Clinical decision support systems and infection prevention: to know is not enough

Development and implementation of a clinical decision support system-based quality initiative to reduce central line-associated bloodstream infections

Background

Central venous lines (CVLs) are frequently utilized in critically ill patients and confer a risk of central line-associated bloodstream infections (CLABSIs). CLABSIs are associated with increased mortality, extended hospitalization, and increased costs. Unnecessary CVL utilization contributes to CLABSIs. This initiative sought to implement a clinical decision support system (CDSS) within an electronic health record (EHR) to quantify the prevalence of potentially unnecessary CVLs and improve their timely removal in six adult intensive care units (ICUs).

Methods

Intervention components included: (1) evaluating existing CDSS' effectiveness, (2) clinician education, (3) developing/implementing an EHR-based CDSS to identify potentially unnecessary CVLs, (4) audit/feedback, and (5) reviewing EHR/institutional data to compare rates of removal of potentially unnecessary CVLs, device utilization, and CLABSIs pre- and postimplementation. Data was evaluated with statistical process control charts, chi-square analyses, and incidence rate ratios.

Results

Preimplementation, 25.2% of CVLs were potentially removable, and the mean weekly proportion of these CVLs that were removed within 24 hours was 20.0%. Postimplementation, a greater proportion of potentially unnecessary CVLs were removed (29%, p < 0.0001), CVL utilization decreased, and days between CLABSIs increased. The intervention was most effective in ICUs staffed by pulmonary/critical care physicians, who received monthly audit/feedback, where timely CVL removal increased from a mean of 18.0% to 30.5% (p < 0.0001) and days between CLABSIs increased from 17.3 to 25.7.

Conclusions

A significant proportion of active CVLs were potentially unnecessary. CDSS implementation, in conjunction with audit and feedback, correlated with a sustained increase in timely CVL removal and an increase in days between CLABSIs.

Clinical decision support for intervention reduction in neonatal patients: A usability assessment

Objective

This study investigated how effectively simplified cognitive walkthroughs, performed independently by four nonclinical researchers, can be used to assess the usability of clinical decision support software. It also helped illuminate the types of usability issues in clinical decision support software tools that cognitive walkthroughs can identify.

Method

A human factors professor and three research assistants each conducted an independent cognitive walkthrough of a web-based demonstration version of T3, a physiologic monitoring system featuring a new clinical decision support software tool called MAnagement Application (MAP). They accessed the demo on personal computers in their homes and used it to walk through several pre-specified tasks, answering three standard questions at each step. Then they met to review and prioritize the findings.

Results

Evaluators acknowledged several positive features including concise, helpful tooltips and an informative column in the patient overview which allows users direct (one-click) access to protocol eligibility and compliance criteria. Recommendations to improve usability include: modify the language to clarify what user actions are possible; visually indicate when eligibility flags are snoozed; and specify which protocol's data is currently being shown.

Conclusion

Independent, simplified cognitive walkthroughs can help ensure that clinical decision support software tools will appropriately support clinicians. Four researchers used this technique to quickly, inexpensively, and effectively assess T3's new MAP tool, which suggests positive actions, such as removing a patient from a ventilator. Results indicate that, while there is room for usability improvements, the MAP tool may help reduce clinician's cognitive load, facilitating improved care. The study also confirmed that cognitive walkthroughs identify issues that make clinical decision support software hard to learn or remember to use.

Computer Informatics for Infection Control

Computer informatics have the potential to improve infection control outcomes in surveillance, prevention, and public health. Surveillance activities include surveillance of infections, device use, and facility/ward outbreak detection and investigation. Prevention activities include awareness of multidrug-resistant organism carriage on admission, identification of high-risk individuals or populations, reducing device use, and antimicrobial stewardship. Enhanced communication with public health and other health care facilities across networks includes automated electronic communicable disease reporting, syndromic surveillance, and regional outbreak detection. Computerized public health networks may represent the next major evolution in infection control. This article reviews the use of informatics for infection control.

Interface, information, interaction: a narrative review of design and functional requirements for clinical decision support

Objective

Provider acceptance and associated patient outcomes are widely discussed in the evaluation of clinical decision support systems (CDSSs), but critical design criteria for tools have generally been overlooked. The objective of this work is to inform electronic health record alert optimization and clinical practice workflow by identifying, compiling, and reporting design recommendations for CDSS to support the efficient, effective, and timely delivery of high-quality care.

Material and Methods

A narrative review was conducted from 2000 to 2016 in PubMed and The Journal of Human Factors and Ergonomics Society to identify papers that discussed/recommended design features of CDSSs that are associated with the success of these systems.

Results

Fourteen papers were included as meeting the criteria and were found to have a total of 42 unique recommendations; 11 were classified as interface features, 10 as information features, and 21 as interaction features.

Discussion

Features are defined and described, providing actionable guidance that can be applied to CDSS development and policy. To our knowledge, no reviews have been completed that discuss/recommend design features of CDSS at this scale, and thus we found that this was important for the body of literature. The recommendations identified in this narrative review will help to optimize design, organization, management, presentation, and utilization of information through presentation, content, and function. The designation of 3 categories (interface, information, and interaction) should be further evaluated to determine the critical importance of the categories. Future work will determine how to prioritize them with limited resources for designers and developers in order to maximize the clinical utility of CDSS.

Conclusion

This review will expand the field of knowledge and provide a novel organization structure to identify key recommendations for CDSS.

Health care worker perceptions toward computerized clinical decision support tools for Clostridium difficile infection reduction: A qualitative study at 2 hospitals

BACKGROUND

Clostridium difficile infection (CDI) is associated with significant morbidity and mortality. Computerized clinical decision support (CCDS) tools can aid process improvement in infection prevention and antibiotic stewardship, but implementation and health care workers (HCWs) uptake of these tools is often variable. The objective of this study was to describe HCWs' perceptions of barriers and facilitators related to uptake of CCDS tools as part of a CDI reduction bundle.

METHODS

We conducted a qualitative study among HCWs at 2 acute care hospitals in Maryland. Semi-structured interviews and structured surveys were completed by HCWs to evaluate their perception to CCDS tools at 2 different stages: predevelopment and preimplementation. Emergent themes and patterns in the data were identified and condensed.

RESULTS

Gaps in CDI-related knowledge and in communication between HCWs were identified throughout the evaluation. HCWs agreed on the potential of the tools to improve CDI diagnosis, prevention, and control. An important barrier for uptake was the perceived loss of autonomy and clinical judgment, whereas standardization and error reduction were perceived advantages.

CONCLUSIONS

These observations shaped the development and implementation of the CDI reduction bundle. Qualitative findings can provide valuable contextual information during the development stages of CCDS tools in infection prevention and antibiotic stewardship.

The design of decisions: Matching clinical decision support recommendations to Nielsen's design heuristics

OBJECTIVE

While general design heuristics exist for graphic user interfaces, it remains a challenge to facilitate the implementation of these heuristics for the design of clinical decision support. Our goals were to map a set of recommendations for clinical decision support design found in current literature to Jakob Nielsen's traditional usability heuristics and to suggest usability areas that need more investigation.

MATERIALS AND METHODS

Using a modified nominal group process, the research team discussed, classified, and mapped recommendations, organized as interface, information, and interaction, to design heuristics. A previous narrative review identified 42 recommendations from the literature to define the design and functional characteristics that impact the performance of CDS in terms of provider preference, process of care, and patient outcomes.

MAIN FINDINGS

We matched 20 out of 42 recommendations to heuristics. The mapping reveals gaps in both heuristics and recommendations, identifying a set of Nielsen's heuristics that are underrepresented in the literature and subsets of recommendations important to design not covered in Nielsen's heuristics. We attributed this, in part, to the evolution of technology since the inception of Nielsen's heuristics. The team created a new interaction heuristic: Integration into real-time workflow to consider the needs of the end-user in the clinical space.

DISCUSSION

Clinical decision support has enabled clinicians to better address arising information needs; however there remains a lack of evidence-based guidelines in terms of functional and design requirements.

CONCLUSION

Results from this review suggest that interaction design principles were not fully satisfied by the current literature of clinical decision support.