Improving Patient Flows With Data Science And Analytics

We now access to more complete data sets that in our experience can be in upwards of the billions of rows and more powerful computational systems we can analyze patient flows and bottlenecks much accurately and effectively.Now with these tools like SQL, R and python we can analyze these data sets quickly.It’s not just about the tools..In fact, with such powerful tools it can be tempting to try to make models and algorithms that can solve all the problems in one go..One of the big issues with this approach when looking at patient flows and bottlenecks in hospitals ( or really any problem) is it is far too general of an angle..It makes it very difficult to assess when an analysis is finished and often keeps the data scientists and analysts spinning for weeks without getting a real answer.The problem here is the scope of looking at everything is very difficult to manage and pinpoint issues..Instead of trying to attack all the processes and procedures a hospital has..It is a better idea to break down several general categories of procedures/patient flows/processes that you believe are likely to have bottle necks..This is because hospitals have so many different possible paths and processes (I am going to use the word process to describe the patient flow below) that blindly looking for some sort of bottleneck will take forever (it is like looking for fraud in healthcare, if you try to do it too generally, then it will be near impossible to find).The first step is to find out the problem areas..Without knowing what you want to target it can be very difficult to know what the solution is..In a perfect world your hospital has a database that tracks all the processes and procedures that are done..This will make it easy to develop a query or Jupyter notebook that can point out the main choke points..This will further help your team limit the amount of unnecessary work that is required..Once your team knows where the problems are, then there are low hanging fruit your teams can use to look for issues.AbnormalitiesAbnormalities, like inconsistent times for patient flows, whether that is specific doctor or in general can state that there is a problem.. More details

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