We are now living in a world where data increasingly plays a large role in providing insights on which we can base our decisions. However, all data is not the same and as it forms the basis of decisions or actions, there is more importance placed on ensuring that we use relevant information.
There are a few criteria you should consider when selecting a data source.
- The ability to provide longitudinal observational data – this enables you to really understand healthcare trends in both prescribing habits but also the prevalence of conditions and treatment pathways over the years.
- Is it nationally representative – it is important to have access to all state and demographic segments to ensure that data is accurate and non-biased.
- Electronic and real-time – relevancy of your data is important and electronic sources provide greater accuracy and immediacy to provide current conditions and trends.
- Privacy compliant – ensure that the data you select is provided by quality sources and de-identified to comply with government privacy regulations.
Applying recent data to provide greater insights into health outcomes
Once you select your data source, applying it to your situation can provide you with greater insights, such as identifying trends and areas that can see improvments in a patient’s health outcomes. While there are many factors affecting patient outcomes, the focus is often on improving patient education and medication adherence.
For example; when reviewing data on type 2 diabetes, the patient population has remained relatively stable. However, recent data shows an influx of new medications onto the PBS.
When reviewing the data it shows that the first line recommended therapy of metformin for diabetes is quite standard with 75% of patients starting on a single monotherapy. As the patient moves through their therapy journey, once they get to 2nd and 3rd line, their pathway becomes extremely complex. There are a multitude of different therapies and drug classes available, with some combinations and other add ons. These include the DPP4s with at least five different drugs and also five different metformin combinations. Then we have the GLP1s, the newer class of SGLT2 inhibitors and of course injectable non-insulin used as mono therapy.
If we map out the treatment pathway of patients, there are literally thousands of different permutations. While we acknowledge that all patient journeys can be different, when reviewing recent data, there is clearly little evidence suggesting common pathways that could marry up with current treatment guidelines.
By reviewing quality data we can understand that these complexities have the potential to negatively impact patient outcomes. This provides insights into ways to streamline treatment options for better patient outcomes in general practice.
For more, don’t miss the upcoming Measuring Health Outcomes Conference taking place in June 2016. Book before May 6th and save $100 on ticket prices!