Meet our new IBM Champion Mia McCroskey
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Today we have with us Mia McCroskey at Emerging Health Montefiore Information Technology who was recognized as IBM Champion this year. She shares with us her thoughts about the requirements management domain.
Welcome to IBM family! It¹s a great pleasure to have you with us as an IBM Champion. Congratulations, How do you feel?
I am honored to be recognized in this way not just this year but for the past several years that I have been asked to present my team's stories at Innovate. It may seem like our little team's requirements management needs are nothing like those of customers with huge DOORS ecosystems. But really we are an R&D site for the evolution of requirements management techniques and strategies. If a member of my team has an interesting idea for how to capture, structure, track, or trace requirements, we can try it without getting high level approvals or disrupting the work of hundreds of people. I take tremendous satisfaction from sharing our successes in a way that may help others improve their best practices.
Can you tell us something about what you do at Emerging Health, Montefiore Information Technology?
Emerging Health is primarily an IT delivery organization supporting healthcare delivery in the Bronx. Montefiore Medical Center is our parent company. My team, Product Development, is a software development shop tucked away in a corner doing very different work from most everyone else. Our application, Clinical Looking Glass, is a browser-based clinical intelligence tool that gives clinicians access to the enormous wealth of patient data gathered by all the other systems. Our end users can get an answer to a question like "are my clinic's diabetic patients getting the level of follow-up care required by our funding sources?" in a few minutes. In most healthcare environments, getting the data that you need to answer this question takes weeks.
My title is Manager, Product Development Lifecycle because I have my fingers on just about every stage of that lifecycle. Specifically, I lead our Requirements Management, Quality Assurance, Education, Support, and Implementation teams. I also manage outsourced development work, manage client relationships, and do hands on end-user training and support. We are an extremely team-oriented organization, with two formal development scrum teams and two teams that are at various stages of adopting an agile process. I'm deeply involved in that right now: it's challenging to apply Scrum to a training and support team, and to a team of data analysts and engineers.
Having said all that, my roots are in requirements. On a team of "happy path" stakeholders who get very excited by ideas for new functionality, I love to dig in and find the challenges that nobody wants to think about -- before we start coding. Sometimes I feel like a real buzz kill!
What are your thoughts on managing requirements effectively?
Agile models have forced us to completely reorganize our requirements elicitation, analysis, and management processes. But one thing that has not changed is my belief in a comprehensive, functionally organized requirements model.
But when I say "comprehensive," I don't mean laboriously detailed. The art of requirements analysis and management is in knowing -- or guessing right -- what details are going to be important later. By later I don't mean to the coders and testers in this iteration, I mean when we want to revise or augment the feature in six months. The requirements analyst has to be deeply plugged in to the business goals and vision in order to predict the future and capture the least amount, but most important information about what the team is doing.
A few years ago I spent many months constructing an "as built" specification for a market data system at the New York Stock Exchange. I had the original ten-year-old spec and a few dozen incremental release documents. We were getting ready to refactor the system and nobody knew every business rule and function. I vowed that no system I worked on would ever lack a spec that described everything it currently did. Incremental requirements specs that aren't integrated into the overall system are defects waiting to be discovered once the coders get ahold of them.
Having argued that I must add that a requirements model in document form is pretty nearly impossible to maintain in the way I describe. You've got to employ a database tool that supports the granularity of each requirement and allows you to describe each one through attributes. Then you can use filters and queries and views to present an infinite number of customized specifications -- all of the requirements implemented in a specific release, or all of the requirements related to a specific functional area, or the completed requirements related to a specific business objective or corporate mandate.
I recently spoke with a software development professional who was very proud of his organization's highly structured and detailed requirements templates that captured every detail before any work began "to be sure we deliver what's wanted." I felt like I was talking to tyrannosaurus rex. We all know that the day after you baseline that 400-page spec it's already out of date.
Agile with its short increments and "only write down what you really need to" mentality can seem seductively freeing. When our organization adopted Scrum, I stuck to my requirements model guns, and sure enough a few months later we couldn't remember decisions that we'd made a few sprints back, nor even exactly which sprint we'd done the work in. Since we weren't supposed to be doing "heavy" requirements, we'd been coached to: use the system and see what happens; or sift through dozens of completed user stories and hope the detail we wanted was actually mentioned in the acceptance criteria (which it was not because it was an in-sprint decision); or try to find relevant test cases and check the expected results. Instead, I launched DOORS, went to the functional area related to the question, and checked our documented business rule. Done.
What are some of the challenges you see in Healthcare Informatics projects?
Deriving meaningful information from the electronic medical record is essential to justifying the cost of those systems. We're piloting the use of predictive analytics -- combining statistical methods with the mass of patient data collected every day at our parent medical center -- to predict outcomes at the population level. To do it you need a very wide range of data: blood pressure, height, and weight, smoking patterns, history of heart disease, current blood sugar level, and on and on. Just bringing all this data together is the first challenge. Next is the analytic tool -- that's CLG. Finally you need big iron to process it. Most local and regional healthcare providers don't have the funding for, say, Watson. My team spent last summer optimizing our hardware and software environment, and CLG itself, to handle analysis of larger data sets faster, but within a medical-center friendly infrastructure budget.
Another area of critical concern is patient information. The need to pool patient data for direct care as well as population research is supported by legislature and funding sources. But we are bound, both legally and ethically, to protect patient identity in every circumstance.
Clinical Looking Glass has the capacity to show patient contact information to users who have been granted permission to see it -- usually clinicians who are actively providing care and need to contact the patients. While this is a critical feature of CLG, we expect to have to develop more granular levels of access as new types of clients adopt the product. For example, our Regional Health Information Organization (RHIO) client has data from twenty-two healthcare institutions. Some patients have declined to have their identity shared across the organization. We have to build the capability to mask these patients' identity even to our users who have permission to see it.