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Using R to Produce Clinical Reports in the Patient Record (Daniel Holmes)

Daniel Holmes
MD, Medical Biochemist at St. Paul's Hospital
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R/Medicine 2020
August 29, 2020, Online, USA
R/Medicine 2020
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Using R to Produce Clinical Reports in the Patient Record (Daniel Holmes)
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About speaker

Daniel Holmes
MD, Medical Biochemist at St. Paul's Hospital

Clinical Professor of Pathology and Laboratory Medicine at the University of British Columbia. Medical Biochemistry at St. Paul's Hospital in Vancouver, BC. Clinical Mass Spectrometry, Endocrinology, R for Lab Medicine Data Science and Stats.

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Hi everyone. Welcome to the the last talked about this session, this will be Daniel Holmes, talking about using our to produce clinical reports in patient and patient records. Thanks very much for the introduction and thank you to Stefan Janoski for inviting me to speak. Today I'm going to be picking up on some of the things that Steven Master spoke about earlier and maybe make allusion to wear what Patrick Mathias will be speaking about later on. I'm going to talk about how we use our to produce Clinic reports in specific to the second reference to a condition called

primary aldosteronism. Where are plays a role in the entire State Automation and Reporting pipeline, so what is primary aldosteronism. It is the most common form of cure, curable, form of hypertension. Most hypertension doesn't have a well-defined cause and so it's just treated with medication primary. Aldosteronism is, is has a specific underlying cause it can, it can either be from excessive growth of the adrenal glands, or it can be due to a tumor of the adrenal gland, usually on one side and occasionally on both sides when is caused by a tumor.

And it's only One side, you can just take that tumor out within a dream left to me. Otherwise you can use medications that are specifically targeted to block the effect of aldosterone and its causes people to have chronic hypertension. That's particularly resistant to medication and to have low potassium. If patients have specific clinical features that will help identify them as the possibly having primary aldosteronism. They tend to be resistant to the usual medications like ACE inhibitors and beta-blockers. They tend to present with with with an incidentally discovered

adrenal Mass send medicine is notorious for having unusual nomenclature, we call these incidentalomas, they're discovered. Incidentally on CT scan hypertension, a young person or hypokalemia that is low blood pressure. Potassium in response to the the normally employed diuretic medications so biochemical screen Is undertaken, with the concomitant measurement of aldosterone and plasma renin activity and an allusion to what Stephen spoke about earlier. These two measurements are notorious for high

variability between the vendors who manufacture the kids to measure them. And so the thresholds for diagnosis and screening are are heavily linked to the analytical methodology that you're using. Whether that be allowed to develop test or a commercially available kit in any case clinicians being what they are. And I need something simple. So the combined information about Austria and Plasma in activity is taken by means of a ratio of those two. And that is what people usually use to help screen for primary aldosteronism. This is a in illustration of the so-called

renin-angiotensin-aldosterone system and not terribly important to us. Except to say that the guitar. Analyte for measuring plasma. Renin activity is the ability to generate Angiotensin 1 over a. Of time. So there's endogenous angiotensinogen. And we measure how much Angiotensin 1 is generated over a. Of time before it at a pH 6.5. And then of course, we measure aldosterone itself and this is just an illustration about those transactions which are to retain potassium and to Wastewater, think about that. If the water has to 3 routine, sodium and

waste potassium is what I meant to say. When you retain sodium water, has to come with it and it causes the intravascular volume to expand and causes the high blood pressure. So these data are generated off a mass spectrometer or else. I'll show you in a moment using allowed developed tests and our data workflow strategy. When we started out was to manually transcribe them, which is one of, you know, my Beast is that we spend a lot of time trying to make perfect down a little Chemistry and then we manually transcribe the results into our lap systems. So that doesn't make a lot of

sense and we were manually adding or interpretive comments also, which often or are canned or just stock comments. But here's the analytical and data workflow that we developed the patient, sample is taken. It will first actually, it's, it's taken to this liquid handling robot from Hamilton. It's subjected to a number of the treatments for aldosterone. It's extracted with methyl. Tert-butyl ether. That is dry down reconstituted and dumb and then thank you said tricks. For telling me that I need to update. When you can bounce. They're in the right corner for a

few minutes. And then after the extraction 8, methyl tert-butyl ether is dried off and, and the, the sample reconstituted methanol wolves. And then we can measure aldosterone I using a multiplex hplc system connect to Sciex Master trometer to get patient identifiers. What's actually just the the barcode that's on the two which isn't a patient identifiers to sample identifier but to get it across, we use our to just do some not some data munching. It's through a shared folder ends up over at the mass spectrometer and then again ASCII text output comes from a

spectrometer but we can't interpret those results by themselves. We need to marry them with the clinical data which is not on the patient. Barcode identifier. So in order to marry it with the clinical data we have to get that clinical data out. Now at the time that I developed this work flow data Innovations, which is appearing down here was not available and so and in the lab information system, people did not want to help me with this cuz they were stretch with other things. So I discovered this language expect which I buy used to strip information directly through a text interface to

the lab system. This is all run by Bosch. I under a bunch of you and using that we get data from the laboratory information system, which is Sunquest. We marry that clinical data produced an Excel file. I know to shameful and the Excel file is used at 2 to review the interpretive comments that have been auto-generated. And then a flat file is the sent over to data Innovations. And then goes to SunQuest into the electronic health record. So, I would just like to talk a little bit about expect because it is kind of a hack that is useful in certain

circumstances. It's a, it's an automation language for text-based interfaces. We were not permitted to have an odbc connection to the lab information system and so because we had to text command line interaction with the lab information system, we could use, we could automate that fraction and get the information from the text file. That gets dumped So expect is an extension of the TCL language that is Beano used for for automating any kind of text command line interaction. There are alternatives to this in. I'm in the modern era has

using a specific automation languages but since we are working on a Mac OS and Linux are we didn't have that. We didn't have the benefit of autohotkey which is a good example of there is no, there is no extension of our that lets you use expect. So these are having be run by Daughter processes. But there is a python extension that will allow you to imitate at the expect language. This is the interpretive process that is applied to our samples. In the middle. We have mostly normal people, these patients with high aldosterone to

plasma. Renin activity are considered part of the screen for primary aldosteronism. We have an indeterminate screen in the orange. We have other conditions where you have high aldosterone, a high Plasma in, on Grand and activities. Such as renal, artery stenosis running Oma laxative abuse, etcetera, we have medication affect Addison's disease, that is to have low adrenal activity and the pink domain is sort of like prolong recumbents that is patients in hospital or something like that. And a couple of other

miscellaneous categories. But this is the interpretive algorithm that is applied by the our script from from the mass spectrometer a uniting it with the clinical data. So our has permitted us to find some other conditions to. We found a number of cases of ACTH dependent Cushing syndrome caused by ectopica carcinoid syndrome carcinoid tumors, we found lots of Addison's disease. We found inappropriate dexamethasone Administration before primary aldosteronism screening, I just happened yesterday. For example, we have a few opportunities for improvement. I've been

using TCL widgets because this was developed before shiny existence. We can move this whole thing to a shiny interface and we can incorporate incorporate more mass spectrometry quality metrics in the reporting and it would be nice to have full automation of some of the interpretive letters that we need to write for the tumor localization procedures, which I haven't had a chance to talk about here. I would like to acknowledge people that help me tirelessly Grace Vander Goten who does all our Mass spectrometry. I asked a development and the msacl for promoting applications of our in

Python to Mastic. Ametrine, of course. Our laboratory technologist to make this possible. Also, dr. Janet Simons. And dr. Andre Matt men who are my user base, we are user base of 3 for this but they provide me important feedback on how to improve the process and and I appreciate that very much. And with that I will, I'll stop. And I will tell Citrix to remind me later. Thanks very much. Daniel for Daniel. You're welcome to contact him at this point. We're going to start the bird, the birds of a feather for today. Thank you very much.

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