RxSafe: Shared Medication Management and Decision Support for Rural Clinicians
Project Final Report (PDF, 730.79 KB) Disclaimer
Disclaimer
Disclaimer details
Project Details -
Completed
-
Grant NumberR18 HS017102
-
AHRQ Funded Amount$1,200,000
-
Principal Investigator(s)
-
Organization
-
LocationPortlandOregon
-
Project Dates09/01/2007 - 08/30/2011
-
Care Setting
-
Medical Condition
-
Health Care Theme
Managing medications can be complex and difficult in acute care, but is especially challenging for long-term management of older individuals with multiple chronic conditions. Health information technology (IT) may help to improve these processes, but limited progress has been made, especially in patients with multiple conditions who are managed by different clinicians using disparate information systems across many organizations. The purpose of this project was to investigate novel approaches to clinician decision-support applied to multidisciplinary-distributed medication management of people with chronic conditions. The project followed two approaches: 1) improving cognitive support for medication management by exploiting the semantics of clinical information; and 2) improving performance in multidisciplinary clinical work by developing software to facilitate collaboration.
The specific aims of the project were to:
- Enhance clinician cognitive performance in medication management tasks by exploiting the underlying semantics of medication lists to improve the organization and presentation of medication list information.
- Implement medication list management tools that are integrated into clinician-specific and task-specific workflows to support medication reconciliation at high-risk transitions as well as in ongoing ambulatory care.
- Increase the effectiveness of medication management activities of clinicians in multiple roles by improving their coordination and communication through the use of shared medication management tools.
- Employ evolving standards and architectures to link external, machine actionable, evidence-based clinical information in context-appropriate ways to support shared medication management by clinicians in ambulatory settings.
Initially, the team: 1) examined medication information in health IT systems, finding great variation in the arrangement and representations of medications among systems; 2) used card sort procedures to reveal that nurses, doctors, and pharmacists organized medications differently depending on task and profession; and 3) used a simulated copying task to find that the order of medications in a list affected recall for novices but not for experienced physicians, and that experienced physicians had greater recall of medications, formed more sophisticated mental models of patients, and spontaneously rearranged medications when copying a list, suggesting that sense-making accompanies even a simple copying task.
The team then observed and interviewed nurses, pharmacists, and physicians performing medication review tasks. The team found that medication management in long-term care was a distributed and multidisciplinary process. Clinicians often seek both simple correspondence (“reconciliation”) of items between lists, but also a coherent model of the patient and their care from other data such as diagnoses, comorbidities, laboratory data, and biomedical knowledge. The overall process was seen to be distributed, dynamic, collaborative, and continuous, involving multiple clinicians performing complementary tasks in different settings.
The team used a record locator service/record exchange service model to develop a proof-of-concept system, SyncRx. This system was meant to synchronize medication information in multiple lists maintained by different organizations as medications are asynchronously started, stopped, or changed by doctors, pharmacists, nurses, or others using non-interoperating task-specific applications. The next step in this research will be to test this prototype for usability with clinicians as they interact with the system.
Finally, the team developed a prototype that demonstrated the feasibility of independent Web-based decision-support services interacting in a service-oriented architecture over a network, including applications to parse medication information, identify and encode medications using existing standards, and enhance this information with Web-based medical knowledge sources.
Disclaimer
Disclaimer details