CHAPTER 10

1. CHAPTER 10 Incorporating Evidence: Use of Computer-Based Clinical Decision Support Systems for Health Professionals

2. INTRODUCTION Decision support systems (DSS) are automated tools designed to support decision-making activities and improve the decision-making process and decision outcomes.

3. CDSS - is designed to support healthcare providers in making decisions about the delivery and management of patient care. - is a “tool” system, not a “rule” system Goals of a CDSS program may include patient safety and improved outcomes for specific patient populations as well as compliance with clinical guidelines, standards of practice, and regulatory requirements.

4. Clinical tasks to which CDSS may be applied: • Alerts and Reminders • Diagnostic Assistance • Therapy Critiques and Plans • Medication Orders • Image Recognition and Interpretation • Information Retrieval PRIMARY GOAL OF CDSS The optimization of both the efficiency and effectiveness with which clinical decisions are made and care is delivered (Tan and Sheps, 1998)

5. NURSING DECISION SUPPORT SYSTEMS NDSS are tools that help nurses improve their effectiveness, identify appropriate interventions, determine areas in need of policy or protocol development, and support patient safety initiatives and quality improvement activities.

6. DEFINITION Johnston et al. (1994) defined CDSS as “computer software employing a knowledge base design for use by a clinician involved in patient care, as a direct aid to clinical decision-making.” Sims et al. (2001) broadened the definition to “CDSS are software designed to be a direct aid to clinical decision-making, in which the characteristics of an individual patient are matched to a computerized clinical knowledge base and patient-specific assessments or recommendations are then presented to the clinician or the patient for a decision.”

7. Three main purposes of a DSS: • Assist in problem solving with semi structured problems • Support, not replace, the judgment of a manager or clinician • Improve the effectiveness of the decision-making process

8. HISTORY OF CDSS • Early Systems • Focus on Diagnosis. One of the earliest known CDSS designed to support diagnosis of acute abdominal pain was developed by de Dombal in 1972 at Leeds University. This system used Bayesian Theory to predict the probability that a given patient, based on symptoms, had one of seven possible conditions. • Other CDSS Uses • ONCOCIN • CASNET • ABEL

9. TYPES AND CHARACTERISTICS OF DSS Types of DSS Administrative and Organizational Systems - in these systems, decisions occur at the strategic, tactical, population or aggregate and operational levels, not the individual level Integrated Systems - such systems are able to support outcomes performance management by integrating operational data with clinical data

10. CHARACTERISTICS OF DSS • Functional class – feedback provided to the clinician, the organization of the data, the extent of proactive information provided, the intelligent actions of the system, and the communication method • Logical class – includes substitute therapy alerts, drug family checking, structured entry, consequent actions, parameter checking, redundant utilization checking, relevant information display, time-based checks, templates and order sets, and profile display and analysis, rule-based event detection, and aggregate data trending • Structural elements – include triggering, dispatching, rule logic, process control, notification/acknowledgement, action choices, action execution, and rule editor

11. KEY CDSS FUNCTIONS • Perreault (1999) organized key CDSS functions as: • Administrative • Management of clinical complexity and details • Cost control • Decision support • DSSs could be divided into: • Data-based systems • Model-based DSSs • Knowledge-based systems • Graphics-based systems

12. Examples of CDSS Applications Therapy critiquing and planning as well as care maps, guidelines, protocols and so on Diagnostic assistance providing patient-specific consultations using diagnostic or management tools such as Problem Knowledge Couplers (PKC) (Weed 1991) Lab systems with interpretation of measured values and automated preparation of reports as well as physician guidance as to which tests to order CDSS have the ability to respond to recorded decisions that alter care (critiques of orders) and requests from decision makers (suggestions systems)

13. DECISION TREE LOGIC DTL is useful for specific straightforward tasks

14. RULE-BASED LOGIC RBL allows for complex decision capacities, is somewhat more flexible with answers, provides consistent outcomes and is adaptable to change; however, it also tends to have rigid solutions and allows little or no clinician autonomy

15. CDSS Impact on Clinicians and Clinical Decisions • Need for Evidence-Based Practice • This became especially true after the Institute of Medicine (IOM) Report (2000) identified human error as a major source of patient care morbidity and mortality. • Barriers to the Use of CDSS Systems • Lack of noticeable benefits • Insufficient cost benefits • Inadequate staff training • Lack of system support • System costs • Lack of exposure to technology

16. Evaluation of CDSS Integrated real-time patient database – combines patient data from multiple sources, lab, radiology, pharmacy, admissions, nursing notes, and so on. Data-drive mechanism – allows event triggers to go into effect and activate alerts and reminders automatically Knowledge engineer – who can translate the knowledge representation scheme used in the system can be extracted and translated into machine executable logic Time-driven mechanism – to permit automatic execution of programs at a specific time to alert provider to carry out a specific action or insure that the action had been completed Long-term clinical data repository – data collected over time from a variety of sources allowing a longitudinal patient record

17. KNOWLEDGE AND COGNITIVE PROCESSES Cognitive Task Analysis (CTA) - refers to a set of methods that attempt to capture the skills, knowledge, and processing ability of experts in dealing with complex tasks. RESPONSIBILITY OF USER: EHTICAL AND LEGAL ISSUES CDSS will be expected to comply with a “duty of care” if it is to become safely integrated into routine patient care. IMPLICATIONS FOR FUTURE USES OF CDSS IN NURSING • Increasing Inclusions of Patients • Dual Purpose of Documentation