Implementation and evaluation of a sterile compounding robot in a satellite oncology pharmacy

Evaluation of Robotic Systems on Cytotoxic Drug Preparation: A Systematic Review and Meta-Analysis

Background and Objectives: With the increased prevalence of patients with cancer, the demand for preparing cytotoxic drugs was increased by health-system pharmacists. To reduce the workload and contamination of work areas in pharmacies, compounding robots preparing cytotoxic drugs have been introduced, and the use of the robots has been expanded in recent years. As reports on the comprehensive and quantitative evaluation of compounding robots remain lacking, a systematic review and meta-analysis were conducted to provide descriptive and quantitative evaluations of the accuracy of preparing injectable cytotoxic drugs. Materials and Methods: A systematic review and meta-analysis were conducted using published studies up to 2020. To identify eligible studies, PubMed, EMBASE, and Cochrane Library were used. All studies reporting the outcomes relevant to drug-compounding robots such as accuracy, safety, and drug contamination were included. Outcomes from included studies were descriptively summarized. Drug contamination by the robot was quantitatively analyzed using the odds ratio (OR) with a 95% confidence interval (CI). The risk of bias was assessed using the Risk of Bias Assessment tool for Non-randomized Studies (RoBANS). Results: A total of 14 compounding robot studies were eligible for review and 4 studies were included in the meta-analysis. Robotic compounding showed failure rates of 0.9–16.75%, while the accuracy range was set at 5%. Two studies reported that robotic compounding needed more time than manual compounding, two reported that robotic compounding needed less time, and one just reported preparation time without a control group. In a meta-analysis regarding the contamination of the compounding area, manual compounding was associated with lower contamination, although the result was not statistically significant (OR 4.251, 95% CI 0.439–51.772). For the contamination of infusion bags, the robot was associated with lower contamination (OR 0.176, 95% CI 0.084–0.365). Conclusions: Robotic compounding showed better accuracy than manual compounding and, without control groups, showed a high accuracy rate and also reduced the risk of drug contamination and compounding workload. The preparation time of the robot was not consistent because the type of robot and introduced system were different. In conclusion, robotic compounding showed mixed results compared to the manual compounding of drugs, so the system should be introduced considering the risks and benefits of robots.

Optimizing Hospital Electronic Prescribing Systems: A Systematic Scoping Review

OBJECTIVE

Considerable international investment in hospital electronic prescribing (ePrescribing) systems has been made, but despite this, it is proving difficult for most organizations to realize safety, quality, and efficiency gains in prescribing. The objective of this work was to develop policy-relevant insights into the optimization of hospital ePrescribing systems to maximize the benefits and minimize the risks of these expensive digital health infrastructures.

METHODS

We undertook a systematic scoping review of the literature by searching MEDLINE, Embase, and CINAHL databases. We searched for primary studies reporting on ePrescribing optimization strategies and independently screened and abstracted data until saturation was achieved. Findings were theoretically and thematically synthesized taking a medicine life-cycle perspective, incorporating consultative phases with domain experts.

RESULTS

We identified 23,609 potentially eligible studies from which 1367 satisfied our inclusion criteria. Thematic synthesis was conducted on a data set of 76 studies, of which 48 were based in the United States. Key approaches to optimization included the following: stakeholder engagement, system or process redesign, technological innovations, and education and training packages. Single-component interventions (n = 26) described technological optimization strategies focusing on a single, specific step in the prescribing process. Multicomponent interventions (n = 50) used a combination of optimization strategies, typically targeting multiple steps in the medicines management process.

DISCUSSION

We identified numerous optimization strategies for enhancing the performance of ePrescribing systems. Key considerations for ePrescribing optimization include meaningful stakeholder engagement to reconceptualize the service delivery model and implementing technological innovations with supporting training packages to simultaneously impact on different facets of the medicines management process.

Use and impact of technology-assisted workflow (TAWF) systems for drug compounding in pharmacy practice: a scoping literature review

Objectives

The aim of this study was to review studies describing the use and the impact of technology-assisted workflow (TAWF) systems for drug compounding in hospital pharmacy.

Content

This is a scoping literature review. A search was conducted on studies describing or evaluating the use of TAWF published from January 1st, 2015 to July 31st, 2021. Two databases were searched (PubMed and Embase), followed by a search on Google Scholar.

Summary

218 articles were screened and 17 were identified as meeting the inclusion criteria. TAWFs all included preparation assistance software (17/17), barcode reader (17/17), photo or video taking (17/17), and some included gravimetric systems (8/17), and the use of robots (2/17). A majority of the studies included used technology for parenteral preparations (15/17, one for oral preparations only (1/17), and one used technology for both types of preparations (1/17). Most of the articles selected presented drugs prepared for adults (10/17), the others presented drugs intended for children (4/17) or for a mix of adults and children (3/17). Four parameters were evaluated: error detection rate (n=15), preparation and validation time (n=7), and costs generated or saved (n=7). Ten studies evaluated the pre-post impact of implantation of a TAWF (10/17).

Outlook

Given the heterogeneity of the data available, the use of TAWF was associated with an increased ability to detect preparation errors, a reduction in preparation time and costs, and increased satisfaction of pharmacy technicians and pharmacists. However, better quality studies are needed to confirm the positive impacts studied.

Evaluation of external contamination on the vial surfaces of some hazardous drugs that commonly used in Chinese hospitals and comparison between environmental contamination generated during robotic compounding by IV: Dispensing robot vs. manual compounding in biological safety cabinet

Objectives

The aims of the study were to evaluate the external contamination of hazardous drug vials used in Chinese hospitals and to compare environmental contamination generated by a robotic intelligent dispensing system (WEINAS) and a manual compounding procedure using a biological safety cabinet (BSC).

Methods

Cyclophosphamide, fluorouracil, and gemcitabine were selected as the representative hazardous drugs to monitor surface contamination of vials. In the comparative analysis of environmental contamination from manual and robotic compounding, wipe samples were taken from infusion bags, gloves, and the different locations of the BSC and the WEINAS robotic system. In this study, high-performance liquid chromatography coupled with double mass spectrometer (HPLC-MS/MS) was employed for sample analysis.

Results

(1) External contamination was measured on vials of all three hazardous drugs. The contamination detected on fluorouracil vials was the highest with an average amount up to 904.33 ng/vial, followed by cyclophosphamide (43.51 ng/vial), and gemcitabine (unprotected vials of 5.92 ng/vial, protected vials of 0.66 ng/vial); (2) overall, the environmental contamination induced by WEINAS robotic compounding was significantly reduced compared to that by manual compounding inside the BSC. Particularly, compared with manual compounding, the surface contamination on the infusion bags during robotic compounding was nearly nine times lower for cyclophosphamide (10.62 ng/cm² vs 90.43 ng/cm²), two times lower for fluorouracil (3.47 vs 7.52 ng/cm²), and more than 23 times lower for gemcitabine (2.61 ng/cm² vs 62.28 ng/cm²).

Conclusions

The external contamination occurred extensively on some hazardous drug vials that commonly used in Chinese hospitals. Comparison analysis for both compounding procedures revealed that robotic compounding can remarkably reduce environmental contamination.

Robotic chemotherapy compounding: A multicenter productivity approach

INTRODUCTION

The aim of this study is to compare productivity of the KIRO Oncology compounding robot in three hospital pharmacy departments and identify the key factors to predict and optimize automatic compounding time.

METHODS

The study was conducted in three hospitals. Each hospital compounding workload and workflow were analyzed. Data from the robotic compounding cycles from August 2017 to July 2018 were retrospectively obtained. Nine cycle specific parameters and five productivity indicators were analysed in each site. One-to-one differences between hospitals were evaluated. Next, a correlation analysis between cycle specific factors and productivity indicators was conducted; the factors presenting a highest correlation to automatic compounding time were used to develop a multiple regression model (afterwards validated) to predict the automatic compounding time.

RESULTS

A total of 2795 cycles (16367 preparations) were analysed. Automatic compounding time showed a relevant positive correlation (ǀr_s|>0.40) with the number of preparations, number of vials and total volume per cycle. Therefore, these cycle specific parameters were chosen as independent variables for the mathematical model. Considering cycles lasting 40 minutes or less, predictability of the model was high for all three hospitals (R²:0.81; 0.79; 0.72).

CONCLUSION

Workflow differences have a remarkable incidence in the global productivity of the automated process. Total volume dosed for all preparations in a cycle is one of the variables with greater influence in automatic compounding time. Algorithms to predict automatic compounding time can be useful to help users in order to plan the cycles launched in KIRO Oncology.

Comparison of IV oncology infusions compounded via robotics and gravimetrics-assisted workflow processes

Disclaimer

In an effort to expedite the publication of articles related to the COVID-19 pandemic, AJHP is posting these 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

A study was conducted to compare an intravenous (IV) gravimetric technology–assisted workflow (TAWF) platform to an IV robotic system. In the study we reviewed both IV technology platforms using the same gravimetric quality assurance system, which allowed for direct comparison.

Methods

All oncology preparations compounded from January 2016 through December 2018 using either system were included in our retrospective analysis. Final preparation accuracy, IV system precision, and workflow throughput (analyzed using lean process methodologies) were evaluated.

Results

Data analysis indicated that use of the IV gravimetric TAWF system was associated with a significantly lower percentage of accuracy errors compared to the IV robotics system (1.58% vs 2.47%, P < 0.001), with no significant difference in absolute precision (1.12 vs 1.12 P = 0.952). Lean analysis demonstrated that overall completion time (17:49 minutes vs 24:45 minutes) and compound preparation time (2:39 minutes vs 6:07 minutes) were less with the IV gravimetric TAWF vs the IV robotics system.

Conclusion

Implementation of either an IV gravimetric TAWF system or IV robotics system will result in similar compounding accuracy and precision. Preparation time was less with use of the IV gravimetric TAWF vs the IV robotic system, but the IV robotic system required less human intervention. Both systems ensure medication safety for patients, although the IV robotic system has increased safeguards in place. Therefore, the primary driver for implementing these systems is alternative factors such as cost of systems implementation and maintenance, employee safety, and drug waste.

Automated compounding technology and workflow solutions for the preparation of chemotherapy: a systematic review

OBJECTIVES

The current systematic review (SR) was undertaken to summarise the published literature reporting the clinical and economic value of automation for chemotherapy preparation management to include compounding workflow software and robotic compounding systems.

METHODS

Literature searches were conducted in MEDLINE, Embase and the Cochrane Library on 16 November 2017 to identify publications investigating chemotherapy compounding workflow software solutions used in a hospital pharmacy for the preparation of chemotherapy.

RESULTS

5175 publications were screened by title and abstract and 18 of 72 full publications screened were included. Grey literature searching identified an additional seven publications. The SR identified 25 publications relating to commercial technologies for compounding (Robotic compounding systems: APOTECAchemo (n=12), CytoCare (n=5) and RIVA (n=1); Workflow software: Cato (n=6) and Diana (n=1)). The studies demonstrate that compounding technologies improved accuracy in dose preparations and reduced dose errors compared with manual compounding. Comparable levels of contamination were reported for technologies compared with manual compounding. The compounding technologies were associated with reductions in annual costs compared with manual compounding, but the impact on compounding times was not consistent and was dependent on the type of compounding technology.

CONCLUSIONS

The published evidence suggests that the implementation of chemotherapy compounding automation solutions may reduce compounding errors and reduce costs; however, this is highly variable depending on the form of automation. In addition, the available evidence is heterogeneous, sparse and inconsistently reported. A key finding from the current SR is a 'call to action' to encourage pharmacists to publish data following implementation of chemotherapy compounding technologies in their hospital, which would allow for evidence-based recommendations on the benefits of chemotherapy compounding technologies.