places that are more dangerous, have work that is more dangerous, have less education, nutrition, and access to primary care than the wealthier members of society. Low Socio Economic Status (SES) is generally speaking, also a health hazard.

As an example, let’s look at a very fancy cardiac unit, a world famous one.
The first successful human to human heart transplant was carried out by the pioneering surgeon, Dr. Chris Barnard at Groote Schuur hospital, in South Africa.
That’s right, not the US nor the UK or France, but South Africa.
In 2001, there were serious moves by the Western Cape government to close the transplant unit, and in the subsequent public and international uproar, one of those involved in the considerations made a rude, surprising, and very accurate argument. South Africa simply couldn’t afford a fancy 1st world cardiac unit serving mainly privileged white men who tended to have long histories of medical self-neglect as the result of over indulgence, when at the same time, thousands of low SES people were dying of entirely curable and preventable diseases like Tuberculosis. During the various brawls over the unit’s fate, the uncomfortable fact was that although the cardiac unit was a heroic and epic institution, it was far less clear if this was the best use of available resources. For every life saved by heroic attempts in the transplant unit, at least an order of magnitude more died because those funds and expertise were not being applied to the things that were killing far more people in South Africa.

Healthcare is often brutal in this way, and the example perhaps exemplifies how the diseases of influential people are more represented in the policies, and thus the infrastructure of a healthcare system than one might notice at first glance. Policies often translate into more and sicker people coming to the ER, and also less funding to address both the causes of the illness and technology and resources to address them.

Processes, Technologies, People

ER is a compression zone in the flow of patients, since many routes lead into ER, and frequently the wisest course when in doubt over severity and acuity of a condition, is to process them through the ER just in case the quietly seated patient quietly dies because nobody took a really good look with the right level of technology and expertise.

All clinician roles are stressful; let that be said before I draw the ire of opticians, dentists, and dermatologists. ER clinicians however are right up there with the highest stress roles in healthcare. Although it must be admitted that ER clinicians generally get to see better outcomes than some specialties, ER clinicians are usually presented with life in its raw state. Torn flesh, broken bones, and mangled people, some still with the smell of gasoline and tire rubber on their bodies, the smudges of nitrocellulose propellant from gunshot wounds on their skin, and lots of vomit, blood, and tears. ER departments are not restful, tranquil, or serene, and no amount of feng shui, fragrance sticks, or furnishings can change that. ER departments have to sort people rapidly into categories and actions to be taken, often in exact opposite order to instinct. Quiet and blue takes precedence over bleeding and screaming, necks take precedence over hands, clear fluids over blood in the ear.

As a result, ER departments have an urgent need to have supporting technologies such as ED Patient Tracking Systems and  Electronic Health Records (EHR), that can remember and track patients that might easily get lost or forgotten, and whose history will be collected accurately and quickly as they transition from the ambulance to the first-look nurse, then triage team, the nurse, perhaps more than a few doctors, specialty care, radiology, laboratory, and yes, accounts. Have they seen this patient before, are there allergies or prior conditions to consider, are they already taking any medications?
However just having an EHR system does nothing unless there is an underlying workflow, and the EHR integrates perfectly with that workflow.

ER workflow is both physical and virtual, and it comprises rules, procedures, activities, equipment, spaces, places, and people. Although some of the people can switch roles in an instant, they are deployed according to a process, licensure, and how the ER facility is physically structured. The very first person must rapidly assess where the patient most needs to go at that instant in order to get them to the right level of care the fastest, and to maximize the use of the very expensive and scarce resources available. The resuscitation team should receive the person with the cardiac arrest; the trauma team gets the one with the bones coming out of the wound, and so on. No sense in blocking the resuscitation bed with the patient with the broken arm. The workflow has priorities, and activities that have primary and secondary actors, and various technologies including equipment, medical gases and fluids, medications, and consumables such as needles, gloves, and dressings.

In figure 1 the fundamental structures of activities within a workflow are shown for typical industrial or business settings  (2), but these map directly to their medical counterparts. Tools relate to equipment and instruments, materials to medications, fluids, and consumables, while utilities relate to medical gases, suction, irrigation, and electrical power.

fig1

Figure 1. Workflow activity substructures

The implication of workflow is that knowledge is applied to the activities by actors in relation to the tasks they carry out and the requisites they use in doing so. As such to have a functional workflow that is supported by an EHR, the ER also needs to consider who knows what and how they will best come by this knowledge in order to apply it effectively at the point of care. The application of knowledge management principles to ER workflow expands this as illustrated in figure 2.

fig 2Figure 2. Knowledge Sources

All things being equal, the ER staff, deployed in space and sequence in a carefully monitored and calculated fashion will quickly identify urgency and action to stabilize, treat, and often admit patients with the maximum efficiency, because in illness, time counts.
However, even a perfect ER, operating at 100% efficiency, will swiftly overcrowd unless the patients can be routed to the next appropriate level of care as efficiently. Whether the next point of care is the patient’s home, their local hospital, or Intensive Care (ICU), the time it takes to process the necessary documentation and route them is not infinitely small, and results in backlog and patients piling up in holding areas in and around ER, and people die in these interstices of care.

The workflow thus needs to integrate with care beyond the ER, so that patients can be drawn off to the next point of care at least as fast as they are processed by ER, and this is where the integration of EHR across the institution comes into play. The workflows at the perimeter of ER can only effectively integrate with those of other services and points of care if the EHR enables seamless transition.

An example of this is the bed management system for inpatient registration. An ER patient that requires definitive care as an inpatient can only be transported to a ward if there is an open bed suitable for the level of care required. To achieve this, the ER clerk must be able to see with great reliability which wards have a currently open and clean bed that has the right associated services, technologies, and level of care. A patient requiring 24hr surveillance may require a telemetry bed, patients with mental health conditions may require special services, and fall-risk patients, and infectious patients have still other bed and location requirements. To complicate matters, ward configurations change, policies changes, and new medical norms arise, requiring the systems and the people to adapt smoothly to changes.
Reflecting on figure 2 one can usefully ask how the ER clerk would know what the current policies are with regard to the patient needs and available beds. The answer is that it will be a combination of embedding the knowledge in the EHR, recruiting people with the right prior application and hospital knowledge, training  on the EHR and the policies, and job aids that are either embedded in the EHR or available in conjunction with it.

Throughout the process from registration to discharge, the integrity of the patient’s record must track smoothly across transitions and locations of care, including follow-up and outpatient care.

Conclusion

Integration of workflow, EHR, and knowledge management methods can provide significant improvements in patient flow management in a hospital, and this can be seen in what is perhaps the starkest situation- the ER. Workflow ensures that the right things are occurring with the right actors and at the right time, while EHR avoids medical mistakes by tracking the patient and their health throughout the system. Knowledge management asks the important question of how all the actors know how to do what they are expected to do. This applies to all the actors involved, whether they are clinicians, administrative staff, the patients themselves, or those that care for them.

Acknowledgement: For his invaluable input on ED Tracking, ER operations, and crowding, special thanks are due to “Mr. BMS” Hub Freeman, MSA, RN, Nurse Executive – BC, Clinical Director for Systems Efficiency and Flow Improvement, Veterans Health Administration

References

1. Hospital Emergency Department Use, Importance Rises in U.S. Health Care System. Hospital Emergency Department Use, Importance Rises in U.S. Health Care System. RAND May 2013.

2. Loxton, Matthew. Knowledge Auditing: An Activity-Based Method for Organisational Success. s.l. : Ark Group, 2013. ISBN: 1783580755.

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Matthew Loxton is a certified Knowledge Management practitioner, and is a peer reviewer for the Journal of Knowledge Management Research & Practice. Matthew works at WBB as a senior analyst applying KM principles to Health IT implementation. Matthew holds a Master’s degree in Knowledge Management from the University of Canberra, and provides pro-bono consulting in Knowledge Management and IT Governance to various medical institutions.

Activity-Based Auditing and Workflow

October 14, 2013

In 2011, I was building an on-boarding plan for an innovative aftermarket logistics model at multinational electronics firm, and I needed to have a knowledge audit element.
Since auditing of knowledge, while not a fully mature science, is at least a very well trodden area of Knowledge Management (KM), I had no doubt that I would find a suitable auditing model within a few looks at the work of fellow KM practitioners, a glance in my bookshelf, or a few minutes browsing websites.
However, to my surprise, although there were indeed a great many knowledge audit templates, none fitted the level of detail required for a production line environment like the one I was facing.

As a result, I needed to build a knowledge audit model almost from the ground up that would match the workflow nature of the business environment in a highly complex and large electronics repair organization that was geographically spread across the world, and which included an integrated supply chain. The target was a reverse-logistics chain that included the customer, a call center, logistics partners, multiple repair centers, and the original equipment manufacturer.

Once the model was created, the basic methodology was published in the JKMRP as a position paper on critical activity knowledge auditing for other KM practitioners to use[1]. Although the intention was to solve a practical gap in a specific area of reverse-logistics, it was obvious in retrospect that the audit model was well suited to any environment in which there are specific goals served by a documented workflow, from clinical and surgical environment, to manufacturing and repair industries. In response to requests to expand on the paper, the Ark Group (a Wilmington company) published “Knowledge Auditing: an Activity-Based Method for Organisational Success” [2]. (Free intro and sample chapter available for download).

Like many long journeys, this one started with a very innocent-looking question: How does the person carrying out this task know how to do it?
Yet when I asked this in practice for repair activities, it became obvious that there was some uncertainty about something that was critical to success.
Laying out the flow sheets of how the repair process worked, it was clear to everyone what sequential steps were to be carried out, and there was reasonable agreement on whom the actor would be, but less clarity on how they knew how to execute.

You might ask why this is important to anyone, yourself in particular.
There are three market pressures and three areas of neglect that make this important, and if you don’t have a solution, you are going to be buried.

Firstly the market changes:

  1. The “Silver Tsunami
  2. Market Turbulence
  3. Globalization

Now the areas of neglect:

  1. Hiring is a mess: In most firms little better than flipping a coin, in many a horror of wasted talent and superstition that is exceeded only by the secrecy and invisibility of just how bad it is. Hiring is typically done with no regard to knowledge.
  2. Training is ineffective: Usually decoupled from the actual job and doing little more than putting “bums on seats” (however you would like to interpret that).
  3. Job instructions are useless: Mostly people have to interrupt each other or create their own “cheat sheets”, which are often out of date, faulty, or downright irrational.

The most knowledgeable people are going to be leaving, there are too few replacements, and those replacements don’t have nearly the training and knowledge of those leaving. The time taken to on-board or even fire up off shoring is excessively long, and efficiency is way down and matched only by worker disaffection.
The market changes rapidly and big players in the top 500 vanish so fast that one can scarcely keep up, while disruptive technologies and business models spring up as if from nowhere. In addition to new customers, new competition, and rapid changes in technology that demand very agile responses and planning, the share of market capitalization has shifted dramatically over the last fifty years. In figure 3 the asset components of the S&P 500 market value is broken down between tangible (standard) and intangible assets. Clearly what a firm knows has become far more important in most cases than what tangible assets like property, equipment, and even cash balance they have.

Figure 3. S&P Market value by asset type Courtesy Ocean Tomo

In a globalized world, new competition and new customers will spring up wherever the market is, not where traditionally located or preferred, and those firms who are unable to rally flexible knowledge application are at a strategic disadvantage to those who know what they know and know how to scale up or down to match market pressures.

If your business has a workflow, then the audit process is designed to identify, on-board, and support workers faster and better, and to result in improvements in the organizational objectives served by those workflows.
The audit does so by making hiring, training, and job aids closely tied to the actual task execution.

The basic auditing principle is not all that hard when one looks at it coldly. The firm comes about to having an actor with the right knowledge, in the right place, and at the right time by some combination of:

  • They were hired to have that knowledge already;
  • The actor was trained in some way; or
  • A job aid would be provided to them at the time of execution.

Precisely which knowledge and what it pertains to would require a bit more granularity, and that hides in the diagram in figure 1 below.

Figure 1. Workflow Sub-Structures

However, this obviously entails a lot of analysis, so another core component of the audit is to focus only on the knowledge that is individually necessary and also collectively sufficient to achieve the organization’s critical goals. After all, organizations have a lot of knowledge that really isn’t on that critical path between work and their main organizational aims. Figure 2 traces the path from the organizational objectives to the individual tasks that lead to their achievement.

Figure 2. Critical Path

So what should you do?
Here’s my suggested shortlist:

  • Gather a team to perform an audit to identify the critical workflows and to audit the knowledge needs
  • Update hiring practices to match the actual knowledge needs at an activity level, and throw out vague and wishful role-based hiring methods
  • Refactor training to align with work activity knowledge needs
  • Build a knowledge base of job aids suited to the activities in the critical knowledge value chains, and that will deliver job aids in a fashion appropriate to the working conditions
  • Build an audit practice that monitors for deviation and applies Lean principles to fixing wasteful workflow

That’s my story, and I’m sticking to it.

References

1.    Loxton, M.H., A simplified integrated critical activity-based knowledge audit template. Knowl Manage Res Prac, 2013.

2.    Loxton, M.H., Knowledge Auditing: an Activity-Based Method for Organisational Success. 2013, London: Ark Group.

Matthew Loxton is a certified Knowledge Management practitioner, and is a peer reviewer for the Journal of Knowledge Management Research & Practice. Matthew works at WBB as a senior analyst applying KM principles to Health IT implementation. Matthew holds a Master’s degree in Knowledge Management from the University of Canberra, and provides pro-bono consulting in Knowledge Management and IT Governance to various medical institutions.


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