Disclaimer In an effort to expedite the publication of articles, AJHP is posting manuscripts online as soon as possible after acceptance. Accepted manuscripts have been peer-reviewed and copyedited, but are posted online before technical formatting and author proofing. These manuscripts are not the final version of record and will be replaced with the final article (formatted per AJHP style and proofed by the authors) at a later time. Purpose The purpose of this study was to describe how the discharge medication cost inquiry (DMCI) consult order and workflow were created and used to communicate transition of care needs and medication access barriers before discharge. Summary Health-system pharmacists collaborated with the information technology department to develop the DMCI consult order and workflow. This institutional review board–approved retrospective case study evaluated use of the DMCI consult order throughout the health system. Outcomes that could not be retrieved electronically were collected for every third patient encounter using manual chart review. The DMCI consult order was used at each hospital in the health system. Physicians placed the most DMCI consult orders; however, pharmacists at the large academic tertiary hospital utilized the DMCI consult order the most. The DMCI consult order was sent most frequently for anticoagulants. Although most medications were covered by insurance, the tool and workflow identified barriers to medication access. Almost 90% of the patients with a DMCI consult order had at least one prescription generated on discharge. Conclusion The DMCI consult order is a novel electronic tool to aid in communicating discharge medication needs. When incorporated into care transition planning, the DMCI consult order and workflow provide a model to ensure patients have access to medications. It can also be used to document and evaluate the role of pharmacy in transitions of care in the health system.
Disclaimer In an effort to expedite the publication of articles, AJHP is posting manuscripts online as soon as possible after acceptance. Accepted manuscripts have been peer-reviewed and copyedited, but are posted online before technical formatting and author proofing. These manuscripts are not the final version of record and will be replaced with the final article (formatted per AJHP style and proofed by the authors) at a later time. Purpose Evidence-based guideline recommendations for vancomycin dosing recently shifted from a trough-based strategy to an area under the curve (AUC) approach. While several AUC dosing methods exist, the optimal approach has not been determined. Literature characterizing time requirements for various vancomycin dosing strategies remains limited. Methods A time and motion study was conducted to measure the time spent by clinical pharmacists dosing vancomycin using an AUC nomogram. Pharmacists who dosed and monitored vancomycin for adult patients on the general medical ward (GMW) or intensive care unit (ICU) of a large academic medical center consented to study participation. Vulnerable patients and vancomycin orders for surgical infection prophylaxis were excluded. The primary outcome was the median amount of time clinical pharmacists dedicated to vancomycin-related clinical activities during an 8-hour weekday shift. Secondary outcomes included the proportion of patients prescribed vancomycin at the beginning of each shift and factors contributing to greater than average time spent on vancomycin-related responsibilities. Results Seven clinical pharmacists collected data on 178 vancomycin orders. The estimated amount of time a clinical pharmacist spent on daily vancomycin responsibilities averaged 10.45 minutes (interquartile range [IQR], 6.94-15.8 minutes). The overall median time requirement per vancomycin assessment was 3.45 minutes (IQR, 1.95-6.7 minutes). The only factor independently associated with prolonged dosing time was follow-up dosing from a previous day. Conclusion The study elucidated time requirements associated with an AUC nomogram–based vancomycin dosing approach. This data could be used to compare time requirements associated with other existing vancomycin dosing strategies, which may help healthcare systems determine the optimal AUC dosing method for their specific practice model.
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