A key paradox in collecting healthcare and patient data is that more data is needed to refine treatment plans and accurately measure outcomes for patients, but the data must be accurate, interpreted effectively, and easy to collect. All too often, healthcare organizations collect whatever data is the easiest and is already captured in existing systems. Occasionally an organization becomes data-hungry and ambitiously collects too much data, burdening staff, patients, which can impact quality, analysis, and the efficient and effective delivery of patient care.
As a result, within the transplant ecosystem there is often an uneven and non-standard approach to data collection, quality, and analysis. This can lead to data silos and a non-standard approach to using data to inform patient care.
Often, there is an inconsistent approach to collecting donor data and sharing it in the primary offer process. Privacy and licensing issues around medical imaging data and reports can be one barrier to sharing all medical information. Urgency and time constraints may be other issues, creating pressure to make a decision. In the transplant world, insufficient data and a lack of timely data can result in organ discards and lives lost.
A modern transplant management system needs to help OPOs, transplant centers, labs, and oversight bodies collect more data with less burden. Three ways it can be done:
- Integrating with EHRs, death registries, HLA lab systems, and legacy donor systems to securely exchange relevant data instantly.
- Capturing new data fields through intuitive workflows with field-level data validations.
- Automating additional data intake processes that is historically time-consuming but a major gap such as post-transplant surveys and patient experience surveys.