Term: Decision Support Systems-DSS


Decision Support Systems, or DSS, primarily consist of programs that are input into the computer to help the user accomplish a given task or make choices. A DSS is an interactive computer-based system or subsystem intended to help decision makers use communications technologies, data, documents, knowledge and/or models to identify and solve problems, complete decision process tasks, and make decisions. Decision Support Systems help to enhance the ability of the user to make decisions. For example, one not need know all information about a particular subject, rather input what is needed and a DSS will output a choice based on the user input. In general, Decision Support Systems are a class of computerized information system that support decision-making activities.


According to Wikipedia, the following are the primary types of DSS applications and their uses:
  • A model-driven DSS emphasizes access to and manipulation of a statistical, financial, optimization, or simulation model. Model-driven DSS use data and parameters provided by users to assist decision makers in analyzing a situation; they are not necessarily data intensive. Dicodess is an example of an open source model-driven DSS generator [14].
  • A communication-driven DSS supports more than one person working on a shared task; examples include integrated tools like Microsoft's NetMeeting or Groove [15].
  • A data-driven DSS or data-oriented DSS emphasizes access to and manipulation of a time series of internal company data and, sometimes, external data.
  • A document-driven DSS manages, retrieves and manipulates unstructured information in a variety of electronic formats.
  • A knowledge-driven DSS provides specialized problem solving expertise stored as facts, rules, procedures, or in similar structures.

These DSS systems are often used in the following situations:
  • medical diagnostics
  • executive management
  • business management

Typical information that a decision support application might gather and present would be:
o Accessing all of your current information assets, including legacy and relational data sources, cubes, data warehouses, and data marts
o Comparative sales figures between one week and the next
o Projected revenue figures based on new product sales assumptions
o The consequences of different decision alternatives, given past experience in a context that is described
The best decision support systems include high-level summary reports or charts and allow the user to drill down for more detailed information. Below is an example of Information Builders' WebFOCUS reporting software which is ideally suited for building decision support systems due to its wide reach of data, interactive facilities, ad hoc reporting capabilities, quick development times, and simple Web-based deployment.



Clinical Decision Support Systems:

By 1970s, the first computerized clinical decision support systems (CDSSs) was developed and used in clinical practices. The implementation of CDSS has been slow as barriers have been preventing large-scale implementation of the electronic decision support system. Here below are some factors benefits and drawbacks concerning the implementation of clinical decision support systems:

The potential benefits of using electronic decision support systems in clinical practice fall into three broad categories:
  1. Improved patient safety e.g. through reduced medication errors and adverse events and improved medication and test ordering;
  2. Improved quality of care e.g. by increasing clinicians available time for direct patient care, increased application of clinical pathways and guidelines, facilitating the use of up-to-date clinical evidence, improved clinical documentation and patient satisfaction;
  3. Improved efficiency in health care delivery e.g. by reducing costs through faster order processing, reductions in test duplication, decreased adverse events, and changed patterns of drug prescribing favoring cheaper but equally effective generic brands.

Informal list of potential benefits
  • Automatic provision of relevant, personalized expert advice, expertise and recommendations sourced from up-to-date, best practice knowledge
  • Reduce variation in the quality of care
  • Can support medical education and training
  • Can help overcome problems of inefficient coding of data
  • Can be cost-effective after initial capital costs and update and maintenance costs
  • Can provide immediate feedback to patients
  • If integrated with an EMR, can help streamline workflow (history taking, diagnosis, treatment) and encourage more efficient data gathering
  • Can provide an audit trail and support research
  • Can maintain and improve consistency of care
  • Can supply clinical information anytime, anywhere it's needed.

Potential drawbacks related to the use of CDSSs
  • Potential 'deskilling' effect
  • Can be perceived as a threat to clinical judgment
  • Can be considered too inflexible (can appear prescriptive, can appear to direct proceedings; can be difficult to depart from ordered, pre-prepared paths)
  • Promote over-reliance on software; limit clinicians' freedom to think?
  • Difficult to evaluate - lack of accepted evaluation standards
  • Can be time-consuming to use, possibly lead to longer clinical encounters and create extra work
  • Uncertain and untested ethical and legal status
  • Costs: maintenance, support and training required after initial outlay
  • A clinician's experience and imagination cannot be duplicated in a computer application.

Factors which may help determine the acceptance and use of CDSSs in clinical practice
  • Cost
  • Attitude of targeted users: breadth and depth of commitment
  • Degree of user acceptance prior to and after installation
  • Ease of use - time needed to learn to use and to use
  • Type, timing, length of training to be provided
  • Availability of support and maintenance
  • Interoperability: ease/extent of integration with legacy systems (hardware, other devices) and existing software programs (integration with patient record and/or any relevant clinical terminologies would avoid need to re-enter patient data)
  • Ease of integration within organizational context and routine workflow - degree to which it entails are design of clinical processes
  • Legal and ethical issues
  • User interface: design, structure, number of forms
  • Style, manner of presentation of advice/ recommendations/ results to user
  • Patients' attitudes to use
  • Provision of evidence justifying advice and/or recommendations
  • Involvement of local users during development phase
  • The quality and reliability of a system and its knowledge base which should be populated with trusted, up-to-date and maintainable knowledge
In the last resort, widespread use of clinical decision support systems in clinical practice will not occur without electronic patient record systems using terminology and data standards that will allow them to be accessed effortlessly during routine patient care.

Web Resources:


Related Terminology:

Database management system
Information systems
Health Informatics decision support system