Discipline of Clinical Pharmacy, School of Pharmaceutical Sciences, Universiti Sains Malaysia, 11800, Gelugor, Penang, Malaysia.
Department of Clinical Pharmacy, Ibn Al Haytham Hospital, Amman, Hashemite Kingdom of Jordan.
BMC Health Serv Res. 2021 Sep 8;21(1):937. doi: 10.1186/s12913-021-06966-4.
Clinical pharmacy interventions (CPI) usually require prior medical authorization. Physicians approve 80% of CPI and reject 20%. If pharmacists show that physicians should authorize all 100% CPI, the profession will step closer to a fully independent prescriber status. This study used an artificial neural network (ANN) model to determine whether clinical pharmacy (CP) may improve outcomes associated with rejected CPI.
This is a non-interventional, retrospective analysis of documented CPI in a 100-bed, acute-care private hospital in Amman, Jordan. Study consisted of 542 patients, 574 admissions, and 1694 CPI. Team collected demographic and clinical data using a standardized tool. Input consisted of 54 variables with some taking merely repetitive values for each CPI in each patient whereas others varying with every CPI. Therefore, CPI was consolidated to one rejected and/or one accepted per patient per admission. Groups of accepted and rejected CPI were compared in terms of matched and unmatched variables. ANN were, subsequently, trained and internally as well as cross validated for outcomes of interest. Outcomes were length of hospital and intensive care stay after the index CPI (LOSTA & LOSICUA, respectively), readmissions, mortality, and cost of hospitalization. Best models were finally used to compare the two scenarios of approving 80% versus 100% of CPI. Variable impacts (VI) automatically generated by the ANN were compared to evaluate the effect of rejecting CPI. Main outcome measure was Lengths of hospital stay after the index CPI (LOSTA).
ANN configurations converged within 18 s and 300 trials. All models showed a significant reduction in LOSTA with 100% versus 80% accepted CPI of about 0.4 days (2.6 ± 3.4, median (range) of 2 (0-28) versus 3.0 ± 3.8, 2 (0-30), P-value = 0.022). Average savings with acceptance of those rejected CPI was 55 JD (~ 78 US dollars) and could help hire about 1.3 extra clinical pharmacist full-time equivalents.
Maximizing acceptance of CPI reduced the length of hospital stay in this model. Practicing Clinical Pharmacists may qualify for further privileges including promotion to a fully independent prescriber status.
临床药学干预（CPI）通常需要事先获得医疗授权。医生批准 80%的 CPI，拒绝 20%。如果药剂师证明医生应该批准所有 100%的 CPI，那么该专业将更接近完全独立的处方地位。本研究使用人工神经网络（ANN）模型来确定临床药学（CP）是否可以改善与拒绝的 CPI 相关的结果。
这是一项非干预性、回顾性分析，记录了约旦安曼一家 100 张床位的急性护理私立医院的 CPI。研究包括 542 名患者、574 次住院和 1694 次 CPI。团队使用标准化工具收集人口统计学和临床数据。输入包括 54 个变量，每个患者的每个 CPI 都有一些仅重复的值，而其他变量则随每个 CPI 而变化。因此，每个患者每次住院的 CPI 被合并为一个被拒绝和/或一个被接受。接受和拒绝的 CPI 组在匹配和不匹配的变量方面进行了比较。随后，对 ANN 进行了培训，并在内部以及交叉验证了感兴趣的结果。结果是接受和拒绝的 CPI 索引后的住院和重症监护时间（分别为 LOSTA 和 LOSICUA）、再入院、死亡率和住院费用。最后，使用最佳模型比较了批准 80%和 100%的 CPI 的两种情况。ANN 自动生成的变量影响（VI）用于评估拒绝 CPI 的效果。主要观察指标是接受和拒绝的 CPI 索引后的住院时间（LOSTA）。
ANN 配置在 18 秒和 300 次试验内收敛。所有模型都显示，接受 100%的 CPI 比接受 80%的 CPI 显著降低 LOSTA，约为 0.4 天（2.6±3.4，中位数（范围）为 2（0-28）与 3.0±3.8，2（0-30），P 值=0.022）。接受这些被拒绝的 CPI 的平均节省为 55 约旦第纳尔（约 78 美元），可以帮助雇用大约 1.3 名全职临床药剂师。
最大限度地接受 CPI 减少了该模型的住院时间。临床药师可能有资格获得进一步的特权，包括晋升为完全独立的处方地位。
