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Lessons learned from transformational HIT projects

Thu, 04 May 2023 14:42:09 GMT

10 rules to help giving birth to transformation in healthcare

Last week the DACH healthcare IT ecosystem – and more of the European one than ever before – met in Berlin at DMEA 23 for what was the biggest, busiest and, for all that matters, most optimistic and excited show ever, even back from the good ole conhIT days.

In football they say “money doesn’t score goals”… and we may debate long and wide about the flaws, lack of overarching strategy or focus on legacy technology which comes with KHZG. But here we are and money actually does move things forward. In Berlin you could see an industry smiling after long and dire years of little progress. I even saw “Becker-fists”, a first at DMEA as far as I can remember.

There is value in progress, even – or shall we say especially – when it is playing catch-up. German healthcare and the HIT industry are energized to proof it. These will be exciting years to come. And for once, the biggest challenge will be resources. What a high class problem!

When I walked the halls and heard about all the important concepts being devised, milestone projects initiated, paper eliminated, I had to think back at some of our lessons learned from the old National Program for IT times. There is a set of 10 rules, that used to help us stay focussed, maintain the energy in tiring times and accept some of the difficulties as what they were: unavoidable but real-life challenges to overcome and not insurmountable obstacles.

For whatever it’s worth, here is a reminder of the 10 rules, that help transformatory and strategic projects in healthcare IT stay the course:

1. KEEP IN MIND: IT’S ABOUT IMPROVING HEALTHCARE

2. DELIVER VALUE EARLY!

Early benefits drive momentum, commitment and ambition

3. IT’S ALWAYS DYNAMIC IN HEALTHCARE
Regulation, policy, medical science and practice change constantly, it’s real life

4. DON’T COMPROMISE ON STANDARDS
Interoperability, integration and semantics are vital!
Don’t re-invent what’s already there, enforce it!

5. IMPROVE AND RE-ENGINEER YOUR WORKFLOW
Digitalising bad processes creates expensive bad processes

6. MAKE LOCAL USERS OWN IT
And build capacity and talent

7. COMMUNICATION, COMMUNICATION, COMMUNICATION
Important messages get easily lost in translation

8. OVER-INVEST IN INFRASTRUCTURE
You’ll never run out of ideas what to do next

9. BUILD YOUR ECOSYSTEM
Complexity is teamwork and dependability is gaining you the future

10. NEVER LET PERFECT GET IN THE WAY OF GOOD
Excellence thrives well without perfection!

Technologieoffenheit

Thu, 06 Apr 2023 09:46:15 GMT

Warum auch in der HIT mehr über Ziele und weniger über Wege geredet werden sollte.

Vielleicht sollte man in einer Zeit, in der oft mehr über Worte als Inhalte gestritten wird, nicht mit einem Wort befassen.

Noch dazu einem mit dem Begriff „Offenheit“. Der Zauber Platons ist heute wieder so leuchtend, wenn auch identitär fragmentiert, und Rawls‘ Freiheitskonzept so vergessen, dass eine „offene Gesellschaft“ manchmal wie Romantik wirkt.

Und zu guter Letzt wurde der früher einmal positive Begriff „Technologieoffenheit“ inzwischen umgewidmet zum Euphemismus für Rennfahrerlobbyismus und Klimagleichgültigkeit.

Dabei ist Technologieoffenheit doch ein erstrebenswerter Wert. Unsere Verfassung verlangt für Gesetze Allgemeingültigkeit (Art. 19 GG) und nicht Einzelfallregelungen. Insofern sollten gesetzliche Regelungen doch geradezu grundsätzlich technologieoffen sein.

Leider haben wir uns zu sehr an die Dominanz taktischer Fragen gewöhnt und geben daher immer öfter nur taktische Antworten. Verbrenner oder Elektro? Ist das wirklich unsere Frage? Als Wettbewerbswirtschaftler der immer noch an Hayeks Katalaxie (Wettbewerb als Suchprozess) und Schumpeters kreative Zerstörung glaubt, kann die Antwort nur sein: Nein! Unsere Frage sollte die nach dem Ziel sein: Was wollen wir erreichen und wie messen wir das? Dann ist die Antwort automatisch technologieoffen, sofern die (messbaren) Ziele erreicht werden. Reduktion von CO ² Emissionen ist doch unser Ziel. Wenn diese Reduktion vorgeschrieben wird, dann ist es tatsächlich gleichgültig, wie sie erreicht wird. Derzeit sehen eFuels eher nach einem Ausstoß von kaum weniger CO ² als Diesel aus, würden also, Stand heute, bei der Zielerreichung keine Rolle spielen. Wenn jemand in der Tat bereit ist, in ein Wunder zu investieren, das diesen Zustand ändert, warum aber nicht?

Was hat das mit Gesundheit und IT zu tun?

Ich glaube, wir haben auch in der Diskussion um die Modernisierung unseres recht veralteten Gesundheitswesens ähnliche Schwierigkeiten. Wir diskutieren über „Digitalisierung“ und das seit vielen, vielen Jahren. Und immer wieder wird dann gefordert, manchmal festgelegt und bisweilen sogar gefördert, was genau „Digitalisierung“ ist. DiGAs, TI, EPA, KHZG Fördertatbestände, Forschungsdatenpools. Wenn man ehrlich ist, das kommt einem alles vor wie eFuels: Der Ersatz von Zieldiskussionen durch vested interests.

Aber brauchen wir wirklich Digitalisierung? Persönlich denke ich: nein, genauso wenig wie EVs. Was wir brauchen ist Effizienz, Transparenz und Patientenorientierung im Gesundheitswesen, so wie wir Klimaschutz für die Welt brauchen. Das eine lässt sich aber vermutlich so wenig ohne Digitalisierung erreichen, wie das andere ohne eine deutlich breitere Nutzung von Elektromobilität. Aber wo genau, wie und mit welcher Technik im Speziellen? Das mag doch der Wettbewerb als Suchprozess bestimmen. Technologieoffen. Vorausgesetzt wir wissen und haben Konsens über die Ziele, die wir erreichen wollen.

Wenn wir einen gesellschaftlichen Konsens fänden, wie digital Patientendaten sein müssen, wer der Eigentümer ist und wie ich dieses Eigentum ausüben kann, dann brauchen wir nicht mehr über eine TI debattieren, die in Jahrzehnten zu keinem Ergebnis gekommen ist (was sicherlich nicht an der Technologie lag). Wir könnten es dem Wettbewerb als Suchprozess überlassen, die beste Möglichkeit zu finden, dieses Ziel zu erreichen. Wenn wir medizinische Ergebnisqualität zum Ziel erklärten und Leistungserbringer, die eine Mindestqualität nicht erreichen, aus dem Markt ausscheiden, dann wäre Medizin ohne integrierte, interoperable Patientendaten kaum denkbar. Digitalisierung wäre notwendiges Mittel, aber eben kein Zweck.

Das könnte Gewinner und Verlierer generieren. Wie das in einer offenen, wettbewerblichen Gesellschaft eben der Fall ist. Es bräuchte aber keine mühsamen und zumeist schnell obsoleten ex-ante Diskussionen über den Weg zum Ziel. Und Ziele könnten endlich auch erreicht werden.

Gleiches gilt für die laufende Diskussion zur Nutzung von Gesundheitsdaten zu Forschungszwecken. Ob EHDS oder GDNG, einmal mehr wird über Datenpools, Dateninfrastrukturen, (öffentliche) Forschungsnetzwerke diskutiert. Statt ein klares Ziel zu formulieren. Verfügbarkeit von RWD zu Forschungszwecken. Wenn wir ein solches Ziel konsensfähig formulieren und die Kriterien zur Zielerreichung klar definieren, dann könnten wir es wieder dem Wettbewerb (gerne auch öffentlichem, aber eben nicht nur) überlassen, wie das Ziel erreicht wird. Derweil muss man kein allzu großer Pessimist sein, wenn man sich Sorgen macht, unsere Forschungsdaten werden den Weg der TI gehen und eine Weile brauchen bis sie etwas Produktives hervorbringen. Gegenfrage: wenn öffentliche Datenpools die Antwort sind, warum haben die zahllosen existierenden Register in den letzten Jahrzehnten nicht längst Forschungsergebnisse und Datenökonomie hervorgebracht? Warum haben wir in drei Jahren Pandemie immer noch keine belastbaren Auswertungen zu Corona, trotz all der sehr teuren zentralistischen Technologien? Dabei müsste man ja gar nichts erfinden, sondern einfach nur über den Gartenzaun schauen.

Ich glaube fest, auch im Gesundheitswesen könnte uns mehr Technologieoffenheit, mehr Allgemeingültigkeit, weniger Spezifizität und vor allem mehr klare Zieldiskussion und -definition sehr helfen. Digitalisierung oder auch Forschungsdaten sind eben keine Ziele. Sie sind lediglich Werkzeuge. Und die Gefahr ist, dass für jemanden mit einem Hammer alle Probleme Nägel sind.

Aber vor allem: wer kein Ziel hat, kann es auch nicht erreichen.

When (or how) will big patient data turn from liability to asset?

hcordes@neoqua.com — Fri, 02 Dec 2022 11:38:33 GMT

Is data oil or soil?

For 20 years and more we hope, expect and believe, if data is the new gold, patient data is platinum. Big data sets have been de-identified, longitudinally matched. They are clinically and medically rich, include lab data, vitals, clinical notes, pain scores, medication data, etc. etc. A real treasure chest. Yet, despite the biggest logos trying extensively to monetise patient data, a business model has still to emerge. IBM Watson is only one of the weary horses by the wayside.

Pharma, the biggest hope for monetisation, has remained hesitant with respect to RWD. There are undisputed benefits (finding overlooked benefits or also off-label uses in challenging constituencies like children, elderly), but pharma has kept a distance to real world patient data. In recent years, there seems to be some movement on this. Reasons may be regulators waking up to the use of data too and increasingly specific molecules have increasingly small benefitting patient populations. Finding patients before and after approval is becoming challenging. But broadly, the hesitance remains, and pharma stays conservative with a view to RWD.

Since before COVID however and accelerated ever since, data usage has become a hype - in contradiction and despite of the above. The hype is related to research. There are several areas in research, where Pharma is extensively using AI, ML and Data Analytics. Designing protein molecules, testing them against vast genomic or biomic data, searching for biomarkers has become common place.

Why therefore has research data analytics, despite being a late-comer, overtaken EMR/patient record analysis? I have my hypothesis: the first generation of patient data (EMR data) was driven by the natural data compilers. Either these were EMR vendors of all types or also academic provider institutions. None of these had neither compelling business use for themselves (even pattern recognition and predictive modelling did and does not generate meaningful revenue streams). For the lack of real business models, data management and modelling did not progress much beyond the "toying" phase. HIT invested the scarce AI resources elsewhere, academia didn't even have that resource. Monetising data did not go beyond “hey, why don’t you pay for using this data pool and try to strike platinum in it?”. Surprisingly, the number of customers stayed few.

With research data analysis for pharma that was different. There was an immediate business model (sales of solutions to dramatically accelerate the research life cycle) as well as the need for solutions – rather than pure data. The reality that pharma – like most non-SW verticals (look at car manufacturers…!) – struggle to develop SW, far less create AI and ML processes, created that need. Thus, if innovative SW companies wanted to sell research solutions, they had to do exactly that: sell a solution and not just crude oil. In other words, not sell data, but analytics, processes, i.e. results that are built with data, on top of data and from data. The Flatiron story stands for many others.

EMRs didn't do that. And thus, they did not really get past the crude oil state. Or in a different metaphor: They were real estate brokers who tried to sell fertile land to Nestlé, Mars or Cadbury to grow sugar beets. Yet, the candy companies do neither know how to grow crop, nor how to harvest and refine it. What they need is sugar. Not land.

Now…, if that hypothesis is correct, the step to monetise EMR data is not so much the collection of more data, but the development of relevant and efficient solutions around it, which allows clients to procure data benefits, rather than data. A company built on data monetisation will need the technical, AI and ML capabilities as well as clinical and process know how of their potential client organisations to be able to extract meaningful value from the data. Just like current pharma research AI companies also have pharmacologists and physicians on staff.

When value from data will be on offer, rather than just data access, I trust we will suddenly see several market niches ripe for the value proposition:

MedTech - like Pharma, they could dramatically benefit from better data analysis, predictive modelling and smart, evidence based management of devices
Medical provider organisations, who could benefit from meaningful and relevant process advise and benchmarking
Start-ups who need access to big data to train their smart algorithms
Pharma for the post clinical phase and in order to stay ahead in the arms race with regulators
Regulators for the same reasons
HIT vendors for deploying clinical intelligence

The trick will be to know the challenges of potential clients better than these themselves and provide evidence-supported answers – rather than burying them under big data, which may contain an answer, but which they can’t handle.

If in this sense a new demand for data-driven knowledge is generated, not only clinical data will become attractive, but also all sorts of operational data, alerts, task management, maintenance life cycles, nutrition data, transporters, HR data (attrition, sick leave), and other.

Last not least, building solutions and tools to produce results and answers from data will catch two more birds with the same stone. Data protection: if there is a digital twin condensed and created from RWD, there won’t be any personal patient data left over. The digital twin becomes a SW tool, void of any personal data. And secondly, working with a twin model to test and finetune hypothesis will not run the risk any more of finding possibly adverse data points in RWD, that a data user may rally not want to find.

Data is not the new oil, it is the new soil indeed. Soil, that needs growing crop, harvesting, refining before producing food. Most people still like to buy candy bars rather than grow beets. Beneficiaries of big patient data too like solutions and results over raw material.

What is transformation?

hcordes@neoqua.com — Wed, 16 Nov 2022 19:49:59 GMT

90% transpiration

• Opportunity, innovation, future.

• Kotter’s 8 steps.

• Energy.

• Excitement.

• Growth.

• Paradigm change.

• The New.

• Improvements.

• 10% genious

• Quality first.

• Kübler/Ross change curve… just stay the course, it will climb up again. … Will it?

• Trough of disillusionment.

• Frustration.

• Excited in the heart… sick in the belly… confused in the mind.

• Transformation chasm.

• Resistance, quicksand.

• 10% impatient winners.

• 10% losers in the trenches.

• 80% indifferent onlookers in waiting position.

• Hurt pride.

• Make it personal.

• Unintended consequences.

• Upstream negligence, downstream drudgery.

• Get it right first time.

• Listening.

• Vision, mission, strategy.

• Structure, process, process, process, tools.

• Communication, communication, communication.

• And communication.

•90% transpiration

It is the workflow and not the tech!

hcordes@neoqua.com — Wed, 16 Nov 2022 19:44:31 GMT

A neglect that comes easy…

Nearly forty years into digitalising healthcare has been a beneficial journey. Yet there also is a feeling of shortcoming, missed opportunity and backwardness when it comes to many people’s perception of where we are today. It is a sobering position to be in, given the promises and especially the opportunities. And while there is even a next wave of possibility emerging surfed by AI, AR, 5G, MD certified algorithms, consumer health, predictive modelling etc., I still need two X-rays if I want to see two physicians on one issue (I guess, I am only slightly exaggerating).
Clinicians blame it on usability challenges and documentation hell. Hospital CFOs blame it on cost and lack of investment funds. IT vendors blame it on end-user indifference and conservatism (“never change a running workflow…”), adverse reimbursement structures, which prevent innovative business models, etc. etc. It is a gordian knot.
Probably everyone somewhat has a point and the truth is, it really is hard. However, I fear that we, HIT professionals, still overlook a majour challenge and more often than not, put ourselves in a position not to address the real cornerstone: workflow.
We talk about it all the time, naturally. We call it workflow engine, decision support, integration or, simply, “more time for the patient”. Yet in the end what IT vendors deliver more often than not, is another product, yet not a solution. All too often, what we continue to focus on is technology, as if we have not moved on from the good old fashioned box-moving times. Those good ole times, when you created a beautiful and superior product, boxed it, shipped it to your customer and said: “it’s great, best in the world, go figure out, what you can do with it!”
That works for a hammer. Anyone can use it. But what about an API?
What I mean is our routinely negligence of the real-life workflows and actual purposes of our end users. Take a sepsis alert. It’s lifesaving decision support. Why would anyone not want it? Yet, even if vitals data was captured and fed real time into a patient record, even if standardized and harmonized data from disparate sources was consolidated and able to be analysed in real-time, even then, what does a nurse have to do, when she picks up the alert from the monitor? Who are all the various roles that need to be informed and with what information? Which is the most urgent step and what has more time? What could be automized in the first place? What are documentation requirements, so that the hospital will also be able to get reimbursed for the emergency routine? Where do I find an ICU bed? And, too, now that the alert is recorded, who is liable if anything goes wrong?
If all a tech company delivered is a smart algorithm and an alert… nobody will want it.
Maybe Sepsis is a bad example. There are sound protocols and every clinicians knows it by heart, do they? But what about less serious, still cost driving and patient jeopardizing workflows? Or, let’s take a different example, what about patient history? If a clinician has access to the integrated life-long patient record, but doesn’t have the time to read all that is in it? Will she or he be liable if they did not find an allergy or other relevant pre-condition? And if they are liable, would they rather not have access to a longitudinal record in the first place, than being obliged to read it all?
All too often we still find one of two situations: either the technology vendor offers new features and functionality, and clinicians raise their eyebrows thinking “More documentation, more data entry, more liability?” Or, while working with clinicians, the old ways and processes are shoe-horned into new technology in order for clinicians not having to change. Leaving IT providers frustrated again about the waste of opportunity for change.
In order to accelerate the digitalisation journey of our time and shorten the cycle of adoption and innovation, we need to start with ourselves, with us as innovators and providers of IT solutions. The thing we need to emphasize with our teams as much as with ourselves, is to always think with the end in mind. What is it, our end users need to do and want to achieve? What else could they achieve and what could be counteracting effects?
Take interoperability. In itself, it is nothing but a technical concept. Yet if we understand, why a role would like to interoperate, what information they need in order to execute what function, interoperability may become meaningful day one. And prioritized towards an achievable short term benefit, rather than boiling the ocean. And while avoiding information overflow at the receiving end, which may have caused prohibitive levels of data digestion cost.
As much as we as IT professionals would like for clinicians to leave their comfort zone a little more often and think outside their (workflow-) box, as much we should step outside our technology box, understand the why of a workflow, design a value proposition around it and only then start designing a technical answer for it. Why do we do something? What do we want to achieve? And only then: how do we do it.
Alfred Marshall, a famous neoclassical economist, once wrote (I am paraphrasing): 1. Use mathematics like a stenographic language, not as a purpose in itself; 2. draw your conclusions; 3. translate into English; 4. illustrate by examples, which are meaningful for the world; 5. burn the formulas; 6. if you fail on 4., burn the formulas and the English!
If we replace economic findings with workflow improvement and mathematics with technology, I think we should do the same: If you cannot illustrate your solution’s benefits with real life workflow examples, burn the whole idea. Purpose-free invention is called art. That is a whole different business. Regardless how beautiful the technology.

Philosophy and business

hcordes@neoqua.com — Wed, 16 Nov 2022 19:41:02 GMT

Some thoughts for the quiet days ending another demanding year.

Some thoughts for the quiet days ending another demanding year.
It is somewhat surprising. Our business world has never been more guided and driven by morale and ethics than it is today. No job ad, that does not require “strong ethics”, “values and integrity”, “being true to a cause, even if unpopular”. Previously perceived as the incarnate of ruthlessness and profit-above-all mindsets, now fund managers and their ESG agendas convert even the most die-hard coal burning CEOs. Specialist labour shortages convince toughest bosses of the value of staff satisfaction (and to think about how to drive it). The world becomes greener, more sustainable, more reflective and fair, less biased. Some may say, “not enough”, “not sufficient” or an abundance of zeal may create challenges of political correctness and the unintended consequences of ethics on steroids.
Yet, compared to where we come from – pick whatever period in history you like – the world has more morale and ethical substance, than before. Even as a relative statement, that is a good thing.
What I find interesting in contrast is a persistent hesitance in business to read and perceive philosophy in its own right. We consume “management literature” by the millions of copies even in its most banal forms, yet talking about philosophical foundations of management concepts is often regarded quirky.
Well, I personally believe that for a humanist – and why should a business person not be humanist? – the world is easier to explain helped by philosophy and easier to navigate too. The theory of knowledge, perception and cognition – epistemology – helps to comprehend the world. Without solid understanding there is no sound strategy.
Platon wrote, what we can see with our eyes are only flickering shades on a cave’s wall. Quite pessimistic. Popper told us too, that we can never be certain whether we deduct correctly from what we see. Yet, rather than despairing like David Hume over the impossibility of knowledge, he tells us very pragmatically: in the meantime help yourself by just using the theory that explains best what you see. And continue using it until it is proven wrong and replaced with a better theory. With the “and” being quite important.
Which gives us a simple distinction: an argument that can be proven wrong is rational and an argument that cannot be proven wrong (or: where factual proof is denied rather than falsified) is believe. With all the conspiracy theories wavering about us, you sometimes think we should use that simple razor more often to avoid useless and fruitless discussions. Belief is belief. Can’t be argued with (because what isn’t rooted in facts, simply can’t be disproved by facts either, for good or bad), but must not interfere with society, please.
So yes, such philosophical concepts hold true in business as well. We will always have to take decisions under conditions of uncertainty. Else, they are no decisions, but consequences. Thus, we cannot wait until we achieve certainty but must decide based on what are the most rational conclusions from the available facts. We need to collect and interpret facts in a neutral fashion, that is: not only to justify and substantiate an already taken decision or opinion. We need to carry the burden and risk of remaining falsifiable. Or else, we will start making bad decisions and end up in a rabbit hole.
Values on the other hand are a compass. That is the other pillar of philosophy which can support business.
In a distinctly continental European environment you obtain a constructivist view of the world. Descartes, rather than Hume: if you know enough of the facts, you will be able to understand the world. Cogito ergo sum.
By far too optimistic, I guess! It leads to Rousseau and the famous supremacy of a volonté générale over the volonté de tous. And we are living the culmination of Rousseau today. Today, we seem to have a myriad of volontés générales (or: “we know it best for you too, shut up!”). But because they all know how the world works, i.e. they all “have the truth”, all these volontés can’t be reconciled, they are mutually exclusive and the basic element of societal consensus, compromise (and respect), is no longer available. Truth against truth, rather than argument against argument has become our reality, all too often, sadly.
The cure to these idealistic dead ends starts from Socrates via Kant and Rawls. Own the consequences of your doing, i.e. be accountable for your deeds. And don’t act in a way, that you would not accept to be acted upon yourself. It’s simple enough and doesn’t even need religion, natural law or utilitarianism to justify. But it helps a lot to find your way in decision making. And it could help shorten a lot of fruitless discussions.
Being accountable and not doing what we wouldn’t want done to ourselves would have made it harder to sell bundled A-rating-bonds made up of F rating subprime mortgages. Or engage in cum-ex-businesses. Or disrespect intellectual property rights. Or trip your colleague.
The simple answer to the question “by rejecting vaccination, will you account for the cost of the disease if you infect someone and is it ok for you to be infected by someone other?” may make people reconsider. Maybe. If there isn’t a rabbit hole already.
Philosophy won’t help us resolve everything in our affluently complex world. There will always be decisions left to improvise on or follow instinct. Yet I believe with some simple tools we can reduce complexity at least a little bit. It will instil an urge to rationalize our decisions, objectively justify them (to yourself if noone else) and ensure they are the best under the given knowledge. It will certainly increase the hit rate of decisions. And increase acceptance, especially for difficult or painful decisions.
It may not make us better people. But it will not do the opposite either. And it doesn’t cost much. Just some thinking. And occasional reading, fun anyway. I still believe, and maybe more than ever, to take the occasional look into the lore of some of our world’s great thinkers, is beneficial.
Especially from a business perspective.

Can healthcare IT be international?

hcordes@neoqua.com — Wed, 16 Nov 2022 19:38:09 GMT

The answer is simple. And complex. Almost like real life.

One of the most common questions, when I talk to investors about healthcare IT, is “how international is HIT”. Of course the background to the question is simple: can you scale an HIT business beyond national boundaries or is the ceiling to growth what used to be the border bars before there was Schengen?
The answer is simple. And complex. Almost like real life.
It is simple, because in theory it is not a problem to take a healthcare IT solution international. At the end of the value chain there is always a patient. There is always biology. And that is, with all its complexity, variability and unpredictability, the same wherever you come. It is complex and difficult everywhere. But it is the same complexity and difficulty everywhere too. If the French, the Germans, the Australians, Americans, Danes, to name but a few, say: “we are sooo different!” – the truth is: they are not. Clinical practice, in my experience, is sometimes more different between one hospital and the next, between one ward (or senior physician) and the next, than it is between one country and the next. In other words, the true workflow differences are nominal in reality.
But then, why has hardly any EPR company achieved to go global? Why is there hardly any seriously global platform? Even those, that earnestly tried to take a one-platform-strategy global, in all reality have not gotten very far. They may be in a handful of countries but have stopped to go further. Some are even backtracking. The companies that actually have a more global footprint do not have a one-platform-strategy. More a type of one-platform-per-country strategy. Which gets us back to the question of why does it seem to be so difficult to go global?
The hidden reality is that it is not clinical practice, patient safety or workflow efficiency that drives EPR adoption. It is, sad and sober truth, reimbursement regulation. No hospital can run without being reimbursed for its services. Banal truth. And a hospital that does not comply with the way reimbursement is handled in a country, will not be able to live. Easy.
Every country however – sometimes even different regions in the same country – has a different reimbursement system. Case based, DRG, volume based, KPI based, fee for service, hybrids of everything, you name it. Even the same thing is not the same. DRGs are to be found in most countries. How to calculate them however is different again wherever you look.
Payment for medical services is the textbook classic for a principal-agent-dilemma. What regulators do, in order to retain a level of (perceived) control over incoming bills and their relation to services rendered (note: not quality delivered), is to increase the documentation requirements. To an ever more complex and detailed level. It is almost an arms race: helped by digitalisation, documentation has become easier. Which led regulators to ask for ever more documentation. Of course clinicians blame that vicious circle on EPRs and their cumbersome documentation routines. However, the real challenges come from the (reimbursement-driven) statutory documentation requirements. Which are different in every country, unpredictable and grown in a random pace and for random areas – when looked at from the outside. Which makes it difficult to bring structure, reason and simple generic workflow concepts to bear. Not even flexible template tools are enough. Architecture matters! A “case” is defined and constructed differently in almost every country. Find the smallest common denominator!
Back to the question of internationalisation hence. If my theory is true and reimbursement drives documentation routines, which drive workflows, which drive layout and customisation of EPRs, then it is very difficult indeed to internationalise an EPR. You would have to design a catch-all architecture and granular datamodel with a very flexible workflow and template engine and at the same time hardened rigour around design principles, terminology and data concepts. And then it would be possible to have one platform for the world. In theory not impossible. In practice however… in practice all EPR platforms have been built for a home market with all its design decisions and restrictions, and then, because they work well, you try to take them global. Which has proven very tough to anyone who tried.
There is another truth in this though. The further you stray from billing rules and reimbursement-driven documentation, the more consistent workflows become across country boundaries. Departmental systems that are very close to the reimbursement cycle are still almost as local as EPRs usually are. Theatre solutions, A&E and the like are still very much local businesses. Yet procedures, that are not part of the reimbursement calculation, like imaging, labs, cardiology, and many other specialties, are areas, where systems become more and more international and even global.
The answer to the question hence is simple: if you have a catch-all datamodel with a powerful and flexible documentation engine, internationalising an EPR is possible. IF you designed it with the end in mind. And provided you acquire the necessary local knowledge on reimbursement/documentation requirements and intricacies.
If you work in specialty areas, whose workflows are a distance away from billing cycles, then you can deploy global best practices much more easily. And clinicians, who are otherwise hesitant to change their workflows, will be interested in how to improve their processes.
When billing is not impacted, clinical practice actually does become innovative and efficient.

The transformation chasm

hcordes@neoqua.com — Wed, 16 Nov 2022 19:32:36 GMT

Genius is 10% inspiration and 90% transpiration. We all know that.

Genius is 10% inspiration and 90% transpiration. We all know that.
Change, even more so transformational change, is 10% strategy and 90% psychology. Yet, like with genius, we keep ignoring it, even as we very well know it.
Discounting the drudgery in retrospect for a “heureka”-moment is understandable. But why are we discounting psychology so often when working on real-life transformation? I believe the answer is simple: because most people involved in or subject of change are telling us that they are excited about it. That they fully support the transformation, they understand the need very well and they are really glad about it finally happening. Until we all, change agents and change subjects, actually believe it to be true. Then we think: “Excellent! The books tell us about resistance and psychology. But here we are in the rare and lucky situation of having a team that is pulling forward 100%. Let’s focus on strategy and execution!” That is just before we hit the quicksand.
Who has not heard about the other theories? There is, for example, the famous Kübler/Ross change curve with its trough of disillusionment. The pitfall of that theory is its optimism. Just carry on and the curve will climb out of the trough by itself, given some time. Really?
And then there is the theory of winners and losers. 10% love transformation, they have indeed waited for it to happen and they will thrive on it and are driven by opportunity and the hope to be a winner in the process. And 10% are the likely or unavoidable losers-out. They hate the transformation and will fight it tooth and bone, albeit in a stealthy bush fight. 80% simply do not care.
As the theory goes, the second 10% make the noise and much energy is wasted to catch them, convince them, win them over, compensate them. So much energy, that the supportive group feels neglected. And while the transforming manager is losing the fight with the resisting group she or he is also losing the support of the ones that are actually driving change. That is when the indifferent 80% feel confirmed: “never try and remember a name that is not around for 2 years!”
Yet, in real life, it is sometimes not as mechanic and clear cut. Frictions may run along the lines of scripture. More often they follow different rifts.
One special case is what I call the transformation chasm. We have learned to think in categories of support, indifference and resistance. These categories however implicitly assume, that all parties have a somewhat consistent understanding of what the intended transformation is and what it needs. Else they couldn’t be for or against it. Even if feedback may not be fully transparent, as transforming managers, we assume an underlying common understanding. Because we understand it and nobody else mentioned, that they don’t.
However, can we assume a common and correct understanding to be the case?
Transformation is about taking an organisation towards a related but entirely new context. From filling out red tape to following a workflow. From car sales to mobility concepts. From travel agent to experience manager. From news”paper” to validated information hub. From highstreet shop to multi channel seller. From curing disease to managing health. Etc. etc.
More often than not, we describe the objective, the new state in the best of colours. And surprisingly all the change resistant organisations turn out to be fully on board, even excited. In the end, who would debate the need for mobility concepts, workflows, web presence and the like. We turn out to be excited ourselves. Mission accomplished: the troops are bought in. They agree with the objective and the importance.
Yet for most people that new state, that objective, is an “and”. It is something else. Something in addition, that comes on top of their world as it exists. In most people’s perception, it has thus nothing to do with their day-to-day routines. It is what the “project team” is working on. They just carry on and wait for the new thing to arrive someday.
Not too long ago a team from the University of Virginia published the results of an experiment. Humans appear to have a very strong tendency to add to a given situation or construction rather than change anything when asked to improve on the status quo. The majority of suggestions, in the experiment, consisted of net additions in order to solidify a given Lego construct - rather than change the given set up. Even if the change approach was monetarily incentivised, the addition approach sanctioned, even when a change was plainly obvious and much simpler than adding bricks, the majority always wanted to add more bricks.
Our brains seem to deconstruct complexity by segregating status quo and change and treat it as two separate things.
If transformation – by definition the replacement of a status quo – is to succeed hence, we will need to find ways to address the 80% indifference. Because it is not indifference in the first place, it is the perception that change has nothing directly to do with us. If that perception holds ground, people can be fully committed, even excited and in approval, yet it will not result in any engagement. To overcome that misunderstanding is what I call the transformation chasm.
Yet, too, the remedy is simple: make it personal.
When we communicate the needs and objectives of transformational change, we need to make it personal. We need to find ways to connect the imminent shift with our team’s personal context, their concrete reality and what it means for them. We need to explain, why a webshop is no add-on and will not work, unless workflows in order-management, billing and collection are supporting it. Guess what, they are still on paper… well, let’s digitalize the backend first, before we create a front-end, that will annoy anyone involved, including our customer. A webshop is not an “and”, it is a different way of doing business for the entire organisation.
Overcoming the transformation chasm is hard work. It is over-communication on top of over-communication. And it is hard, because we always only know about a fraction of the real-life implications that our intended change really causes. We will never be able to verbalize all of the impact beforehand. There will always be a strong element of finding-out.
Transformation and overcoming the transformation chasm needs flexible project management. It needs listening. And adjusting the plans. Improvising and communicating, communicating, communicating. It is hard work.
90% transpiration.

[1] https://www.nature.com/articles/s41586-021-03380-y

Digitalisierung ist nicht die Frage. Prozessmanagement schon.

hcordes@neoqua.com — Wed, 16 Nov 2022 19:27:36 GMT

Zweck zuerst, dann Technik

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What drives change in Healthcare?

hcordes@neoqua.com — Wed, 16 Nov 2022 19:21:21 GMT

Dynamics and secular trends impacting healthcare

Healthcare - big, complex, labour driven, dominated by science, public and private, digitalized and yet still recessive, awe inspiring, (com-) passionate, mission critical, charitable and being a huge corporate industry globally. It’s so many things and fits so few stereotypes that sometimes it feels like a universe in itself. Yet, it is also deeply rooted in our societies, realities and economies, and is subject to strong external forces and trends that impact its trajectory.
When building strategies in healthcare technology it is always helpful to keep in mind the global environment and relevant mega-trends which are impacting this market more than others.

One overarching trend which is shaping the underlying changes in our societies and which is having an imperative impact on healthcare is: demographics. Most industrialized countries have entered into an aging phase of their population’s structure. Some are already even shrinking in absolute numbers, many will follow, and more than a few previously “young” emerging markets show patterns of entering into this transition faster than the old world has done before. Some have called it the movement “from pyramid to urn”, word-playing on the change in the shape of the ancient population pyramid. [1]
The good news for healthcare is the prospect of a decades long growth in demand as the number of aging people keeps growing[2] and with it the need for healthcare in every form. Accepting the reality that the overwhelming majority of health services are delivered to the population past the working age, the extension of life expectancy will over-proportionately extend the demand for healthcare delivery services. At the same time however the supply of resources – both in terms of funds through tax, insurance or social security payments procured from the working population as well as the simple availability of workforce to deliver healthcare services[3] – keeps shrinking. All other things equal, healthcare is thus bound to enter an age of overconsumption and underfunding, which will provide a dangerously unbalanced lever to society.
This dynamic is aggravated by two additional next level developments. Taking cancer therapy as an example, it was not surprising to hear the WHO cautioning against an increase in cancer cases by 60% by 2040.[4] At the same time cancer therapy is making great strives to improve and has already turned several cancer types into ”increasingly becoming a chronic illness”[5] – at the expense of a significant increase in cost per case. The amazing and encouraging rate of successful innovation combined with the “natural” increase in cases is therefore unfortunately also putting more strain on the stretched healthcare funding in most countries.
At the same time, we continue to read more and more about the workforce challenges arising from the generations X, Y and Z. Whether the changes in work-life balance, working-lifetime and working attitude are real is highly debatable. What is not is the material reduction in available resources.[6] Viewed from a global standpoint even immigration, if it will resolve that issue at all, will only move the problem from one place to another. The reality of healthcare having to find sustainable ways to increase its macro-productivity (and its micro-efficiency) is undeniably catching up with us now.
There is however no reason for doom and gloom. These levers are not only great news for us as a population that will, on aggregate, enjoy longer and healthier lives. They are also the impetus for innovation much needed by a largely conservative and change/risk adverse environment in healthcare. Modernization is a must to meet the evolving challenges - not only through innovation in diagnostics and therapies, but also in process, coordination, incentive structures and organization. Technology will be both an enabler as well as beneficiary of these reforms and transformative processes – for example, in facilitating comprehensive care, providing data liquidity or enabling effective telemedicine, prevention and population or disease management.
In addition to the demographic mega-trend which will influence both demand and supply side dynamics in healthcare for decades to come, we see three more specific trends that will impact healthcare markets and customers, and thus strategies: (i) evolving technology, (ii) personalized medicine, (iii) continuously tightening regulation, and (iv) , regionalization of healthcare delivery.
Technology
The technology promise is growing. Whether it is more (and cheaper) sensors, low energy Bluetooth, machine vision, 3D printing, robotics or 5G, options to build out meaningful use cases through cost competitive technology are growing ever more abundant. With the initial build out of a reliable 5G infrastructure, the potential to connect all these use cases in real time is just around the corner. At the same time, medical devices (not long ago significantly high cost items) are commoditizing fast, freeing up budgets for next generation solutions. Technology will soon be able to offer digital data collection at the point of care along the patient’s journey like never before. Technology is only an option or potential though. What are the use cases that create benefit and purpose?
Personalized Medicine
For the best part of 30 years, genomics, biomics and personalized medicine have been the promise and the expectation of innovation in healthcare. Unfortunately, until recently relatively little had been fulfilling that promise. The tide is changing, however, and personalized medicine is coming out of the trough of disillusionment. From immune therapy, personalized radio therapy to 3D reconstruction and tailored prosthesis’, more and more therapies are coming out of the labs and gaining real life approval. The increasing specificity to patient segments of new molecules in pharma research adds to that trend.
Personalized medicine, in the widest sense, is data hungry and will increase to be data hungry. Longitudinal medical data, for a long time believed to be valuable, but never monetized, is suddenly becoming essential. Essential in finding relevant patterns for specific therapies and molecules to be effective in; essential in testing new approaches against relevant patient groups and proofing the benefits (which are otherwise in danger of being diluted with the wrong targets); essential to decision support clinicians, enabling them to find the right treatment for the right patient. With personalized medicine, medical data suddenly has a real and not just assumed value.
The growing ability to generate, collect, harmonize and analyse data at the point of care, and the growing diagnostic and therapeutic demand for that data will, in combination, drive the next round of digitalization in the clinical space. Some may say, finally!
Last, but not least, there are two more very important trends gaining momentum in the healthcare vertical itself. The simple one is regulation.
Continuously Tightening Regulation
With the increasing complexity of both the demand and the provision of healthcare services, the pressure on regulators to risk-manage healthcare will not relax. From a health technology (especially software) perspective the most important regulation is of course the European Union’s medical device directive (MDR)[7] - which is moving many previously unregulated software solutions into the medical device space. Although the European Commission has granted four more years of transition[8], the regulation is coming, like it or not.
Medical device (MD) development means the end of the (much admired) agile development approach and will demand more planning and documentation upfront. Although this feels like a steep hill to climb for many software development organizations, if processes are reviewed and updated, especially the product management and requirement engineering processes, added with some discipline, MD development is neither rocket science nor increasing development cost significantly.
Regionalization of Healthcare Delivery
Another strong dynamic inside the healthcare vertical is an increasing and sustaining regionalization of healthcare provision. With more private ownership structured health economies, like the US, Germany or Switzerland, struggling to outperform public healthcare systems – especially when comparing input-output-ratios – and populations continuing to be attached to public healthcare, we are unlikely to see a move away from public healthcare provision in most mature economies in the near future (emerging and developing countries often have a different history and are in a different stage).
In order to combine economies of scale effects with the avoidance of inefficiencies of centralization, we will continue to see the establishment of regional healthcare provision clusters. The move is trying to marry critical mass with customer (i.e. patient) proximity and will also increasingly allow inter-sectoral coordination and collaboration – an area where we believe the largest productivity reserves remain.
Both vertical dynamics – regulation and regionalization – will be a push for healthcare technology suppliers to professionalize and increase their critical mass. Medical device development processes, albeit not rocket science, require a certain level of coordination, planning and quality control that demands a minimum critical mass from development organizations.
Regional healthcare provision clusters will also create regional procurement and, not the least, IT organizations and capabilities, that will require minimum levels of economic reliability, cloud or hosting options, professional tender replies, long term visions and solution roadmaps from their suppliers. Regionalization is a pan-European trend from the Nordics through the British Isles, Benelux, France, Spain, Italy, etc. [9] and cannot be underestimated in its push for professionalization and critical mass on technology suppliers.
Summary
When demographics continue to accelerate demand for healthcare provision services while the same dynamic creates a gap in resources – funding and workforce – we strongly believe that systemic productivity increases in healthcare are inevitable. Without technology there will not be more productivity gains. The Germans may have achieved the most effective paper-based health system possible, but even there the ceiling is reached.
The next generation of diagnostics and therapies (whether pharma, gene-therapy or devices) all demand more data in order to be effective and efficient. The pull for data is met with an increasing reservoir of technology offerings to enhance, innovate and roll out further digital use cases in healthcare. Together these trends portend an imminent next wave of digitalization.
When developing strategies to harvest the opportunities that are emerging, it will be important to also reflect on the two significant internal dynamics in European healthcare (and beyond): growing regulation and maturing regionalization. Both will create a push for larger, mature supplier organizations and will, slowly but surely, push for a consolidation of the local, relationship based and fragmented, healthcare technology markets in Europe.
Great times ahead for those to become successful, who know what to leave to chance.

[1] Practically all OECD countries show secularly aging populations with most accelerating in the last 10 years, incl. countries with interim shrinkage of average age (e.g. Spain, Russia) with Germany and Japan being the oldest societies. (https://data.oecd.org/pop/elderly-population.htm)
[2] By 2050 population above 65 will increase over 2018 by 28% in Germany, 45% in France, 51% in the UK or 59% in the US with an average of 51%. (https://stats.oecd.org/Index.aspx?DataSetCode=POP_PROJ#)
[3] The OECD predicts a reduction in working age people for Germany from 49m in 2018 to 38m in 2050. (https://stats.oecd.org/Index.aspx?DataSetCode=POP_PROJ#)
[4] https://www.who.int/news-room/detail/04-02-2020-who-outlines-steps-to-save-7-million-lives-from-cancer
[5] https://eu.usatoday.com/story/money/2020/02/05/states-with-the-lowest-and-highest-cancer-rates/41108601/
[6] Just one example: https://www.healtheuropa.eu/nhs-staffing-crisis-a-critical-exception-to-the-immigration-rules/97745/
[7] https://www.johner-institute.com/articles/regulatory-affairs/and-more/mdr-rule-11-software/
[8] https://www.medtechdive.com/news/eu-parliament-set-to-adopt-mdr-class-i-device-compliance-delay/569234/
[9] Whether it is regions and county councils in most of the Nordics, ICGs, CCGs, STPs and Trusts in the UK, ARS and GHTs in France, Autonomic Health Services in Spain, Regions in Italy, etc. most public health systems in Europe intensify their regional set ups.

Prozesssteuerung statt Digitalisierung

hcordes@neoqua.com — Wed, 16 Nov 2022 19:17:48 GMT

Warum wir falsch über digitale Technik sprechen

Seit guten 30 Jahren sind wir dabei, das Gesundheitswesen zu „digitalisieren“. Heute ist es fast sprichwörtlich, dass die Ergebnisse hinter den Möglichkeiten blieben. Selbst – oder gerade – in der HIT Branche wird über ein Glas Wein gern mit der gefühlten Rückständigkeit kockettiert. Warum dieses Gefühl des mangelnden Erfolges?
Oberflächlich könnte man das Gesundheitswesen mit anderen Branchen vergleichen. Vor 30 Jahren wurde GPS eingeführt – und heute ist Logistik ohne GPS nicht mehr denkbar. Eigentlich noch nicht einmal die Suche nach einem Restaurant, dem Klavierstimmer oder der Bankfiliale. Wenn es die überhaupt noch gibt. Ich weiß noch, als die Lufthansa uns extra Meilen anbot, wenn man sich sein Ticket ausdruckte und an einem Automaten eincheckte. Das ist weniger als dreißig Jahre her. In vielen Branchen wurde viel später die Digitalisierung begonnen als im Gesundheitswesen. Aber in praktisch allen ist sie inzwischen weiter vorangeschritten.
Etwas muss also anders sein im Gesundheitswesen. Aber, wenn wir ehrlich sind, all die stereotypen Erklärungsversuche laufen ins Leere. Mit vertraulichen Daten wird in der Bank auch gearbeitet. Um Leben und Tod geht es am Flughafen auch, gerade, wenn die IT nicht funktionieren würde. Komplex und für Laien kaum zu durchschauen ist Vermögensmanagement auch.
Auch das häufig – leise – gehörte Argument, dass Mitarbeiter im Gesundheitswesen IT und Technik ablehnend gegenüberstehen, besonders die alles entscheidenden Ärzte, klingt hohl. Gemeinhin sind gerade die Wohnzimmer von Ärzten immer mit dem Neuesten an Elektronik bestückt. Und die sollen die Bremser sein?
Näher kommen wir dem Kern der Ursache schon, wenn wir die Anreizstrukturen betrachten. Abrechnung heißt im Gesundheitswesen Dokumentation. Nur wer dokumentiert kann abrechnen. Und je komplizierter die Abrechnung, desto komplizierter die Dokumentation. In Gesundheitssystemen, die auf Fallpauschalen basieren – was inzwischen die Mehrheit weltweit ist – wird die Abrechnung und damit auch die Dokumentation digitalisiert. Und dann wird der IT unter Umkehrung der tatsächlichen Kausalität vorgeworfen, dass sie zu mehr Dokumentation führt.
Umgekehrt wird aber auch ein Schuh draus: wo Mehrerlösabgaben die Erträge von Produktivitätssteigerungen (was in der Regel heißt: mehr Output bei gegebenen Kosten) wieder abschöpfen gibt es keinen Anreiz in Produktivität – also IT – zu investieren. Der ROI funktioniert dann einfach nicht. Die erstaunliche „Pflegepersonaluntergrenzen Verordnung“ in Deutschland ist da nur ein weiteres Beispiel für die systemische Beseitigung von Produktivitäts- und Investitionsanreizen. Wer bereits erfolgte Effizienzverbesserungen durch die Verlagerung nicht-pflegerischer Tätigkeiten an nicht-pflegerisches Personal wieder rückgängig machen muss, der wird erst recht nicht in weitere Produktivitätssteigerungen investieren – es ist ja gesetzlich untersagt, effizient zu sein.
Aber auch all diese Erklärungen gehen aus meiner Sicht immer noch am Kern der Herausforderung vorbei. Durch die Fokussierung auf Medizin läuft die Healthcare IT zu häufig in eine nur schwer zu erkennende Falle. Medizin dreht sich um den Menschen, den einzelnen Patienten. Gute Dokumentation sollte daher Patienten-zentrisch aufgebaut sein (natürlich kann man auch beliebig häufig redundant und unzusammenhängend Daten auf einzelnen Inseln sammeln, die bei der Eingabe zu endloser Doppelarbeit und Frustration führen, beim Patienten zu Verwunderung und schließlich Resignation und bei der Abrechnung zu Dokumentations- (=Erlös-) Lücken). Patientenzentrik bedeutet aber auch, dass Daten um einen Patienten strukturiert sind und damit nur mühsam zur Ablaufsteuerung genutzt werden können. Um zu erkennen, welcher Arbeitsschritt als nächstes wichtig und dringend wäre, genügt es nicht, Patientenlisten durchzugehen. Es müssten Prozessschritte orchestriert werden. Die sind aber nicht Patienten- sondern Mitarbeiterzentrisch. Und so findet die eigentliche Arbeit weiter analog statt.
In allen Branchen, in denen die Digitalisierung die Produktivität gesteigert hat, wurde nicht Papier abgeschafft (außer als Nebeneffekt) oder mehr Informationen gesammelt. Es wurden Prozesse verbessert! Bei der Digitalisierung der Flugtickets ging es nicht um die Abschaffung von Papiertickets. Es ging noch nicht einmal um die Produktivitätssteigerung des Verwaltungsprozesses für die Ausstellung von Tickets. Es ging um die bessere Auslastung der Flotte und des fliegenden Personals. Das ist die Kernwertschöpfung von Fluglinien. Genauso verhielt es sich mit der Just-In-Time Fertigung und dem EDIFACT Standard, der sich schon in den 90er Jahren durchsetzte. Es ging nicht um die Senkung von Einkaufskosten, es ging um höhere Maschinenauslastung bei deutlich reduziertem working capital.
Was ist die Kernwertschöpfung im Gesundheitswesen? Jedenfalls nicht Dokumentation und Abrechnung.
Im Gesundheitswesen beschäftigen wir uns intensiv mit der möglichst schnellen und umfassenden Erfassung von (Dokumentations-) Daten, aber verpassen viel zu oft, aus diesen Daten Prozessverbesserungen abzuleiten. Und dann den eigentlich wichtigen nächsten Schritt zu gehen: die Steuerung zu verbessern.
Steuerung. Wer macht was wann und wann nicht? Das erscheint programmierbar in einer Fertigungsstraße, in der sich kurzfristig nur wenige Parameter verändern. Aber in einem Krankenhaus, wo ca. die Hälfte alle Tätigkeiten durch (kurzfristig) unvorhergesehene Ereignisse beeinflusst werden und damit nur schwer planbar sind? Wenn wir in einem solchen Umfeld von Steuerung sprechen, kann es nur Echtzeitsteuerung sein.
Diese Echtzeitsteuerung findet heute fast ausschließlich ad-hoc statt. D. h. die wichtigsten Parameter sind die Entscheidungen der Handelnden vor Ort, deren Erfahrung und auch deren – begrenzter - Ereignishorizont. Und so wird in der Regel nach akuter Dringlichkeit entschieden, statt nach übergreifender Bedeutung. Und die meisten anderen Steuerungsentscheidungen werden an Warteschlangen ausgelagert. Ob es der Stau in der Notaufnahme, vor dem CT ist, oder die entlassfähigen Patienten, die noch auf Labor oder Arztbrief warten, um auch tatsächlich das Haus zu verlassen. Schnell werden diese „Eh-da“-Kosten aber sechs-, wenn nicht siebenstellig. Aber nur ausnahmsweise werden Prozesse entsprechend angepasst und gesteuert.
Wenn nun aber ein grundsätzliches Niveau an Digitalisierung erreicht wurde, warum werden die jetzt in Echtzeit vorliegenden Daten nur so selten auch zur Steuerung genutzt? Eher werden Bilder aufgehängt, um die Wartezimmer aufzuhübschen.
Dazu fehlen zwei notwendige weitere Schritte: Daten werden nicht in einem Leitstand zusammengebracht und wichtige Kennzahlen auf Überschreiten von roten Linien überwacht. Und auch wenn dies geschähe, dann fehlt die Steuerungs-Ressource, die nunmehr in den Prozess eingreift und koordinierend tätig wird. Wenn das Wartezimmer in der Notaufnahme überläuft und Datenanalyse gezeigt hat, dass ab einem bestimmten Niveau die Ergebnisqualität (d. h. die spätere Mortalität und Verweildauer) auf Station signifikant sinkt, dann muss man eigentlich gar nicht wissen warum das so ist, man muss nur eingreifen und das Wartezimmerproblem lösen. Es bedürfte also eines Leitstandes, der die Wartezeiten im Blick hat und im Zweifel dabei unterstützen kann, Betten freizubekommen, Verlegungen zu veranlassen, Ressourcen umzudirigieren, damit der Pegel wieder unter die kritische Schwelle sinkt.
Wenn auf Station jeden Tag hunderte Alarme von bettseitigen Geräten erzeugt werden, entsteht ein ähnlicher Teufelskreis. Mit ständigem Alarmmanagement beschäftigt und dadurch in zusätzlichem Stress, können andere wichtige, aber nicht dringende Aufgaben nicht mehr vollständig ausgeführt werden. Auch stumpft man gegen den Alarmstress ab und läuft Gefahr wirklich kritische Alarme nur verzögert wahrzunehmen. Die Zeit, Daten zu überwachen und kritische Verläufe frühzeitig zu erkennen und einzufangen – was nicht nur dem Patienten zugute kommt, sondern auch die Verweildauer und damit die Kosten reduziert – bleibt fast gar nicht mehr. Würde ein separater Leitstand die verfügbaren Daten in Echtzeit überwachen, könnten erfahrene - menschliche - Ressourcen Alarme nicht nur wie ein Algorithmus grob filtern, sondern überhaupt nur die relevanten Alarme auf Station weitergeben. Man könnte auch die Leitlinien-gerechte Durchführung der nötigen Aktion überprüfen. Und es könnten Patientendaten proaktiv überwacht werden und kritische Tendenzen frühzeitig entdeckt werden, ohne unnötige falsch-positive Nachrichten zu generieren.
Die entsprechenden Echtzeitdaten sind häufig „eigentlich“ vorhanden. Sie müssen nur zusammengeführt werden und die kritischen Entscheidungsschwellen müssen festgelegt werden. Und dann kann ein Leitstand seine Arbeit aufnehmen. Die Möglichkeit, dann in den mobilen Arbeitsbereich hinein zu kommunizieren, ist heute kein Hindernis mehr. Alles kein Hexenwerk.
Entscheidend ist die Erkenntnis, dass der Mehrwert der Digitalisierung in Prozessverbesserung liegt. Und dass diese erarbeitet werden muss – es existiert noch keine KI, die Prozesse automatisch analysiert, Veränderungen vereinbart, schult und kommuniziert. Und die Erkenntnis, dass Prozessverbesserung zumeist mit einer veränderten Verteilung von Ressourcen verbunden ist.
Wir denken also einerseits zu patientenzentrisch – zwar mit gutem Grund aber eben doch zu absolut. Und andererseits denken wir zu schwarz-weiß. Wenn digitalisiert wird kann der Computer bis auf weiteres nur Menschen bei der Arbeit unterstützen und produktiver machen. Sie ersetzen kann er bisher nicht. Weder Banken noch Flughäfen arbeiten ohne Mitarbeiter. Sie haben sogar mehr als vor dreißig Jahren. Aber der Output hat sich noch um ein Vielfaches mehr gesteigert. Durch die hybride Nutzung von IT und menschlichen Ressourcen zur besseren Steuerung.
Wir sollten auch im Gesundheitswesen mehr Augenmerk auf die Nutzung von IT zur Verbesserung der Ablaufteuerung legen. Das wird es uns ermöglichen nach dreißig Jahren auch die Ernte einzufahren.

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Technology and IT Trends in Healthcare 2020

hcordes@neoqua.com — Wed, 16 Nov 2022 19:11:54 GMT

This is a subtitle for your new post

It is not an exact science attempting to forecast future trends. Yet many stakeholders welcome the assistance that the trend analysis industry brings - giving some order and insight into the noisy jungle of innovation, disruption and opportunities.
Healthcare technology is no different in this respect.
When reviewing and collating the various trend predictions for healthcare technology there are very few surprises. “IoT and Wearables will take over”, “AI and big data are going to run the world in healthcare too”, all sorts of realities will help navigate the world and “5G will real-time everything in 2020”.
Despite the striking similarity of healthcare technology trends with the global hypes and buzz-words, it is still meaningless to ask whether these trends are merely a product of the industry echo-chamber.
When we reviewed these “supposed trends” in healthcare technology, we were disappointed to find several stark omissions: while everyone is excited about all of the new gadgets and toys, there does not appear to be any clarity on what the applied use cases and workflow trends are!
Why!
We strongly believe technology and its trends should be rooted in the practical benefits they provide. Otherwise they are simply just “stuff” – interesting it their own right, but of no real value or use. That may seem a bit unfair towards many of the emerging technology solutions, but, without use cases, technology lacks purpose.
Use Cases
Practical application of technology does exist. In demographics and healthy longevity (both on the patient side as well as on the provider side (flatlining supply in funding and workforce), in personalized medicine and genomics, and an exponentially growing suite of technology options, from robotics, 3D printing, sensors and machine vision.
The first will drive significant productivity increases in healthcare after what has been a long period of production increase only. We will see more quality to be asked for per entity of funds, rather than more volume per entity of nurse.
The second is suddenly giving medical and clinical data value, which has been long anticipated but, in all reality, so far never been awarded. (The only value so far was in billing or reimbursement relevant data.)
We are entering an era, where medical big data (as well as small data) will become critical for decision support, assessing, filtering and planning for personalized treatments, operational process improvements and better patient flow (rather than patient output). And, last not the least, will allow to move all the great ideas for a more digitally or data enabled healthcare environment into reality.
Telemedecine
If we review technology trends in healthcare through the prism of a demographics driven pull for productivity and an innovation driven push (pharma and diagnostics) for more data, they present themselves in a different light.
Driven by the increasing need for productivity, especially in the sense of more quality per unit of input, we strongly believe telemedicine will indeed become a mega-trend in healthcare. Few use cases, if any, have such significant productivity and quality reserves to offer like telemedicine in its widest sense.
If that is true, then any supporting and enabling technology which will enhance and elevate the use case offer of telemedicine will benefit from that trend.
Wearables
Wearable glucometers will not catapult remote monitoring forward. But solutions that offer easy deployment (who has ever tried to reliably explain how to connect a Bluetooth device to one’s grand-parents knows what we mean), harmonized data, “noise” filtering and actionable workflow (decision) support, will.
Sensors (wearables, IoMT), when part of an end to end workflow – and companies who offer it – will indeed start revolutionizing prevention and early detection.
AI
Use cases are also emerging for AI. Not because “artificial” is suddenly so much more “intelligent” than it was five years ago, but because there are practical applications in personalized medicine, pharma, medical devices, prevention or decision support, that ask for smart help.
We do not believe that AI has moved much past what we used to call “pattern recognition” in healthcare yet (other than the consumer or advertising market, healthcare is not an area where 80% or even 99% accuracy is good enough), but pattern recognition is a decidedly good enough start. Also, we now have more and more valid digital clinical data available. Companies that drive solutions around normalizing, harmonizing, aggregating and (underestimated but importantly) curating data will be at the core of this trend. AI as a buzzword will not change healthcare more than a step-counter does, but companies that find ways to aggregate data from the usual islands in healthcare, and turn it into information and actionable tasks will.
Data Analytics
There is an area that we believe is underestimated by both trend prophets as well as technology companies alike: data analytics. As an industry we continue to miss the opportunity for good old- fashioned analysis of operational data which we generate in all the various systems and use it to improve efficiency and effectiveness of processes in the healthcare delivery. That may be because we are so focussed on enabling technology that we keep overlooking the soft benefits of data analytics. It may also be because of a still quite limited demand caused by a change-hesitance (sometimes even resistance) of clinical processes. We do however predict (and hope) that companies who understand the value of the data generated and collected in their solutions, and who invest in turning findings into actionable insights and change management, will be surprised by the impact this will have on adoption, retention and recurring revenues.
Summary
There is no doubt that IoMT and AI will play an increasing and important role in healthcare. Without enabling technologies like 5G, Chatbots, Robotics and others, not to mention data security and protection solutions innovation will soon run out of steam. If trend analysis in healthcare does not move beyond repeating buzzwords though, we may altogether miss the opportunities. Wearable sensors which patients struggle to connect, and which just create more noise will be quickly rejected by providers. However, solutions that turn the intersection of enabling, producing, analysing and filtering technology into relevant workflows however will push more open doors than ever before.
Healthcare is at the brink of a next phase in digitalization. If we focus on use cases, workflows and benefits and avoid being seduced by brilliant “gadgets”, we will see a truly new generation of healthcare provision and fulfil generation-old promise after all.

The Importance of Blended Finance in Achieving SDGs and Directing Private Capital to ESG Projects

Wed, 16 Nov 2022 18:54:52 GMT

Achieving Sustainable Development Goals

To achieve mandated Sustainable Development Goals (SDG’s) by 2030 and facilitate the growth of Environmental, Social and Governance (ESG) opportunities globally a substantial increase in investment is needed - from infrastructure projects like schools, hospitals, broadband networks, pipelines and roads to funding innovative national healthcare and technology initiatives.
However, unlocking such investment requires tackling significant obstacles that are currently choking the flow of capital.
Historically there has been a sharp distinction between public sector projects funded by governments, multilateral development banks (MDBs) and overseas development assistance (ODA), and private sector growth funded by commercial banks, finance institutions and other private investors. However, the capital flow from this architecture is proving to be insufficient to facilitate the growth needed to meet SDG targets or fund necessary ESG projects.
An emerging solution is for development finance institutions (DFIs), which include the MDBs together with sovereign wealth funds (SWFs), and government agencies to look to mobilise private capital through Blended Finance.
Blended Finance involves public funders using market-driven risk mitigation tools to mobilise multiples of additional private capital through reduced risk and enhanced returns. This approach has been demonstrated to achieve above market ROI while also achieving the social and environmental outcomes expected of SDG’s and investment in ESG.
Blended Finance can be structured in several ways to address specific barriers inhibiting the flow of private capital. For example:
• Junior equity or guarantee;
• Capped return;
• J-Curve mitigation; or
• Early investment.
In our view, the need for Blended Finance has never been greater and could be the single most important lever in delivering SDGs and much need private investment to ESG (Environmental, Social and Governance) opportunities globally.
With its extensive network of partners and consultants Neoqua is ideally placed assist its clients navigate through the various Blended Finance models.