“When people see a new technology being deployed, they automatically think, ‘Oh, great, I’ve got more work to do,’” said David Sharbaugh, president of SmartRoom, a technology company owned by the University of Pittsburgh Medical Center (UPMC) and jointly funded by IBM. Actually, says Sharbaugh, “We’re trying to subtract work and effort and make life simple and safe for the people out on the front lines.”

The SmartRoom screen can provide information about vital signs, medications, and lab results—pulled directly from the lab’s computers. “The first time that I used it, we caught a life-threatening critical lab, which was potassium less than 2.5 mEq/L, that had yet to make it through the alert system,” said Andrew Watson, MD, a UPMC surgeon.

Since the information on the screen is visible to clinicians and patients, the technology has the potential to involve patients in their own care. An email account where patients can receive messages and pictures is part of the current UPMC system. The connection could eventually be expanded to video conferencing with family and friends or other physicians.

And, supercomputer Watson has the potential to revolutionize how doctors work by providing a plethora of easily accessible information. Supercomputers are likely to feature prominently in the hospital of the future. Some hospitals are already using CAD and decision-support software.
Hospitals are already using computer programs to assist physicians in making accurate diagnoses. For example, United Hospital in St. Paul, MN is participating in a one-year pilot program using Isabel, a Web-based system designed by Isabel Healthcare. Isabel, continuously updated with the latest information from medical textbooks, journals and other sources, quickly prioritizes possible diagnoses based on symptoms entered by the physician combined with the patient’s medical history. Isabel is linked to the hospital’s electronic health record (EHR) system, allowing it to incorporate the patient’s medical history and demographics into its list of possible diagnoses.

Concern about misdiagnosis has already spurred development of targeted computer programs designed to help physicians make faster, more accurate diagnosis of specific diseases or conditions. For example:

• A study published online October 2008 in Brain reported that computers trained to analyze brain scans outperformed radiologists in diagnosing Alzheimer’s disease, correctly classifying the disease 95% of the time vs. a median of 89% among a group of radiologists. The authors noted advantages to automated systems, such as in facilities that lacked trained neuroradiologists or as a screening tool in primary care settings.
• Face-classification software correctly diagnosed 72% of patients with acromegaly compared with 63% accuracy by specialist physicians. The study was published online April 20, 2011 in The Journal of Clinical Endocrinology and Metabolism.
• A CAD tool was more accurate than emergency department physicians at diagnosing urinary tract infections, pneumonia, and bacteremia in young children, according to an April 2010 study published in British Medical Journal.

In addition to improving the accuracy of diagnosis, CAD tools that work with a hospital’s electronic health record system can help ensure that important parts of a patient’s clinical profile aren’t missed. For example, Herbert Chase, MD, Columbia University Medical Center, is working on a chronic kidney disease (CKD) notification tool that reviews patients’ charts automatically, identifies those with CKD, and notifies physicians who have not documented the condition in their outpatient notes.

Progress is also being made in the integration of electronic health records with digital clinical imaging, digital dictation, structured reporting, and voice recognition with picture archiving and communication systems. Under these systems, clinicians receive faster diagnostic results that can improve aspects of patient care and ultimately patient outcome.