Do computerised clinical decision support systems for prescribing change practice? A systematic review of the literature (1990-2007)

Abstract

Background: Computerised clinical decision support systems (CDSSs) are used widely to improve quality of care and patient outcomes. This systematic review evaluated the impact of CDSSs in targeting specific aspects of prescribing, namely initiating, monitoring and stopping therapy. We also examined the influence of clinical setting (institutional vs ambulatory care), system-or user-initiation of CDSS, multi-faceted vs stand alone CDSS interventions and clinical target on practice changes in line with the intent of the CDSS.

Impacts and Risks of Adopting Clinical Decision Support Systems

“…In another study, Subramanian et al (2007) found that the increasing use of CPOE has facilitated the "elimination of handwriting identification problems, reductions in error associated with similar drug names, faster delivery of orders to the pharmacy" (p. 1451). These studies and others from the literature affirm the significant impact of CDSS in reducing medical errors in clinical practice, thereby, improving the quality of care, patient safety, and patient outcomes (Pearson et al, 2009). …”

“…CDSS have been recognized as promising tools for influencing healthcare provider performance to improve and streamline the quality of healthcare delivery (Bassa et al, 2005;Pearson et al, 2009). CDSS originated from Decision Support Systems (DSS).…”

“…Hwang, Chang, Hung, Sung, and Yen (2004) asserted that a "DSS that supports physicians with the potential to minimize practice variation and improve patient care" (p. 240) is known as CDSS. Throughout their inception in the medical arena in the early 1970s, CDSS have evolved immensely to support the workflow of clinicians and improved the effectiveness of decision outcomes (Bassa et al, 2005;Hwang et al, 2004;Pearson et al, 2009). Although several challenges are facing the use and adoption of CDSS in the healthcare setting, the technology still remains promising when it comes to its ability to support evidence-based practice and enhancing the clinical decision-making process of healthcare providers.…”

“…The fact that CDSS have "become increasingly sophisticated by matching patient characteristics with computerised knowledge bases and using algorithms to generate patient-specific assessments or treatment recommendations" (Pearson et al, 2009, p. 155) demand that appropriate management of knowledge is implemented in the CDSS to ensure that the patient-specific assessments and/or treatment recommendations are not based on poor quality data. It is therefore important that narrative information emanating from the CDSS is further processed and analyzed by healthcare providers before clinical decisions are made (Pearson et al, 2009). …”

Assessing the strengths and weaknesses of a computer assisted medication review in hospitalized patients

“…Whereas present studies focus on the alert fatigue or so called false-positives, not reporting of important alerts may be even more serious. An important reason for not providing insight into underreporting comes from the fact that present studies do not directly compare manual medication surveillance with a CDSS in the same patient population, [28,29]. Controls usually consist of a different population or a historical cohort.…”