These are exciting times in healthcare, and one of the most transformative trends is taking place in the clinical arena. Simply put, the electronic health record (EHR) has made it possible to provide precise information to clinicians on an unprecedented scale in near real-time. The result? Physicians now have a powerful decision support tool that enables them to focus with laser-like efficiency on critical patient data and act on it in a timely manner.
Blessing Hospital, a 420-bed facility in Quincy, Ill., stands out as an example of what that means in hard numbers. The community hospital, which went live with its EHR (supplied by the Chicago-based Allscripts Healthcare Solutions Inc.), in 2005, has developed an advanced clinical decision support tool (aCDS), and documented some stunning results over a two-year period, among them: a 45.5-percent drop in its mortality rate; an 8.9-percent decrease in length of stay, resulting in a savings of $744,000; and a drop in variable cost per case of 4.2 percent, resulting in an additional savings of $524,000.
Maureen Kahn, R.N.
Those outcomes were surprising to CEO Maureen Kahn, R.N., her IT informatics leaders and IT team, to which she gives full credit for achieving those impressive results. “For the first time, we had data about ourselves that we could consistently take a look at,” she says, noting that the improvements are evidence of success for the project teams in changing practices to achieve better care outcomes.
A STRATEGIC FOCUS
Kahn says the aCDS project grew out of the hospital’s IT strategic plan. “As we brought in the electronic health record and started to capture data, it was very obvious to all of us that the data was now available at our fingertips, to be able to use it and share the information with our providers, so that we could begin to make sustainable improvements in the quality of care that we deliver in our organization,” she says. Having that capability, the hospital began comparing its own internal data, and, later on, benchmarking against outside databases.
In looking at its own practices, Blessing identified the variability in the approaches and compared provider-to-provider. It also identified evidence that could be used to apply a consistent approach to the care of its patients, to minimize variability of care and try to discover how to improve patient care within the organization. Where it made sense in delivering positive outcomes, the hospital shared best practices with other providers in the organization, she says. “We were looking at our own data and saying, what can we do to drive compliance with evidence-based guidelines.”
The redesign team for CPOE, made up of interdisciplinary staff that worked on developing the processes and testing the system before activation. Photo: Blessing Hospital
Kahn describes the aCDS project as part of a journey of discovery: “We are not 100-percent there; we are taking one project at a time,” she says. The process involves “bringing all stakeholders to the table to understand what the data is.” One thing it is not is a finger-pointing exercise, she emphasizes. “This is about how do we take this information and ask, ‘Is there something that we can learn from one another to improve performance?’”
The aCDS tool grew out of the hospital’s computerized physician order entry (CPOE) implementation. Julie Duke, administrative director of revenue cycle, informatics and quality, explains that through CPOE, “We looked at all of the physicians’ processes and at how they input orders. We were able to streamline processes for them and to provide evidence-based order sets that will allow them to move throughout their workflow with their patients.”
The aCDS goes beyond traditional automated alert-based systems as a form of clinical decision support. The drawback of that traditional approach is that it often results in “alert fatigue,” causing caregivers to ignore the alerts. Blessing Hospital’s innovation has avoided alert fatigue with a form of clinical intelligence that searches all documentation and detects what may be too complex for clinicians to discern. Using the aCDS, physicians are better able to identify their patients’ needs, and address them while reducing unnecessary variations in practice.
Active order sets adjust recommendations to reflect patient-specific clinical characteristics, histories, diagnoses, drugs, lab results and reports. Intelligent order sets guide physicians to make the best decisions. The intelligent order sets are updated for advances in treatment options and evidence-based medicine. In addition, adherence to best practices has been maximized across traditional care boundaries for acute episodes, chronic conditions, and health maintenance issues. These capabilities are integrated into the normal workflows.
Order sets are created to be as user-friendly as possible, Duke says. Medications, for example, are grouped in the most common types of practices, she says. Physicians are given prompts for certain medications to determine whether or not the physician wants to continue, she explains. “When a patient comes out of surgery and the physician is doing his post-ops, the system allows them to be prompted for the orders they want. By doing that, they have their documentation built and their orders sent,” she says. She adds that the prompts result in more complete documentation, which allows the hospital to code more appropriately for reimbursements.