Do we realize when we do not know? Recognizing uncertainty in clinical medicine

Parent-driven technology for decision support in pediatric emergency care

BACKGROUND

A quasi-experimental intervention study composed of control and intervention periods was conducted to determine if a parent-driven health information technology influenced completeness of documentation and adherence to evidence-based emergency care for children.

METHODS

Structured chart abstraction was used to assess documentation and correctness of clinical actions at test ordering, medication prescribed for disease, and medication ordered for pain in a tertiary care pediatric emergency department and a suburban general emergency department. During the intervention periods, parents of children who presented with complaints related to otitis media, urinary tract infection, head trauma, or asthma entered data into a health information technology (ParentLink), which produced treatment plans in the context of evidence-based guidelines.

RESULTS

Of 1,410 subjects analyzed, 1,072 (76%) were assigned to one of four disease categories: urinary tract infection (22%), otitis media (20%), asthma (11%) and head trauma (47%). During ParentLink use, documentation of pain significantly improved (28% incomplete [control] versus 15% [intervention], p = .003). Incorrect actions for pain treatment decreased, but not significantly (33% [control] versus 24% [intervention], p = .13). ParentLink did not influence actions for test ordering or prescribing for disease.

DISCUSSION

Parent-driven health information technology intended to translate parents' knowledge into clinical practice and to support evidence-based care suggested a trend toward modest impact on pain management but did not demonstrate broad effects across diseases or care processes. The emergence and proliferation of personally controlled health records (PCHRs) presents opportunities for patients and parents to control their medical profiles. Although ParentLink is not a comprehensive PCHR, it represents a step in incorporating parent-derived information into medical decision making.

The median frequency of the ECG during ventricular fibrillation: its use in an algorithm for estimating the duration of cardiac arrest

Recent studies have suggested that the initial therapeutic intervention for ventricular fibrillation (VF) may depend on downtime (DT), i.e., the time duration of VF. We characterized the dynamics of the frequency distribution in the power spectrum of the ECG recorded from eleven swine during VF to determine if enough information existed in this domain to estimate DT. We used the median frequency (FM) of the power spectrum to track the frequency distribution. The FM followed a dynamic repeatable course during the first 10 min of VF. Intersubject variability was small. We modeled the FM data of the eleven subjects with a set of first-order polynomial equations and tested the algorithm with data from an additional ten subjects. The algorithm predicted VF duration with an average error of -0.86 min; 71.5% of the predictions fell within the 95% confidence limits of the model. This paper has identified a signal processing tool which may be useful in the prehospital treatment of VF.

Estimating the duration of ventricular fibrillation

As the duration of time between the onset of ventricular fibrillation and the application of defibrillation (downtime) increases, the rate of successful resuscitation decreases. Results of recent animal studies suggest that the rate of successful resuscitation may be increased after a prolonged cardiorespiratory arrest when pharmacologic therapy is instituted before defibrillation. An accurate estimation of downtime could be critical in selecting the most appropriate therapeutic intervention. The purpose of our study was to determine whether changes in the frequency or amplitude of the ventricular fibrillation ECG signal during cardiac arrest could be used to estimate downtime. We characterized the dynamics of both total power and frequency distribution of the power in the ECG during ventricular fibrillation in 11 swine to determine whether enough information existed in either parameter to estimate downtime. The median frequency of the power spectrum was used to track power distribution. Both parameters followed a dynamic, repeatable pattern. However, median frequency showed less intersubject variability than did total power. A mathematical model of median frequency was developed and used with data obtained from ten additional swine to estimate downtime. The model estimated downtime to within 1.3 minutes of actual downtime between one and ten minutes of ventricular fibrillation. Our study has identified a new, potentially useful parameter for studying various management strategies in ventricular fibrillation as a function of downtime.