Bmc Med Inform Decis
-
Bmc Med Inform Decis · May 2016
Attitudes of pediatric intensive care unit physicians towards the use of cognitive aids: a qualitative study.
Cognitive aids are increasingly recommended in clinical practice, yet little is known about the attitudes of physicians towards these tools. ⋯ Our sample of PICU physicians were open to cognitive aids in their practice, as long as such aids preserve the primacy of clinical judgment, focus on team communication, demonstrate effectiveness through preliminary testing, and are designed and implemented with the local culture and work environment in mind. Future knowledge translation efforts to implement cognitive aids would benefit from consideration of these issues.
-
Bmc Med Inform Decis · Mar 2016
Utility of linking primary care electronic medical records with Canadian census data to study the determinants of chronic disease: an example based on socioeconomic status and obesity.
Electronic medical records (EMRs) used in primary care contain a breadth of data that can be used in public health research. Patient data from EMRs could be linked with other data sources, such as a postal code linkage with Census data, to obtain additional information on environmental determinants of health. While promising, successful linkages between primary care EMRs with geographic measures is limited due to ethics review board concerns. This study tested the feasibility of extracting full postal code from primary care EMRs and linking this with area-level measures of the environment to demonstrate how such a linkage could be used to examine the determinants of disease. The association between obesity and area-level deprivation was used as an example to illustrate inequalities of obesity in adults. ⋯ An area based socio-economic measure was linked with EMR-derived objective measures of height and weight to show a positive association between area-level deprivation and obesity. The linked dataset demonstrates a promising model for assessing health disparities and ecological factors associated with the development of chronic diseases with far reaching implications for informing public health and primary health care interventions and services.
-
Bmc Med Inform Decis · Mar 2016
The influence of the type and design of the anesthesia record on ASA physical status scores in surgical patients: paper records vs. electronic anesthesia records.
The American Society of Anesthesiologists Physical Status classification (ASA PS) of surgical patients is a standard element of the preoperative assessment. In early 2013, the Department of Anesthesia was notified that the distribution of ASA PS scores for sampled patients at the University of Iowa had recently begun to deviate from national comparison data. This change appeared to coincide with the transition from paper records to a new electronic Anesthesia Information Management System (AIMS). We hypothesized that the design of the AIMS was unintentionally influencing how providers assigned ASA PS values. ⋯ The transition from paper to electronic AIMS resulted in an unintended but significant shift in recorded ASA PS scores. Subsequent design changes within the AIMS resulted in resetting of the ASA PS distributions to previous values. These observations highlight the importance of how user interface and cognitive demands introduced by a computational system can impact the recording of important clinical data in the medical record.
-
Bmc Med Inform Decis · Feb 2016
Evaluation of the effects of implementing an electronic early warning score system: protocol for a stepped wedge study.
An Early Warning Score is a clinical risk score based upon vital signs intended to aid recognition of patients in need of urgent medical attention. The use of an escalation of care policy based upon an Early Warning Score is mandated as the standard of practice in British hospitals. Electronic systems for recording vital sign observations and Early Warning Score calculation offer theoretical benefits over paper-based systems. However, the evidence for their clinical benefit is limited. Previous studies have shown inconsistent results. The majority have employed a "before and after" study design, which may be strongly confounded by simultaneously occurring events. This study aims to examine how the implementation of an electronic early warning score system, System for Notification and Documentation (SEND), affects the recognition of clinical deterioration occurring in hospitalised adult patients. ⋯ The development of this protocol has been informed by guidance from the Agency for Healthcare Research and Quality (AHRQ) Health Information Technology Evaluation Toolkit and Delone and McLeans's Model of Information System Success. Our chosen trial design, a stepped wedge study, is well suited to the study of a phased roll out. The choice of primary endpoint is challenging. We have selected the time from the first triggering observation set to the subsequent observation set. This has the benefit of being easy to measure on both paper and electronic charting and having a straightforward interpretation. We have collected qualitative measures of system quality via a user questionnaire and organisational descriptors to help readers understand the context in which SEND has been implemented.
-
Bmc Med Inform Decis · Jan 2016
Capturing judgement strategies in risk assessments with improved quality of clinical information: How nurses' strategies differ from the ecological model.
Nurses' risk assessments of patients at risk of deterioration are sometimes suboptimal. Advances in clinical simulation mean higher quality information can be used as an alternative to traditional paper-based approaches as a means of improving judgement. This paper tests the hypothesis that nurses' judgement strategies and policies change as the quality of information used by nurses in simulation changes. ⋯ Improving the quality of information by clinical simulations significantly impacted on nurses' judgement policies of risk assessments. Nurses' judgement strategies also varied with the increased years of experience. Such variations in processing clinical information may contribute to nurses' suboptimal judgements in clinical practice. Constructing predictive models of common judgement situations, and increasing nurses' awareness of information weightings in such models may help improve judgements made by nurses.