Human-Centered & Data-Driven Healthcare: Essential Questions for 2023 Executives

When I moved to the US in 2013, I was very focused on discovering the potential of digital health.

I was a doctor who was broken by his healthcare system and by his country's failed revolution. I wanted to heal both and the whole concept of a "digital health revolution" seemed to be coming at me in the right time at the right moment.

I made a big career shift from a potential cardio-thoracic surgery career to becoming a clinical data consultant and digital health advisor. The hospital was a stifling place for me and my creativity, and I felt like a career in technology would better suit me as I described on my last article.

However as I started to work with Payers and large hospitals, I started to see that the misery of doctors (that I saw in the hospital as an intern) seemed to be increasing over time.

In this article I will share:

• A new approach to look at technology and data strategy that drive retention
• Insights on human trends and the complex relationship between tech and human suffering
• Data strategy questions you need to ask, and proven steps you can take as an executive to drive a true data-driven healthcare organization

A New Understanding

After 10 years in the industry, and with dramatic changes ahead, I realized that we need to be asking new questions.

Once I started asking these questions rather than building adhoc technology, I have been able to get the following results with health systems and clinics.

• Helped a US University health system improve tableau data source utilization by 3x
• Ran data literacy programs for 30 different students with an >90% engagement rate.
• Guided doctors and nurses to build their first dashboard products that tackled antibiotic utilization, first case on time start surgeries, and optimized nursing floor supply.

I will explore 3 of these use cases that improved retention and happiness alongside latest health data industry trends in the US host a webinar next week. Fill out this form if you are interested

Technology alone has increased human suffering

One thing we do not talk about in healthcare is the inflation of human suffering.

We talk about the rising costs of health tech and services (e.g. MRI scans and CT scans get more sophisticated and more pricey - unlike Moore's law), but what about the rising cost of human suffering?

Since my story started as a suffering physician I could not turn a blind eye to the pain that I saw being perpetuated through Electronic Medical Records.

I was experiencing this in 2013.

So where are we now?

In Elsevier's 2022 Clinicians of the Future report (see below), it outlines the following:

• ?? 56% of clinicians predict AI-driven clinical decisions will be the norm.
• ?? However 69% feel overwhelmed by current data volume.
• ?? 69% predict digital health's challenging growth.
• ?? 83% emphasize overhauling training to keep up with tech.

The digital health industry and investors are feeling this happen. Big time.

I do not think this is the end of digital health, but a correction is long overdue.

The answer now -in hindsight- is a simple design proposition: We have built technology that does not satisfy the needs of doctors and nurses.

This simple answer raises a more complex question though.

Why are we building technology in the first place?

Why do we really need data?

And how will data become a real competitive advantage?

Instead of fixing healthcare, the business of healthcare is what fixed digital health companies.

We call it "pivoting" to feel better about ourselves.

I am sure that the people who built the first EMRs where not trying to increase the suffering of those who use it, probably quite the contrary.

However, we now know better when it comes to design principles and design thinking.

Humans are your biggest asset - not technology or data

Today, we live in a world where Generative AI and technology pose another similar opportunity that can turn into a threat for healthcare.

It is coming in a world where economical and mental health suffering is even more rampant.

So will we learn from implementing EMRs?

Or will we dive into another gold rush of throwing tech and money at a problem and hoping it magically disappears?

In case you have not noticed, the humans in healthcare are changing dramatically:

• The frontline is changing: "America will face a shortage of up to 124,000 physicians by 2033, and will need to hire at least 200,000 nurses per year to meet increased demand and to replace retiring nurses." According to an American Healthcare Associaton report
• And the CEO's are also changing: "Hospitals have announced a total of 82 CEO changes this year, an increase of 49% from the 55 Hospital CEOs who left their posts during the same period in 2022." Challenger, Gray and Christmas Report

This is not to say that technology is the culprit. These numbers also represent retirement and an aging generation of executives (CEOs tend to be some of the oldest employees in healthcare).

This all means that the future of healthcare hinges on humans as its most precious resource and competitive edge not technology.

This also means that there is new blood in the industry and hopefully a more open mindset for the challenges to come (and there will be many!).

“It is not freedom from conditions, but it is freedom to take a stand toward the conditions.” Viktor E. Frankl, Man's Search for Meaning

Building a technology and data strategy that drives human retention and happiness

Since my days as a consultant, I have become a data advisor and coach for CEOs and CIOs in healthcare that are looking to make a difference.

My philosophy is simple: Build with (not for) humans.

Here are some things to get you thinking until I share my use cases with you on the webinar.

1- Stop top-down approaches, build your data governance strategy from the bottom up

We do not need anymore executive summaries and powerpoints. We need facilitated conversations that allow us to build long term strategies to meet the human needs.

You also can't get away with having a strong data science team of consultants, while your frontline team can't create any insights from data.

Stop creating surveys that people never see the result of.

This point requires a whole article but here are some questions to get you started.

Your data governance and strategy needs to take the following into consideration:

• How data and technology literate is your workforce?
• What datasets do frontline people find interesting? What problems are interesting for frontline workers? Which of these problems are revenue generating or cost reducing?
• How are patients ingesting these datasets? Do they understand what is on their charts?
• How is data being collected? How happy are doctors with documentation process?
• What is the overall level of data quality in the organization? Does the frontline really trust this?

2- Forget about compliance, find the top performers instead and let them build you a thriving data community.

I have consulted many CEOs and CMOs who are very frustrated with the resistance to new a new culture that they have spent months creating.

When I get their residents or physicians in a room and ask them what they need, one word comes up: Trust.

"We want to be seen, executives don't see what we do or eat our food or see how we sleep or handle patients." one resident told me.

In order to gain the trust of your frontline workers, you need to recognize and empower them.

The first step to ask the questions above, the second step is not to buy technology and force compliance, but to start identifying your health data leaders internally, and to make them shine.

1. Nourish communities of practice, and empower the top tinkerers with data to lead them. Essentially, you want data analytics to be "cool" rather than "another thing admin is asking us to do". The only way to do that is to create a safe learning space and a data community.
2. Further more, you need to build teams that drive frontlinedata ownership. A problem with data is that it can easily turn into a blame game. This is crucial for a healthy data culture, data analysts alone can't do it all, you need the frontline to act as SMEs and take an active role in maintaining the datasets they find interesting.

This is how you build a thriving data culture.

3- Explainability is key

A big challenge for us with LLMs and various forms of AI is that we sometimes can't explain why an AI is recommending something. This makes it challenging for humans to act upon it.

This problem goes deep because if a doctors can't understand it, they can't explain it to a patient.

This is how far downstream you have to think about data literacy and data utilization. It is not about an algorithm making a decision, it is about a whole organization using data the same way blood runs through a human body.

This requires transparency, reliable data and decisions that can be explained.

To summarize:

• Humans are becoming more rare in healthcare, they are your competitive edge.
• Build data strategies that are bottom up not top down. (More on this later)
• Recognize and create safe spaces for everyone to learn data, let the ones who are most interested in tinkering with data lead them.
• Ensure that your algorithms and AI components drive explainability upwards by offering widespread data education that trickles all the way to your patients.

If you are interested in attending my webinar where I will share 3 industry use cases about health data leadership and literacy improving employee retention and happiness > fill this 3 min survey.

More on the topics above in the coming weeks!

Omar

Links for further reading: