Clinical Decision Support Systems Could Be Modified To Reduce 'Alert Fatigue' While Still Minimizing The Risk Of Litigation

Clinical decision support systems--interactive computer systems that help doctors make clinical choices--can reduce errors in drug prescribing by offering real-time alerts about possible adverse reactions. But physicians and other users often suffer "alert fatigue" caused by excessive numbers of warnings about items such as potentially dangerous drug interactions. As a result, they may pay less attention to or even ignore some vital alerts, thus limiting these systems' effectiveness. Designers and vendors sharply limit the ability to modify alert systems because they fear being exposed to liability if they permit removal of a warning that could have prevented a harmful prescribing error. Our analysis of product liability principles and existing research into the use of clinical decision support systems, however, finds that more finely tailored or parsimonious warnings could ease alert fatigue without imparting a high risk of litigation for vendors, purchasers, and users. Even so, to limit liability in this area, we recommend stronger government regulation of clinical decision support systems and development of international practice guidelines highlighting the most important warnings

Clinical Decision Support Systems Could Be Modified To Reduce 'Alert Fatigue' While Still Minimizing The Risk Of Litigation

Clinical decision support systems--interactive computer systems that help doctors make clinical choices--can reduce errors in drug prescribing by offering real-time alerts about possible adverse reactions. But physicians and other users often suffer "alert fatigue" caused by excessive numbers of warnings about items such as potentially dangerous drug interactions. As a result, they may pay less attention to or even ignore some vital alerts, thus limiting these systems' effectiveness. Designers and vendors sharply limit the ability to modify alert systems because they fear being exposed to liability if they permit removal of a warning that could have prevented a harmful prescribing error. Our analysis of product liability principles and existing research into the use of clinical decision support systems, however, finds that more finely tailored or parsimonious warnings could ease alert fatigue without imparting a high risk of litigation for vendors, purchasers, and users. Even so, to limit liability in this area, we recommend stronger government regulation of clinical decision support systems and development of international practice guidelines highlighting the most important warnings

Drug-drug interactions that should be noninterruptive in order to reduce alert fatigue in electronic health records

Objective Alert fatigue represents a common problem associated with the use of clinical decision support systems in electronic health records (EHR). This problem is particularly profound with drug–drug interaction (DDI) alerts for which studies have reported override rates of approximately 90%. The objective of this study is to report consensus-based recommendations of an expert panel on DDI that can be safely made non-interruptive to the provider's workflow, in EHR, in an attempt to reduce alert fatigue. Methods We utilized an expert panel process to rate the interactions. Panelists had expertise in medicine, pharmacy, pharmacology and clinical informatics, and represented both academic institutions and vendors of medication knowledge bases and EHR. In addition, representatives from the US Food and Drug Administration and the American Society of Health-System Pharmacy contributed to the discussions. Results Recommendations and considerations of the panel resulted in the creation of a list of 33 class-based low-priority DDI that do not warrant being interruptive alerts in EHR. In one institution, these accounted for 36% of the interactions displayed. Discussion Development and customization of the content of medication knowledge bases that drive DDI alerting represents a resource-intensive task. Creation of a standardized list of low-priority DDI may help reduce alert fatigue across EHR. Conclusions Future efforts might include the development of a consortium to maintain this list over time. Such a list could also be used in conjunction with financial incentives tied to its adoption in EHR

Recommendations for Providers on Person-Centered Approaches to Assess and Improve Medication Adherence

Medication non-adherence is a significant clinical challenge that adversely affects psychosocial factors, costs, and outcomes that are shared by patients, family members, providers, healthcare systems, payers, and society. Patient-centered care (i.e., involving patients and their families in planning their health care) is increasingly emphasized as a promising approach for improving medication adherence, but clinician education around what this might look like in a busy primary care environment is lacking. We use a case study to demonstrate key skills such as motivational interviewing, counseling, and shared decision-making for clinicians interested in providing patient-centered care in efforts to improve medication adherence. Such patient-centered approaches hold considerable promise for addressing the high rates of non-adherence to medications for chronic conditions

Computer clinical decision support that automates personalized clinical care:a challenging but needed healthcare delivery strategy

How to deliver best care in various clinical settings remains a vexing problem. All pertinent healthcare-related questions have not, cannot, and will not be addressable with costly time- and resource-consuming controlled clinical trials. At present, evidence-based guidelines can address only a small fraction of the types of care that clinicians deliver. Furthermore, underserved areas rarely can access state-of-the-art evidence-based guidelines in real-time, and often lack the wherewithal to implement advanced guidelines. Care providers in such settings frequently do not have sufficient training to undertake advanced guideline implementation. Nevertheless, in advanced modern healthcare delivery environments, use of eActions (validated clinical decision support systems) could help overcome the cognitive limitations of overburdened clinicians. Widespread use of eActions will require surmounting current healthcare technical and cultural barriers and installing clinical evidence/data curation systems. The authors expect that increased numbers of evidence-based guidelines will result from future comparative effectiveness clinical research carried out during routine healthcare delivery within learning healthcare systems