InformationWeek Healthcare's second annual list of IT executives highlights the exceptional thinkers and doers who are moving patient care forward.
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Dr. Peter Greene, the CMIO at Johns Hopkins Medicine, spends a lot of time thinking about ways to improve the health system's clinical decision support system (CDSS). "Alert fatigue is a massive problem in hospitals, so we are trying to create smarter alerts and 'choreographed' alerts to make it easier to manage patient care and reduce the number of unnecessary alerts," he said.
For instance, Greene and his colleagues at Johns Hopkins--which encompasses the university's medical school and integrated health system--have devised a smarter way to order postoperative insulin regimes for diabetic patients. Several hundred different insulin regimens are available for these patients. Instead of making the physician slog through countless screens and alerts in the CPOE, behind-the-scenes programming inserts key pieces of information from the patient's e-chart to help find the right regimen. The ordering physician only needs to answer a few questions before the CDSS makes a specific recommendation.
Greene's team also has tackled the complexities of managing indwelling urinary--a.k.a. Foley--catheters in hospitalized patients. The standard of care for surgical patients calls for removal of the Foley by the end of the second post-op day. On a busy surgical unit, that task is easily overlooked, risking needless complications. Using a team-based decision support approach, Greene said, so-called choreographed alerts are sent to members of the nursing and medical staff at various points in a patient's care. The alerts ask the appropriate clinician to document the presence of the catheter and explain why it's still needed.
Greene's efforts have gone a long way toward easing one of the main reasons so many docs in the trenches hate EHRs--alert noise.
InformationWeek Tech Digest, Nov. 10, 2014Just 30% of respondents to our new survey say their companies are very or extremely effective at identifying critical data and analyzing it to make decisions, down from 42% in 2013. What gives?