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Background Several classification systems for medication errors (MEs) have been established over time, but none of them apply optimally for classifying severe MEs. In severe MEs, recognizing the causes of the error is essential for error prevention and risk management. Therefore, this study focuses on exploring the applicability of a cause-based DRP classification system for classifying severe MEs and their causes. Methods This was a retrospective document analysis study on medication-related complaints and authoritative statements investigated by the Finnish National Supervisory Authority for Welfare and Health (Valvira) in 2013–2017. The data was classified by applying a previously developed aggregated DRP classification system by Basger et al. Error setting and harm to the patient were identified using qualitative content analysis to describe the characteristics of the MEs in the data. The systems approach to human error, error prevention, and risk management was used as a theoretical framework. Results Fifty-eight of the complaints and authoritative statements concerned MEs, which had occurred in a wide range of social and healthcare settings. More than half of the ME cases (52%, n  = 30) had caused the patient’s death or severe harm. In total, 100 MEs were identified from the ME case reports. In 53% ( n  = 31) of the cases, more than one ME was identified, and the mean number of MEs identified was 1.7 per case. It was possible to classify all MEs according to aggregated DRP system, and only a small proportion (8%, n  = 8) were classified in the category “Other,” indicating that the cause of the ME could not be classified to specific cause-based category. MEs in the “Other” category included dispensing errors, documenting errors, prescribing error, and a near miss. Conclusions Our study provides promising preliminary results for using DRP classification system for classifying and analyzing especially severe MEs. With Basger et al.’s aggregated DRP classification system, we were able to categorize both the ME and its cause. More research is encouraged with other ME incident data from different reporting systems to confirm our results.

Background Paediatric patients are prone to medication errors, and only a few studies have explored errors in high-alert medications in children. The present study aimed to investigate the prevalence and nature of medication errors involving high-alert medications and whether high-alert medications are more likely associated with severe patient harm and higher error risk classification compared to other drugs. Methods This study was a cross-sectional report of self-reported medication errors in a paediatric university hospital in 2018–2020. Medication error reports involving high-alert medications were investigated by descriptive quantitative analysis to identify the prevalence of different drugs, Anatomical Therapeutic Chemical groups, administration routes, and the most severe medication errors. Crosstabulation and Pearson Chi-Square (χ2) tests were used to compare the likelihood of more severe consequences to the patient and higher error risk classification between medication errors involving high-alert medications and other drugs. Results Among the reported errors ( n  = 2,132), approximately one-third (34.8%, n  = 743) involved high-alert medications ( n  = 872). The most common Anatomical Therapeutic Chemical subgroups were blood substitutes and perfusion solutions (B05; n  = 345/872, 40%), antineoplastic agents (L01; n  = 139/872, 16%), and analgesics (N02; n  = 98/872, 11%). The majority of high-alert medications were administered intravenously ( n  = 636/872, 73%). Moreover, IV preparations were administered via off-label routes ( n  = 52/872, 6%), such as oral, inhalation and intranasal routes. Any degree of harm (minor, moderate or severe) to the patient and the highest risk classifications (IV-V) were more likely to be associated with medication errors involving high-alert medications ( n  = 743) when compared to reports involving other drugs ( n  = 1,389). Conclusions Preventive risk management should be targeted on high-alert medications in paediatric hospital settings. In these actions, the use of intravenous drugs, such as parenteral nutrition, concentrated electrolytes, analgesics and antineoplastic agents, and off-label use of medications should be prioritised. Further research on the root causes of medication errors involving high-alert medications and the effectiveness of safeguards is warranted.

Background Prescribing is a high-risk task within the pediatric medication-use process and requires defenses to prevent errors. Such system-centric defenses include electronic health record systems with computerized physician order entry (CPOE) and clinical decision support (CDS) tools that assist safe prescribing. The objective of this study was to examine the effects of CPOE systems with CDS functions in preventing dose errors in pediatric medication orders. Material and Methods This study followed the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) 2020 criteria and Synthesis Without Meta-Analysis (SWiM) items. The study protocol was registered in PROSPERO (CRD42021277413). The final literature search on MEDLINE (Ovid), Scopus, Web of Science, and EMB Reviews was conducted on 10 September 2023. Only peer-reviewed studies considering both CPOE and CDS systems in pediatric inpatient or outpatient settings were included. Study selection, data extraction, and evidence quality assessment (JBI critical appraisal tool assessment and GRADE approach) were carried out by two individual reviewers. Vote counting method was used to evaluate the effects of CPOE–CDS systems on dose errors rates. Results A total of 17 studies published in 2007–2021 met the inclusion criteria. The most used CDS tools were dose range check ( n = 14), dose calculator ( n = 8), and dosing frequency check ( n = 8). Alerts were recorded in 15 studies. A statistically significant reduction in dose errors was found in eight studies, whereas an increase of dose errors was not reported. Conclusions The CPOE–CDS systems have the potential to reduce pediatric dose errors. Most beneficial interventions seem to be system customization, implementing CDS alerts, and the use of dose range check. While human factors are still present within the medication use process, further studies and development activities are needed to optimize the usability of CPOE–CDS systems.

ObjectivesTo systematically review automated and semi-automated drug distribution systems (DDSs) in hospitals and to evaluate their effectiveness on medication safety, time and costs of medication care.MethodsA systematic literature search was conducted in MEDLINE Ovid, Scopus, CINAHL and EMB Reviews covering the period 2005 to May 2016. Studies were included if they (1) concerned technologies used in the drug distribution and administration process in acute care hospitals and (2) reported medication safety, time and cost-related outcomes.ResultsKey outcomes, conclusions and recommendations of the included studies (n=30) were categorised according to the dispensing method: decentralised (n=19 studies), centralised (n=6) or hybrid system (n=5). Patient safety improved (n=27) with automation, and reduction in medication errors was found in all three systems. Centralised and decentralised systems were reported to support clinical pharmacy practice in hospitals. The impact of the medication distribution system on time allocation such as labour time, staffing workload or changes in work process was explored in the majority of studies (n=24). Six studies explored economic outcomes.ConclusionsNo medication distribution system was found to be better than another in terms of outcomes assessed in the studies included in the systematic review. All DDSs improved medication safety and quality of care, mainly by decreasing medication errors. However, many error types still remained—for example, prescribing errors. Centralised and hybrid systems saved more time than a decentralised system. Costs of medication care were reduced in decentralised systems mainly in high-expense units. However, no evidence was shown that implementation of decentralised systems in small units would save costs. More comparable evidence on the benefits and costs of decentralised and hybrid systems should be available. Changes in processes due to a new DDS may create new medication safety risks; to minimise these risks, training and reallocation of staff resources are needed.

BackgroundPaediatric patients are prone to medication errors, but an in-depth understanding of errors involving high-alert medications remains limited.ObjectiveWe aimed to investigate incident reports involving high-alert medications to describe medication errors, error chains and stages of the medication management and use process where the errors occur in paediatric hospitals.MethodsA retrospective document analysis of self-reported medication safety incidents in a paediatric university hospital in 2018–20. The incident reports involving high-alert medications were investigated using an inductive qualitative content analysis and quantified (frequencies and percentages). A systems approach to medication risk management based on the Theory of Human Error was applied.ResultsAltogether, 560 medication errors were identified within the study sample (n = 426 incident reports). Most medication errors were associated with administration (43.1 %, n = 241/560) and prescribing (25.2 %, n = 141/560). Error chains involving two to four medication errors in one or more stages of the medication management and use process were present in 26.1% (n = 111/426) of reports, most of which originated from prescribing (62.2%; n = 69/111). The medication errors (n = 560) were classified into 14 main categories, the most common of which were wrong dose (13.9%; n = 78/560), omission of a drug (12.9%; n = 72/560) and documentation errors (10.0%; n = 56).ConclusionsPaediatric medication error chains often start from prescribing and pass through the medication management and use process. Systemic defences are especially needed for manual tasks leading to wrong doses, drug omission and documentation errors. Intravenous medications and chemotherapeutic agents, optimising drug formularies and handling, and high-alert drug use at home require further actions in paediatric medication risk management.

Background Automated dose dispensing (ADD) services have been implemented in many health care systems internationally. However, the ADD service itself is a logistic process that requires integration with medication risk management interventions to ensure safe and appropriate medication use. National policies and regulations guiding ADD in Finland have recommended medication reconciliation, review, and follow-up for suitable risk management interventions. This implementation study aimed to develop a medication management process integrating these recommended risk management interventions into a regular ADD service for older home care clients. Methods This study applied an action research method and was carried out in a home care setting, part of primary care in the City of Lahti, Finland. The systems-approach to risk management was applied as a theoretical framework. Results The outcome of the systems-based development process was a comprehensive medication management procedure. The medication risk management interventions of medication reconciliation, review and follow-up were integrated into the medication management process while implementing the ADD service. The tasks and responsibilities of each health care professional involved in the care team became more explicitly defined, and available resources were utilized more effectively. In particular, the hospital pharmacists became members of the care team where collaboration between physicians, pharmacists, and nurses shifted from parallel working towards close collaboration. More efforts are needed to integrate community pharmacists into the care team. Conclusion The transition to the ADD service allows implementation of the effective medication risk management interventions within regular home care practice. These systemic defenses should be considered when national ADD guidelines are implemented locally. The same applies to situations in which public home care organizations responsible for services e.g., municipalities, purchase ADD services from private service providers.

Background In rural areas, primary care faces several challenges, and medication therapy is one of the most complex processes in primary care. With a specific, proactive, medication-safety self-assessment tool designed for rural primary care units, healthcare professionals could identify development needs in their medication processes. Methods The Delphi consensus method with two Delphi rounds was used to create a medication-safety self-assessment tool for rural primary care units in Finnish Lapland. A preliminary tool was designed based on three national and international risk management tools. Statements of the preliminary tool were evaluated with a two-round Delphi panel by 12 experts in primary care and patient safety. Evaluated aspects were suitability for primary care settings, medication safety relevance, and the necessity of the statements to be included in the developed rural, primary care, medication-safety self-assessment tool. Results In the first Delphi round, a consensus of ≥ 85% on being “sufficiently important and essential” was reached on 39% of the statements ( n  = 118/304), of which 86% ( n  = 101/118) were included, and 14% ( n  = 17/118) were excluded from the final primary care medication- safety self-assessment tool. In the second round, 84% of the statements ( n  = 141/167) reached a consensus, of which 70% ( n  = 98/141) were excluded and 30% ( n  = 43/141) included in the final tool. The included 144 statements were divided into 12 thematic sub-groups: (1) Patient information, (2) Drug information, (3) Communication of drug orders and other drug information; (4) Drug labeling, packaging and nomenclature; (5) Drug storage and distribution, (6) Medication device acquisition and use, (7) Environmental factors, workflow and staffing patterns; (8) Staff competency and education, (9) Patient education, (10) Preventive risk management, 11. Learning from medication safety incidents, and 12. Electronic health record. Conclusions The developed medication-safety self-assessment tool is targeted for proactive medication risk management in rural primary care settings. While experts reached a consensus for the Primary care Medication Safety Self Assessment tool contents, adopting the tool to suit the rural primary care environments in different countries should be further investigated.

Background Community pharmacies are responsible for dispensing of medicines and related counselling in outpatient care. Dispensing practices have remarkably changed over time, but little is known about how the changes have influenced medication safety. This national study investigated trends in dispensing errors (DEs) related to prescribed medicines, which were reported in Finnish community pharmacies within a 6-year period. Methods This national retrospective register study included all DEs reported to a nationally coordinated voluntary DE reporting system by Finnish community pharmacies during 2015–2020. DE rates, DE types, prescription types, individuals who detected DEs and contributing factors to DEs were quantified as frequencies and percentages. Poisson regression was used to assess the statistical significance of the changes in annual DE rates by type. Results During the study period, altogether 19 550 DEs were reported, and the annual number of error reports showed a decreasing trend ( n  = 3 913 in 2015 vs. n  = 2 117 in 2020, RR 0.54, p  < 0.001). The greatest decrease in reported DEs occurred in 2019 after the national implementation of the Medicines Verification System (MVS) and the additional safety feature integrated into the MVS process. The most common error type was wrong dispensed strength (50% of all DEs), followed by wrong quantity or pack size (13%). The annual number of almost all DE types decreased, of which wrong strength errors decreased the most ( n  = 2121 in 2015 vs. n  = 926 in 2020). Throughout the study period, DEs were most commonly detected by patients (50% of all DEs) and pharmacy personnel (30%). The most reported contributing factors were factors related to employees (36% of all DEs), similar packaging (26%) and similar names (21%) of medicinal products. Conclusions An overall decreasing trend was identified in the reported DEs and almost all DE types. These changes seem to be associated with digitalisation and new technologies implemented in the dispensing process in Finnish community pharmacies, particularly, the implementation of the MVS and the safety feature integrated into the MVS process. The role of patients and pharmacy personnel in detecting DEs has remained central regardless of changes in dispensing practices.

ObjectivesThe evaluation and improvement of medication management processes is an essential part of preventive medication risk management strategies in hospitals. The aim of the present study was to identify and analyse risks of a new electronic medication management process and to suggest improvements to manage the identified risks in a secondary care hospital.MethodsThe electronic medication management process of four wards at the Lapland Central Hospital, Finland was evaluated by Healthcare Failure Mode and Effect Analysis (HFMEA). The multidisciplinary HFMEA team consisted of five experts who identified the failure modes and rated their hazard scores (scale of 1–16). In addition, the patient safety incident reports of the hospital were used for identification of failure modes. Safety recommendations were identified, prioritised and implemented with a follow-up evaluation.ResultsThe team identified five phases in the electronic medication management process. Altogether, 35 potential failure modes were found, with eight being classified as the most severe (hazard score >8). The given recommendations (n=15) concerned improvements to the electronic medical record (EMR) (n=8) and to the work processes of the wards (n=7). Only two of the recommendations were fully implemented, and five were under development or partly implemented after a 15-month follow-up period.ConclusionsFor identifying risks associated with electronic medication management and for compiling related safety recommendations, triangulation of different risk identification methodologies is recommended. When implementing electronic medication management, appropriate patient identification in medication administration should be ensured together with EMR development. Systematic efforts should be made for the effective implementation of the safety recommendations. Further research is warranted to explore barriers to implementing safety improvements, especially in small healthcare units in rural areas.

Background Antimicrobial use (AMU) in food-producing animals affects development of antimicrobial resistance. Previous studies have shown that AMU for pigs varies considerably between herds and countries. Finland has relatively low AMU in pigs, although pigs are the main species treated with antimicrobials. In Finland, the use of medicines for pigs is recorded in the national web-based herd health and welfare register Sikava. We aimed to qualitatively and quantitatively describe AMU in Finnish sows using anonymous herd health data and to identify indications for antimicrobial treatment, antimicrobial agents used for each indication, and farm-level risk factors associated with AMU. Forty-eight randomly selected herds with more than 100 sows were selected from the herd register of 905 herds. The register data included AMU in sows, biosecurity evaluations, welfare index calculated by the Sikava system, and scores given by veterinarians during veterinary health care visits in 2022. Visiting veterinarians collect information on housing and environmental conditions, animal health, and welfare using a standardized protocol and record their findings electronically in the herd health register. Farmers record AMU in sows electronically in the register. Data for this study included the product name, active substance, treatment indication, duration of therapy, number of sows treated, and dosage. AMU in sows was quantified at the herd level as milligrams of antimicrobials administered per population-corrected unit (mg/PCU). Additionally, potential farm-level risk factors were identified. Results The median total AMU for the sows was 21.9 mg/PCU (range: 0.3-178.5). The most used antimicrobial was penicillin, and sows were most commonly treated parenterally for locomotory (34% of the treatments), udder (20%), reproductive (12%), and skin (11%) disorders. AMU was higher in large herds than in smaller ones. Piglet producers used more antimicrobials than farrow-to-finish herds, and AMU increased with higher internal biosecurity scores. Conclusions AMU in Finnish sows varied widely between herds. Injectable penicillin was the most commonly used antimicrobial, and sows were most frequently treated for locomotory, udder, and reproductive disorders. Large herds, piglet producers, and herds with higher internal biosecurity scores had the highest AMU.