Virtual Festival of Evidence | Dr. Len Goldschmidt


Taking a systems approach to improving patient pathway: the U.S. Department of Veterans Affairs Care-Coordination Telehealth


Dr. Len Goldschmidt
VA Healthcare


Len Goldschmidt: Telehealth technologies have reduced hospitalisation rates significantly for a variety of chronic diseases. For certain mental health diagnoses rates have reduced by as much as 25 percent from before they were introduced. They’ve also decreased the time that patients spend in the hospital by approximately 25 percent, leading to an improved quality of life for many patients who can now spend more time at home, and less time at clinical offices and hospitals.

Interviewer: How would you say that telehealth demonstrates some of the strengths of simulation modelling?

Len Goldschmidt: Telehealth technologies accelerate the identification of serious medical conditions that would otherwise go unrecognised. Simulation and modelling programmes also anticipate adverse effects sooner than if they weren’t used. The premise of much of telehealth is the idea that by the time you end up in the emergency room or in a grave medical condition that event could have been predicted days, weeks or even months earlier.

Interviewer: So this is a huge experiment in winning people over to the benefits of simulation modelling. What was the lesson from this?

Len Goldschmidt: People need to know what’s in it for them. They need to know (1) it will not take their job away, and that (2) it will potentially make their job more interesting and enriching. But most importantly, (3) – that it will actually advance the quality of care they’re delivering. I think if an employee – regardless of the level of their employment – is aware of those realities and believes them, they will support a programme such as telehealth, which for many people really was a new, very foreign idea, certainly in the early 2000s.

Interviewer: Do you think more needs to be done here in the UK to familiarise medical students with simulation modelling and what it means for healthcare?

Len Goldschmidt: Simulation modelling around the world, but especially in the US, is undergoing a tremendous revolution. When I was in training over 25 years ago, there were no simulators whatsoever. Today most physicians who are trained in the US will undergo simulation modelling. In my opinion, simulation modelling needs to be introduced at an early stage in the education of a medical student, in order to familiarise them with the benefits. People sometimes can become fixed in their ways, but at an early stage when they’re still in training they are receptive to ideas which have been shown to be validated, such as computer modelling, that otherwise they would remain either sceptical or indifferent to later in their careers.



The basis for much of the presentation that I’m going to show today from our US Healthcare System, is the Veterans Health Administration, that takes care of our services’ veterans, 173 hospitals, 1100 clinics, it has the largest integrated healthcare system with an integrated computerised medical record. The question that I’d tried to answer early on in my career is how do you deliver uniform health care of high quality at the largest and smallest facilities, separated by hundreds and thousands of miles.

Here is our Tertiary Care Centre one of the five largest US hospitals a structure when it was built was one of the largest public works projects in the United States with 650,000 ft., [00:01:00] more now. I work in a relatively small clinic here in Livermore, California, about 50 miles away and we serve the population of this system. 40% of people never enter this tertiary hospital they’ll receive care in these smaller facilities, some of which have specialists, some of which have only primary care doctors.

It’s very similar to the structure of the National Health Service, a decentralised system in some ways and with a centralised oversight. I started thinking about how we decide on what we do, how we practice. Even at the clinical level we start with a hypothesis, we have expected results and observations to be tested with actual results and observations, this really gets at the heart of, it’s not all-inclusive [00:02:00] but it does talk about evidence. The quality of evidence, how we go about looking at validating our information, from background information, case-control studies, cohort studies, randomised controlled trials which really are not the goals.

They are the best, they are a considered gold standard, but not free of bias, critically placed individual articles, topics, syntheses and systematic reviews that try to filter our evidence. It’s not easy, we’re talking about a field that really starts with imperfect information, that’s what simulation and modelling is about. It’s about taking some of that imperfect information and creating a risk stratification of probability in our minds [00:03:00] and for an end-user. That’s how I thought of modelling before I came here.

It’s necessary as we just said, you want to be seen as an individual when you’re in the health care system and yet you also want to take advantage of randomised controlled trials, the best treatment that’s available for you, but taking into account all the parameters. Here in our system, this is a very large database, every day from these 173 hospital and a 1000 clinics, information is siphoned off and sent over a large fibre-optic network actually from Hawaii as well as Guam to Austin, Texas, where it is stored and integrated.

I used to say it was the second largest database after the [00:04:00] Internal Revenue, the taxation , but it’s probably after the National Security Agency and others I’m sure and I know huge databases, so it’s just enormous. Right now, it houses an amazing statistic of data, 20 million patients over many years, a billion outpatient encounters, nine million in patient and missions etc., just an enormous quantity of data. We’ll talk a little bit about how this data is used but mostly I want to present evidence for, how this data has made its way into clinical practice.

This data volume doubles every 18 months and so to quote one of our leaders here, I started thinking about this as “what is information, how do we use information in healthcare” and yes, it’s a science, we have to put the information on a formal footing, [00:05:00] yes we also have to look at that total organism of information and yes, we still have people with their needs, with their weaknesses, with their strengths, as our final result. What I’m going to show you, touches each of these systems, I don’t think you have to give it a name and say it’s this that or… Its components of all of this, like democracy, it’s messy and I’m going to show you some of the messiness, but I’m going to show you some of the strengths I hope as well.

I started really looking at this in a fresh light and an American philosopher, Yogi Berra and so this is important to have direction. A lot of the direction that I’m going to show you came out of an obscure report from the Institute of Medicine from 2002 that really responded to, again a crisis in healthcare. A realisation [00:06:00] that, population was getting older, that our clinical outcomes for the amount of money that we were spending, were relatively poor compared to industrial countries and a sense that there was change needed.

So again, we were talking about it informally, a moment of opportunity, a little bit of crisis and a visionary leader, this fellow Ken Kaiser, who had been the Director of Health in a large State in California, who became the Director of the Health Services for Veterans Administration, himself an emergency room physician. He took this report from the Institute of Medicine which had six aims for improvement, safety, effectiveness, patient centeredness, timeliness, efficiency and equity and the benefits of coordinating care. That one voice should talk to another, amongst services and settings and an investment in health information technology to [00:07:00] manage chronic disease.

The report recommended that individuals receive timely care that includes, care approaches outside the realm of traditional face-to-face visits. So armed with this report, Ken Kaiser becomes the Under Secretary of Health for Veterans Administration and begins to completely, radically change everything. During his tenure, there were the 73 hospitals when he started there was zero outpatient clinics, virtually zero. In less than four years, he ramped up over 1000 outpatient clinics and hired individuals and nurses, nurse practitioners to work in those settings.

He also implemented the computerised patient record, so in 2000 at the beginning of his tenure, the computerised patient record began to be rolled out in the Veterans Administration’ and in three years all [00:08:00] of the 173 hospitals and 1000 clinics had it. Today, if you were to walk into any of those it would look extensively the same as another clinic. He pioneered with this computerised patient record, Telehealth and so for most of you I think you know what this involves, but I’m going to show you a little bit of variation of what it is today, 14 years later.

It involves the use of information and telecommunication technologies to provide healthcare related services and situations where patient and provider are separated by geographic distance and the vision of both Ken Kaiser and Adam Darkins, who was the most recent Telehealth Director was that at some point it should be like the telephone, just a mechanism for transmitting information. And there really is a lot of justification in our system and I think also in the National Health Service for using this and I know it is used somewhat widely in National Health Service at present.

[00:09:00]Really, there are two main motivators, increased access to care and cost avoidance. For increased access in our system, 60% of Telehealth Associated Care is to veterans in urban areas, 37% in rural areas, 3% remote areas and this mirrors where our population lives. Patients like this, the question was, are patients going to be taking care of by a machine, are they going to see it as that? The truth is that most patients in satisfaction surveys do not feel this way. For home Telehealth it was 86%, in Store-and-forward Telehealth was even higher, so patients do accept this because again, the question we ask, “what’s in it for them?” And what’s in it for them is increased attention, from the health care system.

A sense that they are not alone, which many of them physically are, they live alone, they may not have caregivers, but this sense that these tools provide them with a link, to the people who are taking care [00:10:00] of them. And cost avoidance, it’s been shown in a number of studies including some that I’ll show you that it does decrease costs significantly, sometimes profoundly and I’ll go over the Home Telehealth data. But data from 2003, showed dramatic 30% reductions, in bed days of care and in Clinical Video Telehealth, 20% reductions in bed days of care.

I’ll define those terms for you, what are these modalities, what am I talking about with these Telehealth? Although they arose separately with from different quote unquote, silos of interest, they became integrated because it was clear that there was a lot of overlap here. So the office of Telehealth Services overseas three modalities and the vision of Telehealth is one that extends across the spectrum of technologies, including, telephones, secure messaging [00:11:00] and mobile applications, in ways that cover what patients need the continuumm of care.

We have Home Telehealth, we have Store-and-forward Telehealth and we have Clinical Video Telehealth, which is what you might think of when you think of a remote consultation for somebody with a cough or heart failure, or some kind of acute clinical problem. Teleradiology uses the same technology and is merged into this system. Around 2002, it became clear through simulation and projection that this was a tremendously ageing population and I’ll tell you that the average age of the patient right now in VA is approximately 65 years old that’s the average, the mean age.

But the number of patients 85 and older were the greatest a year ago, of these [00:12:00] six million patients are very large proportion were 85 and older last year and they’re now dying off at the rate of about 1500 a day. It was an ageing population, this was recognised and at that point this was the needs that were projected and I’ll show you something like this again and you’ll see how we answered this question of what to do. Home Telehealth involves a provider setting, that is in the clinic and a patient setting that is at home.

The technologies include, the messaging devices, interactive voice responses and peripherals for blood pressure, coagulation studies and then for Clinical Video Telehealth, which is carried out in a clinic. A patient would come to one of these 1,000 community clinics rather than the hospital and they would have a [00:13:00] device that was a videoconferencing unit, that would be broadband video or they would be provided with a video phone or peripherals. The staff that takes care of this model is the so called Care Coordinator, often a Nurse or a Social Worker or other train personnel.

Examples of the Store-and-forward include what you call the domiciliary, people who are not in a domiciliary setting, management of chronic conditions, health promotion and disease management. We have weight loss and exercise classes and physical therapy that can be done in this way, as well as acute care case management, obviously not ones that would require the emergency department.

Then in Clinical Video Telehealth examples include, home-based primary care, mental health evaluation, medication management, physical [00:14:00] therapy, home evaluations and care coordination. In the studies of mental health that I’m going to show you from around 2010 those studies were undertaken with broadband video. Those patients went to the community clinics, now we have a home based system for many patients, many mental health patients. Mental health consultations are the greatest use of the system in our organisation.

These are the kinds of things were talking about, they are managed by a variety of companies, they are not owned by the organisation. But the unique thing that the organisation did was the organisation said, if you want to sell to our government, then you need to integrate with our computerised patient record. These disparate companies, have data that enters the system through a phone line [00:15:00] over in the patient’s home and it’s integrated into the computerised patient record.

So that was the condition for selling to the government, this data goes into the patient’s record and it’s stratified, the kinds of devices that are given to the patient, so-called home messaging devices, which have algorithms for many different diseases. For example for heart failure, it will ask the patient each day, are you short of breath today, there will be a scale that will be attached to this and the patient will weigh himself and that data will go to the computerised record. There will be a blood pressure cuff if the patient is being treated for hypertension and the patient may be asked, did you walk today, did you take your medicines?

For some patients, they will get a video phone if it’s necessary to see say [00:16:00] insulin, that the patient has taken their medications or taken their insulin. Then from more advanced patients they’ll actually be given a videoconferencing unit that is produced by a company that integrates a wide variety of peripherals. Many what they call RS232 ports can integrate everything from blood pressure, to stethoscope sounds, to coagulation studies, prothrombin time etc. What the patient is given depends on our risk assessment and that’s the role of the Care Coordinator.

The patient can do this… They are not required to do this every day, but they are encouraged to do it every day and if the patient says this is too intrusive, Then they’ll do it three times a week. Whatever they are willing to do its part of the program. The data goes to a website that is read by [00:17:00] the Care Coordinator daily and the patient has answered these questions based on their clinical condition. If the answers fall out of normal parameters for example, the patient says, yes I am short of breath today, then that gets highlighted and read in the website.

Then the Care Coordinator who manages a panel of between 100 and 150 patients, will give that patient a call or arrange for a home nurse to come to that patient or both. These are just the systems in use and then the information is transmitted and so obviously if we’re going to give these kinds of instruments to the patient, we’ve determined that through previous studies, some that were done in 2003 that this was effective in reducing bed days of care as well as length of stay. Those early studies were done in the [00:18:00] early 2000’s and I’m going to show you data that is only about five months old, in current use of this type of system.

This is another graph that shows how the care coordination programme has met this need and I wish I could say that this was all planned. A lot really depended on having dynamic leaders in the right place at the right time. Of course I don’t speak officially for the government, I’m a clinician in there and I have an official position as Ophthalmology Lead but I’m presenting some of my colleagues, and some of my data, but not as an official spokesman. You can see that over time the program grew from 2000 in pilot studies in 2002, to approximately 90,000, almost 100,000 today.

There’s been tremendous commitment to this program and resources given because as you’ll see from some of the [00:19:00] data, the administration, the leaders believe that this is moving the care in the right direction. This is a study that just came out in May with Adam Darkins, who was the Telehealth Leader until recently for VA, who I had the good fortune to work with over a number of years. This is study that looks at clinical outcomes for 4999 patients under care coordination between 2009 and 2012. It compares them to a matched cohort, so MCG matched cohort group of 183,872 veterans, who were not in the Care Coordination Programme but who were matched for start date for the care.

They’ve all been in the organisation since at least 2009 both groups have home care support services so the group that doesn’t have these devices still is eligible [00:20:00] for home care, as is the group with the devices. Both groups have at least one chronic condition and that includes mental health conditions, from schizophrenia to other serious mental health conditions, not only physical conditions. These algorithms and these devices also have mental health conditions which have been validated to be somewhat predictive of crisis.

No other home care management program, in other words, they don’t necessarily have Medicare Home Care, no long term domiciliary care and they were followed for at least 12 months into enrolment, in the care coordination programme or the matched cohort or their usual care and they were still alive in 2012. So it’s not a randomised trial, it does have limitations which I will go over, but this is the third in a series of papers that he and others have published showing these types of results.

[00:21:00] These are some of the disease conditions that were looking at, arthritis, congestive heart failure, really something like two thirds of the U. S. Health care costs are in five diseases. Congestive heart failure, obstructive lung disease, dementia, diabetes, ischaemic heart disease, the rest are obviously important, but in terms of healthcare cost, it mirrors the National Health Service. These are sick people who have come to this type of end for various reasons, but this is what we deal with.

This is the beginning of the study, comparison of demographic and health care resource utilisation data for the match cohort group and the care coordination group. You can see some things right away and so for simulators out there, you are going to love this because it really shows how messy some of the simulations [00:22:00] can be and how you can think about cleaning them up. The average age is very similar, the enrolment groups, in other words it involves priority groups, patients who are so-called vested, those who have a certain income. If they have a certain income, then they don’t have co-pays, for example.

You don’t want to just take the cream of the patients who were the wealthiest because we know that wealthier people do better with their health, even if they have a chronic condition so they matched it for these different groups. The sex, as you may expect most of the patients are male, although approximately 10% of veterans currently are female in the system. The cost that they had incurred in the previous 12 months, the [00:23:00] emergency room visits, that they had incurred in the previous 12 months hospital admissions, pharmacy costs, clinic visits and Medicare costs.

You can see right off that there are disparities in this standard deviations, and even in the mean and standard deviations. What they did here, they converted the data logarithmically and they showed that with this input of data that the P value was 0.07, in other words that these two groups were essentially identical when you are compared them statistically, logarithmically. This is what they were three years later, this is the comparison of demographic and resource utilisation data in 2012. What you can see is that, the cost in the matched cohort [00:24:00] group was actually 48% higher, that there were more emergency room visits, hospital admissions, pharmacy costs and clinic visits than the matched group.

The cost to Medicare, to the US Health System was actually greater, in other words these were patients who were utilising outside services as well as the VA. And so here’s the admissions for the care coordination group between 2009 and 2012, and you can see that the matched cohort group increased their admissions significantly, statistically significantly. That the expenditures for care coordination changed dramatically for the matched cohort group over three years and was 4% lower in the care coordination [00:25:00] group. Emergency room visits decreased in this group over this time period.

So these are patients who were still alive in 2012, had been examined periodically during this time, they all received usual care, but the main intervention was these devices. But more than the devices, it’s more than the device it’s a culture of care coordination. It’s a sense that a person like me, a specialist seeing a patient in front of me who has say diabetic retinopathy and has poor sugar control, I know from statistics that I can be giving that patient laser or drugs from now until forever and if their blood pressure is 12% over normal, if their sugar is 15% over normal, they will do poorly.

I can make a referral, the specialist can make a referral, talk to the patients and say, would you like to have some special attention here and [00:26:00] see if you can get your risk factors under control. Most of the time, they’ll say, let me look at it, why don’t you have them call me. The conclusions to the study were, that pharmacy costs were 22% higher in the care coordination group versus 15% higher in the control group, we believe, because there was a greater emphasis on compliance, there was somebody calling that patient saying, did you take your medicines today, there was a pharmacist looking at utilisation, they got an extra measure of attention.

Emergency room and hospital visits declined as we said, but Medicare and analysis showed that these patients were not using emergency services that were billed to Medicare, they were using emergency services that were in VA. Most interestingly, was the mortality rate and this was very, very striking, the mortality rate in 2012 after three years [00:27:00] of study was 98% in the care coordination group versus 16.5% in these controlled patients, a very dramatic change. This comes on the heels of earlier studies in the early 2000, as I was mentioning, where Home Telehealth did a study of 1500 patients that were hospitalised over a period of time, they showed 53% reduction in bed days of care, in patients who were using this program.

Telemental Health this is early data I’m going to show you recent data, early data showed a 25% reduction in bed days of care and I’m going to show you current data. So this is mental health, show you different aspects of mental health here or different aspects of Telehealth and one of them being mental health [00:28:00] care coordination. The hypothesis of the psychiatrist doing the study was that patients with increased access to mental health services through remote technologies would demonstrate decreased hospital utilisation, as evidenced by decreased numbers of admissions and days of hospitalisation.

The data was acquired through this computerised data system by what’s called a dashboard, which basically is an index of when were patients admitted to the hospital and how many clinic visits did they have etc. This was a dashboard that was used to assess clinical outcomes for Telemental Health, so it was aggregate data stripped of individual patient information, right down to fires, it was obtained for all patients who received mental health services by remote high-speed videoconferencing for the first time between 2006 and 2010. Telemental Health conditions were defined by a primary VA mental health [00:29:00] visit code, so they were coded and that’s how we identified what the patient diagnosis was and how much resources the patient was utilising.

What they showed is that in 2007 before enrolment, this is in one health care system, so it was in the VA Connecticut Healthcare system and they showed that of this many patients being treated, of 19,000 patients being treated before enrolment there were 800 and admissions, after enrolment there was as significant decrease in admissions and also the days of hospitalisation also decreased. The incidents of admissions as well as [00:30:00] the bed days of care, both decreased suggesting that when the patient, to me anyway looking at this, suggesting that when the patient was admitted they were not as grave in their prognosis as they were before these interventions were undertaken.

That is one way of interpreting these types of things and I’d like you to consider the thought that I know Richard and many of the people that I’ve talked to today share and I think it is coming around and that is, by the time somebody is admitted to the hospital, they didn’t just get there. That was predictable months before, weeks before and even days before and if somebody is not asleep at the wheel and is looking at these types of videoconferencing units. These types of answers that patients are given to these clinical algorithms that you could capture when those [00:31:00] emergent acts happen.

I really have come to believe this and just looking as a student of biology, a student of the brain, thinking that it didn’t just happen all of a sudden that the patient got their heart attack when they showed up at the emergency room. It was a lifestyle, it was acute events, it was somewhat predictable. That is the premise of the Care Coordination system to find acute events before they become really grave and to intervene before a high utilisation event happens. Here four years later they had a total of 609 patients and there was a 24% decrease in the rate of hospitalisation and 26% decrease in days of hospitalisation.

The outcomes here, we talked about the decrease in psychiatric [00:32:00] admissions, we talked about the decrease in hospitalisations, the number of admissions and days of hospitalisations decreased in both men and women and in 83% of the age groups, at a time when the general trend in VA was not to have this kind of decrease in admissions. This was not happening in other VAs or in other parts of the country.

I’d like to talk to you last about Store-and-forward Telehealth and that involves something, Teleretinal Imaging and Teledermatology this talks about a software device that stores these images called Vista Imaging, it takes place in the clinic when patients are there for other uses. For their primary care, somebody will look and say that they haven’t had their eye exam in the past year and so they will get a non-dilated image. [00:33:00]

It involves a non-dilated camera, non-mydriatic camera and it involves a Telehealth Technician, so the VA hired a cadre of people that they have trained, over 1500 to serve this population that is trained in all three modalities. They can go into the home, they can set up a Telehealth device, they can go into the community clinic and they can set up a videoconferencing session for mental health and they can capture images on the digital camera, it’s a whole new category of technician.

And the examples are retinal imaging, wound care, pathology, cardiology and gynaecology. Here’s the Teleretinal Imaging program. It involves implementation of Teleretinal Imaging for diabetic eye disease since 2006 within the primary care clinics or in [00:34:00] 30% of cases in the eye clinic itself. Image acquisition and reading centres were linked by computerised patient records and the image archiving system as well as the reading system. There’s a training centre for Teleretinal images and readers, so there is support. It’s really an entire program that also includes the other parameters, in other words, all people who are doing this have to take web-based training and have to be recertified every two years to understand their roles, to try to make this into a uniform program.

Early on in 2003, this program had a pilot that was conducted in Boston and it showed that the relationship between reading and image and seeing the patient in person, that 72% of the time there was exact agreement on the level of pathology. Almost 90% of the time there was agreement [00:35:00] within one level of disease and the appropriate referral, regardless of the level was made 92% of the time. Then there were other referable findings such as cataract and other findings seen as well, so early on, there was a sense that this was a programme that was validated.

In most recent study, this gets to simulation and what simulation really does in my mind, so simulation in an ideal form would predict a paper like this. This is a paper that just came out in September, by a woman who’s in a very high administrator position named Mary Lynch, who was initially opposed to this programme. Her argument was, well I started this program and my clinic is flooded I am seeing a ton [00:36:00] of people because of this program. Some of whom do not need to be seen, some of whom do need to be seen and so she did a study.

She said, of the patients who are seen, of the 1935 patients who underwent screening, how many of them needed referral and how many of them had increased cost to the system and that was her basis. But she became a believer because of the results of the study and we’ll go over… She was a believer before, but this really verified it. Basically of the 1935 patients who underwent screening, 465 were referred for an ophthalmic examination in the two years subsequently, but only 55.9% were actually seen.

I’ll try to remember to talk about what happened to the 44% who weren’t seen. So she looked at the reasons for referral, the agreement between teleretinal reading and face-to-face visits, the resource burden. [00:37:00] How much did these patients cost in the two years after that they were imaged and barriers to patient care. She showed that there were a host of other diseases that were picked up by this condition and they cost a fair amount of money. So she showed that many patients had optic nerve related diseases, many patients ended up being treated for macular degeneration.

They had macular disease that ended up being treated, and most significantly, many of them were treated for what we call diabetic macular oedema or swelling of the retina, of the macular which is the main cause of blindness in diabetes. Proliferative diabetic retinopathy is important, but the prevalence of this disease is higher than the new growth of new blood vessels. Many of them have cataract and [00:38:00] there were other causes as well that were picked up on examination. And they required a tremendous number of procedures, they required for macular oedema, they required diagnostic procedures, surgical procedures, injections and it was just the beginning of the system.

But there was high sensitivity and specificity in picking up these diseases and that’s why Mary Lynch became a real believer in the programme. The endpoint is that 40% of the patients had diseases that wouldn’t have been picked up if they hadn’t had Teleretinal Imaging. Even though they cost the system more the theory, the thinking is that if you hadn’t picked them up the morbidity of these patients, the blind resources, the resources that these patients would need if they hadn’t had cataract surgery, if they hadn’t had treatment for macular degeneration would be much greater.

[00:39:00] So there are increased costs and this is the thing that a good simulation would build in to the system, so this type of study is ideal as a starting point for talking about simulation in medicine because it really gets at the heart of the strength of simulation modelling in my opinion. That is to try to anticipate, which was her goal, Dr Lynch, who is directing this program also has a national position had a sense that this was the truth. So she did the study to actually quantify what the numbers were but her sense was that by doing a study like this, people who actually made the decisions for hiring, people who made the decisions for budgeting, people who made the decisions for space allocation would have a basis for a valid decision.

That’s what modelling and simulation really can do [00:40:00] and what I would hope to try and get at during these days of the conference. This is coming at the problem from another side, this is a paper from 20 years ago from 1994, in which a model system which may be familiar to you, it was not familiar to me until I started researching this presentation, the prospective population health event tabulation, a modelling system. It’s a epidemiology based network simulation program modelling chronic diseases and basically it was one of the first models that actually had a major impact in US health care.

And I think healthcare in industrialised nations, showing that the main cause of blindness under age 60 in working-class population was diabetes and that if you could intervene with laser treatment, then you [00:41:00] could save the total budget a tremendous amount of money, these are 1994 dollars. Last year a group of health economists and other researchers did a study, looking at 900 type I and type II diabetics enrolled in a Telemedical screening programme for diabetic retinopathy.

They looked at the cost effectiveness of this program, they asked the question, of all the money that you’re spending on Telehealth Coordinators, on cameras, on clinician time, of all those funds, is it justified that you have saved enough potential blindness that this program should be validated? Their endpoints were, the presence of diabetic retinopathy, the presence of the main cause of diabetic retinopathy blindness [00:42:00] macular oedema, blindness from other causes related to diabetes and associated quality of life years that we saw in the previous model.

So they showed in their model, this was just a chart review this was looking at the data and looking at the total cost that were available to them from the database. They showed something interesting, that it was cost effective only if you were taking care of more than 3500 patients in a given geographic area, that it was most cost effective for people if they were less than 80 years old, it was cost effective for all racial groups and the kinds of trends they showed were that the number of known diabetic retinopathy cases detected has increased as a result of the program.

That the overall age of patients receiving screenings have decreased, suggesting [00:43:00] that you are getting patients more frequently. The standard of care in the United States and here as well is that patients should have an eye exam every year. In commercial insurance in the US, the rate of having that exam is approximately 55%. In the VA and in National Health Care systems such as UK it’s closer to 90%. So a variation of this system is in effect in the UK and is no doubt without a doubt saving vision and saving lives. The idea is that patients are getting this routinely now because diabetic retinopathy has a known progression and the idea that you’re going to see a certain poor prognosis is increased if you see certain early markers of that condition.

It did [00:44:00] decrease the average number of miles that patients had to go to get a screening, so now there are 750 cameras in the system that has 1100 clinics. It turned out to be cost effective to put a camera, a $15,000 a £10,000 camera into one of these clinics even if you had a relatively small number of patients with diabetes and many patients are getting their screening in this way. This program that I have been part of since 2006 has now screened over 1.5 million people and some programs are using it as, it’s not a substitute for an eye exam but for the diabetics where we cannot screen everyone necessarily in person, we believe it is saving vision.

Just a few words [00:45:00] on the diabetic computerised patient record, just to show you an interface, I learned this when I first started work that you could be the best clinician, you’re really only as good as what you know. If the patient record is not available to you, or is scattered, is being faxed, is being rescanned, is unavailable to you, at best you’re useless, at worst you’re dangerous. I really came to believe this early on as we were making the transition to computerised records. So it’s linked to all labatory results, current and future progress notes, procedure, consult operative notes and the same movement is underway in the UK.

Basically, it’s organised along active problems, allergies, postings, psychotropic drug consents, active medications, clinical reminders so these [00:46:00] would be for the primary care. This gets at the heart of preventative medicine, where the primary care is expected, do now, is expected to talk to them about immunisation for influenza, for tetanus etc, etc. Recent immunisations, vital signs, these can be graphed and the next appointments that the provider can see. Some of this data is available also to the patient on the portal for the patient, which is available to them called HealtheVet. Vista Imaging is one of the tools, so there are many tools that are available to the clinician, there are seamless in this use they are under the tool menu, but they are obviously separate servers.

One of those separate servers, so Stentor for example, allows the clinician to look at all the x-rays, all the radiographs and the Vista Imaging is one that the VA uses [00:47:00] for as I mentioned, 65 different file formats such as, scanned images, colonoscopy results and funders photographs. Then this is a Telereader, which is what we use to read the images wherever we are, so we can read the images remotely, there are group reading centres.

So to summarise, this is a lot of information that we are accumulating and clinical researchers at the rate of 30,000 a month are accessing this data. The question is today, how do you deliver uniform health care of high quality, at the largest and smallest facilities? I would argue, while not complete for certain models, the model of Telecare has been validated. If you talk to an ophthalmologist today, who really is aware [00:48:00] and you ask him, is it just is good to get a retinal photograph as to see you for an in-person exam? Most of them who are familiar with the medical literature and who are familiar with the current state of ophthalmology, will say yes.

So in the UK, which is one of the largest systems for this, that is how many images for diabetics are acquired today and in this system as well. The problem in the private sector is that the billing for reading these has not kept pace with the technology. And so while the technology would be available to put this in a primary care or an endocrinologist’s office, the compensation and the incentives to do it are not as robust as they are in an integrated healthcare system.

Over 6.6 million patients receive care in our system and I would argue that [00:49:00] these types of programs and the modelling for their improvement, we have by no means in my opinion have reached the apex of efficiency. So I think simulations for these types of programs and making them even more efficient, certainly are the next frontier for the organisation. It builds on our technology investment and the metrics for success are in place and people are working on mobile and I’m working on mobile cell applications and based on social media for improved clinical outcomes.

I don’t know if this is the future, I don’t know if it will be progress, but it could be the future. So I thank you for your attention and I remain an eternal optimist, most of the time. Thank you.