The effect of electronic prescribing on medication errors and adverse drug events: a systematic review

Strategies used to detect and mitigate system-related errors over time: A qualitative study in an Australian health district

BACKGROUND

Electronic medical record (EMR) systems provide timely access to clinical information and have been shown to improve medication safety. However, EMRs can also create opportunities for error, including system-related errors or errors that were unlikely or not possible with the use of paper medication charts. This study aimed to determine the detection and mitigation strategies adopted by a health district in Australia to target system-related errors and to explore stakeholder views on strategies needed to curb future system-related errors from emerging.

METHODS

A qualitative descriptive study design was used comprising semi-structured interviews. Data were collected from three hospitals within a health district in Sydney, Australia, between September 2020 and May 2021. Interviews were conducted with EMR users and other key stakeholders (e.g. clinical informatics team members). Participants were asked to reflect on how system-related errors changed over time, and to describe approaches taken by their organisation to detect and mitigate these errors. Thematic analysis was conducted iteratively using a general inductive approach, where codes were assigned as themes emerged from the data.

RESULTS

Interviews were conducted with 25 stakeholders. Participants reported that most system-related errors were detected by front-line clinicians. Following error detection, clinicians either reported system-related errors directly to the clinical informatics team or submitted reports to the incident information management system. System-related errors were also reported to be detected via reports run within the EMR, or during organisational processes such as incident investigations or system enhancement projects. EMR redesign was the main approach described by participants for mitigating system-related errors, however other strategies, like regular user education and minimising the use of hybrid systems, were also reported.

CONCLUSIONS

Initial detection of system-related errors relies heavily on front-line clinicians, however other organisational strategies that are proactive and layered can improve the systemic detection, investigation, and management of errors. Together with EMR design changes, complementary error mitigation strategies, including targeted staff education, can support safe EMR use and development.

Stakeholder perspectives on electronic prescribing in primary care: A scoping review

BACKGROUND

Electronic prescribing (e-prescribing) provides a convenient, efficient, paperless mechanism for the legal transfer of prescriptions between service users, prescribers, and dispensers. There have been advances in e-prescribing processes and increased uptake of e-prescribing globally, in recent years.

OBJECTIVE

To explore stakeholder perspectives on e-prescribing in primary care settings.

METHODS

A scoping review was conducted by systematically searching Medline, EMBASE, Scopus, and International Pharmaceutical Abstracts databases, using the key concepts "primary care", "e-prescribing", and "perspectives". Publications were selected by screening for eligibility against inclusion and exclusion criteria, whereby any publication written in English exploring e-prescribing in primary care settings from the perspective(s) of at least one type of stakeholder was eligible for inclusion. Following a systematic screening process, relevant data were extracted, collated, and synthesized.

RESULTS

Two thousand publications were identified and systematically screened, rendering 44 publications (e.g., primary research articles, abstracts) eligible for inclusion in this review. Most publications reported on studies conducted in the USA, the UK, and Europe and explored the views of pharmacists, pharmacy technicians, and pharmacy staff. Barriers to e-prescribing included system design and technical issues, lack of adequate training and communication issues between stakeholders. Enablers for e-prescribing included time savings, convenience, and increased legibility of prescriptions.

CONCLUSIONS

This review highlights many benefits of e-prescribing such as time efficiency, convenience, increased legibility, and less mishandling. Despite this, key barriers to e-prescribing within primary care settings were also recognized, including system design, technical issues, and lack of adequate training. As such, forcing functions, prescription tracking technologies, and better training have been identified as potential ways to address these barriers. While some negative experiences were reported, stakeholders were generally satisfied and had positive experiences with e-prescribing.

Secondary uses of electronic prescribing and pharmacy data in UK hospital care: a national survey

Electronic hospital pharmacy (EHP) systems are ubiquitous in today's hospitals, with many also implementing electronic prescribing (EP) systems; both contain a potential wealth of medication-related data to support quality improvement. The reasons for reuse and users of this data are generally unknown. Our objectives were to survey secondary use of data (SUD) from EHP and EP systems in UK hospitals, to identify users of and factors influencing SUD.A national postal survey was sent out to all hospital chief pharmacists with pre-notifications and follow-up reminders. Descriptive statistical analysis was performed.Of 187 hospital organisations, 65 (35%) responded. All had EHP systems (for ≥20 years) and all reused data; 50 (77%) had EP systems (established 1-10 years) but only 40 (80%) reused data. Reported facilitators for SUD included medication safety, providing feedback, benchmarking, saving time and patient experience. The purposes of SUD included audits, quality improvement, risk management and general medication-related reporting. Earlier introduction of SUD could provide an opportunity to heighten local improvement initiatives.Data from EHP systems is reused for multiple purposes. Evaluating SUD and sharing experiences could provide richer insight into potential SUD and barriers/factors to consider when implementing or upgrading EP/EHP systems.

A Dedicated Outpatient Pharmacy Improves Access to Discharge Medications in a Pediatric Emergency Department: A Quality Improvement Study

STUDY OBJECTIVE

Following discharge from a pediatric emergency department (ED) or urgent care, many families do not pick up their prescribed medications. The aim of this quality improvement study was to increase the percentage of patients discharged home with medications in-hand from 6% to 30% within 6 months.

METHODS

Due to the planned construction of a new ED, urgent care, and dedicated pharmacy, a multidisciplinary team was formed to increase access to discharge medications. We performed a pilot study in the urgent care to improve the discharge prescription process and expanded its scope to the ED. We evaluated the effect of our interventions on the percentage of patients discharged with medications in-hand through statistical process control charts. Process measures included the percentage of prescriptions electronically prescribed and directed to an on-site pharmacy.

RESULTS

Between June 21, 2021 and March 27, 2022, 7,678 patients were discharged with at least 1 medication in-hand. The percentage of patients discharged with medications in-hand increased from 6.2% to 60.6%. The percentage of prescriptions e-prescribed and directed to an on-site pharmacy increased to 94.6% and 65.6% respectively.

CONCLUSIONS

In this study, the availability of a 24-hour on-site pharmacy appears to be the most impactful intervention increasing access to discharge medications for families. Other interventions, such as a pilot study in the urgent care and implementing default electronic prescribing, may have potentiated the effect of the new pharmacy.

Interprofessional Evaluation of a Medication Clinical Decision Support System Prior to Implementation

BACKGROUND

 Computerized physician order entry (CPOE) and clinical decision support systems (CDSS) are widespread due to increasing digitalization of hospitals. They can be associated with reduced medication errors and improved patient safety, but also with well-known risks (e.g., overalerting, nonadoption).

OBJECTIVES

 Therefore, we aimed to evaluate a commonly used CDSS containing Medication-Safety-Validators (e.g., drug-drug interactions), which can be locally activated or deactivated, to identify limitations and thereby potentially optimize the use of the CDSS in clinical routine.

METHODS

 Within the implementation process of Meona (commercial CPOE/CDSS) at a German University hospital, we conducted an interprofessional evaluation of the CDSS and its included Medication-Safety-Validators following a defined algorithm: (1) general evaluation, (2) systematic technical and content-related validation, (3) decision of activation or deactivation, and possibly (4) choosing the activation mode (interruptive or passive). We completed the in-depth evaluation for exemplarily chosen Medication-Safety-Validators. Moreover, we performed a survey among 12 German University hospitals using Meona to compare their configurations.

RESULTS

 Based on the evaluation, we deactivated 3 of 10 Medication-Safety-Validators due to technical or content-related limitations. For the seven activated Medication-Safety-Validators, we chose the interruptive option ["PUSH-(&PULL)-modus"] four times (4/7), and a new, on-demand option ["only-PULL-modus"] three times (3/7). The site-specific configuration (activation or deactivation) differed across all participating hospitals in the survey and led to varying medication safety alerts for identical patient cases.

CONCLUSION

 An interprofessional evaluation of CPOE and CDSS prior to implementation in clinical routine is crucial to detect limitations. This can contribute to a sustainable utilization and thereby possibly increase medication safety.

The effect of electronic medical records on medication errors, workload, and medical information availability among qualified nurses in Israel- a cross sectional study

BACKGROUND

Errors in medication administration by qualified nursing staff in hospitals are a significant risk factor for patient safety. In recent decades, electronic medical records (EMR) systems have been implemented in hospitals, and it has been claimed that they contribute to reducing such errors. However, systematic research on the subject in Israel is scarce. This study examines the position of the qualified nursing staff regarding the impact of electronic medical records systems on factors related to patient safety, including errors in medication administration, workload, and availability of medical information.

METHODS

This cross-sectional study examines three main variables: Medication errors, workload, and medical information availability, comparing two periods- before and after EMR implementation based on self-reports. A final sample of 591 Israeli nurses was recruited using online private social media groups to complete an online structured questionnaire. The questionnaires included items assessing workload (using the Expanding Nursing Stress Scale), medical information availability (the Carrington-Gephart Unintended Consequences of Electronic Health Record Questionnaire), and medical errors (the Medical Error Checklists). Items were assessed twice, once for the period before the introduction of electronic records and once after. In addition, participants answered open-ended questions that were qualitatively analyzed.

RESULTS

Nurses perceive the EMR as reducing the extent of errors in drug administration (mean difference = -0.92 ± 0.90SD, p < 0.001), as well as the workload (mean difference = -0.83 ± 1.03SD, p < 0.001) by ∼ 30% on average, each. Concurrently, the systems are perceived to require a longer documentation time at the expense of patients' treatment time, and they may impair the availability of medical information by about 10% on average.

CONCLUSION

The results point to nurses' perceived importance of EMR systems in reducing medication errors and relieving the workload. Despite the overall positive attitudes toward EMR systems, nurses also report that they reduce information availability compared to the previous pen-and-paper approach. A need arises to improve the systems in terms of planning and adaptation to the field and provide appropriate technical and educational support to nurses using them.

Impact of implementing the aseptic compounding management system, Medcura, on internal error rates within an oncology pharmacy aseptic unit: a mixed methods evaluation

BACKGROUND

As cancer survivorship improves, pressure on oncology services to provide safe, timely treatments increases. Traditional manual compounding processes are error prone, putting patients at risk. Additionally, errors have a detrimental impact on service delivery and staff morale. Information technology is increasingly utilised to improve safety and service delivery of systemic anti-cancer therapy (SACT). The compounding process control system, Medcura, was developed to manage the end-to-end process and reduce transcription and calculation errors.

OBJECTIVES

To evaluate the impact of implementing Medcura on internal errors and staff perceptions of errors.

METHOD

An aseptic process control system, Medcura, was implemented in a busy pharmacy chemotherapy production unit. Internal error and severity data were collected and analysed for 14 months before and during implementation, and 24 months after implementation. In addition, one-to-one semi-structured interviews were carried out with pharmacy staff, pre- and post-implementation. Interviews were transcribed and thematically analysed.

RESULTS

Error rates decreased after implementation from 2.9% to 2.1%. The types of error detected also changed with a decrease in worksheet and labelling errors, and an increase in assembly errors. The severity of the errors, as a percentage of total errors made, also decreased after implementation. Staff were predominantly positive about Medcura; it reduced the number of errors, eased the preparation of worksheets and labels, reduced pressure and work-related stress, and improved job satisfaction.

CONCLUSIONS

Implementing Medcura has resulted in a reduction in both error rate and severity. Specifically, errors related to label and worksheet generation have seen the largest reduction. Staff have viewed these changes positively and report reduced levels of work-related stress. Further development and roll-out will improve patient safety and staff morale.

Reduced prevalence of drug-related problems in psychiatric inpatients after implementation of a pharmacist-supported computerized physician order entry system - a retrospective cohort study

Introduction

In 2021, a computerized physician order entry (CPOE) system with an integrated clinical decision support system (CDSS) was implemented at a tertiary care center for the treatment of mental health conditions in Lübeck, Germany. To date, no study has been reported on the types and prevalence of drug-related problems (DRPs) before and after CPOE implementation in a psychiatric inpatient setting. The aim of this retrospective before-and-after cohort study was to investigate whether the implementation of a CPOE system with CDSS accompanied by the introduction of regular medication plausibility checks by a pharmacist led to a decrease of DRPs during hospitalization and unsolved DRPs at discharge in psychiatric inpatients.

Methods

Medication charts and electronic patient records of 54 patients before (cohort I) and 65 patients after (cohort II) CPOE implementation were reviewed retrospectively by a clinical pharmacist. All identified DRPs were collected and classified based on 'The PCNE Classification V9.1', the German database DokuPIK, and the 'NCC MERP Taxonomy of Medication Errors'.

Results

325 DRPs were identified in 54 patients with a mean of 6 DRPs per patient and 151.9 DRPs per 1000 patient days in cohort I. In cohort II, 214 DRPs were identified in 65 patients with a mean of 3.3 DRPs per patient and 81.3 DRPs per 1000 patient days. The odds of having a DRP were significantly lower in cohort II (OR=0.545, 95% CI 0.412-0.721, p<0.001). The most frequent DRP in cohort I was an erroneous prescription (n=113, 34.8%), which was significantly reduced in cohort II (n=12, 5.6%, p<0.001). During the retrospective in-depth review, more DRPs were identified than during the daily plausibility analyses. At hospital discharge, patients had significantly less unsolved DRPs in cohort II than in cohort I.

Discussion

The implementation of a CPOE system with an integrated CDSS reduced the overall prevalence of DRPs, especially of prescription errors, and led to a smaller rate of unsolved DRPs in psychiatric inpatients at hospital discharge. Not all DRPs were found by plausibility analyses based on the medication charts. A more interactive and interdisciplinary patient-oriented approach might result in the resolution of more DRPs.

Development and implementation of medication-related clinical rules for obstetrics, gynaecology, and paediatric outpatients

OBJECTIVES

Prescription errors can cause serious adverse drug events. Clinical decision support systems prevent prescription errors; however, real-time clinical rules in obstetrics, gynaecology, and paediatric outpatients remain unexplored. We evaluated the effects of localised, real-time clinical rules on alert rates and acceptance rates compared with manual prescription review.

METHODS

We developed real-time clinical rules that incorporate information systems to obtain characteristic information and laboratory values. We conducted a retrospective cohort study to compare the alert and recommendation acceptance rates of all prescription error types before and after clinical rule implementation in obstetrics, gynaecology, and paediatrics. Clinical rules, prescription error types, and alerts were determined by a prescribing review committee comprising physicians, pharmacists, nurses, and administrators. The difference in alert and acceptance rates between the groups was analysed using relative risk.

RESULTS

The number of alerts increased after clinical rules implementation; the number of on-duty pharmacists for review decreased from 10 to 2. Compared with those with manual review, the alert rates for paediatrics and obstetrics and gynaecology increased with the clinical rules by 3.97- and 11.26-fold, respectively, and the alert rates for drug-drug interactions (DDIs) and combined medication errors in obstetrics and gynaecology increased with the clinical rules by 26.10- and 26.54-fold, respectively. In paediatrics, the alert rate for all prescription error types was higher with the clinical rules review than with the manual review; the alert rates for DDI, dosage, and combination medication errors were significantly different between the clinical rules and the manual review. However, there was no difference in the recommendation acceptance rate between the manual review and the clinical rules.

CONCLUSIONS

Clinical rules can identify prescription errors that manual review cannot detect and ensure real-time review efficiency in high-volume outpatient prescription settings. The high acceptance rate and modification of prescriptions may be relevant to highly customised and localised clinical rules.

A Practical Approach to Optimize Computerized Provider Order Entry Systems and Reduce Clinician Burden: Pre-Post Evaluation of Vendor-Derived "Order Friction" Data

Computerized provider order entry (CPOE) systems have been cited as a significant contributor to clinician burden. Vendor-derived measures and data sets have been developed to help with optimization of CPOE systems. We describe how we analyzed vendor-derived Order Friction (OF) EHR log data at our health system and propose a practical approach for optimizing CPOE systems by reducing OF. We also conducted a pre-post intervention study using OF data to evaluate the impact of defaulting the frequency of urine, stool and nasal swab tests and found that all modified orders had significantly fewer changes required per order (p<0.01). Our proposed approach is a six-step process: 1) understand the ordering process, 2) understand OF data elements contextually, 3) explore ordering user-level factors, 4) evaluate order volume and friction from different order sources, 5) optimize order-level design, 6) identify high volume alerts to evaluate for appropriateness.

Prescription Precision: A Comprehensive Review of Intelligent Prescription Systems

Intelligent Prescription Systems (IPS) represent a promising frontier in healthcare, offering the potential to optimize medication selection, dosing, and monitoring tailored to individual patient needs. This comprehensive review explores the current landscape of IPS, encompassing various technological approaches, applications, benefits, and challenges. IPS leverages advanced computational algorithms, machine learning techniques, and big data analytics to analyze patient-specific factors, such as medical history, genetic makeup, biomarkers, and lifestyle variables. By integrating this information with evidence-based guidelines, clinical decision support systems, and real-time patient data, IPS generates personalized treatment recommendations that enhance therapeutic outcomes while minimizing adverse effects and drug interactions. Key components of IPS include predictive modeling, drug-drug interaction detection, adverse event prediction, dose optimization, and medication adherence monitoring. These systems offer clinicians invaluable decision-support tools to navigate the complexities of medication management, particularly in the context of polypharmacy and chronic disease management. While IPS holds immense promise for improving patient care and reducing healthcare costs, several challenges must be addressed. These include data privacy and security concerns, interoperability issues, integration with existing electronic health record systems, and clinician adoption barriers. Additionally, the regulatory landscape surrounding IPS requires clarification to ensure compliance with evolving healthcare regulations. Despite these challenges, the rapid advancements in artificial intelligence, data analytics, and digital health technologies are driving the continued evolution and adoption of IPS. As precision medicine gains momentum, IPS is poised to play a central role in revolutionizing medication management, ultimately leading to more effective, personalized, and patient-centric healthcare delivery.

Community pharmacists' perspectives towards automated pharmacy systems and extended community pharmacy services: An online cross-sectional study

Background

Private sector partnerships through community pharmacies are essential for effective healthcare integration to achieve the United Nations 2030 Agenda for Sustainable Development Goals. This partnership can provide significant clinical outcomes and reduce health system expenditures by delivering services focused on patient-centred care, such as public health screening and medication therapy management.

Objectives

To assess the understanding of the proposed strategic and health system reform in Saudi Arabia by exploring community pharmacists' perspectives towards the capacity and readiness of community pharmacies to use automated pharmacy systems, provide extended community pharmacy services, and identify perceived barriers.

Materials and methods

This multicentre, cross-sectional, web-based survey was conducted in Saudi Arabia (October-December 2021). Graphical and numerical statistics were used to describe key dimensions by the background and characteristics of the respondents, and multiple ordinal logistic regression analyses were sought to assess their associations.

Results

Of the 403 consenting and participating community pharmacists, most were male (94%), belonged to chain pharmacies (77%), and worked >48 h per week (72%). Automated pharmacy systems, such as electronic prescriptions, were never utilised (50%), and health screening services, such as blood glucose (76%) and blood pressure measurement (74%), were never provided. Services for medication therapy management were somewhat limited. Age groups ≤40 years, chain pharmacies, >10 years of experience and ≥ 3 pharmacists in place with <100 daily medication prescriptions and Jazan province were significantly more likely to provide all medication therapy management services than others. Operational factors were the barriers most significantly associated with the independent variables.

Conclusion

The results showed that most services and automated pharmacy systems remained limited and well-needed. When attempting to implement these services to drive change, community pharmacies face numerous challenges, and urgent efforts by private and government sectors are essential to improve pharmaceutical care in community pharmacy settings.

Quality indicators for systemic anticancer therapy services: a systematic review of metrics used to compare quality across healthcare facilities

PURPOSE

The number of systemic anticancer therapy (SACT) regimens has expanded rapidly over the last decade. There is a need to ensure quality of SACT delivery across cancer services and systems in different resource settings to reduce morbidity, mortality, and detrimental economic impact at individual and systems level. Existing literature on SACT focuses on treatment efficacy with few studies on quality or how SACT is delivered within routine care in comparison to radiation and surgical oncology.

METHODS

Systematic review was conducted following PRISMA guidelines. EMBASE and MEDLINE were searched and handsearching was undertaken to identify literature on existing quality indicators (QIs) that detect meaningful variations in the quality of SACT delivery across different healthcare facilities, regions, or countries. Data extraction was undertaken by two independent reviewers.

RESULTS

This review identified 63 distinct QIs from 15 papers. The majority were process QIs (n = 55, 87.3%) relating to appropriateness of treatment and guideline adherence (n = 28, 44.4%). There were few outcome QIs (n = 7, 11.1%) and only one structural QI (n = 1, 1.6%). Included studies solely focused on breast, colorectal, lung, and skin cancer. All but one studies were conducted in high-income countries.

CONCLUSIONS

The results of this review highlight a significant lack of research on SACT QIs particularly those appropriate for resource-constrained settings in low- and middle-income countries. This review should form the basis for future work in transforming performance measurement of SACT provision, through context-specific QI SACT development, validation, and implementation.

E-prescribing and medication safety in community settings: A rapid scoping review

Background

Medication prescribing is essential for the treatment, curing, maintenance, and/or prevention of an illness and disease, however, medication errors remain common. Common errors including prescribing and administration, pose significant risk to patients. Electronic prescribing (e-prescribing) is one intervention used to enhance the safety and quality of prescribing by decreasing medication errors and reducing harm. E-prescribing in community-based settings has not been extensively examined.

Objective

To map and characterize the current evidence on e-prescribing and medication safety in community pharmacy settings.

Methods

We conducted a rapid scoping review of quantitative, qualitative, and mixed methods studies reporting on e-prescribing and medication safety. MEDLINE All (OVID), Embase (Elsevier), CINAHL Full Text (EBSCOHost), and Scopus (Elsevier) databases were searched December 2022 using keywords and MeSH terms related to e-prescribing, medication safety, efficiency, and uptake. Articles were imported to Covidence and screened by two reviewers. Data were extracted by a single reviewer and verified by a second reviewer using a standardized data extraction form. Findings are reported in accordance with JBI Manual for Evidence Synthesis following thematic analysis to narratively describe results.

Results

Thirty-five studies were included in this review. Most studies were quantitative (n = 22), non-experimental study designs (n = 16) and were conducted in the United States (n = 18). Half of included studies reported physicians as the prescriber (n = 18), while the remaining reported a mix of nurse practitioners, pharmacists, and physician assistants (n = 6). Studies reported on types of errors, including prescription errors (n = 20), medication safety errors (n = 9), dispensing errors (n = 2), and administration errors (n = 1). Few studies examined patient health outcomes, such as adverse drug events (n = 5).

Conclusions

Findings indicate that most research is descriptive in nature and focused primarily on rates of prescription errors. Further research, such as experimental, implementation, and evaluation mixed-methods research, is needed to investigate the effects of e-prescribing on reducing error rates and improving patient and health system outcomes.

Proof-of-concept solution to create an interoperable timeline of healthcare data

OBJECTIVES

To overcome the barriers of interoperability by sharing simulated patient data from different electronic health records systems and presenting them in an intuitive timeline of events.

METHODS

The 'Patient Story' software comprising database and blockchain, PS Timeline Windows interface, PS Timeline Web interface and network relays on Azure cloud was customised for Epic and Lorenzo electonic patient record (EPR) systems used at different hospitals, using site-specific adapters.

RESULTS

Each site could view their own clinical documents and view each other's site specific, fully coded test sets of (Care Connect) medications, conditions and allergies, in an aggregated single view.

DISCUSSION

This work has shown that clinical data from different EPR systems can be successfully integrated and visualised on a single timeline, accessible by clinicians and patients.

CONCLUSION

The Patient Story system combined the timeline visualisation with successful interoperability across healthcare settings, as well giving patients the ability to directly interact with their timeline.

Transition to ePrescribing for systemic anti-cancer therapy - Perceptions of a multidisciplinary haematology/oncology team in a large teaching hospital

INTRODUCTION

A National Cancer Information System is planned for phased implementation in Irish cancer centres to enable electronic prescribing (ePrescribing) of systemic anti-cancer therapy. This study aimed to capture the opinions of healthcare professionals in a hospital setting relating to the current paper-based workflow for systemic anti-cancer therapy prescribing and their attitudes and expectations of the new ePrescribing system to develop recommendations, which assist in the planning and implementation of future ePrescribing systems.

METHODS

A mixed methods study of concurrent design was conducted. Interviews with healthcare professionals primarily aimed to evaluate processes and identify areas requiring improvement within the current paper-based workflow for systemic anti-cancer therapy prescribing. An online questionnaire adapted from the Information Systems Expectations and Experiences tool primarily aimed to capture expectations of the new ePrescribing system and attitudes towards the transition.

RESULTS

Twelve healthcare professionals were interviewed, and 50 healthcare professionals responded to the online questionnaire (response rate: 33.3%). Eight major themes emerged from interview transcripts relating to opinions on the paper-based workflow. Questionnaire respondents reported positive attitudes towards ePrescribing implementation and had high expectations for workflow improvements and functionalities of the new system. Seven recommendations for ePrescribing implementation were developed: (1) prioritise specific processes; (2) plan for changes in communication; (3) repeat research in the post-implementation setting; (4) ensure good information technology infrastructure and system support; (5) ensure optimum training; (6) outline limitations of clinical decision support; (7) provide clear instructions on local configurability.

CONCLUSION

This study identifies potential challenges in transitioning to ePrescribing and provides recommendations, which assist stakeholders in ensuring safe and effective transitions, thus informing future ePrescribing systems' implementation in haematology/oncology settings.

[Does recommending the dosing frequency in the electronic prescription improve its adequacy? Before and after study]

OBJECTIVE

To assess whether reporting the dosing frequency into the prescription module of the Institut Català de la Salut (ICS) primary care electronic clinical workstation improves the dosing frequency's adequacy of the prescriptions.

DESIGN

Before and after study with non-equivalent control of prescriptions without any change in the dosing frequency. The study periods includes from September 1st, 2019 to February 29th, 2020.

LOCATION

Primary care setting.

PARTICIPANTS

Prescriptions issued by ICS General Practitioner, during the study period of those medicines which indications have a single appropriate dosing frequency or mostly appropriate, are included.

INTERVENTION

Recommendation of the appropriate dosing frequency in the prescription module.

MAIN MEASUREMENTS

Adequacy defined as the coincidence between the prescribed dosing frequency and the appropriate dosing frequency.

RESULTS

After the intervention there was a 22.75% increase in prescriptions with adequate dosing frequency. The largest increase occurred in the medicines for the genitourinary system and sex hormones. In absolute terms, the group of anti infective for systemic use is the one that obtained more prescriptions with an adequate dosing frequency between the two periods.

CONCLUSIONS

The intervention increased the dosing frequency's adequacy leading to improvements in the safety and effectiveness of the treatments. It is evident that the design and implementation of improvements in electronic prescription systems contributes to increasing the quality of the prescription.

Assessment of the operation status of electronic prescription at community pharmacies in Chengdu, China: a simulated patient study

BACKGROUND

Information and technologies relevant to eHealth have developed rapidly over the past two decades. Based on this, China piloted "Internet + " pattern and some regions piloted electronic prescription services to explore telepharmacy services.

OBJECTIVE

To describe the processes and assess the operation status of electronic prescription services mode for community pharmacies in China.

METHODS

The simulated patient methodology was used to conduct a cross-sectional study in 317 community pharmacies from six districts in Chengdu, China in 2019. Simulated patients expressed three levels of service demands based on scenario about acute upper respiratory tract infections to evaluate the recommendation strength of electronic prescription services and telepharmacy service in community pharmacies. The descriptive statistics was completed to obtain the characteristics of the visit process, student t-test and χ2 test (P < 0.05 was considered statistically significant) were used for inferential statistical analysis to determine differences in characteristics and degree of recommendation between pharmacies.

RESULTS

Three Hundred Seventeen record sheets were effectively collected. The third-party platform was recommended in 195 (61.5%) interactions. The main reason for not recommending is non-prescription dispensing of prescription drugs (27.1%). 90.3% interactions waited less than 1 min, the counseling duration was less than 5 min in all interactions, and most community pharmacies had good network conditions (81.5%). 97.4% remote physicians offered professional counseling, only 22.1% of the pharmacists provided medication advice.

CONCLUSIONS

The electronic prescription services mode for community pharmacies in Chengdu provides a convenient drug purchase process but remains some problems. For example, prescribing drugs without a prescription and services provided by pharmacists was poor, etc. The relevant supporting policies should be improved in future development process.

Complex implementation mechanisms in primary care: do physicians' beliefs about the effectiveness of innovation play a mediating role? Applying a realist inquiry and structural equation modeling approach in a formative evaluation study

BACKGROUND

The adoption of digital health technologies can improve the quality of care for polypharmacy patients, if the underlying complex implementation mechanisms are better understood. Context effects play a critical role in relation to implementation mechanisms. In primary care research, evidence on the effects of context in the adoption of digital innovation for polypharmacy management is lacking.

STUDY AIM

This study aims to identify contextual factors relevant to physician behavior and how they might mediate the adoption process.

METHODS

The physicians who participated in this formative evaluation study (n = 218) were part of the intervention group in a cluster-randomized controlled trial (AdAM). The intervention group implemented a digital innovation for clinical decision making in polypharmacy. A three-step methodological approach was used: (1) a realist inquiry approach, which involves the description of a context-mechanism-outcome configuration for the primary care setting; (2) a belief elicitation approach, which involves qualitative content analysis and the development of a quantitative latent contextualized scale; and (3) a mediation analysis using structural equation modeling (SEM) based on quantitative survey data from physicians to assess the mediating role of the contextualized scale (n = 179).

RESULTS

The key dimensions of a (1) context-mechanism-outcome model were mapped and refined. A (2) latent construct of the physicians' innovation beliefs related to the effectiveness of polypharmacy management practices was identified. Innovation beliefs play a (3) mediating role between the organizational readiness to implement change (p < 0.01) and the desired behavioral intent of physicians to adopt digital innovation (p < 0.01; R² = 0.645). Our contextualized model estimated significant mediation, with a relative size of 38% for the mediation effect. Overall, the model demonstrated good fit indices (CFI = 0.985, RMSEA = 0.034).

CONCLUSION

Physician adoption is directly affected by the readiness of primary care organizations for the implementation of change. In addition, the mediation analysis revealed that this relationship is indirectly influenced by primary care physicians' beliefs regarding the effectiveness of digital innovation. Both individual physician beliefs and practice organizational capacity could be equally prioritized in developing implementation strategies. The methodological approach used is suitable for the evaluation of complex implementation mechanisms. It has been proven to be an advantageous approach for formative evaluation.

TRIAL REGISTRATION

NCT03430336 . First registration: 12/02/2018.

CLINICALTRIALS

gov.

Physicians' perceptions of electronic prescribing of controlled medications in the West Bank, Palestine: A pre-implementation assessment

BACKGROUND

In Palestine, prescribing controlled medications is still done on paper. Despite valuable regulatory efforts, there is a high risk of undetected abuse and "doctor shopping". These problems can be addressed with electronic prescribing of controlled medicines (EPCM). User adoption is essential to the successful implementation of any technology. Therefore, it is crucial to determine the perception of end users at an early stage. This topic has never been addressed in Palestine. Our study aims to investigate the perception of Palestinian physicians towards the introduction of EPCM.

METHODS

This cross-sectional study was conducted among Palestinian physicians in the West Bank who are familiar with controlled medications prescribing. Data were collected using a self-administered questionnaire based on the Unified Theory of User Acceptance and Use of Technology (UTAUT) from a convenience sample of 300 physicians. Data were analyzed using SPSS version 26. Bivariate analysis and binary and multivariate logistic regression were performed to identify factors associated with physicians' perceptions of ECPM.

RESULTS

Most physicians expressed their willingness to use EPCM, with an acceptance rate of 85%. This perception was significantly affected by performance expectancy, effort expectancy and trust. None was moderated by age, gender, or experience with electronic prescribing. Age and specialization level were independent factors significantly influencing the intention to use EPCM. The level of current workflow challenges did not correlate with the intent to use EPCM.

CONCLUSION

Palestinian physicians will accept EPCM. Based on the results of this study, it is recommended that the following be considered: ensuring maximum efficiency of the system, selecting user-friendly interfaces and high-security measures to prevent system breaches.

Developing a minimum data set for cardiovascular Computerized Physician Order Entry (CPOE) and mapping the data set to FHIR: A multi-method approach

Many medical errors occur in the process of treating cardiovascular patients, and most of these errors are related to prescription errors. There are several, one of the methods to prevent prescription errors is the use of a computerized physician order entry (CPOE) system. One of the obstacles of implementing this system is improper design and non-compliance with user needs. one of the issues that should be considered in designing information systems is having a standard minimum data set (MDS). Although many computerized physicians order entry (CPOE) systems have been developed in the world, no study has identified the necessary data and minimum data set (MDS) of CPOE system, and published the process of creating this MDS. This study aimed to develop an MDS for cardiovascular CPOE and standardize it with Fast Healthcare Interoperability Resources (FHIR). A multi-method approach including systematic review for identifying data elements of CPOE, reviewing the content of medical records, validation of the data elements using the expert panel and, determination of the necessary data elements using a survey was conducted. Classification of the data elements and mapping them to FHIR were done to facilitate data sharing and integration with the electronic health record (EHR) system as well as to reduce data diversity. The final data elements of MDS were categorized into 5 main categories of FHIR (foundation, base, clinical, financial, and specialized) and 146 resources, where possible. Mapping was done by one of the researchers and checked and verified by the second researcher. Non-mapped data elements were added to relevant resources as extensions of existing FHIR resources. In total, 270 data elements were identified from the systematic review. After reviewing the content of 20 patients' medical records, 28 data elements were identified. After combination of data elements of two previous phases and removing duplication, 282 data elements remained. Data elements that were considered necessary to be included in CPOE by conducting a survey among cardiovascular physicians were 109 elements. From 146 resources of FHIR, the data elements of this MDS are covered by 5 resources. This study introduced an MDS for cardiovascular CPOE by combining suggested data elements of previous research, and the practical and local requirements identified in patients' medical records. To facilitate data sharing and integration with EHR, reduce data diversity, and also to categorize data, this MDS was standardized with FHIR. The steps we used to develop this MDS could be a model for creating MDS in other CPOEs and health information systems. This is the first time that the process of developing an MDS for cardiovascular CPOE has been presented in the literature.

Reducing prescribing errors: making electronic prescribing work for cystic fibrosis inpatients

Children admitted to our hospital with cystic fibrosis had frequent medication errors due to polypharmacy and addition of specialist and high-risk medications despite an electronic prescribing and medicines administration system in place. We describe a multidisciplinary quality improvement project that combined a computerised order entry system (CPOE) with human factor process changes. Over 12 months, our run chart showed a 43% reduction in prescription errors. For medications prescribable via the CPOE, errors reaching the patient reduced from 50% to 29%. Electronic prescribing can be seen by clinicians as a fixed unalterable system contributing to rather than ameliorating errors. Improving safety requires whole team engagement and working closely with programmers to adapt function and influence human factors.

Detection of Drug-Related Problems through a Clinical Decision Support System Used by a Clinical Pharmacy Team

Clinical decision support systems (CDSSs) are intended to detect drug-related problems in real time and might be of value in healthcare institutions with a clinical pharmacy team. The objective was to report the detection of drug-related problems through a CDSS used by an existing clinical pharmacy team over 22 months. It was a retrospective single-center study. A CDSS was integrated in the clinical pharmacy team in July 2019. The investigating clinical pharmacists evaluated the pharmaceutical relevance and physician acceptance rates for critical alerts (i.e., alerts for drug-related problems arising during on-call periods) and noncritical alerts (i.e., prevention alerts arising during the pharmacist’s normal work day) from the CDSS. Of the 3612 alerts triggered, 1554 (43.0%) were critical, and 594 of these 1554 (38.2%) prompted a pharmacist intervention. Of the 2058 (57.0%) noncritical alerts, 475 of these 2058 (23.1%) prompted a pharmacist intervention. About two-thirds of the total pharmacist interventions (PI) were accepted by physicians; the proportion was 71.2% for critical alerts (i.e., 19 critical alerts per month vs. 12.5 noncritical alerts per month). Some alerts were pharmaceutically irrelevant—mainly due to poor performance by the CDSS. Our results suggest that a CDSS is a useful decision-support tool for a hospital pharmacist’s clinical practice. It can help to prioritize drug-related problems by distinguishing critical and noncritical alerts. However, building an appropriate organizational structure around the CDSS is important for correct operation.

Using Technology to Improve Diabetes Care in Hospital: The Challenge and the Opportunity

The past 10 years have seen a revolution in technology improving the lives of people with diabetes. This has implications for diabetes care in hospitalized inpatients. These technological developments have the potential to significantly improve the care of people with diabetes in hospital. Combining point of care glucose monitoring, electronic prescribing, electronic observations with electronic referral, and electronic health records allow teams to daily oversee the whole hospital population. To make the most of these tools as well as developing the use of pumps and glucose sensors in hospital, the diabetes team needs to work in new ways. To date, very little work has described how these should be combined. We describe how this technology can be combined to improve diabetes care in hospital.

Using automated methods to detect safety problems with health information technology: a scoping review

OBJECTIVE

To summarize the research literature evaluating automated methods for early detection of safety problems with health information technology (HIT).

MATERIALS AND METHODS

We searched bibliographic databases including MEDLINE, ACM Digital, Embase, CINAHL Complete, PsycINFO, and Web of Science from January 2010 to June 2021 for studies evaluating the performance of automated methods to detect HIT problems. HIT problems were reviewed using an existing classification for safety concerns. Automated methods were categorized into rule-based, statistical, and machine learning methods, and their performance in detecting HIT problems was assessed. The review was conducted in accordance with the Preferred Reporting Items for Systematic Reviews and Meta Analyses extension for Scoping Reviews statement.

RESULTS

Of the 45 studies identified, the majority (n = 27, 60%) focused on detecting use errors involving electronic health records and order entry systems. Machine learning (n = 22) and statistical modeling (n = 17) were the most common methods. Unsupervised learning was used to detect use errors in laboratory test results, prescriptions, and patient records while supervised learning was used to detect technical errors arising from hardware or software issues. Statistical modeling was used to detect use errors, unauthorized access, and clinical decision support system malfunctions while rule-based methods primarily focused on use errors.

CONCLUSIONS

A wide variety of rule-based, statistical, and machine learning methods have been applied to automate the detection of safety problems with HIT. Many opportunities remain to systematically study their application and effectiveness in real-world settings.

[Development of a methodological guide on the implementation of a pharmaceutical decision support system: Feedback from a French university hospital]

OBJECTIVE

Develop a methodological guide on the implementation of a PDSS (pharmaceutical decision support system).

METHOD

Observational study, retrospective conducted at Lille University Hospital from May 2017 to December 2020, corresponding to the period of implementation and then use of the software. The different phases of the project are described as well as the methodology at each stage.

RESULTS

Four stages seem necessary for the establishment of the PDSS: reflection and preparation of the project, contracting, implementation, use and evaluation. Based on these results and our experience, in particular the difficulties encountered, a methodological diagram of the various steps necessary for the implementation of a PDSS is proposed.

CONCLUSION

The establishment of a PDSS, especially in the field of clinical pharmacy, is a long multidisciplinary process. Several steps, from project preparation to production start-up are necessary. Planning the different stages is essential for the proper implementation of the SADP so that the installation is as efficient as possible.

Electronic unified therapy record as a clinical risk management tool in the Italian healthcare system

Digitization of health records is still struggling to take hold in the Italian healthcare context, where medical records are still largely kept manually on paper. Besides being anachronistic, this practice is particularly critical if applied to the drug chart. Poor handwriting and transcription errors can generate medication errors and thus represent a potential source of adverse events. In the present study, we attempt to test the hypothesis that the application of a computerized medical record model may represent a useful tool for managing clinical risk and medical expenditure. We shall do so through the analysis of the preliminary results of the application of such a model in two private hospitals in Northern Italy. The results, although preliminary, are encouraging. Among the benefits of digitizing drug records, we recorded a greater accuracy and adequacy of prescriptions, a reduction in the overall workload for nurses (no longer required to manually transcribe the list of drugs from one chart to another), as well as an optimization of the management of drug stocks by hospital pharmacies. The results in terms of clinical risk reduction will be monitored through a prospective cohort study that will take place in the coming months.

Interventions to reduce the incidence of medical error and its financial burden in health care systems: A systematic review of systematic reviews

Background and aim

Improving health care quality and ensuring patient safety is impossible without addressing medical errors that adversely affect patient outcomes. Therefore, it is essential to correctly estimate the incidence rates and implement the most appropriate solutions to control and reduce medical errors. We identified such interventions.

Methods

We conducted a systematic review of systematic reviews by searching four databases (PubMed, Scopus, Ovid Medline, and Embase) until January 2021 to elicit interventions that have the potential to decrease medical errors. Two reviewers independently conducted data extraction and analyses.

Results

Seventysix systematic review papers were included in the study. We identified eight types of interventions based on medical error type classification: overall medical error, medication error, diagnostic error, patients fall, healthcare-associated infections, transfusion and testing errors, surgical error, and patient suicide. Most studies focused on medication error (66%) and were conducted in hospital settings (74%).

Conclusions

Despite a plethora of suggested interventions, patient safety has not significantly improved. Therefore, policymakers need to focus more on the implementation considerations of selected interventions.

Characteristics and Consequences of Medication Errors in Pediatric Patients Reported to Ramathibodi Poison Center: A 10-Year Retrospective Study

Purpose

This study was performed to evaluate the clinical characteristics of, consequences of, and factors associated with medication errors (MEs) that cause harm to pediatric patients (<15 years of age) treated in the hospital setting.

Patients and Methods

We performed a 10-year retrospective study (January 2011–December 2020) by analyzing data from the Ramathibodi Poison Center. MEs were classified into categories A to I according to the severity of the outcome.

Results

In total, 121 patients were included in the study. Most (51.24%) patients were male. Their median age was 1 year (range, 1 hour–14 years). Infants, newborns, and toddlers were the three most common age groups in which MEs were reported. Most MEs occurred during the afternoon shift [n = 60 (49.59%)] and in the inpatient department (66.12%). The most common type of MEs was a dose error (64.46%). Antibiotics, sedative agents, and bronchodilators were the three most common classes of ME drugs. Four patients died. Three deaths occurred because of a dose error. One patient was a 1-year-old girl who received an iatrogenic intravenous phenytoin overdose of 10 times the normal dose, resulting in a phenytoin level of 72.4 mcg/mL. She died 22 hours after the ME occurred. The work shift was the only factor that significantly differed between patients with category C and D MEs and those with category E to I MEs.

Conclusion

Small children were at highest risk for MEs. MEs induced harm and deaths in some patients. A preventive and safety system, including appropriate shift work administration, should be emphasized and implemented to prevent and/or decrease the occurrence of MEs.

Practical Considerations of PRN Medicines Management: An Integrative Systematic Review

Background and objectives: Highly widespread use of pro re nata (PRN) medicines in various healthcare settings is a potential area for improper medication prescription and administration leading to patient harm. This study aimed to summarize and integrate the findings of all relevant individual studies regarding the practical considerations of PRN medicines management including strategies and interventions by healthcare professionals for safe prescription, dispensing, administration, monitoring, and deprescription of PRN medicines in healthcare settings. Methods: An integrative systematic review on international databases were performed. Electronic databases including Web of Knowledge, Scopus, PubMed (including MEDLINE), and Cinahl were searched to retrieve articles published until end of May 2021. Original qualitative, quantitative, and mixed methods studies written in English were included with a focus on PRN medicines management in healthcare settings. Research synthesis using the narrative method was performed to summarise the results of included studies. Results: Thirty-one studies on PRN medicines in healthcare settings by different healthcare providers were included after the screening of the databases based on eligibility criteria. They were published from 1987 to 2021. The majority of studies were from Australia, the United States, Canada, and the United Kingdom and were conducted in psychiatric settings. Given variations in their purposes, methods, and outcomes, the research synthesis was conducted narratively based on diversities and similarities in findings. Eight categories were developed by the authors as follows: "PRN indications and precautionary measures," "requirements of PRN prescription," "interventions for PRN administration," "monitoring and follow up interventions," "deprescription strategies," "healthcare professionals' role," "participation of patients and families," and "multidisciplinary collaboration." Each category consists of several items and describes what factors should be considered by healthcare professionals for PRN medicines management. Conclusion: The review findings provide insights on the practical considerations of PRN medicines management in clinical practice. The suggested list of considerations in our review can be used by healthcare professionals for optimal PRN medicines management and safeguarding patient care.

AI Models for Predicting Readmission of Pneumonia Patients within 30 Days after Discharge

A model with capability for precisely predicting readmission is a target being pursued worldwide. The objective of this study is to design predictive models using artificial intelligence methods and data retrieved from the National Health Insurance Research Database of Taiwan for identifying high-risk pneumonia patients with 30-day all-cause readmissions. An integrated genetic algorithm (GA) and support vector machine (SVM), namely IGS, were used to design predictive models optimized with three objective functions. In IGS, GA was used for selecting salient features and optimal SVM parameters, while SVM was used for constructing the models. For comparison, logistic regression (LR) and deep neural network (DNN) were also applied for model construction. The IGS model with AUC used as the objective function achieved an accuracy, sensitivity, specificity, and area under ROC curve (AUC) of 70.11%, 73.46%, 69.26%, and 0.7758, respectively, outperforming the models designed with LR (65.77%, 78.44%, 62.54%, and 0.7689, respectively) and DNN (61.50%, 79.34%, 56.95%, and 0.7547, respectively), as well as previously reported models constructed using thedata of electronic health records with an AUC of 0.71–0.74. It can be used for automatically detecting pneumonia patients with a risk of all-cause readmissions within 30 days after discharge so as to administer suitable interventions to reduce readmission and healthcare costs.

The effect of external store reliance on actual and predicted value-directed remembering

We often rely on external devices to store to-be-remembered information in our everyday lives (e.g., writing grocery lists, setting reminders), yet there is limited research about how certain information (i.e., valuable information) may be differentially encoded when we rely on our internal memory versus an external store. Across three preregistered experiments, we examined the effect of relying on an external store on the recall of high-value and low-value information. In Experiments 1a and 1b, we presented participants with words associated with point values and examined mean recall performance during two critical trials in which the external store was not available: (1) a trial in which participants were told that they would have access to an external memory store at test (told-external-store) and (2) a trial in which participants were told that they would not have access to their external store at test (told-no-external-store). In Experiment 2, we explored participants' metacognitive predictions of performance on the recall test. Critically, across all of the experiments, we found that the value effect (i.e., better recall for valuable information) was significantly reduced when individuals were told that they could rely on an external store. The same pattern was present in participant's metacognitive judgements. Together, these results suggest that when relying on external stores, individuals forgo (to some extent, at least) selective encoding by value and that individuals might be aware of this change in strategy.

An e-Delphi study to obtain expert consensus on the level of risk associated with preventable e-prescribing events

Aims

We aim to seek expert opinion and gain consensus on the risks associated with a range of prescribing scenarios, preventable using e‐prescribing systems, to inform the development of a simulation tool to evaluate the risk and safety of e‐prescribing systems (ePRaSE).

Methods

We conducted a two‐round e‐Delphi survey where expert participants were asked to score pre‐designed prescribing scenarios using a five‐point Likert scale to ascertain the likelihood of occurrence of the prescribing event, likelihood of occurrence of harm and the severity of the harm.

Results

Twenty‐four experts consented to participate with 15 pand 13 participants completing rounds 1 and 2, respectively. Experts agreed on the level of risk associated with 136 out of 178 clinical scenarios with 131 scenarios categorised as high or extreme risk.

Conclusion

We identified 131 extreme or high‐risk prescribing scenarios that may be prevented using e‐prescribing clinical decision support. The prescribing scenarios represent a variety of categories, with drug–disease contraindications being the most frequent, representing 37 (27%) scenarios, and antimicrobial agents being the most common drug class, representing 28 (21%) of the scenarios. Our e‐Delphi study has achieved expert consensus on the risk associated with a range of clinical scenarios with most of the scenarios categorised as extreme or high risk. These prescribing scenarios represent the breadth of preventable prescribing error categories involving both basic and advanced clinical decision support. We will use the findings of this study to inform the development of the e‐prescribing risk and safety evaluation tool.

Evaluation of two European risk models for predicting medication harm in an Australian patient cohort

PURPOSE

To externally evaluate the performance of two European risk prediction models, for identifying patients at high-risk of medication harm, in an Australian hospital setting.

METHODS

This was a secondary analysis of a pre-existing cohort study described in a recently published study by Falconer et al. (Br J Clin Pharmacol 87(3):1512-1524, 2021) describing the development of a predictive risk model for inpatient medication harm. We retrospectively extracted relevant variables using the electronic health records of general medical and geriatric patients admitted to a quaternary hospital, in Brisbane, over 6 months from July to December 2017. This dataset was used to externally evaluate the two European models, The Brighton Adverse Drug Reaction Risk (BADRI) model by Tangiisuran et al. and a risk model developed by Trivalle et al. The variables were entered into both models and the patients' risk of medication harm was calculated, and compared with actual patient outcomes. Predictive performance was evaluated by measuring area under the receiver operative characteristic (AuROC) curves.

RESULTS

The Australian patient cohort included 1982 patients (median age 74 years), of which 136 (7%) patients experienced ≥ 1 medication harm event(s). External evaluation of the two European models identified that both the BADRI and the Trivalle models had reduced predictive performance in an Australian patient cohort, compared with their original studies (AuROC of 0.63 [95% CI: 0.58-0.68] and 0.60 [95% CI: 0.55-0.65], respectively).

CONCLUSION

Neither model demonstrated sufficient discrimination to warrant further evaluation in our local setting. This is likely a result of variations between the development and the validation cohorts, and the change in healthcare systems over time, and highlights the need for an up-to-date and context-specific risk prediction model.

Patients', pharmacists', and prescribers' attitude toward using blockchain and machine learning in a proposed ePrescription system: online survey

Objective

To evaluate the attitudes of the parties involved in the system toward the new features and measure the potential benefits of introducing the use of blockchain and machine learning (ML) to strengthen the in-place methods for safely prescribing medication. The proposed blockchain will strengthen the security and privacy of the patient’s prescription information shared in the network. Once the ePrescription is submitted, it is only available in read-only mode. This will ensure there is no alteration to the ePrescription information after submission. In addition, the blockchain will provide an improved tracking mechanism to ensure the originality of the ePrescription and that a prescriber can only submit an ePrescription with the patient’s authorization. Lastly, before submitting an ePrescription, an ML algorithm will be used to detect any anomalies (eg, missing fields, misplaced information, or wrong dosage) in the ePrescription to ensure the safety of the prescribed medication for the patient.

Methods

The survey contains questions about the features introduced in the proposed ePrescription system to evaluate the security, privacy, reliability, and availability of the ePrescription information in the system. The study population is comprised of 284 respondents in the patient group, 39 respondents in the pharmacist group, and 27 respondents in the prescriber group, all of whom met the inclusion criteria. The response rate was 80% (226/284) in the patient group, 87% (34/39) in the pharmacist group, and 96% (26/27) in the prescriber group.

Key Findings

The vast majority of the respondents in all groups had a positive attitude toward the proposed ePrescription system’s security and privacy using blockchain technology, with 72% (163/226) in the patient group, 70.5% (24/34) in the pharmacist group, and 73% (19/26) in the prescriber group. Moreover, the majority of the respondents in the pharmacist (70%, 24/34) and prescriber (85%, 22/26) groups had a positive attitude toward using ML algorithms to generate alerts regarding prescribed medication to enhance the safety of medication prescribing and prevent medication errors.

Conclusion

Our survey showed that a vast majority of respondents in all groups had positive attitudes toward using blockchain and ML algorithms to safely prescribe medications. However, a need for minor improvements regarding the proposed features was identified, and a post-implementation user study is needed to evaluate the proposed ePrescription system in depth.

It's like sending a message in a bottle: A qualitative study of the consequences of one-way communication technologies in hospitals

OBJECTIVE

We examine how physicians and nurses use available communication technologies and identify the implications for communication and patient care based on the theory of workarounds.

MATERIALS AND METHODS

We conducted a qualitative study at 4 U.S. hospitals during 2017. Researchers spent 2 weeks at each hospital conducting unit-based observation, shadowing, interviews, and focus groups with nurses and physicians. Using an iterative process, we inductively coded and thematically analyzed data to derive preliminary themes. The theory of workarounds provides an organizational lens on workarounds, consisting of 5 components: antecedents, types, effects, managerial stance, and organizational challenges of workarounds. The first 3 components of the theory helped us to organize and explain our findings.

RESULTS

Communication technologies consisted of pagers and telephones. Antecedents to workarounds included one-way information flow, differential access related to differences in technology types, and technology mismatch. Types of workarounds included bypassing a variety of obstacles and substituting for unavailable resources. Direct effects of workarounds included pager fatigue, interruptions in patient care, and potential errors.

DISCUSSION

One-way communication technologies created an environment where workarounds could flourish. By placing results within the context of the theory of workarounds, we extend what we know about why and how workarounds develop, and offer strategies to minimize workarounds' adverse effects.

CONCLUSIONS

Through the theory of workarounds, we see that there is a trajectory to workarounds with potential consequences for clinicians and patients. Two-way communication technologies could minimize workarounds and gaps in information exchange, and reduce unnecessary interruptions and the potential for adverse events.

Trends in Calcium Channel Blocker Use in Patients with Heart Failure with Reduced Ejection Fraction and Comorbid Atrial Fibrillation

BACKGROUND

Heart failure with reduced ejection fraction and atrial fibrillation commonly coexist. Most calcium channel blockers are not recommended in heart failure with reduced ejection fraction, but their use has been seldom evaluated. For patients with heart failure with reduced ejection fraction and comorbid atrial fibrillation, we sought to 1) determine the proportion discharged on contraindicated calcium channel blockers, 2) describe how clinicians' use of these medications at discharge have changed over time, and 3) identify predictors for contraindicated calcium channel blocker prescription at discharge.

METHODS

We analyzed 395 patients discharged with heart failure with reduced ejection fraction and atrial fibrillation between 2008 and 2018. Discharge on a contraindicated calcium channel blocker (any calcium channel blocker except amlodipine) was the primary outcome. Changes in calcium channel blocker prescription over time were evaluated with a Cochran-Armitage trend test. Multivariable logistic regression was used to identify predictors of calcium channel blocker prescription at discharge.

RESULTS

Twenty-nine (7.3%) patients were discharged on a contraindicated calcium channel blocker without change over time (P_trend = .38). Of these, 26 (86.7%) were discharged on multiple atrioventricular nodal blocking medications. Hypertension (odds ratio [OR] 7.87; 95% confidence interval [CI], 1.04-59.40) and female sex (OR 3.01; 95% CI, 1.36-6.67) were both associated with contraindicated calcium channel blocker prescription at discharge while diabetes mellitus was negatively associated with this outcome (OR 0.34; 95% CI, 0.14-0.88).

CONCLUSION

One in 14 patients with heart failure with reduced ejection fraction and comorbid atrial fibrillation were discharged on a contraindicated calcium channel blocker, without change over time. Most patients were discharged on multiple atrioventricular nodal blockers, highlighting potential need for greater coordination between discharging physicians, pharmacists, and electrophysiology.

How Physicians Renew Electronic Prescriptions in Primary Care: Therapeutic Decision or Technical Task?

In long-term pharmacotherapies, the renewal of prescriptions is part of the medication use process. Although the majority of medicines are used with renewed prescriptions, little research has focused on renewal practices. The aim of this study was to explore current renewal practices from a primary care physician’s perspective to identify system-based challenges and development needs related to the renewal practices. This qualitative study was conducted in two phases in public primary health care centres of Kirkkonummi, Finland. First, five physicians were shadowed on-site while they renewed prescriptions. The findings of the shadowing phase were further discussed in two focus group discussions with seven other physicians than in the shadowing phase. Inductive content analysis was used for data analysis utilizing Reason’s risk management theory as a theoretical framework. Due to problems in the renewal process, including impractical information systems, a lack of reconciled medication lists, and a lack of time allocated for renewing prescriptions, physicians felt that monitoring and reviewing each patients’ medications for renewal was complicated. Therefore, they felt that renewing, at times, became a technical task rather than a therapeutic decision. The physicians suggested information system improvements, enhanced interprofessional cooperation, and patient involvement as strategies to ensure rational pharmacotherapy and patient safety in the renewal of prescription medicines.

The clinical pharmacist's role in enhancing the relevance of a clinical decision support system

BACKGROUND

Clinical decision support systems (CDSSs) can improve the quality of patient care by helping physicians to review their prescriptions and thus to optimize drug treatments. Nevertheless, the "alert fatigue" brought on by a large number of irrelevant alerts can decrease a CDSS's effectiveness and thus clinical value. Involving a clinical pharmacist in the development and management of a CDSS can reduce the number of irrelevant alerts presented to physicians. Clinical pharmacists screen alerts and suggest PIs for physicians, corresponding to any proposed therapeutic change about health products, only for relevant alerts could improve the relevance and the acceptance of the information given to physicians about the risks faced by their patients.

OBJECTIVE

To assess the value of involving clinical pharmacists in the development and maintenance of decision support rules for generating alerts and pharmaceutical interventions (PIs) and to describe the level of acceptance of these PIs by the physicians.

METHOD

In a retrospective, single-centre study, we evaluated the number of PIs accepted from alerts generated by the CDSS when a clinical pharmacist had developed and managed this tool. During the first 7 months of development of the CDSS, a clinical pharmacist analyzed alerts triggered by the CDSS according to its technical validity and pharmaceutical relevance. Lastly, for alerts that led to a PI, the level of acceptance by physicians was documented.

RESULTS

During the study, 1430 alerts were analysed: 186 (13%) were considered to be technically invalid - mainly due to the characteristics of the interface. Of the 1244 (87.0%) technically valid alerts, 353 (24.6%) were pharmaceutically relevant and led to a PI. The three main causes of pharmaceutical irrelevance were a lack of specificity in the CDSS (70.8%), lack of relevance with regard to the ward's habits (15.6%), and the pharmacist's decision to recommend monitoring for the patient rather than sending a PI immediately (10.8%). 64.6% of the submitted PIs were accepted by the physicians.

CONCLUSION

The standardized analysis of alerts by a clinical pharmacist appears to be a good way of improving the development of CDSS by limiting the generation of irrelevant alerts and the latter's transmission to physicians. The involvement of a clinical pharmacist in the development and implementation of a CDSS appears to be novel and may help to optimize drug treatment.

Analysis of Patient Safety Incidents in Primary Care Reported in an Electronic Registry Application

OBJECTIVES

(1) To describe the epidemiology of patient safety (PS) incidents registered in an electronic notification system in primary care (PC) health centres; (2) to define a risk map; and (3) to identify the critical areas where intervention is needed.

DESIGN

Descriptive analytical study of incidents reported from 1 January to 31 December 2018, on the TPSC Cloud™ platform (The Patient Safety Company) accessible from the corporate website (Intranet) of the regional public health service.

SETTING

24 Catalan Institute of Health PC health centres of the Tarragona region (Spain).

PARTICIPANTS

Professionals from the PC health centres and a Patient Safety Functional Unit.

MEASUREMENTS

Data obtained from records voluntarily submitted to an electronic, standardised and anonymised form. Data recorded: healthcare unit, notifier, type of incident, risk matrix, causal and contributing factors, preventability, level of resolution and improvement actions.

RESULTS

A total of 1544 reports were reviewed and 1129 PS incidents were analysed: 25.0% of incidents did not reach the patient; 66.5% reached the patient without causing harm, and 8.5% caused adverse events. Nurses provided half of the reports (48.5%), while doctors reported more adverse events (70.8%; p < 0.01). Of the 96 adverse events, 46.9% only required observation, 34.4% caused temporary damage that required treatment, 13.5% required (or prolonged) hospitalization, and 5.2% caused severe permanent damage and/or a situation close to death. Notably, 99.2% were considered preventable. The main critical areas were: communication (27.8%), clinical-administrative management (25.1%), care delivery (23.5%) and medicines (18.4%); few incidents were related to diagnosis (3.6%).

CONCLUSIONS

PS incident notification applications are adequate for reporting incidents and adverse events associated with healthcare. Approximately 75% and 10% of incidents reach the patient and cause some damage, respectively, and most cases are considered preventable. Adequate and strengthened risk management of critical areas is required to improve PS.

Effect of Electronic Prescribing Compared to Paper-Based (Handwritten) Prescribing on Primary Medication Adherence in an Outpatient Setting: A Systematic Review

BACKGROUND

Electronic prescriptions are often created and delivered electronically to the pharmacy while paper-based/handwritten prescriptions may be delivered to the pharmacy by the patients. These differences in the mode of creation and transmission of the two types of prescription could influence the rate at which outpatients fill new prescriptions of previously untried medications.

OBJECTIVES

This study aimed to evaluate literatures to determine the impact of electronic prescribing compared with paper-based/handwritten prescribing on primary medication adherence in an outpatient setting.

METHODS

The keywords and phrases "outpatients," "e-prescriptions," "paper-based prescriptions," and "primary medication adherence" were combined with their relevant synonyms and medical subject headings. A comprehensive literature search was conducted on EMBASE, CINAHL, and MEDLINE databases, and Google Scholar. The results of the search were screened and selected using predefined inclusion and exclusion criteria. The Critical Appraisal Skills Program (CASP) was used for quality appraisal of included studies. Data relevant to the objective of the review were extracted and analyzed through narrative synthesis.

RESULTS

A total of 10 original studies were included in the final review, including 1 prospective randomized study and 9 observational studies. Nine of the 10 studies were performed in the United States. Four of the studies indicated that electronic prescribing significantly increases initial medication adherence, while four of the studies suggested the opposite. The remaining two studies found no significant difference in primary medication adherence between the two methods of prescribing. The variations in the studies did not allow the homogeneity required for meta-analysis to be achieved.

CONCLUSION

The conflicting findings relating to the efficacy of primary medication adherence across both systems demonstrate the need for a standardized measure of medication adherence. This would help further determine the respective benefits of both approaches. Future research should also be conducted in different countries to give a more accurate representation of adherence.

Predicting self-intercepted medication ordering errors using machine learning

Current approaches to understanding medication ordering errors rely on relatively small manually captured error samples. These approaches are resource-intensive, do not scale for computerized provider order entry (CPOE) systems, and are likely to miss important risk factors associated with medication ordering errors. Previously, we described a dataset of CPOE-based medication voiding accompanied by univariable and multivariable regression analyses. However, these traditional techniques require expert guidance and may perform poorly compared to newer approaches. In this paper, we update that analysis using machine learning (ML) models to predict erroneous medication orders and identify its contributing factors. We retrieved patient demographics (race/ethnicity, sex, age), clinician characteristics, type of medication order (inpatient, prescription, home medication by history), and order content. We compared logistic regression, random forest, boosted decision trees, and artificial neural network models. Model performance was evaluated using area under the receiver operating characteristic curve (AUROC) and the area under the precision-recall curve (AUPRC). The dataset included 5,804,192 medication orders, of which 28,695 (0.5%) were voided. ML correctly classified voids at reasonable accuracy; with a positive predictive value of 10%, ~20% of errors were included. Gradient boosted decision trees achieved the highest AUROC (0.7968) and AUPRC (0.0647) among all models. Logistic regression had the poorest performance. Models identified predictive factors with high face validity (e.g., student orders), and a decision tree revealed interacting contexts with high rates of errors not identified by previous regression models. Prediction models using order-entry information offers promise for error surveillance, patient safety improvements, and targeted clinical review. The improved performance of models with complex interactions points to the importance of contextual medication ordering information for understanding contributors to medication errors.

How effective are electronic medication systems in reducing medication error rates and associated harm among hospital inpatients? A systematic review and meta-analysis

OBJECTIVE

To conduct a systematic review and meta-analysis to assess: 1) changes in medication error rates and associated patient harm following electronic medication system (EMS) implementation; and 2) evidence of system-related medication errors facilitated by the use of an EMS.

MATERIALS AND METHODS

We searched Medline, Scopus, Embase, and CINAHL for studies published between January 2005 and March 2019, comparing medication errors rates with or without assessments of related harm (actual or potential) before and after EMS implementation. EMS was defined as a computer-based system enabling the prescribing, supply, and/or administration of medicines. Study quality was assessed.

RESULTS

There was substantial heterogeneity in outcomes of the 18 included studies. Only 2 were strong quality. Meta-analysis of 5 studies reporting change in actual harm post-EMS showed no reduced risk (RR: 1.22, 95% CI: 0.18-8.38, P = .8) and meta-analysis of 3 studies reporting change in administration errors found a significant reduction in error rates (RR: 0.77, 95% CI: 0.72-0.83, P = .004). Of 10 studies of prescribing error rates, 9 reported a reduction but variable denominators precluded meta-analysis. Twelve studies provided specific examples of system-related medication errors; 5 quantified their occurrence.

DISCUSSION AND CONCLUSION

Despite the wide-scale adoption of EMS in hospitals around the world, the quality of evidence about their effectiveness in medication error and associated harm reduction is variable. Some confidence can be placed in the ability of systems to reduce prescribing error rates. However, much is still unknown about mechanisms which may be most effective in improving medication safety and design features which facilitate new error risks.

A Retrospective Study of Pediatric Medication Errors in Saudi Arabia

Background: The peculiarities of medication errors (MEs) among the pediatric population in the Middle East have not been adequately explored. In this study, we describe the MEs reported at the largest tertiary hospital in Saudi Arabia. Methods: This study is a retrospective analysis of MEs reported by health care professionals at a large tertiary hospital in Saudi Arabia between 2015 and 2016. Results: There were a total of 9123 MEs involving 84 different medications. In total, 109 382 drugs were ordered. Thus, 8.3 MEs per 100 prescriptions were reported during the study period. Thirty-nine errors (0.4%) reached the patient, but did not cause any harm. Transcribing errors accounted for more than half of the MEs (n = 4856, 53.2%). Physicians were the least likely to report an ME (n = 159, 1.7%), whereas pharmacists reported more MEs than any other health care professional (n = 4924, 54%). The most common drug causes of MEs were paracetamol, salbutamol, and amoxicillin, which accounted for 21.0%, 16.6%, and 12.4% of MEs, respectively, over the study period. Conclusions: Medication errors are common in pediatric care, especially for drugs such as paracetamol and amoxicillin that are frequently prescribed. Transcription error was common in this study and is more likely to be reported by pharmacists.

The effectiveness of interruptive prescribing alerts in ambulatory CPOE to change prescriber behaviour & improve safety

BACKGROUND

Prescribing alerts of an electronic health record are meant to be protective, but often are disruptive to providers. Our goal was to assess the effectiveness of interruptive medication-prescriber alerts in changing prescriber behaviour and improving patient outcomes in ambulatory care settings via computerised provider order entry (CPOE) systems.

METHODS

A standardised search strategy was developed and applied to the following key bibliographical databases: PubMed, Embase, CINAHL and The Cochrane Library. Non-comparison studies and studies on non-interrupted alerts were eliminated. We developed a standardised data collection form and abstracted data that included setting, study design, category of intervention alert and outcomes measured. The search was completed in August 2018 and repeated in November of 2019 and of 2020 to identify any new publications during the time lapse.

RESULTS

Ultimately, nine comparison studies of triggered alerts were identified. Each studied at least one outcome measure illustrating how the alert affected prescriber decision-making. Provider behaviour was influenced in the majority, with most noting a positive change. Alerts decreased pharmaceutical costs, moved medications toward preferred medications tiers and steered treatments toward evidence-based choices. They also decreased prescribing errors. Clinician feedback, rarely solicited, expressed frustration with alerts creating a time delay.

CONCLUSION

The current evidence shows a clear indication that many categories of alerts are effective in changing prescriber behaviour. However, it is unclear whether these behavioural changes lead to improved patient outcomes. Despite the rapid transition to CPOE use for patient care, there are few rigorous studies of triggered alerts and how workflow interruptions impact patient outcomes and provider acceptance.

The impact of computerised physician order entry on prescribing in general paediatric units in Hong Kong

OBJECTIVES

This study aimed to evaluate the effect of a closed-loop computerised physician order entry (CPOE) system on prescribing in a general paediatric unit in Hong Kong. We studied the effect of the CPOE system on medication prescribing error and the characteristics of these errors before and after the implementation of the system.

METHODS

This was a single-site, prospective, observational study at a public hospital's general paediatric unit in Hong Kong, conducted during the pre- and post-implementation of the system from March to April 2019 and 2020, respectively. Collected data included the number of medication orders processed, the number of prescribing errors identified, and the characteristics of errors, such as the severity, children's age group, drug formulation, and drug class.

KEY FINDINGS

The prescribing error rate was significantly reduced from 6.7% to 3.9% after CPOE implementation. The causes of prescribing errors were found to be significantly different, as the implementation eradicated handwriting-related errors and reduced dosage selection-related errors. However, we found that CPOE increased other causes of error, such as missing entry of patient information that might affect the dispensing process, thus delaying patients in receiving their medications on time.

CONCLUSION

The CPOE system significantly reduced prescribing errors and altered some of the characteristics of these errors. Poor system design or inadequate user training could result in the creation of new causes of error.