Electronic Medical Records

Because of the emphasis by the Obama Administration on converting 100,000 primary-care physicians using paper-based medical records to become users of electronic medical records (EMRs) that achieve meaningful use (MU), there is strong interest in how well the EMR market is doing.

Driven by CCHIT certification, meaningful use and ARRA/HITECH incentive programs, the purchase of electronic health records/electronic medical records systems is looming large on many hospitals’ horizons – most likely for this fiscal year.

According to a report recently released by the American College of Physicians, “Increasing the use of quality measurement as part of EHR systems is critical to achieving meaningful use of health information technology.”

Clinicians are able to insert their thoughts and assessments into the documentation, allowing subsequent caregivers to understand and coordinate care more effectively.

If one reads clinician-authored critiques of the current state of electronic health records (EHRs), a recurring theme emerges: the poor quality of clinical notes in EHRs. The authors may cite excessive use of “cut and paste” to replicate past documentation (often without appropriate changes), excessive citation of results that needlessly expand a note’s length, and the absence of any clear articulation of the clinician’s thoughts, judgments and priorities.

Today, barely more than a quarter of physicians use electronic medical records (EMR) in an ambulatory setting, and roughly only 10 percent of hospitals have the technology to allow physicians to enter orders directly into a computer for transmission to the laboratory, pharmacy or other units. The consolidation inherent in a move to EMR has a number of implications, including the increased importance of IT infrastructure recovery capabilities.

LibertyHealth upgraded its wireless network to assure users had the 24-hour access needed by healthcare applications.

Patients’ vital signs are not the only information LibertyHealth needs to monitor at its hospitals, health centers and other facilities in the Jersey City, N.J., region. From high-tech infant care and adult surgery to in-hospital rehabilitation and home-care services, the system’s medical personnel depend on a wide range of networked applications. These, in turn, depend on a reliable wireless network.

Two systems replace traditional paper-based informed-consent process with an electronic time-out checklist integrated into electronic records.

The "time-out" process is an established, but often overlooked, mechanism for preventing a critical patient-safety issue: wrong-site/wrong-procedure/wrong-patient surgery. At a minimum, this process involves a standard by which members of the surgical team are required to agree on the correct patient identity, the correct procedure site and the procedure to be performed.

Healthcare system replaces time-consuming review process with a content-management system for developing and maintaining evidence-based order sets.

In the spring of 2008, Aurora Health Care experienced tremendous growth and was set to launch two healthcare facilities. The creation, adoption and maintenance of clinical order sets within the hospitals and clinics at Aurora was time consuming and inefficient. The process for summarizing clinical evidence, creating, reviewing and standardizing order sets, particularly in reaching a consensus among the physicians, was slow.

An Aide for EMRs

By Farida Ali, CEO, Dynamic Computer

The industry is witnessing the beginning of a trend of including automatic identification and data capture (AIDC) with electronic medical-record (EMR) adoption. EMR adoption has lagged despite a strong push from both private and public entities. Simultaneously, there has been an increase in the adoption of real-time locating systems (RTLS) and other technologies in the healthcare market. The paired adoption of EMR and AIDC systems holds the highest potential for improving patient care, reducing costs and minimizing risks.

AIDC refers to methods that automatically identify objects and then capture data about them directly into computer systems. These include radio frequency identification (RFID) technologies, bar codes, biometrics, optical character recognition (OCR), voice recognition and other electronic means of automatically identifying people and tagged objects.