The following is a guest blog post by Brian Levy, MD, Senior Vice President and Chief Medical Officer for Health Language.
Effective medication reconciliation across the continuum of care is a critical element to eliminating medication errors and adverse drug events (ADEs). It is a focal point of such national initiatives as Meaningful Use (MU) and the Joint Commission’s National Patient Safety Goals and will also be crucial to ensuring performance metrics are met under Value-Based Purchasing and the Hospital Readmissions Reduction Program.
Simply put, one of the primary end-goals of current industry movements is to eliminate the revolving door effect in healthcare where patients are readmitted soon after discharge due to ADEs or lack of good information across the continuum. A growing body of research points to enhanced medication reconciliation as an effective way for hospitals to reduce readmission rates to meet this objective.
A 2012 study published in the Joint Commission Journal on Quality and Patient Safety found that accurate preadmission medication lists—acquired as part of medication reconciliation strategies— reduced ADEs both in the hospital and following discharge. Another paper published in the November 2012 edition of Pharmacotherapy also points to the critical role ADEs play in readmission rates and how ineffective care transitions, especially as they relate to medication management, exacerbate the situation.
The logistics of medication reconciliation has historically been an uphill battle for many clinicians. Without an electronic method for capturing information, the scene usually comes down to a Q&A session where physicians, nurses or other clinicians rely on patients to give them an accurate medication list. When a patient is unaware of the name of a medication, it usually results in a protracted delay in patient care while phone calls are made and consults conducted to accurately identify medications and avoid the potential for error.
EHRs provide the first step to correcting this inefficient way of gathering information. And while these systems are great repositories of patient information, the difficulty for medication reconciliation has been a lack of standards—specifically the lack of a standardized medical vocabulary. A number of proprietary medical terminologies exist within the industry, and without a standard for information exchange, the risk is that one drug could be identified by a number of different terminology codes depending on the proprietary system used.
Clinicians need an effective method for exchanging patient medication information between disparate systems in a standardized format that can be translated accurately by various healthcare organizations, providers and departments involved in patient care. MU is addressing this issue on one level through the introduction of RxNorm, a normalized naming system produced by the National Library of Medicine for generic and branded drugs and a tool that supports semantic interoperability between drug terminologies and pharmacy knowledge base systems.
RxNorm is a critical first step to ensuring the feasibility of building and accessing an accurate medication summary, thus minimizing the possibility of duplicate therapies, drug allergies and drug interactions. By adopting this standard, healthcare organizations and providers will begin receiving RxNorm codes in important CCD summary of care documents and HL7 messages. This standard will complement the use of the Systematized Nomenclature Of Medicine Clinical Terms (SNOMED CT®), a widely-used clinical terminology set also required under MU for the creation of problem lists.
While RxNorm provides efficient and accurate capture of medication information from external systems, healthcare organizations and providers will still require a method of converting codes from RxNorm to internal systems and visa-versa. This step ensures that internal medicine systems and drug information and interactions databases like Medi-Span, First Databank, Micromedex and Multum can also reconcile important patient medication information.
To address the full picture of data normalization, healthcare providers can leverage a healthcare terminology management solution to ensure automated mapping of patient medication data received from disparate sources to standardized terminologies. This process de-duplicates data, creating a normalized code across all clinical systems used internally, minimizing the potential for error.
This approach also provides an effective way for leveraging a comprehensive, longitudinal patient record, which is a primary goal of the health IT movement to enhance patient care. A foundation of standardized codes enables healthcare organizations to more fully develop advanced clinical decision support functions, where alerts can be received immediately for clinical activity impacting individual patients or within populations of patients.
As the healthcare’s industry move toward higher-quality care and more efficient care delivery continues to mature, the use of standardized medical terminologies will be paramount to effective clinical information exchange. While some initiatives like RxNorm and SNOMED CT are addressing this need for standardization, healthcare organizations can further advance data normalization strategies by leveraging the efficiencies and advantages of healthcare terminology management solutions.