Look at your DSRIP project plan. Find the metrics you haven't moved the needle on in two years. If a metric has a 98% compliance rate (floor) or a 2% rate (irrelevant), stop collecting it at full frequency. Move it to a quarterly sample, not a monthly census.
Write specific code to strip out non-Medicaid patients at the point of ingestion , not at the point of reporting. Use a lightweight ETL (Extract, Transform, Load) process that drops irrelevant records before they ever hit your analytics server. The Bottom Line DSRIP was never meant to be a permanent state of chaos. It is a reform program. But reform requires agility.
If your DSRIP data pipeline is bloated, you are spending millions of dollars to tell the state that you are "trying" rather than actually improving care. Trim the fat. Focus on the five metrics that actually drive a reduction in avoidable hospitalizations. bloat dsrip
Why your DSRIP dashboard feels sluggish and how to fix the data weight problem.
We’ve all heard the complaint from hospital CFOs and quality officers: “Our DSRIP reporting is turning into a beast.” Look at your DSRIP project plan
Stop joining five tables. Pick one system as your master patient index for DSRIP. If your EHR is the source for clinical measures, do not let the billing system override it. Bloat happens when two systems argue. Pick a winner.
Have you experienced DSRIP data bloat in your organization? Share your worst "report crash" story in the comments below. Move it to a quarterly sample, not a monthly census
But recently, a new term has crept into the lexicon of Medicaid transformation: