Archimedes Model Introduction

An Overview of the Archimedes Healthcare Model The Archimedes Project Kaiser Permanente

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This presentation will address three main topics: • What the Archimedes model is • How it can be used • How we know it works

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Until now, there have been four main kinds of mathematical models in health care • Biological modeling – e.g. glucose metabolism, Starling heart equation • Clinical Medicine – e.g. Regression equations, Markov models • Operations research / management science – e.g. Schedule operating rooms, plan hospitals • Economic / system resources – e.g. Forecasting A KAISER PERMANENTE INNOVATION

Archimedes is a new type of mathematical model of health care: it includes all four components Biological modeling Clinical medicine Care processes System resources A KAISER PERMANENTE INNOVATION

Archimedes is also new because it is anchored to reality through clinical trials Biological modeling Clinical medicine Care processes System resources A KAISER PERMANENTE INNOVATION

This presentation will address four main topics. Let’s begin with: • • • • • •

What the Archimedes model is How it can be used How we know it works What we plan to do with it How you will be able to get access to it What’s on this website A KAISER PERMANENTE INNOVATION

Archimedes is • Object oriented • Continuous • Physiology based • Very deep and very broad • and it operates at the level of detail that clinicians and administrators consider essential for making decisions A KAISER PERMANENTE INNOVATION

Now let’s define those terms. This is what we mean by “object oriented” • All the important objects in reality have corresponding objects in the model, one-to-one, at a high level of detail ƒ Patients, organs, parts of organs ƒ Facilities ƒ Health care personnel

ƒ Equipment, supplies ƒ Policies and procedures ƒ Budgets, regulations, more A KAISER PERMANENTE INNOVATION

More specifically, this means that • There are thousands of simulated people in the model, each one of them different • They can get sick, and go see simulated doctors • In simulated offices • And get simulated tests, that use simulated pieces of equipment • And get simulated treatments • And so forth A KAISER PERMANENTE INNOVATION

This is what we mean by “continuous” • Biological variables that are continuous in reality are continuous in the model (e.g. BP, LDL cholesterol) – No “clinical states”, “strata” • Time is continuous; any event can occur at any time – No “ticks”, “steps” or “annual jumps”

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The concept of “physiology based” needs more explanation. And we’re going to need a volunteer I’ll volunteer Thanks. What’s your name? Joe. Joe Miner OK Joe. I hope you’re not ticklish…

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… because we’re going to need to look inside your belly. Can you come a bit closer? Sure

A little bit closer, if you can A KAISER PERMANENTE INNOVATION

How’s this?

That’s good. Nice belly, Joe. Now we’re going to need to do a sort of x-ray

OK. The reason we’re doing this is that we want to show you that every simulated person in the model, like Joe, has organs, such as…

Heart And every organ has all of its types of cells, like these beta cells of the pancreas

Liver

Circulatory system

Pancreas

Fat cells Gut

Muscle

The organs and their cells carry out metabolic functions, such as…

GLYCOGEN GLYCOGEN GLUCOSE GLUCOSE

HEPATIC GLUCOSE PRODUCTION

CIRCULATING GLUCOSE

GLUCOSE UPTAKE BY MUSCLE GLUCOSE UPTAKE BY FAT

SUGARS

In the model, these functions are regulated just as they are in a real person. For example, in response to the circulating levels of glucose, the pancreatic beta cells will secrete insulin

GLYCOGEN GLUCOSE

HEPATIC GLUCOSE PRODUCTION

GLUCOSE UPTAKE BY FAT

CIRCULATING GLUCOSE INSULIN

SUGARS

GLUCOSE UPTAKE BY MUSCLE

And diseases can occur. For example, in a person with diabetes the effect of insulin on uptake of glucose by the muscle and fat is decreased.

GLYCOGEN GLUCOSE

HEPATIC GLUCOSE PRODUCTION

INSULIN

Diabetes

GLUCOSE UPTAKE BY FAT

Diabetes

SUGARS

GLUCOSE UPTAKE BY MUSCLE

Diabetes also affects the effect of insulin on production of glucose by the liver cells

GLYCOGEN GLUCOSE

Diabetes HEPATIC GLUCOSE PRODUCTION

GLUCOSE UPTAKE BY FAT

INSULIN

SUGARS

GLUCOSE UPTAKE BY MUSCLE

If we were to illustrate the biological variables and relationships in the model that affect the metabolism of glucose, it would look something like this

Family history

Gliburide

Insulin treatment

Insulin level

Unexplained variance in OGT

Sex Type 1 Diabetes feature Race/ ethnicity

Type 2 Diabetes feature

Joint Diabetes feature

Insulin production (Pancreas) Insulin efficiency (Muscle)

Age

BMI

Height

Insulin efficiency (Liver)

Age, sex, race/ ethnicity

Weight

Diabetes blood pressure factor Peripheral resistance

Glucose uptake by muscle

OGT

OGTT test

Random plasma glucose

Random plasma glucose test

Random error and variation

FPG test

FPG HbA1c test

Glucose production by liver Untreated insulin level

Care processes

Normal liver glucose production

Urine ketone test

Metformin

Fractional change in Insulin

Ketoacidosis

Diet and exercise

FPG

Hypoglycemia

HDL cholesterol

Diabetes diagnosis

LDL cholesterol

Triglyceride s

Systolic blood pressure

Coronary artery stenosis

Smoking

Diabetes cardiac risk factor

Propensity to blurred vision

To treatment models

Patient takes action Blurred vision Memory

Mean arterial pressure

Propensity to polyuria

Polyuria

FPG Perception

Cardiac output

Arterial compliance

Pulse \ pressure To the Retinopathy model

To the Nephropath y model

To the Neuropathy model

To the Coronary artery disease model

Propensity to fatigue

Fatigue

Propensity to thirst

Thirst

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All of that, and many, many more variables that are important to the complications of diabetes and to other diseases, are being calculated continuously in every simulated person in the model

Family history

Gliburide

Insulin treatment

Insulin level

Unexplained variance in OGT

Sex Type 1 Diabetes feature Race/ ethnicity

Type 2 Diabetes feature

Joint Diabetes feature

Insulin production (Pancreas) Insulin efficiency (Muscle)

Age

BMI

Insulin efficiency (Liver)

Age, sex, race/ ethnicity

Glucose uptake by muscle

Random plasma glucose test

Random error and variation

Diabetes diagnosis

FPG test

HbA1c test

Glucose production by liver Untreated insulin level Normal liver glucose production

UKPDS data Weight

OGTT test

FPG

Metformin

Height

OGT

Random plasma glucose

Diet and exercise

Diabetes blood pressure factor

HDL cholesterol

LDL cholesterol

Triglyceride s

Peripheral resistance

Mean arterial pressure

Systolic blood pressure

Coronary artery stenosis

Cardiac output

Arterial compliance

Pulse \ pressure

Smoking

Diabetes cardiac risk factor

Care processes

Urine ketone test

Fractional change in Insulin

Ketoacidosis

FPG

Hypoglycemia

Propensity to blurred vision

Blurred vision

Propensity to polyuria

Polyuria

Propensity to fatigue

Fatigue

Propensity to thirst

Thirst

To treatment models

Patient takes action

Memory

FPG Perception

To the Retinopathy model

To the Nephropath y model

To the Neuropathy model

To the Coronary artery disease model

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And there are lots of simulated people, thousands in fact, all of them with different risk factors, physiologies, behaviors, et cetera. (The differences are shown as different colors of their aprons)

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Thanks Joe, you can go back to the model now.

You’re welcome. Good bye

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That was “physiology-based”. Let’s move on now. Here’s what we mean by “broad and deep” • Object oriented • Continuous • Physiology based • Very deep and very broad • and it operates at the level of detail that clinicians and administrators consider essential for making decisions A KAISER PERMANENTE INNOVATION

“Very broad and very deep ” means that the model includes • Not only – Anatomy, Physiology, Pathology, Signs and symptoms, Tests and treatments

• But also – Patient and provider behaviors – Care processes: e.g. guidelines, disease management, CQI – System resources: e.g. facilities, personnel, equipment, supplies, costs … A KAISER PERMANENTE INNOVATION

To get the idea of “very deep and very broad”, let’s follow a problem from the cellular level to the parking lot • All the simulated people in the model have all the important organs. E.g. hearts, kidneys, immune systems… • All the simulated organs have all the important parts. E.g. hearts have coronary arteries, ventricles, myocardium, sino-atrial node… • All the part have all the important subparts. e.g. arteries have lumens, walls… • All the organs and their parts have functions. e.g. arteries carry blood to the myocardium A KAISER PERMANENTE INNOVATION

There’s more •

Things can go wrong with the organs or their functions. e.g. coronary arteries can occlude.

•

When something goes wrong, it affects other things. e.g. when arteries occlude, blood flow to the myocardium is reduced. When blood flow is reduced, the feels pain (angina).

•

All the simulated patients have behaviors; when the pain reaches a threshold, the patient makes a simulated call to a simulated hospital.

•

Simulated telephone operators at simulated call centers use simulated protocols to triage calls. A KAISER PERMANENTE INNOVATION

And still more • Patients go to simulated emergency departments. (This is where the parking lot comes in) • They are seen by simulated personnel (e.g., nurses). • Simulated tests are performed…tests use equipment and supplies • Diagnoses are made…and mistakes are made • Patients are admitted, rooms are occupied, … • Treatments are given… A KAISER PERMANENTE INNOVATION

You get the idea. “Very broad” and “very deep” means that the effects of any encounter keep ramifying through the simulated health care system, just as happens in the real world • • • •

Logistics happen… Utilization occurs… Outcomes occur… Costs occur… A KAISER PERMANENTE INNOVATION

There’s one more thing to discuss, the level of detail • • • • •

Object oriented Continuous Physiology based Very deep and very broad It operates at the level of detail that clinicians and administrators consider essential for making decisions A KAISER PERMANENTE INNOVATION

The level of detail is determined by the people who will use the model • If a clinician says that a particular variable is critical to their own thinking, and the model won’t be credible without it … • We include the variable – e.g. ejection fraction, insulin level, “beta cell fatigue”, peripheral resistance • Ditto for administrators – E.g. there are 37 different types of office visits A KAISER PERMANENTE INNOVATION

Now let’s talk about: • What the Archimedes model is • How it can be used • How we know it works

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The purpose of Archimedes is to create a virtual world • • • • • • • •

Virtual people who have virtual physiologies get virtual diseases have virtual signs and symptoms go to virtual doctors get virtual tests and treatments and have virtual outcomes just like real people A KAISER PERMANENTE INNOVATION

If it works, then we can use the virtual world to try out, evaluate, explore, optimize, plan, improve, predict…lots of different things. Such as… • • • • • •

Guidelines Disease management programs Nursing algorithms Changes in care processes Continuous quality improvement programs Performance measures and targets A KAISER PERMANENTE INNOVATION

And more… • • • •

Priority setting Strategic goals Research How “ideal” research trials translate to “real” clinical settings • Logistics, use of resources • Costs, cost-effectiveness, and value • Planning A KAISER PERMANENTE INNOVATION

The idea is that we can use the virtual world to learn the effects of lots of different types of interventions that would be infeasible to study through empirical methods (more research), for a variety of reasons: • • • •

Too high a cost Too long time needed for a new study Too many patients needed Unwillingness of patients and/or physicians to participate • Too large a number of options to study • Technologies that are changing too rapidly A KAISER PERMANENTE INNOVATION

This is very important, because • An empirical study – e.g. an evaluation study or clinical trial – of a single intervention will – cost hundreds of thousands, or even hundreds of millions of dollars – require hundreds, or thousands of people – take years • Whereas an Archimedes simulation takes much less time and costs less A KAISER PERMANENTE INNOVATION

Sounds good. And I’m happy to help out. But if you don’t mind, I’ve got a question. All this is premised on an assumption that it works right. How do you know that it works? I mean, I know that my equations are working fine. But I’m not so certain about the other jokers who are in here with me. A KAISER PERMANENTE INNOVATION

Thanks Joe, that is indeed a crucial question: • What the Archimedes model is • How it can be used • How do we know it works?

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Here’s how: • We compare what happens in the virtual world with what happens in the real world, • in lot’s of different settings, • that test the parts of the model that will be used for the types of applications we want to do – i.e. similar people, similar treatments, similar outcomes A KAISER PERMANENTE INNOVATION

The best way to do this is to use clinical trials because we know the most about them A trial involves people who meet the entry criteria for the trial

The trial is conducted

And the outcomes are measured

They get the treatments specified in the protocols of the trial A KAISER PERMANENTE INNOVATION

We use the virtual world of the model to simulate the real-world trial People Treatments We use the same criteria to select people We have simulated physicians follow the same treatment protocols

Real clinical trial

Real Outcomes

And we compare the results We let the model do its thing

We count the outcomes, using the same definitions and protocols A KAISER PERMANENTE INNOVATION

There are 10 steps involved in performing a validation 1. We start with a large population of simulated people, just like a simulated city 2. We identify the inclusion criteria for the trial 3. We randomly select from the large population a sample who meet the inclusion criteria for the trial 4. Confirm that major characteristics match (“Table 1”) 5. Randomize the simulated people A KAISER PERMANENTE INNOVATION

There are 10 steps involved in performing a validation (Cont’d) 6. Identify the treatment protocols used in the trial 7. Have simulated providers apply the treatment protocols to the simulated people 8. Have the simulated providers apply the follow-up protocols 9. Record the results seen in the real trial 10. Compare the simulated results to the real results A KAISER PERMANENTE INNOVATION

You can think of these validations as being previews of real applications • We used the populations that were in the trials – But we could have used the population that would be candidates for your guideline (or performance measure, etc)

• Similarly for the tests, treatments, outcomes, etc. A KAISER PERMANENTE INNOVATION

Archimedes has been validated against these trials, so far MRC

HOPE

DCCT primary

SHEP

4-S

DCCT secondary

HHS

CARE

MICRO-HOPE

LLRC

LIPID

IRMA

WOSCOPS DPP

Lewis

HPS

IDNT

UKPDS

VA-HIT A KAISER PERMANENTE INNOVATION

Here’s an example: the Heart protection Study • Population: adults age 40 – 80, at high risk of MI because of high LDL, or other arterial occlusive disease, or diabetes • Treatments: Simvastatin vs. placebo • Size: 20,500 • Duration: 6 years A KAISER PERMANENTE INNOVATION

This was the rate of major coronary artery events in the placebo and treated groups Major Coronary Events in Heart Protection Study 0.14

Solid lines are the real results

Fraction of patients

0.12 0.1

Placebo group

0.08 0.06

Treated group

0.04 0.02 0 0

0.5

1

1.5

2

2.5 Years

3

3.5

4

4.5

5

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The dotted lines showed what the model calculated Major Coronary Events in Heart Protection Study 0.14

Dotted lines are the model’s results Fraction of patients

0.12 0.1

Placebo group 0.08 0.06

Treated group 0.04 0.02 0 0

0.5

1

1.5

2

2.5 Years

3

3.5

4

4.5

5

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Here’s another example, the Diabetes Prevention Program • Population: men and women over age 25. broad range of racial and ethnic groups. Prediabetes (IGT or IFG) • Treatments: intensive lifestyle vs. Metformin vs. standard care • Size: 3000 • Mean duration: 2.8 years A KAISER PERMANENTE INNOVATION

In this case, the results were calculated by the model before the real results were known. This is what the model predicted. DPP: Diabetes Progression 0.5

Control Metformin Lifestyle

0.45 0.4

Fraction

0.35 0.3 0.25 0.2 0.15 0.1 0.05 0 0

1

2

3

4

5

Time (years) A KAISER PERMANENTE INNOVATION

The dotted lines are what the model predicted. The solid lines are the results that were eventually published. DPP: Diabetes Progression 0.5

Control Metformin Lifestyle

0.45 0.4

Fraction

0.35 0.3 0.25 0.2 0.15 0.1 0.05 0 0

1

2

3

4

5

Time (years) A KAISER PERMANENTE INNOVATION

Here’s an example of a long term trial that measured the effects of treatment on complications of diabetes: UKPDS • Population: middle aged men and women, with newly diagnosed type 2 diabetes • Treatments: intensive treatment vs. conventional treatment • Size: 3900 • Duration: 15 years A KAISER PERMANENTE INNOVATION

This shows the effect of treatment on the most important outcome: heart attacks UKPDS: MI (fatal and non-fatal) 0.3

The solid lines are the real results

Fraction of patients

0.25

Conventional treatment

0.2

0.15

Intensive treatment

0.1

0.05

0 0

2

4

6

8 Time (years)

10

12

14

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This is what was calculated by the model UKPDS: MI (fatal and non-fatal) 0.3

The dotted lines are the model’s results

Fraction of patients

0.25

Conventional treatment

0.2

0.15

Intensive treatment

0.1

0.05

0 0

2

4

6

8 Time (years)

10

12

14

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We have done this for 74 different combinations of populations, treatments and outcomes. This chart compares results calculated by the model (y-axis) against results of the real trial (x-axis). Results calculated by model

0.6

Each dot represents an arm of a trial. The real result of the trial is plotted against the result calculated by the model. Perfect correspondence would be the 45º line

0.5

0.4

0.3

0.2

0.1

0 0

0.1

0.2

0.3

0.4

Results from trials

0.5

0.6 A KAISER PERMANENTE INNOVATION

One would not expect perfect correspondence because of random factors, related to the number of people in the trial • 71 of 74 are well within sampling error • The other 3 have good explanations – either it just missed (e.g. p = .04) (which is to be expected statistically) – or the description of the trial was incomplete • 54 of 74 are within ± 1 standard deviation • For all 74 exercises: r = 0.99 A KAISER PERMANENTE INNOVATION

For some of the trials, some of the data from the trial were used to help build parts of the model. The other trials are 100% independent • For the exercises that were not used at all to build the model (100% independent), the correlation between the model and the trial was still extremely high • The correlation was still r = 0.99 A KAISER PERMANENTE INNOVATION

These validations are important for several reasons • They give us confidence that for applications that are spanned by validations, the model is accurate • They illustrate the types of applications that the model can do • No other model of clinical medicine has been validated in this way • The alternative to the model, expert judgment, has not been validated in this way either (no offense intended)

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The “span” of the validations is important, because it indicates the types of populations, organ systems, and treatments we can be confident about

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Imagine that the disease that we want to understand is represented by an island. We need to completely map out and reach every part of that island

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Imagine that the available research can be represented as radio beacons on the island. The bigger and better the trial, the wider its signal.

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Now suppose that Archimedes has been validated against all of those trials. Using this visual image, we can talk about the usefulness of Archimedes for new applications

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If you ask it a question about this part of the island (A), it should do extremely well

A

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If you ask it a question about this part of the island (B), it should do very well

B

A KAISER PERMANENTE INNOVATION

If you ask it a question about this part of the island (C), it should do fairly well

C

A KAISER PERMANENTE INNOVATION

If you ask it a question about this part of the island (C), it should do fairly well, but we’d like to see a new trial done down here

C

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If you ask it a question about this part of the island (D), we’ll say “OK, but only use the model for “what if” type questions We’d rather help you design a new trial

D

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If you ask it a question about that is out in the ocean (E), We’ll say “Archimedes can’t do that yet. Help us raise some money and we’ll build a new model for that”

E

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With that in mind, it is important that Archimedes has been validated for a wide range of populations ƒ ƒ ƒ ƒ ƒ ƒ ƒ ƒ ƒ ƒ

Average risk Hypercholesterolemia Diastolic hypertension Systolic hypertension Many risk factors Angina or MI Diabetes MI average Cholesterol MI high Cholesterol Pre diabetes

ƒ ƒ ƒ ƒ ƒ ƒ ƒ ƒ

Newly diagnosed diabetes Type 1, uncomplicated Type 1, retinopathy Type 1, moderate to severe nephropathy Type 2, uncomplicated Type 2, mild nephropathy Type 2, moderate nephropathy Young, Middle age, Old A KAISER PERMANENTE INNOVATION

…and organ systems • • • • •

Liver Pancreas Heart Vascular Nerves

• • • • • •

Muscle Fat Kidneys Eyes Lungs Gut

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…and treatments • • • • • • •

Nothing (placebo) Cholestyramine Gemfibrozil Anti-hypertensive Pravastatin Simvastatin ACE Inhibitors

• Angiotensin –IIreceptor antagonists • Insulin • Metformin • Sulphonylurea • General diet advice • Intensive lifestyle A KAISER PERMANENTE INNOVATION

That’s what we mean when we say that Archimedes is anchored to reality Biological modeling Clinical medicine Care processes

(74 anchors)

System resources A KAISER PERMANENTE INNOVATION

What does all this mean? • It is possible to write equations that represent human physiology, disease, treatments and outcomes using existing information • In the “virtual world” created by these equations, simulated patients behave like patients in the real world, … • …at least as we know it through the most important epidemiological studies and clinical trials A KAISER PERMANENTE INNOVATION

It means the virtual world can be used for many purposes, such as • • • • • • •

Guidelines Performance measures Disease management programs Continuous quality improvement Strategic goals and priority setting Research planning Estimating patient-specific outcomes A KAISER PERMANENTE INNOVATION

And that’s good, because it’s a whole lot easier to explore problems and programs in the virtual world • Much faster • Much less expensive • Much more flexible • Can explore many more options • Can tell you the critical points to watch A KAISER PERMANENTE INNOVATION

If you want to use the model, there is one more thing you will need to understand • Real people like you will still have to make the final decisions • Archimedes will give you much better information than you’ve ever had before • But there are always elements of a decision that can not be quantified and that require value judgments • This is the role of humans • Thus the model is a just a tool -- a very powerful tool, but just a tool A KAISER PERMANENTE INNOVATION

But watch out. I’m gaining on you.

Family history

Gliburide

Insulin treatment

Insulin level

Unexplained variance in OGT

Sex Type 1 Diabetes feature Race/ ethnicity

Type 2 Diabetes feature

Joint Diabetes feature

Insulin production (Pancreas) Insulin efficiency (Muscle)

Age

BMI

Insulin efficiency (Liver)

Age, sex, race/ ethnicity

Glucose uptake by muscle

Random plasma glucose test

Random error and variation

Diabetes diagnosis

FPG test

FPG HbA1c test

Untreated insulin level Normal liver glucose production

UKPDS data Weight

OGTT test

Glucose production by liver

Metformin

Height

OGT

Random plasma glucose

Diet and exercise

Diabetes blood pressure factor

HDL cholesterol

LDL cholesterol

Triglyceride s

Peripheral resistance

Mean arterial pressure

Systolic blood pressure

Coronary artery stenosis

Smoking

Diabetes cardiac risk factor

Care processes

Urine ketone test

Fractional change in Insulin

Ketoacidosis

FPG

Hypoglycemia

Propensity to blurred vision

Blurred vision

Propensity to polyuria

Polyuria

To treatment models

Patient takes action

Memory

FPG Perception

Cardiac output

Arterial compliance

Pulse \ pressure To the Retinopathy model

To the Nephropath y model

To the Neuropathy model

To the Coronary artery disease model

Propensity to fatigue

Fatigue

Propensity to thirst

Thirst

A KAISER PERMANENTE INNOVATION