Posts Tagged ‘Technorati Tag’

Learning from the Past – Risk Management at National Scale Using PHR

July 23, 2014


The 2014 World Development Report from the World Bank sketches how confronting risks, preparing for them, and adopting appropriate coping strategies can make a vast difference in outcomes, sometimes at an epic scale. In 2010, both Haiti and Chile were victims of large natural disasters of similar destructive capacity. Both countries experienced serious earthquakes, the larger of which struck Chile. However, while Chile suffered a loss of 300 lives as a result, Haiti lost in the order of 250,000 lives.

The World Bank attributes this to several causes, one of which is the degree to which Chile learned from a previous experience and invested in insurance, undertook preparation to reduce risk, and improved their capacity to cope with the aftereffects of future disasters. Chile confronted the lessons of the previous disaster, there was a national awareness, and as a result, building codes were changed, and the country took insurance both against damage and in terms of divestiture of investments and commerce. These changes allowed Chile to suffer less damage to people and infrastructure, recover faster from the shock economically, and to learn from what worked and what did not. Without these investments, it is believed that Chile’s death toll in the 2010 earthquake would have been of an even greater magnitude than that of Haiti.

The WDR2014 report is an evolution from early risk management approaches, and instead of the highly technical perspective taken in earlier years, the report views risk management as a long-term and strategic process. The WDR2014 report sketches two principles in risk management: To be realistic, and to build foundations. In the former, they are recommending that risk reduction attempts be pragmatic and simple rather than theoretical and extensive, and in the latter case, they are advising that risk reduction efforts build on each other and take a long-term view. To comply with this advice and to manage risk effectively requires that the efforts take into account several obstacles, such as the information requirements of the population involved, human behavior and change, resources available, and the uncertainty of risk.

Risk Management in the WDR2014 report thus rests on four “pillars”

  • Knowledge
  • Insurance
  • Protection
  • Coping

The focus of this article takes a cue from the two principles, and offers a narrow perspective on a single issue, that of the health records of people forced to migrate because of shocks such as natural disasters. This focus addresses the knowledge needs when receiving healthcare organizations must care for refugees and people affected by shocks such as natural disasters, but could hold true for any form of shock in which healthcare delivery was disrupted. The paper addresses a form of insurance in the shape of planning for eventualities, protection from medical delays and mistakes, and a coping strategy for dealing with migrant patients or disrupted healthcare delivery.

Case: Typhoon Haiyan 2013

In November of 2013, typhoon Haiyan reached the Philippines with the strongest winds ever recorded. As a result, the infrastructure was severely damaged, a large proportion of the population was displaced, and over six-thousand people died. The Philippines comprise over 7,000 islands, and few hospitals or health care providers (HCP) have Electronic Health Records (EHR). One highly specific problem was that people’s health records became unavailable both for those who fled and to those who stayed but were unable to reach their HCP.

For this article, a local doctor providing endocrine care was interviewed on Twitter using the hashtag #wdrrisk.

Throughout the typhoon, many Tacloban residents went to Manila either to escape danger or join family or friends who had left, and of these were people who were already ill with current or long-term chronic illnesses such as cancer, or became ill while away from their homes in Tacloban. Few people had made provision to take their medical records with them, and valuable medical information such as test results was lost or otherwise not available to HCPs in Manila.

The doctor interviewed for this paper is an endocrine specialist based in Manila, and saw many patients who were refugees from Tacloban. Patients typically had no documentation of their medical history, and no ability to access the facilities in Tacloban where their records were kept. Because few medical facilities in the region use electronic records available through the cloud, even those patients whose providers were on an EHR lacked the ability to access their records. Patients typically have only a vague recollection of what tests or procedures they have previously undergone, when these were carried out, and what the results were. As a result, patients without medical records experienced increased risks, delayed care, and additional burden of repeated tests. Where patients were on medication, a lack of a definitive history regarding dosages, patient reactions, and allergies required that HCPs started drug regimens from base dosages and take a conservative and cautious approach in order to avoid potential overdose or adverse reactions. As a result, many patients may have experienced sub-optimal results until the drug selection and dosages were calibrated to their individual needs and responses.

The doctor reported that repeating tests delayed treatment, increased patient risk, and raised the cost of care, but some tests cannot be repeated at all because the results are based on historical progression of a condition. The doctor was unable to fill in the blanks in some cases, and was left with an incomplete clinical picture that increased patient risk. For example, for some chronic patients the doctor needed histology test results that are helpful in cancer staging and which could not be reconstructed. Without these historical data, the doctor had uncertainty and had to make best estimates that may have increased patient risk or resulted in sub-optimal care. The lack of a longitudinal view of these patient’s history and healthcare journey, lost or missing data, and gaps in patient history increased the risk of inappropriate or ineffective care.

Personal Health Records

In order to provide effective healthcare, clinicians and other providers need information related to the patient’s present condition, past medical history, and core health records such as medication use, existing conditions and treatment, and medical images, prescriptions, and procedures. These are usually kept by the person’s primary care facility, and may be kept either as physical records such as patient files, x-ray plates, and the like, or as electronic records and images. However, when the patient migrates or their provider’s infrastructure is disrupted, these records may be unavailable. Personal Health Records (PHR) are an alternative that gives individuals the ability to either carry their health records on removable storage such as thumb drives, DVD, etc. or to link to them on the web using a secure repository, e.g. Microsoft HealthVault.

PHR puts the patient’s medical history in their own hands in a way that is likely to be transportable during a disaster, and unlike paper records, can be encrypted and secured in order to maintain patient privacy. The downside is that PHR relies on a certain level of technology and computer literacy on the part of the patient to realize the full benefits. However, simply providing the patient with their records in the form of an encrypted memory stick requires minimal computer literacy on the part of the patient, and is more likely to accompany the patient and be available during disasters than paper records.

The advantages of having PHR are:

  • Faster triaging leading to fewer delays in care
  • Definitive drug and test data, enabling better targeting of treatment
  • Longitudinal views of illness progression, allowing more appropriate treatment and drug dosing
  • Documented endorsement back to their home town HCP, allowing better continuity of care


Tacloban had been hit previously by natural disasters, and although many aspects of the four pillars of Knowledge, Insurance, Protection, and Coping had been addressed with regard to physical infrastructure and administrative processes, the need for maintaining the fidelity of medical histories was not adequately addressed. Lack of learning from those events with regard to medical records resulted in preventable morbidity and mortality across the region, but there is hope for improvements due to new frameworks. The PHR framework for the Philippines described by Dr. Alvin Marcelo outlines a way in which lessons from Haiyan and other natural disasters in the Philippines could be put to use in creating a way to utilize PHR to avoid losing valuable medical data, and reduced cost, patient risk, and delays in provision of care during disasters.


This paper was developed as a result of interactions with the participants of the #HealthXPh tweetchat where the issue was first discussed. Further thanks go to #HCLDR, #BioEthx, and #HCSM tweet groups. A special thank you is due to Dr. Iris Thiele Isip Tan for her willingness to be interviewed online for this paper and for providing insight into the effects of not having access to patient history during disasters. Doc Iris also provided the links to the PHR framework created by Dr. Marcelo.

The Connected Patient: My Adventures as an ePatient

March 26, 2014


Firstly, let’s talk about what this is.

This is a blog – not an academic or research paper, not a product analysis, and not a study on healthcare.
It describes my experiences as I have pieced together one approach to connected health, and how I went about that.

With that disclaimer, here we go.

One of the big themes in healthcare over the last year has been the concept of “Connected Health” and the “ePatient“, and considerable hope is pinned on the idea that if patients are more active (and discerning) in the monitoring and maintenance of their own health, and use of healthcare services, population health will improve and healthcare costs will drop.
The premise being that autonomy and control will lead to better health outcomes at a lower cost. It all happens at the corner of individual responsibility and public health.

There is a lot of talk in the industry about a patient driven revolution, one that acknowledges that patients understand the impact of their disease and the associated treatments, that sees an urgent need for clinicians and patients to work in partnership , and accepts a need to challenge the status quo of practices and behaviors. (BMJ 2014;348:g1209). Tessa Richards, blogger at the BMJ, speaks to this with regard to patient data, and the role of the patient as an active participant, rather than just the subject of data within an EHR.

Part of this puzzle of improving healthcare is the concept of patient generated data (PGHD), and the idea that data on vitals, diet, and exercise, immunizations, sleep, and use of medications can be monitored by the individual to guide their own choices, and also be sent to their primary healthcare provider (HCP) – typically the person’s general practitioner. These data would fill in a more complete health picture, and the HCP could monitor and see patterns emerge that allowed lower-cost interventions to prevent or mitigate chronic disease. There could be fewer office visits, lower probability of emergency room (ER) visits, hospitalizations, or readmissions.

The three salient components of this view are:

  • Increased autonomy and control lead to improved health choices by the individual
  • More data over longer periods in the hands of HCPs lead to more focused and timely interventions, that will lower the use of high cost medical services
  • Monitoring of basic health and chronic conditions can enable better and cheaper care

So far, so good.

There are some behaviors that this is likely to give rise to, mostly for the better.
If providers know that their notes are going to be shared by their EHR with the patient’s PHR, they are going to take more care and be more complete than if they think only they will ever read them. This also drives patient compliance since the connected patient will be able to re-read the notes and instructions rather than walk out of the consultation room in a daze and then try to remember all the things the provider told them. The implications for patient safety are also important – being able to actually read the provider’s instructions are a vast improvement over trying to recall them from memory.
If patients think that skipping on walking for a few days or eating five burgers in a week is going to wind up alerting their doctor, they might be motivated to behave in a slightly better fashion.
It isn’t that this knowledge stops unhealthy behavior on both sides, they could simply not report, or think “what the heck”, but it certainly is likely to have an effect to the better, and for many problems, just a small change in behavior will be effective.
On the cost side, it means that instead of only showing up at the provider when there are symptoms, unhealthy behaviors and emerging signs and symptoms can trigger an alert to the provider to intervene. A single provider can handle a great many more patients by exception than in person. Monitoring a hundred patients in this way is far cheaper than seeing a hundred at the office, and far cheaper both in terms of time and the level of intervention.

In practical terms, a nurse practitioner could monitor for values coming across from the PHR to their EHR that exceed upper or lower control parameters of a large number of health metrics, ranging from exercise and sleep to compliance with meds, diet, or blood pressure and glucose measurements carried out by the patient. These alerts can trigger them to look closer at what is going on in the data over time for a specific patient, and either respond directly to the patient with suggestions or make a recommendation for an office appointment. They could also routinely examine individual patient records and reach out to the patients with encouragement or suggestions. Since the data include a large number of population health markers, new discoveries in medicine or changes in protocols could lead to a targeted outreach to patients with new information, suggestions, or closer monitoring.

Worth mentioning is that the connected patient is very important to the industry move towards patient care teams and initiatives like the patient centered medical home.

(My) Technology Approach

Of course there are technical and logistical considerations, such as whether people are able to generate health data without undue complexity and effort, whether they are able to get the relevant data into the hands of the HCP, and whether the HCP has the technology to do something with the data.

As an experiment, I put together components of PGHD to monitor some basic health data of my own. I selected a relatively low-cost approach, and one that at face value I would be likely to be able to sustain over a potentially indefinite period.

Firstly, I experimented with a range of fitness apps on the Android platform, and various Personal Health Record (PHR) applications both on the device and cloud based.
Some I rejected after only a short while due to stability issues or ineffective functionality, and I gradually arrived at some specific requirements based on hands-on experience.
I selected, and then signed up for, a Microsoft HealthVault account as my primary PHR, since this provided a fairly comprehensive set of health records in a free, cloud-based solution.
This choice naturally limited the usefulness of many of the Android apps, but since interoperability with a secure and extensive cloud-based repository is important, the remaining apps are more realistic than ones that are standalone and can only store health data on the device.

Health Records

Health records span an enormous field, from diet, through exercise, to medical records such as conditions, medications, and labs.
To give you an idea of the breadth of the health records that can be stored to HealthVault, here is a snapshot of the fields that can be shared from HealthVault and a carer or an HCP. This is but a small drop in the ocean of data that could be collected on a person’s health, and a truly quantified self would be an epic undertaking, far beyond what we can currently achieve with any sort of scalability.

Figure 1. HealthVault Sharable Data

My next step was to transition from the somewhat inaccurate (but free) step-counters and fitness apps that I could download onto my smartphone, and buy a FitBit Flex.
The Flex was chosen according to:

  1. Interoperability with HealthVault
  2. Price
  3. Features and reputation

The FitBit Flex tracks some things automatically, and more things manually.

Automatic Manual
Step count Weight goal
Distance walked Food consumed
Calories burned Water consumed
Very Active Minutes Sleep Activity*
Sleep Activity* Exercise
Calories remaining


Sleep activity is one of those that is partly automated and partly manual input, and here’s how it works.
Since the Flex can’t tell if you are awake or not, you have to put it into “sleep” mode manually, and then take it out of sleep mode again when you wake up. This of course leads to some days of missed data because you either forgot to put it into sleep mode or to take it out again. The way in which it is done also presents a few challenges – it works by tapping on it three times in rapid succession, and this is mimicked by some day to day actions like knocking on a door, clapping, or some kitchen activities.

So if you applaud during a show, you have to verify that the Flex doesn’t think you are sleeping.

To get the data into HealthVault requires setting up the FitBit smartphone app and configuring HealthVault to receive data from FitBit.
This process was fairly smooth, but not without its share of oddities, like waiting 24-48 hours for the first upload. Initially I thought I must have misconfigured and wasted a lot of time troubleshooting a working configuration.

Obviously not all fields are interoperable between FitBit and HealthVault, and even within a single concept, not all the field dimensions are interoperable or visible to the user.
For example, sleep and exercise data are transferred but there isn’t a perfect match of fields.


FitBit Field FitBit Value HealthVault Field HealthVault Value
Time 20:58 Bed Time 8:58:00.000 PM
Time 06:01 Wake Time 6:01:00.000 AM
Sleep Time 8h 20min Sleep Minutes 500
? ? Settling minutes 7
Wake State fully awake
Restless 18 min x 13
Awake 11 min x 2


Some values captured by FitBit, such as the Restless and Awake periods are not being used by HealthVault, while two of the values that HealthVault evidently received don’t appear to match anything that the FitBit app displays. “Settling minutes” is either received or calculated by HealthVault, but doesn’t show up in the FitBit app, and the meaning of “Wake State” is unclear and doesn’t obviously map onto anything in the FitBit app.


FitBit Field FitBit Value HealthVault Field HealthVault Value
Distance 4.92 miles Distance 4.92 miles
Calories burned 2,544 Calories burned 2544 Calories
Steps 10,157 Number of steps 10157 Steps
Very Active Minutes 67


The exercise interoperability maps slightly better, but also has a field in the FitBit side that doesn’t map to anything on the HealthVault side.

All in all, the average user should be able to navigate and configure this without help, and can get some basic health data uploaded from a device like FitBit to HealthVault.

Medical Images

Medical images are a challenge, and typically if you want to provide images to your provider or upload to HealthVault just for your own record, you need a third application that can convert jpeg or png images to Digital Imaging and Communications in Medicine (DICOM) format. It isn’t as simple as taking a photo of the lump on your hand and uploading. Firstly you need to get the photo as a jpeg (easy with a smartphone), upload to an application such as MIPAV and then navigate around a fairly large number of fields to be filled in that are part of the DICOM metadata standard. Some DICOM apps are somewhat inscrutable and at this point they probably assume you are a radiologist or somebody in the field. Typical data you will need to enter include Date, Patient Name, Description, Study Instance UID, Referring Physician, Study Type, and Body Part. It was obvious that the apps were geared towards practitioners rather than patients doing their own imaging.

In my case it took quite a few attempts, and I had to get HealthVault Support (thanks guys) to help troubleshoot. It turned out that the MIPAV app was incorrectly packing a certain required field with spaces that was meant to be null, and HealthVault was applying the standard rigorously and rejected the image. As a workaround I first converted the image to jpeg-2000, and then into DICOM, and that allowed it to upload.

In terms of general usability and maturity, I would say that image uploads are not yet ready for the average user.


The next challenge is to transfer the data from HealthVault to your healthcare providers or to get your medical images and data from your provider.
For this I set up the HealthVault Message Center, and there are a number of options.

At the lowest level of interoperability, you can simply print out the health record from HealthVault and take it with you to the provider appointment, and then get paper records back from them after the appointment and re-enter the data into HealthVault or scan them and load them into HealthVault– not very satisfactory either in terms of efficacy or security. Losing a piece of paper is a very real possibility for some of us. Scanning them in is fairly simple if you have a scanner, and you can upload them either as a Continuity of Care Document (CCD) or a Continuity of Care Record (CCR), This is a bit of a cheat, since CCR and CCD are actually competing healthcare record standards, and have specific fields and meanings that would not be parsed into computable health data from just uploading a scanned document. However, it is better than leaving the paper lying around in a file folder, and if they are in HealthVault you at least have an opportunity to find them again and nobody else will chance upon them while looking in your filofax for the electric bill.

A second option is to set up a provider or custodian in the Message Center, provide their email address and optional password, and then select which of the data in Figure 1 you wish them to be able to see. This however requires a provider to navigate to the website and to go through the login process. It is more secure, under the patient’s control, but requires a fair amount of effort on the side of the provider, who will need to keep a record of the login details for each ePatient. This is not really a scalable model since from the provider’s side it would require them to keep a record of each patient’s chosen PHR, the login procedure, and login credentials. Not all patients will share the same things, and not all PHRs will have the same fields available or in the same format, so it would be a very complicated world for the provider once significant numbers of patients share in this manner. It is the flip side to the mistaken idea that patient portals are a solution, but in that case each patient would have to keep a record of multiple provider portals, logins, etc. Since the average person has ~4 providers, and patients with chronic illnesses have ~15, portals simply don’t scale well.

The most integrated option I had was to set up a Direct account in HealthVault that gives you a <yourname> address.
This address only sends between Direct addresses, and is encrypted – so no spam and pretty secure. No paper records lying around, no manual portal-surfing, and no proliferation of user codes and passwords to remember. The patient sees everything in their chosen PHR and the provider sees everything in their EHR.

HealthVault even provides you with a natty little printout or email that you can give to your provider that tells them what to do:

If you are using an electronic health record (EHR) system that is certified for Meaningful Use Stage 2, then your software may be able to generate a CCDA and send it to me using the Direct protocol. (As you may know, Direct is a security-enhanced health messaging protocol designed to help protect health information when it is sent from one computer system to another.) Your EHR software vendor should be able to provide instructions. If you can’t yet send information via Direct, can you give me electronic records another way, such as on a disc? HealthVault accepts structured information in CCDA, CCD, CCR, and BlueButton formats, as well as information in unstructured files such as images, PDFs, and text. You can find more information about HealthVault and how it supports Meaningful Use Stage 2 at

Microsoft provides ample educational and instructional materials for providers, such as this overview on sending health information to patients

This option allows health records to be sent securely and effectively from the provider’s EHR to your HealthVault account and vice versa, with no extra work on the providers side, and only one login to your HealthVault account to you as the patient.

So far so good.

Unfortunately for me, this is where the wheels come off because of my four healthcare providers, none are able to use Direct.

  1. General Practitioner in Colorado: Only has paper health records
  2. General Practitioner in DC: Has an EHR, but staff don’t know how to get it to work to provide electronic records. (They spent huge money for an EHR but still print records)
  3. Dentist: has an EHR, but doesn’t have the functionality to work with Direct. Instead sent me my dental images over unencrypted email (!)
  4. Optometrist: has images on a standalone machine that doesn’t connect to anything, and all other records on paper

So at the moment I have limited ability to do any real work as an ePatient or be part of a meaningful care team with my providers. The technology is ready enough, cheap enough, and usable enough to support at a minimal level, but my providers are just not there yet. The question that occurs to me on many of the #bioethx, #hcldr and #hcsm tweet chats, is that at some point I might start looking for providers that are further along the curve, and are willing and able to connect. From a provider perspective, this might be a competitive advantage issue, and providers that aren’t able to offer ePatients a workable data exchange schema may find that their patient population is dwindling and they are left with high-cost low profit patients.


So what did I learn?

Firstly, you can get basic health info including allergies, insurance details, vitals, and essential fitness data into a handy, secure, and easy to use PHR.
Secondly, if you are conscientious, you can keep track of things like blood pressure, diet, water consumption, alcohol and smoking, etc. in the PHR, but you will have to stick with it and remember to keep inputting the data.
Thirdly, if you have a participating provider, and they are also ahead of the curve, you can start transferring some pretty useful health data to them, and get responses back with useful guidance. This should enable you to have better health, get expert advice, and do so cheaper and more efficiently.

The future looks better though – and probably just in time for Meaningful Use 3: weight, blood pressure, sleep, etc. will be things that can automatically be sent to a provider.
The ability to collect and share health data with a virtual team of providers is a game changer, and is allied to the ability to set personal targets, monitor dietary intake and exercise, collect vitals over time, through the combination of wearable tech and Meaningful Use.
It occurs to me when I wait for my turn in a provider’s waiting room, that the bulk of visits to the provider could be done remotely with these tools, and my provider team need not be in the same practice, town, or even the same country. There is nothing at this point that should stop the ePatient from building a care team themselves that might span the globe, and achieve better healthcare, cheaper. A big artifact of the connected patient may be the mass customization and commoditization of healthcare that many other industries have experienced over the last 30 years.

Perhaps it is time.

The Ethics of Knowledge: The Taboo Topic of Our Times

November 11, 2013

This blog post doesn’t set out to provide any great answers, but hopefully lays some of the groundwork for the question of knowledge ethics.

Usually discussions about knowledge management revolve around the perennial topics of technology, teams, and talk. If we aren’t exalting or defiling the latest SharePoint application or collaboration platform, we are arguing about teaming and communities, or expanding on how everything is about stories and story telling. The one topic that never seems to enter the fray is ethics. When is sharing morally right, and when is it better to hoard or hide, than share? What about employees and employers that lie about knowledge?

What of secrecy and privacy?

Let’s roll back time a little – It wasn’t all that long ago that doctors routinely held back information from patients, and especially so from women, and the concept of a “freedom of information” law was not just absent, but was unthinkable to most governments. It wasn’t that healthcare providers were swine back then and dead set to harm their patients, in fact reading the medical texts from then, it was thought to be a kinder and more responsible thing to do than to burden the patient with unwelcome knowledge. Now, of course, we see this as unconscionable paternalism at best, and outright abuse at worst – which of course begs the question of what we might be doing right now that future generations will look at and wonder “just what were they thinking?”.

The one area in which the ethics of knowledge gets some play is in ownership of knowledge, largely because money comes into play, but also because of the concept of secrecy.

First the money

Almost all cultures have some sort of regulation of intellectual property – knowledge that can be said to be somebody’s property, to use, rent, or sell as they see fit. Therefore, patents can be held by someone and denied to others, and the owner has legal recourse if that knowledge is used in any of a number of ways that they don’t want. Intellectual property laws and treatments have expanded over time from simply protecting logos and brands, and patents and copyrights, to making some forms of intellectual property a fungible asset in the eyes of the law. In some cases, one can use a copyright or patent as collateral for a bank loan, and patent auctions, swaps, and collectives are a frequent feature of modern business.

It this sense, there are a few quandaries about who exactly owns rights to knowledge that somebody acquires through the course of their work or as part of their career. Most employers ask that employees sign expansive intellectual property rights over to the employer, and many of these are probably neither legal nor possible to enforce. We might then ask how moral it is to try to turn the employees mind into a lockbox, and to attempt to deny them the basic freedom of thinking up new ideas, to synthesize experiences into knowledge, or seeking to improve their station in life by applying that. Should the employer have first rights to something that developed in the mind of the employee, forever? Seems wrong at so many levels.

That was the easy part.

Development and beneficiation

It is probably safe to bet that everyone comes to work on their first day with some level of knowledge that is needed in the organization’s value chain. Presumably, the payment of wages is recognition to some degree of this knowledge, and that the employer pays for its use in achievement of organizational goals. When firms pay for training or when training is carried out during paid hours, the firm invests in developing knowledge that they expect to be used towards operational goals. Many firms require the worker to remain in employ for some period after training, and this is explicable in terms of the value of the knowledge, or at least the cost of creating it. By that standard, the worker owes it to the employer to apply that knowledge to achieving operational goals set by the employer. It becomes less clear when the employee takes the experience of work itself to increase their knowledge. Does simply being in that environment create a duty on the part of the worker if that exposure leads to them having new knowledge? Employees may carry out studies on their own time, or undertake other forms of discretionary self-development that result in a growth or refinement of their knowledge. Do they owe something to the employer for the exposure to a work environment that develops their knowledge? Does the employer owe the worker something if they put that new knowledge to work in the interests of the organization? Sometimes organizations clearly do reward self-development either in the form of direct pay-rate raises, or indirectly through expanded roles or promotion.

Hoarding and Hiding

In the plainest sense, hoarding can be either ethical or unethical – there may after all be reasonable justifications to keep a private stash of knowledge, whether that is tacit or explicit. For example, if the existing knowledge repositories are unreliable, one may simply set up a personal cache to prevent downstream risks of needing it and not having it at hand. Some forms of hoarding, however, may imply that the knowledge is thereby unavailable to others who might need it as part of their work. In knowledge hiding, knowledge is withheld from access by others; it may also be deliberately kept secret so that others are not even aware of its existence. One might argue that in some firms there are abusive or manipulative environments that might make it ethical for the worker to respond by hiding knowledge, but clearly, there is an intention to do harm at some level. As an aside, knowledge hiding may be a clear indication of a lack of attachment when the worker hides knowledge at work that is of value in the course of business operations.

Plain old lying

In a similar vein, and perhaps more frequently, workers and employers may mislead each other with regard to knowledge they claim to have. An employee may give indications, either overtly or tacitly, that they have knowledge or a level of knowledge that they do not in fact have – perhaps taking payment for a state of knowledge that they do not actually possess, especially when they are offered a job based on knowledge they claim to have. In the case of employers, there may be an impression created that they will provide the worker with access to knowledge or opportunities to develop knowledge that do not exist. Employers may lead the erstwhile worker to believe that they will be exposed to knowledge that will be of value in terms of their professional development. Most commonly though, the employer may mislead the worker as to what knowledge they will be using in the course of the role. Many workers discover to their immense disappointment that the true nature of the role they accepted is unlike what they were led to believe, and that skills and knowledge they anticipated using, lie fallow. In cases where these skills or knowledge are core to the person’s self-identity, the person may experience severe and even debilitating stress.

Some experts estimate that up to 80% of job applicants lie about the knowledge they possess, but this is probably dwarfed by the degree to which employers lie about the opportunities that employees will have to use, develop, and acquire knowledge that will be to their benefit.

Up close and personal

People also hold that some things are private and even secret to an extent, and that escape of that knowledge can be harmful to varying degrees. This may range from practical knowledge of how to do something in the sense of knowledge hoarding or knowledge hiding at work, to the intimate details of beliefs and preferences.

The other side of the coin is those who disclose or steal knowledge that is held to be secret by others. Sometimes this is done with intent for a beneficial outcome to the person whose secret is being revealed – such as that they have quietly performed pro-social work, or that they have valued talents or attributes that they didn’t advertise. Often the disclosure is harmful even when no malevolence was intended, such as inadvertently “outing” somebody who preferred to remain anonymous about their donations to a charity, and finds themselves embarrassed by the disclosure. It can also be intentionally harmful, such as the atrocious phenomenon of “revenge porn”.

People even withhold knowledge from themselves, either choosing to be ignorant or selecting to ignore aspects of themselves or others that they prefer not to believe. People routinely rationalize their behavior to maintain a positive self-image, and may become angry and combative when brought into a situation of cognitive dissonance.


With knowledge becoming ever more salient to business survival, the advent of social media, and the disappearance of employment for life, the ethics of knowledge will become an increasingly pressing area of discussion. There are many features to knowledge ethics, and many stakeholders, and it is high time the knowledge management fraternity and business managers rolled up their collective sleeves, gritted their teeth, and got involved with it.

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.


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.

Why KM isn’t going away anytime soon

September 4, 2012

There have been a fair number of people in the blogosphere over the last few years who have trumpeted that KM is “Dead” – some of them mean it in an ironic way or simply as a provocative hook to get eyeballs on their blogs, some think the way we understand KM is changing and that the old ways are “dead”, and some actually believe that KM is a term best ceded to IT and that the next shiny thing beckons – be that complexity, agile, or something else.

The real acid test is whether there is an increase in the number of jobs that are either about KM or require some degree of expertise in it, and whether they mention KM activities or compliance with KM practices as an essential part of jobs – But this is something I can’t answer just yet, since getting Monster, Indeed, etc. to pony up data on what KM jobs there were over the past decades is not easy.

Until then, let’s look at three things that would individually drive a need for Knowledge Management.

  1. Business variance and volatility – i.e. “Turbulence”
  2. Increase in the share of firm’s market capitalization due to Intangible Assets
  3. Demographics

My position is that the swell produced by each of these three market dynamics would individually create a need for Knowledge Management, but that collectively they make it an imperative – firms that do not get this right are in my view already dead men walking.


One of the markers I look for in firms to tell me if Knowledge Management is likely to deliver ROI, is the degree to which they are subject to variation and volatility. To get a metric on that I measure inter alia the following:

  • Change in regulations, laws, technologies, and players in their market space.
  • Product churn and variation
  • Staff turnover, skills variation, and performance variation.

Many economists have a similar measure that they simply call “Turbulence”
Here’s an interesting image that is typical of a measure of turbulence that just keeps showing up wherever one looks. It is a measure of business change in terms of new startups, mergers & acquisitions, business closures, etc.

This example is focused on healthcare, but as I said, the same shape keeps showing up – very little turbulence in the decades prior to the 70’s, with an explosion in the 90’s, and a small amount of calming running through the oughts, but no sign of anything like a return to the stable days of the 50’s and 60’s.

(HBR, 2012)

This is the “new normal” of the business world, with turbulence of an order of magnitude higher than what was previously “normal” and a status quo in which turbulence is a constant companion.
The days of a person doing the same job for decades, or a firm staying in the same business, or ownership of the firm staying constant are gone and never to return – and consequently, the ability to acquire knowledge fast, to be able to use it effectively, and to be able to “manage” one’s knowledge assets both tacit and explicit are critical to survival both for individuals and for organizations.

Intangible Assets

As per the image from Savage (1996) there was a time when “wealth” pretty much meant owning land – Being a big landowner meant having status, position, power.
Then it shifted to access to labour and wealth meant being able to acquire, mobilize, and manage a workforce.
Then it was having access to capital to fund business operations.

… and now it means controlling knowledge.

(Savage, 1996)

Over the last century, the proportion the market value of a publicly-traded firm that an auditor could capture with the balance-sheet in one hand and a pencil in the other has gone from over 90% at the start of the 1900’s to a low of under 20% in the 2010’s. The balance is made up mostly of “Intangible Capital”, and was often tossed into a bucket marked “goodwill”.

(Ocean-Tomo, 2010)

In fact, if you look at the data from Ocean Tomo, just since 1975 the proportion of market value of the S&P 500 has gone from just 17% to 80% in 2010.

So picture this if you will – you are an investor, and you have a bag of cash and want to grow it by purchasing a firm that you believe stands ready to take advantage of new needs and to generate a tidy profit for you (or your backers). You send in the bean-counters, and they take stock of the firm, ticking off as they walk the premises every line item on the balance sheet – raw materials, buildings, plant and equipment, finished goods, cash in hand, etc. By the time they have met with your banker (who might also want to see the results), and have walked the floor, they could give you circa 1910, an account that was close to 90% accurate as to the worth of the firm.

No doubt you would be happy with this statement of affairs and you could make the purchase with not too many sleepless nights.
Barring unforeseen circumstance, all should be well and the small amount that was unaccounted for and lies in the entry marked “goodwill” was merely icing, and if push came to shove you could just sell off the assets and still be in the black.

Fast forward to 2012 and your accountants return to you a balance sheet and inventory that reflect only 20% of the value of the firm, and they report that they think that maybe there is another 80% hidden in the “goodwill” line, but they aren’t sure. It may be 0%, it might be 90%, they just don’t know.
You spend days with your stomach churning, and if you represent investors, you fret over how you will explain this.

At this point investors, bankers, analysts, and increasingly shareholders, are simply not satisfied.
Leaving 80% of the value of a firm to guesswork simply is not acceptable, and they have various plans afoot to force firms to identify the value of their intangibles – ranging from the SHRM attempt to have value metrics for Human Capital, to more complex evaluations of the worth of a firm’s knowledge.

2012 saw some banks put dollar value against patents for the purposes of loan collateral, and who can forget all the patent auctions of 2011-2012, with more no doubt coming.
IC is no longer something that is seen as a bit of icing, it is now the major part of the cake itself – >80% in fact.

Demographic Change

We talk a lot about the “Baby Boomers” and their immanent retirement, but have you ever actually seen it?

Here is what a population pyramid for Germany looks like:

(Source US Census Bureau 2012)

What this means is that there are way fewer people in each age-group following those who are now at the peaks of their career, and the number of people entering the job market won’t be able to fill the spots as the groups above them shift up and the oldest shift out. The bulk of that 80% of value represented by IC lies in the skills, knowledge, and traits of the knowledge workers you employ – and generally the older ones are the most valuable to you. They know how, they know what and when, and most of all, they know why.

If you create a population pyramid for the Knowledge Workers in your firm, you might be in for a nasty shock (especially those of you with a need for highly-skilled practitioners such as engineers, planners, and managers) – you simply might not have enough people to replace the older skilled workers as they shift out of the job market, and you don’t have all that long to figure out what to do. In fact, in some firms it is already too late, they are simply going to go bust as their older and most experienced and qualified people retire.
The best such firms can do is plan for a somewhat orderly shutdown.

Knowledge Management

Let’s agree not to play “definition” bingo and to go down the rabbit-hole of the myriad somewhat-overlapping definitions of “Knowledge Management”, and suffice it to say that what we are trying to achieve is to have a clear picture of what the organization needs to know in order to execute its operational activities, to organize, regulate, control that required knowledge, and to maintain levels of it sufficient to meet operational needs.
So if we were to lay out an ISO9000 diagram of all the operational processes necessary to achieve the organization’s tier-1 goals, and then determine for each activity in the flow what the person would need to know, we would arrive at a list of what knowledge was minimally necessary (and perhaps not even sufficient) to meet EBITDA and other requirements.

The terrain in which KM practitioners operate is for the most part that of Intangible Capital, as depicted below.

(Adams & Oleksak, 2010)

The role of the person(s) responsible for Knowledge Management in the organization would be to see that the needs for knowledge were identified, to identify and measure the degree to which these were met, and have a plan and processes to make sure that the organization acquired, maintained, and put to work that knowledge in the most cost-effective and timely manner possible.

This is not going to be the IT guy any more than the IT guy is responsible for running the finances of the organization.


There has never been another time during which control over knowledge assets has been more important, and firms that do not have a robust knowledge management practice humming along will experience very high rates of failure as we track forward.
Far from being “dead”, knowledge management is going to be a significant determinant of which firms survive, and which roll over and sink as the combined effect of turbulence, the value of IC, and demographic change swells up around them.


Adams, M., & Oleksak, M. (2010). Intangible Capital: Praeger.

HBR (2012). The Volatile U.S. Economy, Industry by Industry Retrieved 09/04/2012, 2012, from

Ocean-Tomo (2010). Intangible Asset Market Value Retrieved 09/04/2012, 2012, from

Savage, C. M. (1996). Fifth generation management : co-creating through virtual enterprising, dynamic teaming, and knowledge networking (Rev. ed.). Boston: Butterworth-Heinemann.


Matthew Loxton is a Knowledge Management practitioner, and is a peer reviewer for the Journal of Knowledge Management Research & Practice. 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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