It’s a little hard to think 12 weeks have passed already. But as they say, all good things must come to an end. So goes Google Summer of Code 2017 with OpenMRS.

This summer, I worked on the Operation Theater module to bring it up to speed with 2017. The project had 2 main targets.

1. Migrate the module to work with the current OpenMRS platform.
2. Add workflow enhancements pertaining to pre, post and in-theater stages.

To remind what the operation theater module does, it basically helps us to schedule surgeries in the operation theaters within a hospital. We can add operation theater locations, save available procedures, schedule surgeries for patients and have a scheduling engine come up with the best schedule for current surgeries.

We can also add a team of surgeons and other people who will be taking part in the surgery. But after making the module, it was somehow left behind and wasn’t updated along with the core of OpenMRS & other modules. It just went beep for 3 years.

So my first task was to get it up and running. For this I had to first check what had changed between those 3 years and update the module codebase. I learned much about how the concept of time is handled in the programming world. I learned about Optaplanner, and constraint satisfaction problems in general (shout out to Charith sir for the Intelligent Systems lectures!). And bloody hell, I replaced an entire time library with two other libraries.

Along with that, there were database changes. OpenMRS had migrated from Hibernate 3.x to 4.x, so the Operation theater module needed some changes on that front. There I learned a bit of Hibernate, the ORM (Object-relational mapping. It’s a database thing). So the first month was spent on updating the module codebase and dependencies.

And we revved up the module.

After adding an operation theater location from settings, we can access the scheduling page and start scheduling. But wait, you need to add some procedures first. Otherwise, what surgery are you going to schedule?

And we’re good. So, first task, done!

Next, we started doing workflow enhancements. The main focus here was on the collection of data throughout the surgery. Before starting a surgery, it’s important to know the history of the patient. What procedures have they done before? Are there any drugs we need to give before the surgery? Is the guy even fit to go into surgery? Curiosity to save a life. Or two, counting the surgeon’s.

I initially planned to collect data as notes – free text. But the community suggested that we do it with concepts and observations, the preferred method of collecting data into OpenMRS. This way, we can use the collected data to generate reports and perform analytics. You can probably guess how hard that would be with free text.

I was halfway through doing it with free text when I got the suggestion. After that, I rewrote the code with appropriate concepts. So now, we’re adhering to standards and working neater overall.

We record past surgery data, allergies, physical condition and drug prescriptions during the pre-theater data collection.

We do the same for in-theater and post-theater data. As for in-theater data, we decided to capture it in the post-operative form as it’s not practical to enter the data during the surgery.

And that’s target number two, down. We’re all good with the primary tasks 😀

After that, I started documenting the code and the module. I’ve written some tests to cover the code and tried to clean it up.

I’ve learned a lot in these past few months, specially how a real project handles collection of data in a flexible manner. This is especially useful for some of my personal projects as well.

As next steps, I’d much rather fully rewrite the scheduling engine myself. Then I know the module inside out from its core, and can help other people to get involved in maintaining it. Another possible extension is generating reports from the data we collect. It’s just a matter of presenting the data in suitable formats.

And that’s it for this time, people. We’ll wrap it up after the final evaluations in one more post.

Until then, take care.

Over the 11th week, I tried to refactor the code to use as many concepts as possible for data collection. I have added required concepts to be loaded via the module activator at module startup. Then I tested adding data to the system with the saved concepts.

We’re now properly using concepts to store theater workflow data with observation groups where necessary. This is a major milestone as this means we’ve effectively standardized the data collection over the long term, enabling people to make use of the gathered data. My mentors provided feedback on the module and discussed the possibility of shipping the module with the next release of the Reference Application 😀

That’s a big deal, but I feel we’re short of that yet.  I’d personally rewrite the scheduling engine completely, as at the moment it’s a mess of one guy’s solution and another guy’s attempt at bringing it to 2017. It works, but with a few quirks here and there – like sometimes it schedules surgeries after the theater open hours. But with the time constraints, this’ll be a task for after the GSoC deadline.

On unit testing side, I wrote test cases for checking availability of initial concepts, adding data with concepts and retrieving them. I plan to document a guide on using the module over the next week. We will also make a video about our work as the final presentation of the project.

We’re nearly done with all development now. This week I went through CIEL and identified existing concepts that I can use for data collection.

It turns out that the whole set of data collected for past surgery history are available in CIEL. Instead of past procedures, they call it procedure history. There’s a set of concepts to record past surgery details as below.

160714 – Procedure history (Grouping concept)
1651       – Procedure performed
160715 – Procedure date/time
160716 – Procedure comment
160721 – Procedure outcome
163049 – Procedure site

During this week I refactored my code to use these concepts for past surgery data collection. I also added them to the module activator to ensure that they are available in any deployment environment.

Apart from that, I spent some time looking into how unit tests are written for OpenMRS modules. We have less than two weeks left of the coding period, so I plan to finish off development with feedback from the community this week.

Wow, two months gone just like that. This week, my focus was on implementing the pre-theater data collection as per our discussions over the previous weeks. If you followed along,  you’d remember that we decided to use concepts and obs groups to  record the collected data.

The first thing I did was getting the patient’s allergies and showing them alongside the surgery data. Documentation is scarce on this but I remembered that the new Reference Application contained Allergy module by default. So when I view a patient, his or her allergies are listed on the profile itself. Now I just had to see the corresponding code.

Well, that didn’t work out too well. I couldn’t find how the patient profile view was coded. Fret not, let’s explore the OpenMRS core. Rummaging through the core API, I came across the PatientService class and there I found a method to get all the allergies of a patient.

Then I wanted to see the source code of the Allergies, Allergy and Allergen classes (seriously, they’re modeled like that for reasons unknown to me). But GitHub doesn’t support Ctrl-click to view source (it should. It’s 2017!) so I downloaded it, revved up an IntelliJ instance and loaded it up. Ctrl-clicked away to my heart’s content. Ah.

The Allergies class allows us to manipulate allergy data as a whole. The Allergy class drills it down to a specific allergy. Allergens are what cause the allergy, and have a particular set of reactions for it. AllergyReaction class, you see where we’re going with this.

Anyway, so I needed to use all 4 classes to display the allergies of a particular patient. Maybe we should document that somewhere in the wiki. Huh…

Another thing I did was rearranging the Surgery page. Right now I’m using the Surgery Edit view to display its summary (reuse, reuse!) so it needed a bit of moving things around to accommodate the new stuff I was adding to it.

And we really need to have a standard guide with examples on UI development. Nobody knows how the existing fragments in the UI Commons library look or work. You have to go through the code and figure things out by trial and error to get it working. And adding icons is another mess. Maybe I missed an existing guide somewhere… I doubt it though.

That’s all for this week. In-theater data collection is the next step.

During the 7th week, I got feedback on the mock-ups for pre-theater data collection. Just as I suspected, letting the user simply note data as free text was not the best idea.

Although a simple note might be useful in communicating the patient history, it’s not usable for analytical purposes. I mean, a text paragraph is not granular enough to analyze trends in patient history and can’t be used to generate reports. We need to organize the data collection such that they can be analyzed in the future. This means breaking it down into contextual chunks. Then structuring the DB to store them allowing easy querying.

My first idea about implementing  this was a little complex. I thought about making 3 tables – tags, surgeries and surgery_tags. The tags table would denote the past surgeries. Surgeries would store the master entity. The surgery_tags table would add multiple entries with past surgery data before doing a new surgery.

But then I was directed towards Obs Groups and the OpenMRS Concepts Dictionary. Those two blew my mind. Literally.

Let’s start with the concepts dictionary. It defines the medical concepts that are used within a particular implementation of OpenMRS. As many institutions use OpenMRS around the world, they add the concepts they use into their instance. To quote the docs,

the concept is the basic element of flexibility in OpenMRS. Concepts are the individual data points collected from a population of patients. Concepts include both questions and answers.

For example, blood type data is collected for a patient.  The question is “What is the blood type for the patient?”, with a set of discrete answers of “A, B, AB or O”.  To implement this in OpenMRS with concepts, the question is a concept (“blood type“) and each response (“A“, “B“, “AB” and “O“) is also a concept.  For this one question, a total of 5 concepts are required.

Here are the docs, it’s an interesting approach that allows future modifications to the data collected within the server. This works in tandem with Obs, or observations.

An observation is anything that is actively measured or observed during an encounter (-> a patient’s interaction with the doctor). This could be the white blood cell count of a patient. Or the mode of transportation to the hospital.

Logical groupings of observations are called Obs Groups. For example, there may be an obs group called “TRAVEL TO CLINIC”, which may include the member observations “MODE_OF_TRANSPORTATION”, “DISTANCE_TRAVELED”, “TIME_SPENT_TRAVELING” and such. You can read the docs here to get a better idea about it.

So in our particular case, we’d need to register an obs group called past surgeries, as this would be an observation made during an encounter before scheduling the surgery. Then, the date of the past surgery, its name and diagnosis would be member observations. These would be recorded as concept entries within the DB.

This will take some time to implement, and we’re supposed to be done with the pre-theater workflow enhancements in a week. I discussed with my mentor and we’ll implement as much as we can during the available time.

Another thing I noticed is that we can’t view the details of a surgery once we finish entering its details the first time. There’s no way to view a single surgery and info about it. We get a summary page of the surgery when we finish creating it, but you can never get back to it once you exit from there. So I connected that page to the overall surgeries page so that we can click on a particular surgery and view details of it at a later point. Such a simple thing, I’m not sure how this was not discovered before.

And that’s all for this week, folks. I’m sorry that I’m late to post this (hell, I got asked why I’m late). Work, you know how it is during the intern period.

Until later, then. Ciao.

Another week passes and we’re done with the first round of development. In this round we worked to migrate the Operation Theater module to the current platform, and the last week focused on modifying the theater scheduler.

We’ve finished modifying it, and the results are mind-boggling. No, seriously, it’s messed up. Right now it schedules activities one after the other on the same day, without looking at the open hours of the theaters. So not what we want.

It’s got something to do with the timelines used when running the scheduler. The start and end times of a theater, and those of a procedure seem to be having an error in the way they get time zones. I need to take a deeper look at that.

Our main goal of migrating the module is complete. Correcting some errors is what’s left of it.

The second round of development focuses on pre-theater data collection. This is the first part of the workflow of any procedure. We need to collect data about the patient’s condition, medications and things that need to be done before the procedure. I’ve listed some of the data I’ve identified as important below.

• Evaluating patient medical history
  • Past surgeries
  • Diseases that may affect the surgery
  • Current medications – may cause complications
  • Allergies – for chemicals, drugs or anything else used in surgery
• Fitness for surgery
  • Checking the body condition of the patient for signs that the surgery may not be viable
• Prescriptions to be taken before the surgery
  • Dyes
  • Anesthetics, antibiotics, antifungals, analgesics, IV fluids, Electrolytes, anticoagulants, diuretics, barbiturates
• Fasting periods
  • NBM periods for the surgery
• Legal requirements (where applicable)
  • Documents requiring legal consent of the patient for the surgery

With this data, I’ve outlined the data model for storing them in the database. I’ll post a diagram here soon.

So the next week, we’re going to start implementing the pre-theater data collection. Forms, Spring and Hibernate.