Experiences and Outcomes of Using e-Prescribing for Opioids: Rapid Scoping Review

BACKGROUND

e-Prescribing is designed to assist in facilitating safe and appropriate prescriptions for patients. Currently, it is unknown to what extent e-prescribing for opioids influences experiences and outcomes. To address this gap, a rapid scoping review was conducted.

OBJECTIVE

This rapid scoping review aims to (1) explore how e-prescribing has been used clinically; (2) examine the effects of e-prescribing on clinical outcomes, the patient or clinician experience, service delivery, and policy; and (3) identify current gaps in the present literature to inform future studies and recommendations.

METHODS

A rapid scoping review was conducted following the guidance of the JBI 2020 scoping review methodology and the World Health Organization guide to rapid reviews. A comprehensive literature search was completed by an expert librarian from inception until November 16, 2022. Three databases were electronically searched: MEDLINE (Ovid), Embase (Ovid), and Scopus (Elsevier). The search criteria were as follows: (1) e-prescribing programs targeted to the use or misuse of opioids, including those that were complemented or accompanied by clinically focused initiatives, and (2) a primary research study of experimental, quasi-experimental, observational, qualitative, or mixed methods design. An additional criterion of an ambulatory component of e-prescribing (eg, e-prescribing occurred upon discharge from acute care) was added at the full-text stage. No language limitations or filters were applied. All articles were double screened by trained reviewers. Gray literature was manually searched by a single reviewer. Data were synthesized using a descriptive approach.

RESULTS

Upon completing screening, 34 articles met the inclusion criteria: 32 (94%) peer-reviewed studies and 2 (6%) gray literature documents (1 thesis study and 1 report). All 33 studies had a quantitative component, with most highlighting e-prescribing from acute care settings to community settings (n=12, 36%). Only 1 (3%) of the 34 articles provided evidence on e-prescribing in a primary care setting. Minimal prescriber, pharmacist, and clinical population characteristics were reported. The main outcomes identified were related to opioid prescribing rates, alerts (eg, adverse drug events and drug-drug interactions), the quantity and duration of opioid prescriptions, the adoption of e-prescribing technology, attitudes toward e-prescribing, and potential challenges with the implementation of e-prescribing into clinical practice. e-Prescribing, including key features such as alerts and dose order sets, may reduce prescribing errors.

CONCLUSIONS

This rapid scoping review highlights initial promising results with e-prescribing and opioid therapy management. It is important that future work explores the experience of prescribers, pharmacists, and patients using e-prescribing for opioid therapy management with an emphasis on prescribers in the community and primary care. Developing a common set of quality indicators for e-prescribing of opioids will help build a stronger evidence base. Understanding implementation considerations will be of importance as the technology is integrated into clinical practice and health systems.

The impact of health information technology on prescribing errors in hospitals: a systematic review and behaviour change technique analysis

BACKGROUND

Health information technology (HIT) is known to reduce prescribing errors but may also cause new types of technology-generated errors (TGE) related to data entry, duplicate prescribing, and prescriber alert fatigue. It is unclear which component behaviour change techniques (BCTs) contribute to the effectiveness of prescribing HIT implementations and optimisation. This study aimed to (i) quantitatively assess the HIT that reduces prescribing errors in hospitals and (ii) identify the BCTs associated with effective interventions.

METHODS

Articles were identified using CINAHL, EMBASE, MEDLINE, and Web of Science to May 2020. Eligible studies compared prescribing HIT with paper-order entry and examined prescribing error rates. Studies were excluded if prescribing error rates could not be extracted, if HIT use was non-compulsory or designed for one class of medication. The Newcastle-Ottawa scale was used to assess study quality. The review was reported in accordance with the PRISMA and SWiM guidelines. Odds ratios (OR) with 95% confidence intervals (CI) were calculated across the studies. Descriptive statistics were used to summarise effect estimates. Two researchers examined studies for BCTs using a validated taxonomy. Effectiveness ratios (ER) were used to determine the potential impact of individual BCTs.

RESULTS

Thirty-five studies of variable risk of bias and limited intervention reporting were included. TGE were identified in 31 studies. Compared with paper-order entry, prescribing HIT of varying sophistication was associated with decreased rates of prescribing errors (median OR 0.24, IQR 0.03-0.57). Ten BCTs were present in at least two successful interventions and may be effective components of prescribing HIT implementation and optimisation including prescriber involvement in system design, clinical colleagues as trainers, modification of HIT in response to feedback, direct observation of prescriber workflow, monitoring of electronic orders to detect errors, and system alerts that prompt the prescriber.

CONCLUSIONS

Prescribing HIT is associated with a reduction in prescribing errors in a variety of hospital settings. Poor reporting of intervention delivery and content limited the BCT analysis. More detailed reporting may have identified additional effective intervention components. Effective BCTs may be considered in the design and development of prescribing HIT and in the reporting and evaluation of future studies in this area.

Medication safety improvements during care transitions in an Australian intensive care unit following implementation of an electronic medication management system

BACKGROUND

For patients requiring admission to the Intensive Care Unit (ICU), transfers of care (TOC) during admission to and discharge from the ICU are particularly high-risk periods for medication errors. In the Australian setting, commonly general wards and the ICU do not share an integrated Electronic Medical ecord (EMR) and specifically an Electronic Medication Management System (EMMS) as part of the EMR.

PURPOSE

To evaluate the effect of a hospital wide integrated EMMS on medication error rates during ICU admission and at TOC.

METHOD

A 6-month historical control study was performed before and after implementation of the EMMS in the ICU of a tertiary hospital. Prescribing errors detected by pharmacists in the study period were divided into phase 1, (pre-EMMS, 6months), phase 2 (3 months post implementation after shakedown stage) and phase 3 (next 3 months of post implementation). They were categorized as prescribing error types under system or clinical intervention. Chi square statistics and interrupted time series analysis were used to determine if there was significant change in the proportion of patients who had an error at TOC during each phase. Logistics regression was used to determine the relationship between the dependent (error type) and the independent variable (study phase) for errors that occurred during TOC.

RESULTS

Errors occurred during TOC in 42 %, 64 % and 19 % of patients in phase 1, 2 and 3 respectively. There was a significant decline in the proportion of patients with an error between phase 1 and 3 (p < 0.01). During a patient's ICU admission, at least one medication error occurred in 28.3 %, 62.6 % and 25.1 % in phase 1, 2 and 3 respectively. Besides procedural errors, the likelihood of an error occurring was greatest in phase 1, compared to phase 2 and 3 across system-related error categories.

CONCLUSION

Medication errors during TOC reduced following implementation of the integrated ICU EMMS. EMMS safety features facilitated reduced system related prescribing errors as well as the severity of errors made.

Standardising the Classification of Harm Associated with Medication Errors: The Harm Associated with Medication Error Classification (HAMEC)

Classifying harm associated with a medication error can be time consuming and labour intensive and limited studies undertake this step. There is no standardised process, and few studies that report harm assessment provide adequate methods to allow for study replication. Studies typically mention that a clinical review panel classified patient harm and provide a reference to a classification tool. Moreover, in many studies it is unclear whether potential or actual harm was classified as studies refer only to ‘error severity’. The tools used to categorise the severity of patient harm vary widely across studies and few have been assessed for inter-rater reliability and criterion validity. In this paper, we describe the systematic process we undertook to synthesise the defining elements and strengths, while mitigating the limitations, of existing harm classification tools to derive the Harm Associated with Medication Error Classification (HAMEC). This new tool provides a harm classification for use across clinical and research settings. The provision of an explicit process for its application and guiding category descriptors are designed to reduce the risk of misclassification and produce results that are comparable across studies. As the World Health Organisation embarks on its international safety challenge of reducing medication-related harm by 50%, accompanying methodological advances are required to measure progress.

Patient and clinician perspectives of an integrated electronic medication prescribing and dispensing system: A qualitative study at a multisite Australian hospital network

BACKGROUND:

While clinician attitudes towards electronic prescribing (e-prescribing) systems have been widely studied, little is known about the perspectives of patients, despite being the primary beneficiaries of these systems.

OBJECTIVE:

The objective of this study is to explore and compare patient and clinician attitudes towards an integrated e-prescribing and dispensing system, in order to guide improvements in system implementation, service delivery and enhancements to system functionality.

METHOD:

A cross-sectional survey was developed and administered to patients and multidisciplinary clinicians at a multisite Australian metropolitan teaching hospital network in all areas where e-prescribing was fully implemented. Participants' views on perceived impact and valued features of the e-prescribing system were elucidated.

RESULTS:

Overall, 783 participants (400 patients and 383 clinicians) completed the survey. Although 98% of clinicians were aware of the transition to e-prescriptions, only 36% of patients were aware prior to the study. Over 80% of patients and clinicians perceived improvements in prescribing and dispensing safety and clinician workflow; 90% of patients were comfortable with information privacy associated with e-prescriptions; and 86% of patients preferred e-prescriptions to handwritten prescriptions. Although over 80% of patients valued features that improved access to information and medication safety, clinicians were more discerning about valued system features.

CONCLUSION:

The majority of patients and clinicians reported a positive impact of e-prescribing on safety and efficiency. Both groups valued safe and effective use of medicines, although differences existed in the importance placed on key system features. A greater focus on patient engagement and communication is needed to optimise the delivery of patient-centred care.