In the first post of this 2 part blog we explored the big challenges with the demands that the ARRA HITECH and other compliance and regulatory impositions have impacted Healthcare IT: HIPAA’s Version 5010 conversion, ICD-10 migrations, Meaningful Use of EHRs and their Attestation and Accountable Care Organizations. We also briefly touched the popular topic of the imminent end of the world in 2012 according to the Mayan calendar prediction.
If you read carefully you would have noticed that my predictions, well, they have some small glitches now and then, or you may call them “bugs” due to my software developer background. So at the end of this blog we’ll have to revisit the end of the world prediction. Sorry folks.
The ICD-10 deadline, as of last week, was announced by the HHS Secretary Kathleen G. Sebelius the intent to delay the compliance date. Hopefully the delay will not be such that it has a big impact on healthcare interoperability projects. ICD-10 would help the way healthcare data is stored and exchanged between systems. One of the drawbacks of ICD-9 is that since it lacked codes to describe many diagnosis or procedures clinicians and related clerical staff would use the code that closely matched the reimbursement amount expected. Pro-active healthcare organizations should move forward with their ICD-10 conversion projects since it solves many inherent problems contained in their data that hinders interoperability in a meaningful way.
Data Aggregation and Mining for Successful Quality Measurement Reporting and Performance Improvement Requirements
Going back to the topics we left off in our previous post, I would like to dive a little into data aggregation. Healthcare data is contained in many source systems inside a hospital organization and more frequently it can be found outside of the organization. I have been in several projects where I’ve had to aggregate data located in 3 different states in the US!
If your organization plans to successfully meet Meaningful Use stages 1, 2 and 3 then getting control of your data is of paramount importance. Meaningful Use stage 1 may appear to be trivial to many organizations but don’t let this mislead you as to the growing complexities of stages 2 and 3. Albeit we don’t know the details of the requirements for stage 2, which are to be announced shortly, what we do know is that they will require more data from the different source systems.
Health BI, as an aggregation platform, can receive healthcare data from myriad sources; whether it’s from the inpatient Health Information System (HIS) , the outpatient Electronic Medical Record (EMR) or the Laboratory Information System (LIS) it can all come together in a single repository from which up to 600 Clinical Quality Measures can be reported! Health BI is modeled after the HL7 v3.0 RIM.
Health BI can accept data in various formats: HL7 v2.x, text files, ftp, HL7 v3.0 CDA documents (e.g., CCD) and HITSP C32 among others. Our approach is to create accelerators or connectors to the most common Healthcare Source Systems in the domain.
For more information on how Perficient’s health BI (Business Intelligence) solution can assist you with your 44 Eligible Professional (EP) or 15 Eligible Hospital (EH), depending on your particular case, of the Meaningful Use (MU) Clinical Quality Measures (CQM) – refer to the Meaningful Use Measure sheets for Eligible Professionals or Eligible Hospitals.
CPOE Implementations
Meaningful Use requires a scalable approach to the implementation of a Computerized Physician Order Entry system or as it is known by its acronym ‘CPOE’. For MU stage 1 it is required that more than 30 percent of all unique patients with at least one medication in their medication list being treated by the Eligible Professional have at least one medication order entered using CPOE. There is an exclusion for an EP that writes less than 100 prescriptions during the EHR reporting period. For Meaningful Use stages 2 and 3 it will be required that 60% and 80% of all unique patients, respectively, under the same criteria as stage 1, have at least one medication order entered using CPOE. The stage one bar is low in order to get the eligible professionals started but as the bar raises more automation and interoperability should be put in place by using certified electronic health record products.
CDA and the CCD template based document generation
The Continuity of Care Document, or CCD, is a CDA based constrained template derived from ASTM’s Continuity of Care Record. The Clinical Document Architecture, or CDA, is based on the HL7 RIM.
Exchanging healthcare information has been one of the main premises of implementing certified Electronic Health Records for Meaningful Use.
The CCD was designed to provide a human readable and electronically consumable document that contained a snapshot of the relevant healthcare information of a patient after an encounter with a healthcare professional or provider.
It is estimated that many organizations will start exchanging CCDs or CCRs to meet Meaningful Use criteria during stages 2 and 3. It is probable that your organization would have to embark on a project revolving around a CCD.
Health BI is capable of ingesting and aggregating data from myriad source systems in order to produce a CCD document that can be exchanged with other source systems or HIEs.
To learn more about the HL7 CCD you can visit this wiki: http://wiki.hl7.org/index.php?title=Product_CCD (Note: Some sections may require membership privileges.)
Natural Language Processing (NLP)
In every project of aggregating data to be leveraged for various use cases the valuable and relevant clinical data is hidden in transcriptions, nursing notes, scanned forms and documents and many other non-structured formats.
This is what has been the major blocker in true interoperability in healthcare. Over and over again I witness IT professionals from other domains enter the healthcare vertical believing that they have the silver bullet for interoperability but they all end up dismayed and disheartened when they run into the reality.
NLP is a promising Artificial Intelligence technology that will ease some of the pains of abstracting this hidden data. Today, most of this data has to be manually abstracted which takes its toll on specialized resources and time.
IBM is investing a lot of money and energy into Watson. Microsoft Research is also working on NLP applied to healthcare.
If you are in a larger healthcare organization, expect to be encountering this technology soon. It’s probably the only way to overcome interoperability hurdles that will be encountered while trying to meet many meaningful use criteria.
You can learn more about IBM’s Watson technology here: http://www-03.ibm.com/innovation/us/watson/
Private Health Information (PHI) in the Cloud
The cloud is here to stay and exchanging information nationwide has to be able to traverse artificial barriers that IT departments have created in their healthcare organizations. These barriers to protect PHI were put in place much before technology that is extremely secure had matured.
Many organizations, like Amazon, already provide cloud-based spaces that can protect PHI data even better than most healthcare organizations can!
Expect to be involved in many cross-organizational projects where healthcare data has to be sent to and received from the cloud. Learn the new security and privacy protocols that cloud technology is creating or improving.
Internal demand for emerging technologies
Tablets and smartphones have become ubiquitous in the healthcare realm. Physicians have really been eager adopters of this new technology. I’ve been in a few projects where the biggest scope creep requirement has been to make tablets browsers compatible with the Internet or Intranet solution being deployed enterprise wide in the healthcare organization.
The pressure for providing support to mobile technology will grow and especially from the point of care use cases and workflows. Mobile technology in healthcare is probably the hottest theme after MU and ACOs.
This endeavor entails a lot of coordination between the vendors and the IT security department. Little portable devices are prone to get lost a lot easier than bigger laptops or stationed devices.
The Mayan prediction of the end of the world
I’m just hoping that NASA won’t change their mind like CMS HHS did with regard to the intent to delay the implementation of ICD-10. But just in case I’ll provide once again their doomsday link in this second part of the blog to see if we have to embark on a project to sail away from planet Earth before 2012 ends.
What do you think are the biggest challenges in Health IT?
