Data is extremely valuable to the healthcare industry and that’s why The Top Healthcare Outcome Measures always include data integration strategies and patterns. As ubiquitous as data is, it can be sometimes hard to access, and even when it is accessed it can be hard to interpret. Data integration helps to solve this problem by making data not only accessible but easy to understand, interpret and use for different problem solving and decision-making activities. In order to make data usable, data integration patterns can be created to standardize the integration process.
Two Major Data Integration Patterns for Outcome Measures
Data patterns are discovered and established based on use. Think of a hiking trail or a path across a field on a campus, it is established based on frequent use and the more it’s used the more prominent the path or pattern becomes. Healthcare outcome measures establish data patterns based on use and based on the needs of the healthcare organization. In general there are many data integration patterns and there are possibilities for so many more, however, some patterns have occurred more frequently than others and this has led to the identification of some major data integration patterns. We discuss these patterns below
Data Migration for Healthcare Outcome Measures
Migration is the process of moving data from one system to another. Migration requires the source system and the destination system to work together. Prior to execution, the source system contains the data and it determines the scope of data be migrated and provides all the information needed for the migration and possible transformation of the data. It also contains information on the destination system where the data will be migrated to. The migration system has the ability to capture the data migration from the original state to the destination state or location.
Any healthcare organization that has data operations of any sort, will have a use and need for a migration system. Migration is key for the creating and maintaining of data. For data to be relevant an useful, it has to be able to be moved from one system or file to another without its quality being compromised.
Without data migration, healthcare organizations will be forced to lose all data that they have amassed over time and there will be no way to upgrade a data management software or system without losing relevant data. Data migration makes the use of data and technology more productive in a healthcare organization. Data migration is most useful when there is a need to upgrade from one system to another.
The emergence of technology and healthcare is more prominent in this times than ever in history and this has leed to the frequent invention of new and more efficient healthcare technologies and data system. This means that there is an increased need to migrate data from one system to another as healthcare organizations work towards staying up to date with new technologies. A proper data migration system helps with backing up a dataset, adding nodes to database clusters, replacing database hardware, consolidating systems and many more
Broadcast Data for Healthcare Outcome Measures
A broadcast is a term used to describe the process of syncing data from one system to many. It is the act of moving data from a single source to many destinations often in an on-going and real-time basis. This probably reminds you of the phrase “broadcast television”. It essentially is the same foundation with broadcast data. A broadcast is used by companies to keep their data updated across many systems.
During a broadcast, data only moves in one direction that is from the source system to other systems. One major difference between a broadcast system and a migration system is that in a migration system the priority is to process a large volume of data. In a broadcast system, the priority is to process data and systems as quickly as possible. This ensures reliability and prevents the loss of critical data during transit from one system to another. A broadcast system only captures data that have a change in value since the last broadcast.
A broadcast is most valuable when there is a need to inform one system with real-time data. So for example, if systems A needs real-time data that it does not have but system B has access to this real-time data, then a broadcast is used to share the data including real-time updates. This is used a lot in a customer-facing business where there needs to be a constant flow of real-time data from one system to another.
It is also great in a healthcare organization for measuring outcomes in different levels of the car process. Doctors can broadcast information about a patient from their system to that of the nurses of the labs and vice versa. Put, a broadcast system is used when you want to take an important piece of information from an originating system and broadcast it to one or more receiving systems as soon as possible after the event happens. In order to determine if you need a broadcast system n your healthcare organization (or any organization for that matter) and for measuring outcomes, then you should answer the following questions
- Does system B need to know as soon as the event happens – Yes
- Does data need to flow from A to B automatically, without human involvement – Yes
- Does system A need to know what happens with the object in system B – No
If your answers to the above question are the same, then you most definitely will benefit from using a broadcast system.