Here are the top 10 technology trends that healthcare informaticists are embracing.
Top 10 Tech Trends:
1.) Performance imperatives
2.) Population Health Management and Re-admissions
3.) Turing Healthcare’s Business Model Inside Out
4.) Bridging the Care Transition Gap
5.) Second-Generation Clinical Decision Support
6.) Year of the CISO
7.) Private Health Information Exchange on the Upswing
8.) Imaging Informatics and the Enterprise
9.) The Bring Your Own Device Revolution
10.) The Game Changer
I will go in detail about the first 5 tech trends and continue with the last 5 later on in the week.
1.) Performance imperatives: healthcare leaders recognize the need for formal performance improvement methodologies such as Lean Management, Six proscar propecia finalop Sigma, Toyota production system (TPS); adopting business processes from other industries
2.) Population Health Management and Re-admissions: preventing re-admissions and utilizing population health management analytics to focus on issue; utilizing population health management strategies to avoid readmissions
3.) Turning Healthcare’s Business Model Inside Out: pharmacy canada IT maturity model for accountable
care has 3 phases
kamagra store
First phase includes 12 foundational elements that includes establishing ambulatory electronic health records, health information exchange, disease registry, physician engagement, patient engagement, and quality improvement
Second phase: creating performance risk and bundled payment models for end to end acute care episodes (i.e. surgeries) and for ambulatory episodes (i.e. chronic diseases)
Third phase involves accepting utilization risks for a population of patients by employing preventive medicine
4.) Bridging the Care Transition Gap: care transitions problem during the discharge process, medication reconciliation, information flow, and patient and caregiver interaction; information technology can streamline discharge process in an organized and efficient way.
5.) Second Generation Clinical Decision Support – implementing an effective clinical decision support system and embedding clinical decision support into clinical systems to improve patient care
