The Value-Added of Electronic Medical Records

An article in ADVANCE for Nurses looks at the ways in which health information technology is improving care, outcomes and nurses' work environments in health care settings around the country, particularly when that IT is built with nursing in mind.

At Baptist Health South Florida, patient barcodes allow nurses quick and easy access to their patients' full profiles. The barcodes have dramatically reduced wait time for pain medication and also helped to ensure that nurses know the exact doses and frequency of dosage for each of their patients' medications. Several INQRI studies have addresses nurses' role in medication management, including reducing medication errors and improving regimen adherence post hospital discharge.

Other uses of health IT, include automating the admissions process, so that when information on a patient is recorded during intake, that information is shared with other health care providers and hospital staff who may help provide care.

The article also discusses younger nurses' higher comfort level with information technology and ways that hospitals are successfully orienting new hires to their electronic medical records (EMR) systems and how schools of nursing are preparing students to use those records. A recent post on the RWJF Human Capital Blog by Ann Marie Mauro, an associate professor at NYU College of Nursing discusses how the college's simulation program also helps nursing students learn how to use EMR.

Will Dr. Robot Open New Doors for Nurses?

By Olga Yakusheva, PhD and Richard C. Lindrooth, PhD

Olga Yakusheva, PhD, is an associate professor of economics at Marquette University. Richard C. Lindrooth, PhD, is an associate professor at the University of Colorado Anschutz Medical Campus. Both are INQRI grantees.

Technological innovation is rapidly transforming patient care. A new generation of innovations will potentially change the most fundamental aspect of the patient experience – patients’ interactions with physicians and nurses. The FDA recently approved the first autonomous telemedicine robot for use in acute care hospitals. Even more advanced technologies, some capable of processing up to tens of millions of pages of plain medical text per second, are being tested and may soon be used to diagnose conditions and recommend treatment, with limited input from clinicians.

This new technology has the potential to perform several tasks more efficiently than clinicians, albeit with some limitations. It can quickly and effectively sift through large amounts of information and, based on a complex set of guidelines, create a probability-weighted list of diagnoses and recommendations. The result will be purely evidence-based and free of human cognitive decision-making biases.  The technology can drastically speed diffusion of new research and guidelines through electronic dissemination, similar to automatic software updates, and make most novel treatment regimens instantly available to patients.

However, even the smartest technology may not perform well when guidelines require information that is not easily quantifiable, nor when decision-making requires patient-specific judgment. Furthermore, technology is unlikely to supplant humans in direct patient care, including procedures and tasks that require empathy and emotional support.