RESUMEN
Objectives: Pharmacists in over half of the United States can prescribe contraceptives; however, low pharmacist adoption has impeded the full realization of potential public health benefits. Many barriers to adoption may be addressed by leveraging an electronic health records (EHR) system with clinical decision support tools and workflow automation. We conducted a feasibility study to determine if utilizing a contraceptive-specific EHR could improve potential barriers to the implementation of pharmacist-prescribed contraceptive services. Materials and Methods: 20 pharmacists each performed two standardized patient encounter simulations: one on the EHR and one on the current standard of care paper-based workflow. A crossover study design was utilized, with each pharmacist performing encounters on both standardized patients with the modality order randomized. Encounters were timed, contraceptive outputs were recorded, and the pharmacists completed externally validated workload and usability surveys after each encounter, and a Perception, Attitude, and Satisfaction survey created by the research team after the final encounter. Results: Pharmacists were more likely to identify contraceptive ineligibility using the EHR-based workflow compared to the paper workflow (P = .003). Contraceptive encounter time was not significantly different between the 2 modalities (P = .280). Pharmacists reported lower mental demand (P = .003) and greater perceived usefulness (P = .029) with the EHR-based workflow compared to the paper modality. Discussion and Conclusion: Pharmacist performance and acceptance of contraceptive services delivery were improved with the EHR workflow. Pharmacist-specific contraceptive EHR workflows show potential to improve pharmacist adoption and provision of appropriate contraceptive care.
RESUMEN
Cardiac arrest victims who present with pulseless electrical activity (PEA) usually have a grave prognosis. Several conditions, however, have cause-specific treatments which, if applied immediately, can lead to quick and sustained recovery. Current teaching focuses on recollection of numerous conditions that start with the letters H or T as potential causes of PEA. This teaching method is too complex, difficult to recall during resuscitation, and does not provide guidance to the most effective initial interventions. This review proposes a structured algorithm that is based on the differentiation of the PEA rhythm into narrow- or wide-complex subcategories, which simplifies the working differential and initial treatment approach. This, in conjunction with bedside ultrasound, can quickly point towards the most likely cause of PEA and thus guide resuscitation.