Don't let unexpected EHR hurdles undermine implementation

Most providers can prepare for well-known issues regarding electronic health record implementation, such as making sure to allocate sufficient time for training. But there are some less advertised mistakes can trip up unsuspecting providers trying to implement their EHRs and meet the Meaningful Use criteria, according to Tracy Welsh, vice president at Hayes Management Consulting, in an article recently published in Health Data Management

Welsh identifies four particular problem areas that most providers don't--but should--anticipate. They include:

  • Using a consistent format for naming elements of the EHR system: There should be consensus on labeling beforehand, such as whether labels should be in all capital letters, especially if more than one person is involved in building the system. This consistency is needed for reporting clinical quality measures, Welsh says.    
  • Making sure dictation data is discrete: If the data is not stored in discrete elements, then users won't be able to search it or use it in reports. Welsh suggests that templates be created that format the dictation in a way that populates the discrete data elements.
  • Using caution and paying attention to detail when setting up master files: Similar to naming elements, the master files need to be created consistently and in a way that works for the organization. For instance, there needs to be a way for different lab results to be separated out within the master file, Welsh says. 
  • Not skimping on the security process: This may be more problematic for smaller providers, where job roles are less defined. Welsh recommends that providers take their time determining access rights and roles for each user.

To learn more:
- read the full Health Data Management piece

Suggested Articles

Roche, which already owned a 12.6% stake in Flatiron Health, has agreed to buy the health IT company for $1.9 billion.

Allscripts managed to acquire two EHR platforms for just $50 million by selling off a portion of McKesson's portfolio for as much as $235 million.

Artificial intelligence could help physicians predict a patient's risk of developing a deadly infection.