Data Exchange for Meaningful Usability
Interoperability in healthcare is defined as the ability for multiple systems or technologies to be able to communicate with one another and share data. The data exchange must lead to true usability that is meaningful. While a push for national standards through Health Information Governance has created national standards, the level of ambiguity has still made this complex world of information very difficult to traverse from a practical sense in the daily routines of Healthcare Management.
Data in healthcare is inherently complicated. We look at data across a health system to determine trends and improve quality, reduce costs and risk (e.g. value-based purchasing, population health, disease prevention). Everything we do is patient centric in Healthcare and yet the data sets which drives our decisions are so complex, so segregated and in many cases still lacking true consistent structure that the job of aggregating the data is time consuming and costly. Then just as you standardize on a dataset the rules governing the data change based on new evidence-based medicine or value-based standards. The link to clinical and financial data is important and we ought to be cognizant of trends that will reduce costs and improve access to care. But while we are addressing cost and quality through complex algorithms we’ve lost touch with the basic principles of solid data management.
Let’s consider medication management as an example. In its simplistic form the association of medication to a patient should not be that complicated; yet it is. Medication lists for patients should have national standards. Every prescription should be retained in a national database associated to a patient with a national patient identifier accessible through a single interoperable exchange mechanism that is shared by patients, providers, systems and payers. Dr. Jonathan Goldner Chief Medical Officer, Pocono Medical Center states, “The only way to solve the complex problem of medication reconciliation is to have all healthcare providers’ access and prescribe from one universal list for each patient.” Instead, the data is in redundant silos and patients are expected to have an accurate medication list at the time of care; which in many cases is not planed (e.g. emergency care, trauma care). Even when care is planned patients will bring their medication with them because of the complexity of drug nomenclature. We’ve established national databases that know how much cash I have in my checking account, that know what my credit score looks like, that know if I’ve committed a crime; why is the data collection for prescribed medication so complicated we can’t develop a national standard?
“It would be in the best interest of the Healthcare industry if there were national standards for all healthcare datasets, not only in content and context but in format and access methods”
It would be in the best interest of the healthcare industry if there were national standards for all healthcare datasets, not only in content and context but in format and access methods. Along with standards, all modifications and changes should go through a regulatory approval process to maintain the integrity and accessibility of the data into the future. We need to eliminate inconsistencies and introduce new consistencies throughout the healthcare landscape. These standards should not stifle the creativity of Electronic Medical Record (EMR) vendors to create new and innovative ways to use and present data. Instead, the consistency will enhance the ability to trend data and improve performance from a clinical, quality and financial perspective. When data is standardized and consistent, intelligence and data mining tools will have an enhanced effectiveness.
At Pocono Medical Center, we work closely as a team to thwart the perils of managing multiple electronic medical records, data sources and none integrated platforms. Nikunj Kumar Patel, Chief Technology Officer who over see’s our decision support analysts, regularly shares with me the lack of understanding that having a deep knowledge of the data is critical and many times the users who request reports often don’t understand the data. He states, “Clinical data is not all mathematical data. It is not just about profit and loss; datasets are far more complex and have qualitative dependencies. Understanding them is imperative. With six EMR's we are highly dependent on our EMR vendors to provide us data dictionaries to better understand the data. Many times they don’t exist, which creates and interdependency between the analyst and the end users to evaluate and document the meaning of data elements; this is a laborious process.” We have a long way to go in healthcare! It’s time for universal data standards.