Smart Pump Station for Cross Country Pipelines

Cross-country pipelines are the safest mode of transportation for petroleum products. A typical hydrocarbon multi-product cross-country pipeline network consists of Dispatch station, cross-country Pipeline, Intermediate Pump Stations, Sectionalizing Valve Stations, intermediate pigging stations and Receipt Stations. Dispatch station, Intermediate Pump Stations and Receipt stations are manned stations to meet the operational and maintenance requirements in the pipeline network. Since pipelines operate round the clock, operations work force are required on 24 × 7 basis at these control rooms. Typically, work force expenses account for more than 25% of total operating cost. Cross-country pipelines are often laid in areas away from Urban and Industrialized areas. Intermediate Booster stations are also mostly located in remote areas. The work force operating these stations have to stay in hardship locations to ensure pipeline operations are unhindered. In order to optimize the work force requirements at Intermediate Pump stations and to ensure seamless and safe operations, it is proposed to construct Smart pump stations. The smart pump stations are intelligent enough with state of the art instrumentation to be monitored / controlled / operated from a remote controlling station which is a non-hardship location. The smart pump stations are designed such that it will have self-sufficient systems which will require minimum human interface from remote controlling stations. HPCL has implemented the smart pump station design philosophy in its ongoing Vijayawada Dharmapuri Pipeline project wherein two Intermediate Pump (IP) stations viz. Donakonda & Kalakada are designed and are being constructed as smart pump stations which are being completely automated and will be remotely monitored / controlled from remote controlling stations at Vijayawada & Kadapa respectively. Design philosophy of Smart Stations entails developing a completely new and a tailor made design philosophy for Process, mechanical, Electrical, Instrumentation, cathodic protection system, SCADA, Telecom & allied systems, fire & safety and accordingly getting all the equipment selected / manufactured / installed / commissioned.

Impact of smart pump-electronic health record interoperability on patient safety and finances at a community hospital

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 Integrating smart pumps with an electronic health record (EHR) reduces medication errors by automating pump programming and EHR documentation. This study describes the patient safety and financial impact of pump-EHR interoperability at a community hospital. Methods A 316-bed community hospital in Sugar Land, TX, went live with pump-EHR interoperability in October 2019. Data were collected from April 1, 2019, to June 30, 2019 (before implementation) and from April 1, 2020, to June 30, 2020 (after implementation). Rates of drug library compliance, alert firing, alert override, override within 2 seconds, high-risk alert override, and alert resulting in pump reprogramming were measured. Financial impact was measured by Current Procedural Terminology code capture per kept appointment in the infusion center. Results Drug library compliance increased from 73.8% to 82.9% with pump-EHR interoperability (P < 0.001). Infusions generating alerts among all infusions programmed with the drug library decreased from 3.5% to 2.6% (P < 0.001), overridden alerts increased from 64.8% to 68.9% (P < 0.001), alerts overridden within 2 seconds decreased from 17.3% to 13.8% (P < 0.001), and reprogrammed alerts decreased from 20.7% to 18.3% (P = 0.002). Conclusion Pump-EHR interoperability leads to safer administration of intravenous medications based on improved drug library compliance and more accurate smart pump programming.

Nurse and Pharmacist Knowledge of Intravenous Smart Pump System Setup Requirements

Objective: The primary purpose of this research was to describe nurse and pharmacist knowledge of setup requirements for intravenous (IV) smart pumps that require head height differentials for accurate fluid flow. Methods: A secondary analysis of anonymous electronic survey data using a database of prerecruited clinicians was conducted. A survey was sent by email to 173 pharmacists and 960 nurses. The response rate for pharmacists was 58% (100 of 173), and the response rate for nurses was 52% (500 of 960). After removing respondents who did not provide direct care and who did not use a head height differential IV infusion system, the final sample for analysis was 186 nurses and 25 pharmacists. Results: Overall, less than one-half of respondents (40%) were aware that manufacturer guidelines for positioning the primary infusion bag relative to the infusion pump were available. Slightly more (49.5%) were aware of the required head height differentials for secondary infusion. Only five respondents selected the correct primary head height, eight respondents selected the correct secondary head height, and one respondent selected both the correct primary and secondary head heights. Conclusion: The results of this study identify a substantial lack of knowledge among frontline clinicians regarding manufacturer recommendations for accurate IV administration of primary and secondary infusions for head height differential infusion systems. Both increased clinician education and innovative technology solutions are needed to improve IV smart pump safety and usability.

Integrating and Evaluating the Data Quality and Utility of Smart Pump Information in Detecting Medication Administration Errors: Evaluation Study

Background At present, electronic health records (EHRs) are the central focus of clinical informatics given their role as the primary source of clinical data. Despite their granularity, the EHR data heavily rely on manual input and are prone to human errors. Many other sources of data exist in the clinical setting, including digital medical devices such as smart infusion pumps. When incorporated with prescribing data from EHRs, smart pump records (SPRs) are capable of shedding light on actions that take place during the medication use process. However, harmoniz-ing the 2 sources is hindered by multiple technical challenges, and the data quality and utility of SPRs have not been fully realized. Objective This study aims to evaluate the quality and utility of SPRs incorporated with EHR data in detecting medication administration errors. Our overarching hypothesis is that SPRs would contribute unique information in the med-ication use process, enabling more comprehensive detection of discrepancies and potential errors in medication administration. Methods We evaluated the medication use process of 9 high-risk medications for patients admitted to the neonatal inten-sive care unit during a 1-year period. An automated algorithm was developed to align SPRs with their medica-tion orders in the EHRs using patient ID, medication name, and timestamp. The aligned data were manually re-viewed by a clinical research coordinator and 2 pediatric physicians to identify discrepancies in medication ad-ministration. The data quality of SPRs was assessed with the proportion of information that was linked to valid EHR orders. To evaluate their utility, we compared the frequency and severity of discrepancies captured by the SPR and EHR data, respectively. A novel concordance assessment was also developed to understand the detec-tion power and capabilities of SPR and EHR data. Results Approximately 70% of the SPRs contained valid patient IDs and medication names, making them feasible for data integration. After combining the 2 sources, the investigative team reviewed 2307 medication orders with 10,575 medication administration records (MARs) and 23,397 SPRs. A total of 321 MAR and 682 SPR dis-crepancies were identified, with vasopressors showing the highest discrepancy rates, followed by narcotics and total parenteral nutrition. Compared with EHR MARs, substantial dosing discrepancies were more commonly detectable using the SPRs. The concordance analysis showed little overlap between MAR and SPR discrepan-cies, with most discrepancies captured by the SPR data. Conclusions We integrated smart infusion pump information with EHR data to analyze the most error-prone phases of the medication lifecycle. The findings suggested that SPRs could be a more reliable data source for medication error detection. Ultimately, it is imperative to integrate SPR information with EHR data to fully detect and mitigate medication administration errors in the clinical setting.

P19 Direct observational study of infusion errors associated with smart-pump technology in paediatric intensive care

AimsProcesses for delivery of high-risk infusions in paediatric intensive care units (PICUs) are complex. Standard concentration infusions (SCIs), smart-pumps and electronic prescribing are recommended medication error reduction strategies.1 2 Implementation rates are low in Irish and UK hospitals.2 3 Since 2012, the PICU of an Irish tertiary paediatric hospital has been using a smart-pump SCI library, interfaced with electronic infusion orders (Philips ICCA®). The incidence of infusion errors is unknown. This study aims to determine the frequency, severity and distribution of smart-pump infusion errors and to identify contributory factors to the occurrence of infusion errors.MethodsProgrammed infusions are directly observed at the bedside. Parameters are compared against medication orders and auto-populated infusion data. Identified deviations are categorised as either medication errors or discrepancies. Five opportunities for error (OEs) were identified: programming, administration, documentation, assignment, data transfer. Error rates (%) are calculated as: infusions with errors; and errors per OE. Pre-defined definitions, multi-disciplinary consensus and grading processes are employed.ResultsA total of 1023 infusions for 175 patients were directly observed on 27 days between February and September 2017. 74% of patients were under 1 year, 32% under 1 month. The drug-library accommodated 96.5% of all infusions. Compliance with the drug-library was 98.9%. 55 infusions had ≥ 1 error (5.4%); a further 67 (6.3%) had ≥ 1 discrepancy. From a total of 4997 OEs, 72 errors (1.4%) and 107 discrepancies (2.1%) were observed. Documentation errors were most common; programming errors were rare (0.32% OE). Errors are minor, with just one requiring minimal intervention to prevent harm.ConclusionThis study has highlighted the benefits of smart-pumps and auto-populated infusion data in the PICU setting. Identified error rates are low compared to similar studies.4 The findings will contribute to the limited existing knowledge base on impact of these interventions on paediatric infusion administration errors.ReferencesInstitute for Safe Medication Practices, ISMP. 2018–2019 Targeted medication safety best practices for hospitals2018 [Available from: http://www.ismp.org/tools/bestpractices/TMSBP-for-Hospitalsv2.pdf [Accessed: June 2019]Oskarsdottir T, Harris D, Sutherland A, et al. A national scoping survey of standard infusions in paediatric and neonatal intensive care units in the United Kingdom. J Pharm Pharmacol 2018;70:1324–1331.Howlett M, Curtin M, Doherty D, Gleeson P, Sheerin M, Breatnach C. Paediatric standardised concentration infusions – A national solution. Arch Dis Child. 2016;101:e2.Blandford A, Dykes PC, Franklin BD, et al. Intravenous Infusion Administration: A comparative study of practices and errors between the United States and England and their Implications for patient safety. Drug Saf. 2019;42:1157–1165