Decision Support
By C. Jeanne Solberg, RHIA

Decision Support systems (DSS) can be defined in a variety of ways via systems, tools and technologies. DSS is typically a class of computerized information systems that support decision-making activities. Other terms used for DSS include Executive Information Systems (EIS), geographic information system (GIS), OLAP, software agents, and knowledge discovery systems. Any interactive computer-based system that can help decision makers use communications technologies, data, documents, knowledge and/or models to support decision making can be considered a DSS.

DSS systems are becoming more common in the healthcare field to successfully assist in medial decision making and healthcare planning tasks. These DSS enterprise-wide systems can link large data warehouses of information, pulled together from many disparate systems within a healthcare organization.

In the healthcare field, knowledge management and data mining decision support systems often gather patient demographic and medical diagnosis/procedure related information; detail-level charge information for care provided to the patient; payroll data; and general ledger information into a central repository. Using a variety of data extracting tools, the facility is able to analyze the cost and care of patients rendered to patients at a detail level (i.e., by diagnoses or procedures, DRG-level analysis, patient utilization of resources by physician or diagnosis, patient origin or age by diagnosis, cost of care by nursing unit or clinic, etc.) Contracts held with third party providers can also be modeled in some DSS. Healthcare facilities can use “what if” analysis, to determine the impact of new technology for patient groups or by reviewing healthcare reimbursement current contract against proposed terms, for negotiating purposes. Data can be compared to external data in order to benchmark quality of care indicators. Other tools within DSS may permit for analysis of episodes of care or longitudinal care (care provided across separate visits for the same diagnosis);

With the widespread use of electronic data capture and automation of medical records, clinical or medical diagnostic decision support systems (MDSS) have become a valuable aid in improving the accuracy of medical diagnosis and treatment. Their purpose is to enhance, not replace, a physician's ability in the complex and highly intuitive process of medical diagnosis. These DSS help support real time decisions. Clinical DSS also vary in the type of decisions that they support. Some programs support diagnostic decisions based upon patient data and the results of tests with the DSS proposing a diagnosis. Other systems may focus on therapeutic decisions that have alert capabilities such as drug-drug interactions, drug dose and other expert dose and algorithmic calculations. These systems recommend a treatment or aid the clinician in executing a treatment.

The skill sets to support and/or manage a decision support system are inherent in our profession. AHIMA has defined several emerging roles for our profession, with decision support being one of them (www.ahima.org/certification/emerging.cfm). Skill sets/competencies necessary for decision support include: business analysis skills; data analysis skills, including relational, dimensional, legacy and stand-alone data; data presentation skills; knowledge of data feeds and need for accuracy; and an understanding of end user requirements/needs. Take a look around the healthcare community as there are growing opportunities for you to step into a DSS role.

Reprinted with permission from MHIMA Uplink, Spring 2004

Jeanne Solberg, RHIA, is a Senior Application Consultant with McKesson Corporation. She was Manager of Decision Support Services at Regions Hospital in St. Paul, MN for 6 years; Clinical Manager of Decision Support; Director of Medical Records, Quality Management and Utilization Review at Lancaster General Hospital in Lancaster, Pennsylvania. She is currently a member of AHIMA's Council on Accreditation and has chaired AHIMA's Program Committee. Solberg has been active in the Minnesota HIMA, serving as president and program committee co-chair. She was also active in the Pennsylvania serving as chairman of the program, education and public relations committees. She has also served as a member of the nominating, arrangement and bylaws committees. Solberg has spoken on multiple occasions on subjects including decision support, data management, and computerized record technology.

Thanks to ex-Texan Karen Robey, RHIT, for this article. Karen is now at the Minnesota HIMA central office.