Prevention of adverse drug reactions in intensive care patients by personal intervention based on an electronic clinical decision support system. Intensive Care Med. 2010;36:665-672. [PMID: 20143221 DOI: 10.1007/s00134-010-1778-8]

Applying the Non-Adoption, Abandonment, Scale-up, Spread, and Sustainability Framework Across Implementation Stages to Identify Key Strategies to Facilitate Clinical Decision Support System Integration Within a Large Metropolitan Health Service: Interview and Focus Group Study

BACKGROUND

Computerized clinical decision support systems (CDSSs) enhance patient care through real-time, evidence-based guidance for health care professionals. Despite this, the effective implementation of these systems for health services presents multifaceted challenges, leading to inappropriate use and abandonment over the course of time. Using the Non-Adoption, Abandonment, Scale-Up, Spread, and Sustainability (NASSS) framework, this qualitative study examined CDSS adoption in a metropolitan health service, identifying determinants across implementation stages to optimize CDSS integration into health care practice.

OBJECTIVE

This study aims to identify the theory-informed (NASSS) determinants, which included multiple CDSS interventions across a 2-year period, both at the health-service level and at the individual hospital setting, that either facilitate or hinder the application of CDSSs within a metropolitan health service. In addition, this study aimed to map these determinants onto specific stages of the implementation process, thereby developing a system-level understanding of CDSS application across implementation stages.

METHODS

Participants involved in various stages of the implementation process were recruited (N=30). Participants took part in interviews and focus groups. We used a hybrid inductive-deductive qualitative content analysis and a framework mapping approach to categorize findings into barriers, enablers, or neutral determinants aligned to NASSS framework domains. These determinants were also mapped to implementation stages using the Active Implementation Framework stages approach.

RESULTS

Participants comprised clinical adopters (14/30, 47%), organizational champions (5/30, 16%), and those with roles in organizational clinical informatics (5/30, 16%). Most determinants were mapped to the organization level, technology, and adopter subdomains. However, the study findings also demonstrated a relative lack of long-term implementation planning. Consequently, determinants were not uniformly distributed across the stages of implementation, with 61.1% (77/126) identified in the exploration stage, 30.9% (39/126) in the full implementation stage, and 4.7% (6/126) in the installation stages. Stakeholders engaged in more preimplementation and full-scale implementation activities, with fewer cycles of monitoring and iteration activities identified.

CONCLUSIONS

These findings addressed a substantial knowledge gap in the literature using systems thinking principles to identify the interdependent dynamics of CDSS implementation. A lack of sustained implementation strategies (ie, training and longer-term, adopter-level championing) weakened the sociotechnical network between developers and adopters, leading to communication barriers. More rigorous implementation planning, encompassing all 4 implementation stages, may, in a way, help in addressing the barriers identified and enhancing enablers.

The PrescIT platform: An interoperable Clinical Decision Support System for ePrescription to Prevent Adverse Drug Reactions and Drug-Drug Interactions

INTRODUCTION

Preventable medication errors have been proven to cause significant public health burden, and ePrescription is a key part of the process where medication errors and adverse effects could be prevented. Information systems and "intelligent" computational approaches could provide a valuable tool to prevent such errors with profound impact in clinical practice.

OBJECTIVES

The PrescIT platform is a Clinical Decision Support System (CDSS) that aims to facilitate the prevention of adverse drug reactions (ADRs) and drug-drug interactions (DDIs) in the phase of ePrescription in Greece. The proposed platform could be relatively easily localized for use in other contexts too.

METHODS

The PrescIT platform is based on the use of Knowledge Engineering (ΚΕ) approaches, i.e., the use of Ontologies and Knowledge Graphs (KGs) developed upon openly available data sources. Open standards (i.e., RDF, OWL, SPARQL) are used for the development of the platform enabling the integration with already existing IT systems or for standalone use. The main KG is based on the use of DrugBank, MedDRA, SemMedDB and OpenPVSignal. In addition, the Business Process Management Notation (BPMN) has been used to model long-term therapeutic protocols used during the ePrescription process. Finally, the produced software has been pilot tested in three hospitals by 18 clinical professionals via in-person think-aloud sessions.

RESULTS

The PrescIT platform has been successfully integrated in a transparent fashion in a proprietary Hospital Information System (HIS), and it has also been used as a standalone application. Furthermore, it has been successfully integrated with the Greek National ePrescription system. During the pilot phase, one psychiatric therapeutic protocol was used as a testbed to collect end-users' feedback. Summarizing the feedback from the end-users, they have generally acknowledged the usefulness of such a system while also identifying some challenges in terms of usability and the overall user experience.

CONCLUSIONS

The PrescIT platform has been successfully deployed and piloted in real-world environments to evaluate its ability to support safer medication prescriptions.

The comorbidity and co-medication profile of patients with progressive supranuclear palsy

BACKGROUND

Progressive supranuclear palsy (PSP) is usually diagnosed in elderly. Currently, little is known about comorbidities and the co-medication in these patients.

OBJECTIVES

To explore the pattern of comorbidities and co-medication in PSP patients according to the known different phenotypes and in comparison with patients without neurodegenerative disease.

METHODS

Cross-sectional data of PSP and patients without neurodegenerative diseases (non-ND) were collected from three German multicenter observational studies (DescribePSP, ProPSP and DANCER). The prevalence of comorbidities according to WHO ICD-10 classification and the prevalence of drugs administered according to WHO ATC system were analyzed. Potential drug-drug interactions were evaluated using AiDKlinik®.

RESULTS

In total, 335 PSP and 275 non-ND patients were included in this analysis. The prevalence of diseases of the circulatory and the nervous system was higher in PSP at first level of ICD-10. Dorsopathies, diabetes mellitus, other nutritional deficiencies and polyneuropathies were more frequent in PSP at second level of ICD-10. In particular, the summed prevalence of cardiovascular and cerebrovascular diseases was higher in PSP patients. More drugs were administered in the PSP group leading to a greater percentage of patients with polypharmacy. Accordingly, the prevalence of potential drug-drug interactions was higher in PSP patients, especially severe and moderate interactions.

CONCLUSIONS

PSP patients possess a characteristic profile of comorbidities, particularly diabetes and cardiovascular diseases. The eminent burden of comorbidities and resulting polypharmacy should be carefully considered when treating PSP patients.

A prospective intervention study to identify drug-related emergency department visits comparing a standard care group and a pharmaceutical care group

BACKGROUND AND IMPORTANCE

Adverse drug reactions impose a major burden. Those adverse drug reactions might lead to hospitalization but are often not correctly identified in the emergency department (ED). Clinical pharmacists, although not routinely implemented, can help identify adverse drug reactions.

OBJECTIVE

The primary objective was to examine the drug association of ED visits in a pharmaceutical group with a clinical pharmacist integrated in the ED team compared with a standard group without additional support.

DESIGN/SETTING/PARTICIPANTS

This prospective intervention study was performed in the ED of a tertiary care university hospital in Leipzig, Germany. Patients who were ≥50 years old were included. From 1 March 2020 to May 31, 2020 patients were enrolled in the standard group. From 1 March 2021 to 31 May 2021, the pharmaceutical group was enrolled. The clinical pharmacist supported the ED team with patient´s detailed medication history and medication analysis. In both groups, patients were evaluated whether their ED visit was drug-related.

OUTCOME MEASURES AND ANALYSIS

The number of identified drug-related ED presentations were compared between the two groups. Interventions performed on adverse drug reaction management, causative drugs and patient characteristics were evaluated.

MAIN RESULTS

A total of 798 patients were enrolled in the standard group and 827 patients in the pharmaceutical group. Patients whose ED visit was drug-related had a median age of 77 years [(Q25-Q75) 63.5-83.5] and took 7 [(Q25-Q75) 5-8] drugs in standard group. In the pharmaceutical group median age was 78 years [(Q25-Q75) 66-83] and number of drugs taken was 9 [(Q25-Q75) 5.25-11]. 31 (3.9%) drug-related ED visits were identified in the standard group compared to 104 (12.6%) in the pharmaceutical group (OR 3.56; 95% CI 2.35-5.38). An intervention on the patient's pharmacotherapy was performed in 16 drug-related ED visits in standard group compared to 77 in the pharmaceutical group.

CONCLUSION

In this study the implementation of a clinical pharmacist was associated with improved identification of drug-related ED visits. Discontinuations of causal medications and dose reductions were significantly higher in the pharmaceutical group compared to the standard care group.

Using Theories, Models, and Frameworks to Inform Implementation Cycles of Computerized Clinical Decision Support Systems in Tertiary Health Care Settings: Scoping Review

BACKGROUND

Computerized clinical decision support systems (CDSSs) are essential components of modern health system service delivery, particularly within acute care settings such as hospitals. Theories, models, and frameworks may assist in facilitating the implementation processes associated with CDSS innovation and its use within these care settings. These processes include context assessments to identify key determinants, implementation plans for adoption, promoting ongoing uptake, adherence, and long-term evaluation. However, there has been no prior review synthesizing the literature regarding the theories, models, and frameworks that have informed the implementation and adoption of CDSSs within hospitals.

OBJECTIVE

This scoping review aims to identify the theory, model, and framework approaches that have been used to facilitate the implementation and adoption of CDSSs in tertiary health care settings, including hospitals. The rationales reported for selecting these approaches, including the limitations and strengths, are described.

METHODS

A total of 5 electronic databases were searched (CINAHL via EBSCOhost, PubMed, Scopus, PsycINFO, and Embase) to identify studies that implemented or adopted a CDSS in a tertiary health care setting using an implementation theory, model, or framework. No date or language limits were applied. A narrative synthesis was conducted using full-text publications and abstracts. Implementation phases were classified according to the "Active Implementation Framework stages": exploration (feasibility and organizational readiness), installation (organizational preparation), initial implementation (initiating implementation, ie, training), full implementation (sustainment), and nontranslational effectiveness studies.

RESULTS

A total of 81 records (42 full text and 39 abstracts) were included. Full-text studies and abstracts are reported separately. For full-text studies, models (18/42, 43%), followed by determinants frameworks (14/42,33%), were most frequently used to guide adoption and evaluation strategies. Most studies (36/42, 86%) did not list the limitations associated with applying a specific theory, model, or framework.

CONCLUSIONS

Models and related quality improvement methods were most frequently used to inform CDSS adoption. Models were not typically combined with each other or with theory to inform full-cycle implementation strategies. The findings highlight a gap in the application of implementation methods including theories, models, and frameworks to facilitate full-cycle implementation strategies for hospital CDSSs.

Adverse drug reactions and correlations with drug–drug interactions: A retrospective study of reports from 2011 to 2020

Introduction: Adverse drug reactions (ADRs) represent a public health problem worldwide that deserves attention due to the impact on mortality, morbidity, and healthcare costs. Drug–drug interactions (DDIs) are an important contributor to ADRs. Most of the studies focused only on potential DDIs (pDDIs), while the detailed data are limited regarding the ADRs associated with actual DDIs.

Methods: This retrospective study evaluated ADRs reported between 2011 and 2020 in a tertiary hospital. The causality and severity of ADRs were evaluated through the Naranjo Algorithm and Hartwig’s scale, respectively. Preventability classification was based on the modified Schoumock and Thornton scale. For ADRs with at least two suspected drugs, pDDIs were identified according to the Lexi-Interact. We further checked whether the ADR description in the reports corresponded to the clinical consequences of the pDDIs.

Results: A total of 1,803 ADRs were reported, of which 36.77% ADRs were classified as mild, 43.26% as moderate, and 19.97% as severe. The assessment of causality showed that the distributions of definite, probable, and possible categories were 0.33%, 58.68%, and 40.99%, respectively. A total of 53.97% of ADRs were identified as preventable ADRs, while 46.03% were recognized as unpreventable. The severity of ADRs was significantly correlated with age, the number of suspected drugs and preventability. Antimicrobial agents were the most common implicated pharmacological group, and the most frequently affected system was the gastrointestinal system. Considering individual drugs, aspirin was the most frequently reported drug. Among 573 ADRs with at least two suspected drugs, 105 ADRs were caused by actual DDIs, of which only 59 and 6 ADRs were caused by actual DDIs in category D and X, respectively. The most frequent drugs involved in actual DDIs of category D were aspirin and heparin, with the majority of ADRs being gastrointestinal bleeding.

Conclusion: This study analyzed the pattern of ADRs in detail and obtained clinical evidence about ADRs associated with actual DDIs. These findings may be useful to compare patterns between different centers and to design preventive strategies for ADRs. Continuous education and training should be provided for physicians regarding the knowledge and recognition of ADRs associated with DDIs.

Risk assessment tools for QT prolonging pharmacotherapy in older adults: a systematic review

Purpose

Many drugs are associated with the risk of QT prolongation and torsades de pointes (TdP), and different risk assessment tools (RATs) are developed to help clinicians to manage related risk. The aim of this systematic review was to summarize the evidence of different RATs for QT prolonging pharmacotherapy.

Methods

A systematic review was conducted using PubMed and Scopus databases. Studies concerning risk assessment tools for QT prolonging pharmacotherapy, including older adults, were included. Screening and selection of the studies, data extraction, and risk of bias assessment were undertaken.

Results

A total of 21 studies were included, involving different risk assessment tools. Most commonly used tools were risk scores (n = 9), computerized physician order entry systems (n = 3), and clinical decision support systems (n = 6). The tools were developed mainly for physicians and pharmacists. Risk scores included a high number of risk factors, both pharmacological and non-pharmacological, for QT prolongation and TdP. The inclusion of patients’ risk factors in computerized physician order entry and clinical decision support systems varied.

Conclusion

Most of the risk assessment tools for QT prolonging pharmacotherapy give a comprehensive overview of patient-specific risks of QT prolongation and TdP and reduce modifiable risk factors and actual events. The risk assessment tools could be better adapted to different health information systems to help in clinical decision-making. Further studies on clinical validation of risk assessment tools with randomized controlled trials are needed.

Supplementary Information

The online version contains supplementary material available at 10.1007/s00228-022-03285-3.

The Acceptance of Interruptive Medication Alerts in an Electronic Decision Support System Differs between Different Alert Types

BACKGROUND

 Through targeted medication alerts, clinical decision support systems (CDSS) help users to identify medication errors such as disregarded drug-drug interactions (DDIs). Override rates of such alerts are high; however, they can be mitigated by alert tailoring or workflow-interrupting display of severe alerts that need active user acceptance or overriding. Yet, the extent to which the displayed alert interferes with the prescribers' workflow showed inconclusive impact on alert acceptance.

OBJECTIVES

 We aimed to assess whether and how often prescriptions were changed as a potential result of interruptive alerts on different (contraindicated) prescription constellations with particularly high risks for adverse drug events (ADEs).

METHODS

 We retrospectively collected data of all interruptive alerts issued between March 2016 and August 2020 in the local CDSS (AiDKlinik) at Heidelberg University Hospital. The alert battery consisted of 31 distinct alerts for contraindicated DDI with simvastatin, potentially inappropriate medication for patients > 65 years (PIM, N = 14 drugs and 36 drug combinations), and contraindicated drugs in hyperkalemia (N = 5) that could be accepted or overridden giving a reason in free-text form.

RESULTS

 In 935 prescribing sessions of 500 274 total sessions, at least one interruptive alert was fired. Of all interruptive alerts, about half of the sessions were evaluable whereof in total 57.5% (269 of 468 sessions) were accepted while 42.5% were overridden. The acceptance rate of interruptive alerts differed significantly depending on the alert type (p <0.0001), reaching 85.7% for DDI alerts (N = 185), 65.3% for contraindicated drugs in hyperkalemia (N = 98), and 25.1% for PIM alerts (N = 185).

CONCLUSION

 A total of 57.5% of the interruptive medication alerts with particularly high risks for ADE in our setting were accepted while the acceptance rate differed according to the alert type with contraindicated simvastatin DDI alerts being accepted most frequently.

Investigating Potential Drug-Drug Interactions from Greek e-Prescription Data

BACKGROUND

The prevalence of potential drug-drug interactions (pDDIs) is indicative of the prevalence of actual drug-drug interactions and prescription quality. However, they are significantly understudied in Greece.

OBJECTIVE

To determine the prevalence of pDDIs among outpatients and identify factors associated with their occurrence.

METHODS

Anonymous e-prescription data between 2012 and 2017 were obtained from community pharmacies in Thessaloniki, Greece. Patients taking more than one medication for at least three months were included. pDDIs were identified and categorized depending on their clinical significance using Drug Interactions Checker. Crude and adjusted odds ratios (ORs) with accompanying 95% confidence intervals (CIs) of risk factors of pDDIs occurrence were identified using multivariable logistic regression.

RESULTS

During the study period, 6,000 anonymous e-prescriptions (1,000 per year) satisfying the inclusion criteria, were collected. The overall prevalence of major pDDIs was 17.4% (63.0% for moderate pDDIs). The most common major pDDIs were between amlodipine and simvastatin (22.8% of major interactions) followed by clopidogrel and omeprazole (6.4% of major interactions). Polypharmacy (≥5 concomitantly received medications) was associated with an increased risk of major pDDIs (adjusted OR, 5.72; 95% CI, 4.87-6.72); no associations were observed regarding age, sex and number of prescribing physicians.

CONCLUSION

The prevalence of pDDIs in this study was higher than previously reported in other European countries, with polypharmacy being a potential risk factor. Those results argue for a need for improvement in the area of prescribing in Greece.

Assessing Prescriber Behavior with a Clinical Decision Support Tool to Prevent Drug-Induced Long QT Syndrome

OBJECTIVE

Clinical decision support (CDS) alerts built into the electronic health record (EHR) have the potential to reduce the risk of drug-induced long QT syndrome (diLQTS) in susceptible patients. However, the degree to which providers incorporate this information into prescription behavior and the impact on patient outcomes is often unknown.

METHODS

We examined provider response data over a period from October 8, 2016 until November 8, 2018 for a CDS alert deployed within the EHR from a 13-hospital integrated health care system that fires when a patient with a QTc ≥ 500 ms within the past 14 days is prescribed a known QT-prolonging medication. We used multivariate generalized estimating equations to analyze the impact of therapeutic alternatives, relative risk of diLQTS for specific medications, and patient characteristics on provider response to the CDS and overall patient mortality.

RESULTS

The CDS alert fired 15,002 times for 7,510 patients for which the most common response (51.0%) was to override the alert and order the culprit medication. In multivariate models, we found that patient age, relative risk of diLQTS, and presence of alternative agents were significant predictors of adherence to the CDS alerts and that nonadherence itself was a predictor of mortality. Risk of diLQTS and presence of an alternative agent are major factors in provider adherence to a CDS to prevent diLQTS; however, provider nonadherence was associated with a decreased risk of mortality.

CONCLUSION

Surrogate endpoints, such as provider adherence, can be useful measures of CDS value but attention to hard outcomes, such as mortality, is likely needed.

Identifying and Characterizing Serious Adverse Drug Reactions Associated With Drug-Drug Interactions in a Spontaneous Reporting Database

Background: Drug-drug interactions (DDIs) are an important cause of adverse drug reactions (ADRs). In literature most of studies focus only on potential DDIs, while detailed data on serious ADRs associated with DDIs are limited. Our aim is to identify and characterize serious ADRs caused by DDIs using a spontaneous reporting database.

Methods: All serious ADR reports, not related to vaccines and with a “definite”, “probable” or “possible” causality assessment, inserted into the National Pharmacovigilance database from Veneto Region (January 1, 2015 to May 31, 2020) were analyzed. A list of drug pairs was created by selecting the reports containing at least two suspected or concomitant drugs. We verified which drug pairs potentially interacted according to the online version of DRUGDEX^® system. For each potential DDI we controlled whether the ADR description in the report corresponded to the interaction effect as described in Micromedex. A detailed characterization of all serious reports containing an occurring DDI was performed.

Results: In the study period a total of 31,604 reports of suspected ADRs from the Veneto Region were identified, of which 2,195 serious reports (6.9% of all ADR reports) containing at least two suspected or concomitant drugs were analyzed. We identified 1,208 ADR reports with at least one potential DDI (55.0% of 2,195) and 381 reports (17.4% of 2,195 reports) with an occurring ADR associated with a DDI. The median age of patients and the number of contraindicated or major DDIs were significantly higher in reports with an occurring DDI. Warfarin was the most frequently reported interacting drug and the most common ADRs were gastrointestinal or cerebral hemorrhagic events. The proton pump inhibitors/warfarin, followed by platelet aggregation inhibitors/warfarin were the drug-drug combinations most frequently involved in ADRs caused by DDIs. The highest proportion of fatal reports was observed with platelet aggregation inhibitors/warfarin and antidepressants/warfarin.

Conclusion: Our findings showed that about one-third of patients exposed to a potential DDI actually experienced a serious ADR. Furthermore, our study confirms that a spontaneous reporting database could be a valuable resource for identifying and characterizing ADRs caused by DDIs and the drugs leading to serious ADRs and deaths.

Impact of a clinical decision support tool targeting QT-prolonging medications

PURPOSE

To evaluate the impact of a newly implemented clinical decision support (CDS) tool targeting QT interval-prolonging medications on order verification and provider interventions.

METHODS

A multicenter, retrospective quasi-experimental study was conducted to evaluate provider response to CDS alerts triggered during ordering of QT-prolonging medications for adult patients. The primary outcome was the proportion of orders triggering QTc alerts that were continued without intervention during a specified preimplementation phase (n = 49) and during a postimplementation phase (n = 100). Patient risk factors for QTc prolongation, provider alert response, and interventions to reduce the risk of QTc-associated adverse events were evaluated.

RESULTS

The rate of order continuation without intervention was 82% in the preimplementation phase and 37% in the postimplementation phase, representing an 55% reduction in continued verified orders following implementation of the QT-focused CDS tool. Most alerts were initially responded to by the prescriber, with pharmacist intervention needed in only 33% of cases. There were no significant differences in patient QTc-related risk factors between the 2 study groups (P = 0.11); the postimplementation group had a higher proportion of patients using at least 2 QTc-prolonging medications (48%, compared to 26% in the preimplementation group; P = 0.02).

CONCLUSION

Implementation of the CDS tool was associated with a reduction in the proportion of orders continued without intervention in patients at high risk for QTc-related adverse events.

Psychopharmacological Treatment in Older People: Avoiding Drug Interactions and Polypharmacy

BACKGROUND

As the elderly population increases, so, too, does the number of multimorbid patients and the risk of polypharmacy. The consequences include drug interactions, undesired side effects of medication, health impairment, and the need for hospital- ization. 5-10% of hospital admissions among the elderly are attributable to undesired side effects of medication.

METHODS

This review is based on publications retrieved by a selective search in PubMed and the Cochrane Library that employed the search terms "drug interaction," "undesired side effect," "polypharmacy," "pharmacokinetics," and "pharmacody- namics."

RESULTS

Elderly patients are particularly at risk of polypharmacy, both because of the prevalence of multimorbidity in old age and because of physicians' uncritical implementation of guidelines. The more drugs a person takes, the greater the risk of drug interactions and undesired side effects. Age-associated changes in pharmacokinetics and pharmacodynamics elevate this risk as well. Physicians prescribing drugs for elderly patients need to know about the drugs' catabolic pathways, protein binding, and inductive and inhibitory effects on cytochrome P450 in order to avoid drug interactions and polypharmacy.

CONCLUSION

Multiple aids and instruments are available to ensure practical and reasonable drug monitoring, so that the risks of drug interactions and undesired side effects can be detected early and avoided.

Impact of Clinical Pharmacist's Interventions on Potential Drug-Drug Interactions in the Cardiac Care Units of Two University Hospitals in Shiraz, South of Iran

Objective:

The main objective of this study aimed to assess drug–drug interactions (DDIs) in the cardiac care unit (CCU) and cardiac surgery units and the role of a clinical pharmacist in detecting and preventing the expected DDIs.

Methods:

This cross-sectional study was conducted in the CCU Units of Nemazee and Shahid Faghihi Hospitals, two referral hospitals in Shiraz, South of Iran, from August to February 2016. Patients older than 18 years, who were admitted and had received >24 h of inpatient services in these wards with two or more medication orders, were included in this study. All medication orders were evaluated by a pharmacist and DDIs were examined based on the Lexi-Interact™ software. In cases with serious DDIs (D or X), the physicians and nurses were informed, and intervention was conducted by a clinical pharmacist.

Findings:

A total of 3706 medical orders were evaluated. 6478 DDIs were detected, of which, 446 (6.88%) belonged to Classes D and X, and a total of 43.43% of all hospitalizations had at least one DDI. Factors with the most considerable influence on DDIs included an increased number of prescribed medications and patients underlying disease. The physicians accepted 62% of the interventions. The most frequent drugs responsible for interactions of Classes C, D, and X were aspirin, warfarin, and clopidogrel, respectively.

Conclusion:

This study shows that a significant number of clinical DDIs exist in hospitalized patients, especially among consumers of warfarin and aspirin. The role of a clinical pharmacist in preventing such interactions and safer pharmacotherapy management for hospitalized patients is essential.

Effect of Electronic Prescribing Strategies on Medication Error and Harm in Hospital: a Systematic Review and Meta-analysis

BACKGROUND

Computerized physician order entry and clinical decision support systems are electronic prescribing strategies that are increasingly used to improve patient safety. Previous reviews show limited effect on patient outcomes. Our objective was to assess the impact of electronic prescribing strategies on medication errors and patient harm in hospitalized patients.

METHODS

MEDLINE, EMBASE, CENTRAL, and CINAHL were searched from January 2007 to January 2018. We included prospective studies that compared hospital-based electronic prescribing strategies with control, and reported on medication error or patient harm. Data were abstracted by two reviewers and pooled using random effects model. Study quality was assessed using the Effective Practice and Organisation of Care and evidence quality was assessed using Grading of Recommendations Assessment, Development, and Evaluation.

RESULTS

Thirty-eight studies were included; comprised of 11 randomized control trials and 27 non-randomized interventional studies. Electronic prescribing strategies reduced medication errors (RR 0.24 (95% CI 0.13, 0.46), I² 98%, n = 11) and dosing errors (RR 0.17 (95% CI 0.08, 0.38), I² 96%, n = 9), with both risk ratios significantly affected by advancing year of publication. There was a significant effect of electronic prescribing strategies on adverse drug events (ADEs) (RR 0.52 (95% CI 0.40, 0.68), I² 0%, n = 2), but not on preventable ADEs (RR 0.55 (95% CI 0.30, 1.01), I² 78%, n = 3), hypoglycemia (RR 1.03 (95% CI 0.62-1.70), I² 28%, n = 7), length of stay (MD - 0.18 (95% - 1.42, 1.05), I² 94%, n = 7), or mortality (RR 0.97 (95% CI 0.79, 1.19), I² 74%, n = 9). The quality of evidence was rated very low.

DISCUSSION

Electronic prescribing strategies decrease medication errors and adverse drug events, but had no effect on other patient outcomes. Conservative interpretations of these findings are supported by significant heterogeneity and the preponderance of low-quality studies.

A new approach on assessing clinical pharmacists' impact on prescribing errors in a surgical intensive care unit

Background With a clinical pharmacists’ participation in an intensive care unit (ICU) previous international studies have shown a reduction of medication errors, drug costs and improvements of clinical outcomes. Still there is a lack of qualitative data on clinical pharmacists’ impact on prescribing error rates in the ICU. Therefore, a new approach was developed relating prescribing errors to the number of monitored medications including physicians’ approval on all prescribing errors. Objective This study investigates the influence of clinical pharmacists’ medication review on the prescribing error rate in an ICU. Setting A controlled interventional study was conducted in a surgical ICU with one control phase (P0) and two intervention phases (P1 and P2). Method The investigation aimed to determine if the medication review by clinical pharmacists results in a significant reduction of prescribing errors related to a control period. In contrast to previous studies, prescribing errors detected by the clinical pharmacists, were only taken into account, if consent with the physicians was achieved. Secondary outcomes were the reduction of potentially severe prescribing errors, the number of days without systemic anti-infective therapy and the ICU length of stay. Throughout P0 the data was collected retrospectively without any intervention. During the intervention periods P1 and P2, two clinical pharmacists screened the medical records for prescribing errors and discussed them with the senior physician in charge. During P2 one clinical pharmacist attended ward rounds additionally. Main Outcome Measure The main outcome measure of this study was the number of prescribing errors detected related to the number of monitored medications. Results The incidence of prescribing errors was significantly reduced from 1660 in P0 to 622 in P1 respectively 401 in P2 (P0 vs. P1/P2 respectively; both p < 0.001; Fisher’s Exact Test) in total, respective 14.12% in P0 vs. 5.13% in P1 and 3.25% in P2 related to the monitored medications (P0:11755; P1:12134; P2:12329). Conclusion Clinical pharmacists’ interventions led to a significant reduction of prescribing errors in the ICU, contributing to a safer medication process. We strongly recommend a broad implementation of clinical pharmacists in ICUs.

Are drug-drug interactions a real clinical concern?

Aim:

Although drug-drug interactions (DDIs) cause major adverse drug reactions (ADRs) in patients under polypharmacy, the risk of some specific DDIs may be overrated in literature and different software. This study was conducted to determine the frequency and type of potential and clinically significant DDIs among inpatients admitted in a tertiary care hospital in South India.

Materials and Methods:

This longitudinal study was conducted for 30 days. Preformatted forms were used to collect data on the second day of admission. “Medscape Drug Interaction Checker” was used to evaluate and grade the DDIs. All the potential serious DDIs were intimated to the treating physicians and their responses in the prescriptions were noted. The same patients were followed up to evaluate the occurrence of any clinically significant DDIs.

Results:

A total of 763 drugs with 125 discrete types were prescribed in 155 patients with an average of 4.9 drugs per patient. One hundred and eight minor, 169 significant, and 24 serious potential DDIs were identified. Patient's age did not correlate, but number of drugs prescribed strongly correlated (P < 0.001) with the incidence of different types of DDIs. The prescription was modified in only 6 (25%) cases where potential serious DDIs were reported. Interestingly, no ADRs or impaired efficacy was observed due to the potential serious DDIs.

Conclusion:

There was a disparity between the potential and clinically relevant DDIs. Hence, clinical prudency is required before changing prescription due to potential DDIs reported by different software.

Coverage rate of ADME genes from commercial sequencing arrays

Pharmacogenomics offers remarkable potential for the rapid translation of discoveries into changes in clinical practice. In the present work, we are interested in evaluating the ability of commercially available genome-wide association sequencing chips to cover genes that have high pharmacogenomics potential.We used a set of 2794 variations within 369 absorption, distribution, metabolism, and elimination (ADME) genes of interest, as previously defined in collaboration with the Pharma ADME consortium. We have compared the Illumina TrueSeq and both Agilent SureSelect and HaloPlex sequencing technologies. We have developed Python scripts to evaluate the coverage for each of these products. In particular, we considered a specific list of 155 allelic variants in 34 genes which present high pharmacogenomics potential. Both the theoretical and practical coverage was assessed.Given the need to have a good coverage to establish confidently the functionality of an enzyme, the observed rates are unlikely to provide sufficient evidence for pharmacogenomics studies. We assessed the coverage using enrichment technology for exome sequencing using the Illumina Trueseq exome, Agilent SureSelectXT1 V4 and V5, and Haloplex exome, which offer a coverage of 96.12%, 91.61%, and 88.38%, respectively.Although pharmacogenomic advances had been limited in the past due in part to the lack of coverage of commercial genotyping chips, it is anticipated that future studies that make use of new sequencing technologies should offer a greater potential for discovery.

A novel method to evaluate quality of care from the perspective of cataract patients

PURPOSE

To evaluate quality of care from patient's perspective following cataract surgery using a novel questionnaire and to assess validity of the survey in context with the identification of lacks in quality of care.

METHODS

Assessment of quality of care in 150 patients (150 eyes) who underwent cataract surgery in an Austrian clinical setting based on a novel "Quality of Care from Patient's perspective following Cataract Surgery" (QCPCS)-questionnaire including 10 subjective, 10 objective and 7 general health care criteria. Quality of care was graded according to importance (range: 1 = not important to 4 = extremely important) and frequency of occurrence (range: 1 = never to 4 = often, 0 = not applicable). Quality-impact indices (QI-respective grading by patient/4) were assessed.

RESULTS

Mean performance score was 3.84 (SD = 0.42, range: 1-4). Mean QI was 0.89 for subjective, 0.90 for objective and 0.96 for general health care criteria (p = 0.29). All-over skewness and coefficient of variation were -2.65 and 5.85 respectively. Internal consistency was high (Cronbach's α = 0.75) confirming causal taxonomy of disease-specific and generic items.

CONCLUSION

A valid new method to reliably and holistically evaluate patient's satisfaction related to cataract surgery including a broad range of patient needs is presented, suitable to assess potential lacks in quality of health care in daily ophthalmological clinical practice.

Potential Drug-Drug Interactions in a Cohort of Elderly, Polymedicated Primary Care Patients on Antithrombotic Treatment

INTRODUCTION

Drug-drug interactions (DDIs) are an important risk factor for adverse drug reactions. Older, polymedicated patients are particularly affected. Although antithrombotics have been detected as high-risk drugs for DDIs, data on older patients exposed to them are scarce.

METHODS

Baseline data of 365 IDrug study outpatients (≥ 60 years, use of an antithrombotic and one or more additional long-term drug) were analyzed regarding potential drug-drug interactions (pDDIs) with a clinical decision support system. Data included prescription and self-medication drugs.

RESULTS

The prevalence of having one or more pDDI was 85.2%. The median number of alerts per patient was three (range 0-17). For 58.4% of the patients, potential severe/contraindicated interactions were detected. Antiplatelets and non-steroidal anti-inflammatory drugs (NSAIDs) showed the highest number of average pDDI alert involvements per use (2.9 and 2.2, respectively). For NSAIDs, also the highest average number of severe/contraindicated alert involvements per use (1.2) was observed. 91.8% of all pDDI involvements concerned the 25 most frequently used drug classes. 97.5% of the severe/contraindicated pDDIs were attributed to only nine different potential clinical manifestations. The most common management recommendation for severe/contraindicated pDDIs was to intensify monitoring. Number of drugs was the only detected factor significantly associated with increased number of pDDIs (p < 0.001).

CONCLUSION

The findings indicate a high risk for pDDIs in older, polymedicated patients on antithrombotics. As a consequence of patients' frequently similar drug regimens, the variety of potential clinical manifestations was small. Awareness of these pDDI symptoms and the triggering drugs as well as patients' self-medication use may contribute to increased patient safety.

Effectiveness of a complex intervention on Prioritising Multimedication in Multimorbidity (PRIMUM) in primary care: results of a pragmatic cluster randomised controlled trial

OBJECTIVES

Investigate the effectiveness of a complex intervention aimed at improving the appropriateness of medication in older patients with multimorbidity in general practice.

DESIGN

Pragmatic, cluster randomised controlled trial with general practice as unit of randomisation.

SETTING

72 general practices in Hesse, Germany.

PARTICIPANTS

505 randomly sampled, cognitively intact patients (≥60 years, ≥3 chronic conditions under pharmacological treatment, ≥5 long-term drug prescriptions with systemic effects); 465 patients and 71 practices completed the study.

INTERVENTIONS

Intervention group (IG): The healthcare assistant conducted a checklist-based interview with patients on medication-related problems and reconciled their medications. Assisted by a computerised decision support system, the general practitioner optimised medication, discussed it with patients and adjusted it accordingly. The control group (CG) continued with usual care.

OUTCOME MEASURES

The primary outcome was a modified Medication Appropriateness Index (MAI, excluding item 10 on cost-effectiveness), assessed in blinded medication reviews and calculated as the difference between baseline and after 6 months; secondary outcomes after 6 and 9 months' follow-up: quality of life, functioning, medication adherence, and so on.

RESULTS

At baseline, a high proportion of patients had appropriate to mildly inappropriate prescriptions (MAI 0-5 points: n=350 patients). Randomisation revealed balanced groups (IG: 36 practices/252 patients; CG: 36/253). Intervention had no significant effect on primary outcome: mean MAI sum scores decreased by 0.3 points in IG and 0.8 points in CG, resulting in a non-significant adjusted mean difference of 0.7 (95% CI -0.2 to 1.6) points in favour of CG. Secondary outcomes showed non-significant changes (quality of life slightly improved in IG but continued to decline in CG) or remained stable (functioning, medication adherence).

CONCLUSIONS

The intervention had no significant effects. Many patients already received appropriate prescriptions and enjoyed good quality of life and functional status. We can therefore conclude that in our study, there was not enough scope for improvement.

TRIAL REGISTRATION NUMBER

ISRCTN99526053. NCT01171339; Results.

Drug-drug interactions and their harmful effects in hospitalised patients: a systematic review and meta-analysis

PURPOSE

Drug-drug interactions (DDIs) are often avoidable and, if undetected, can lead to patient harm. This review aimed to determine the prevalence of potential DDIs (pDDIs), clinically relevant DDIs (DDIs that could lead to measurable patient harm, taking into account the patient's individual clinical profile) and DDIs that resulted in actual patient harm during hospitalisation.

METHOD

Four databases were scanned for English papers published from 2000 to 2016. Papers that reported prevalence of DDIs in the outpatient setting, at admission or discharge, involving only specific drugs, or in specific disease populations or age groups were excluded.

RESULTS

Twenty-seven papers met the inclusion criteria and were graded for quality using the Critical Appraisal Skills Programme (CASP) cohort study checklist. Ten papers were rated as 'poor', 14 as 'fair' and only three papers as 'good'. Overall, the meta-analysis revealed that 33% of general patients and 67% of intensive care patients experienced a pDDI during their hospital stay. It was not possible to determine the prevalence of clinically relevant DDIs or DDIs that resulted in actual patient harm as data on these categories were limited. Of the very few studies that reported on harm, only a small proportion of DDIs were found to have resulted in actual patient harm.

CONCLUSIONS

Standardisation of DDI definitions and research methods are required to allow meaningful prevalence rates to be obtained and compared. Studies that go further than measuring pDDIs are critically needed to determine the impact of DDIs on patient safety.

The prevalence and preventability of potentially relevant drug-drug interactions in patients admitted for cardiovascular diseases: A cross-sectional study

AIM

The aim was to describe the type and prevalence of potentially relevant drug-drug interactions (pDDIs) in a population of patients admitted for cardiovascular diseases (CVD), and management strategies for reducing the occurrence of pDDIs.

METHODS

A retrospective cross-sectional study was performed on Cardiology ward of University Clinical Hospital Center in Belgrade, Serbia. A total of 527 patients, with more than one prescription during hospital stay, were enrolled in this study. Data were obtained from medical records. LexiInteract was used as the screening tool.

RESULTS

At least one potentially relevant pDDI was identified in 83.9% of patients. Occurrence was significantly more prevalent in patients with higher number of drugs, multimorbidity, longer length of stay, arrhythmia, heart failure, infectious and respiratory disease. About 13% of pDDIs exposures were accompanied with concurrent renal or liver disease, as an additional risk for DDI manifestation. Among CVD, patients with a history of myocardial infarction possessed the highest additional risk. The most common potential clinical outcome was the effect on cardiovascular system 48.5%, renal function and/or potassium 22.3%, bleeding 9.5%, impaired glucose control 6.8% and digoxin toxicity 4.6%. Main management strategies to avoid X or D class included using paracetamol instead of NSAID or alternative NSAID (38%), alternative antibiotic or antifungal (20.4%), H₂ receptor antagonist instead of PPI (8.3%), avoiding therapeutic duplication (7.3%), and alternative HMG-CoA reductase inhibitor (7%). Heart rate, blood pressure, electrolytes/potassium and blood glucose could have been employed in monitoring for potential consequence of 72.2% C class pDDIs.

CONCLUSIONS

Use of drug interaction screening tools can be beneficial risk mitigation strategy for potentially relevant pDDIs in CVD patients. DDI screening software could be linked to the patient's laboratory results or clinical data regarding renal or liver function, as an approach to reinforce DDIs alert quality.

Comparison of Overridden Medication-related Clinical Decision Support in the Intensive Care Unit between a Commercial System and a Legacy System

BACKGROUND

Electronic health records (EHRs) with clinical decision support (CDS) have shown to be effective at improving patient safety. Despite this, alerts delivered as part of CDS are overridden frequently, which is of concern in the critical care population as this group may have an increased risk of harm. Our organization recently transitioned from an internally-developed EHR to a commercial system. Data comparing various EHR systems, especially after transitions between EHRs, are needed to identify areas for improvement.

OBJECTIVES

To compare the two systems and identify areas for potential improvement with the new commercial system at a single institution.

METHODS

Overridden medication-related CDS alerts were included from October to December of the systems' respective years (legacy, 2011; commercial, 2015), restricted to three intensive care units. The two systems were compared with regards to CDS presentation and override rates for four types of CDS: drug-allergy, drug-drug interaction (DDI), geriatric and renal alerts. A post hoc analysis to evaluate for adverse drug events (ADEs) potentially resulting from overridden alerts was performed for 'contraindicated' DDIs via chart review.

RESULTS

There was a significant increase in provider exposure to alerts and alert overrides in the commercial system (commercial: n=5,535; legacy: n=1,030). Rates of overrides were higher for the allergy and DDI alerts (p<0.001) in the commercial system. Geriatric and renal alerts were significantly different in incidence and presentation between the two systems. No ADEs were identified in an analysis of 43 overridden contraindicated DDI alerts.

CONCLUSIONS

The vendor system had much higher rates of both alerts and overrides, although we did not find evidence of harm in a review of DDIs which were overridden. We propose recommendations for improving our current system which may be helpful to other similar institutions; improving both alert presentation and the underlying knowledge base appear important.

A survey of attitudes, practices, and knowledge regarding drug-drug interactions among medical residents in Iran

Background When prescribing medications, physicians should recognize clinically relevant potential drug-drug interactions (DDIs). To improve medication safety, it is important to understand prescribers' knowledge and opinions pertaining to DDIs. Objective To determine the current DDI information sources used by medical residents, their knowledge of DDIs, their opinions about performance feedback on co-prescription of interacting drugs. Setting Academic hospitals of Mashhad University of Medical Sciences (MUMS) in Iran. Methods A questionnaire containing questions regarding demographic and practice characteristics, DDI information sources, ability to recognize DDIs, and opinions about performance feedback was distributed to medical residents of 22 specialties in eight academic hospitals in Iran. We analyzed their perception pertaining to DDIs, their performance on classifying drug pairs, and we used a linear regression model to assess the association of potential determinants on their DDI knowledge. Main Outcome Measure prescribers' knowledge and opinions pertaining to DDIs. Results The overall response rate and completion rate for 315 distributed questionnaires were 90% (n = 295) and 86% (n = 281), respectively. Among DDI information sources, books, software on mobile phone or tablet, and Internet were the most commonly-used references. Residents could correctly classify only 41% (5.7/14) of the drug pairs. The regression model showed no significant association between residents' characteristics and their DDI knowledge. An overwhelming majority of the respondents (n = 268, 95.4%) wished to receive performance feedback on co-prescription of interacting drugs in their prescriptions. They mostly selected information technology-based tools (i.e. short text message and email) as their preferred method of receiving feedback. Conclusion Our findings indicate that prescribers may have poor ability to prevent clinically relevant potential DDI occurrence, and they perceive the need for performance feedback. These findings underline the importance of well-designed computerized alerting systems and delivering performance feedback to improve patient safety.

Evaluation of medication-related clinical decision support alert overrides in the intensive care unit

PURPOSE

Medication-related clinical decision support (CDS) has been identified as a method to improve patient outcomes but is historically frequently overridden and may be inappropriately so. Patients in the intensive care unit (ICU) are at a higher risk of harm from adverse drug events (ADEs) and these overrides may increase patient harm. The objective of this study is to determine appropriateness of overridden medication-related CDS overrides in the ICU.

MATERIALS AND METHODS

We evaluated overridden medication-related alerts of four alert categories from January 2009 to December 2011. The primary outcome was the appropriateness of a random sample of overrides based on predetermined criteria. Secondary outcomes included the incidence of adverse drug events (ADEs) that resulted from the overridden alert.

RESULTS

A total of 47,449 overridden alerts were included for evaluation. The appropriateness rate for overridden alerts varied by alert category (allergy: 94%, drug-drug interaction: 84%, geriatric: 57%, renal: 27%). A total of seven actual ADEs were identified in the random sample and where the medication(s) was administered (n=366), with an increased risk of ADEs associated with inappropriately overridden alerts (p=0.0078).

CONCLUSIONS

The appropriateness of medication-related clinical decision support overrides in the ICU varied substantially by the type of alert. Inappropriately overridden alerts were associated with an increased risk of ADEs compared to appropriately overridden alerts.

Drug-drug interactions in the intensive care unit: Do they really matter?

PURPOSE

To describe prevalence and patterns of potential drug-drug interactions (pDDIs) in the intensive care unit (ICU), occurrence of adverse drug events (ADEs), and agreement between different compendia and intensivists' perceptions.

METHODS

A cross-sectional study. Drug profiles of all adult patients from 2 academic ICUs were screened on day 3 upon admission. We identified pDDIs using 3 compendia (Stockley's, Micromedex, and Epocrates) and documented their mechanism of action, clinical consequences, severity, level of evidence, and management. Medical records were searched to identify ADEs potentially related to major pDDIs. Agreement between information sources (compendia, intensivists) was evaluated.

RESULTS

We identified 1120 pDDIs among 275 patients. Median number of pDDIs per patient was 3.0 (interquartile range, 1-6), with 79% of patients presenting with at least 1 pDDI. Major pDDIs were detected in 18% of patients, with potentially related to ADEs in 4% of patients. Only 13% of all pDDIs were documented simultaneously in all 3 compendia. Different information sources (compendia, clinicians) showed "no" to "fair" agreement.

CONCLUSIONS

Potential drug-drug interactions occurred in most ICU patients, contrasting with low rates of potentially related ADEs, which may have been underestimated. Sources of information are inconsistent, challenging the identification of pDDIs.

Pilot study to test the feasibility of a trial design and complex intervention on PRIoritising MUltimedication in Multimorbidity in general practices (PRIMUMpilot)

OBJECTIVE

To improve medication appropriateness and adherence in elderly patients with multimorbidity, we developed a complex intervention involving general practitioners (GPs) and their healthcare assistants (HCA). In accordance with the Medical Research Council guidance on developing and evaluating complex interventions, we prepared for the main study by testing the feasibility of the intervention and study design in a cluster randomised pilot study.

SETTING

20 general practices in Hesse, Germany.

PARTICIPANTS

100 cognitively intact patients ≥65 years with ≥3 chronic conditions, ≥5 chronic prescriptions and capable of participating in telephone interviews; 94 patients completed the study.

INTERVENTION

The HCA conducted a checklist-based interview with patients on medication-related problems and reconciled their medications. Assisted by a computerised decision-support system (CDSS), the GPs discussed medication intake with patients and adjusted their medication regimens. The control group continued with usual care.

OUTCOME MEASURES

Feasibility of the intervention and required time were assessed for GPs, HCAs and patients using mixed methods (questionnaires, interviews and case vignettes after completion of the study). The feasibility of the study was assessed concerning success of achieving recruitment targets, balancing cluster sizes and minimising drop-out rates. Exploratory outcomes included the medication appropriateness index (MAI), quality of life, functional status and adherence-related measures. MAI was evaluated blinded to group assignment, and intra-rater/inter-rater reliability was assessed for a subsample of prescriptions.

RESULTS

10 practices were randomised and analysed per group. GPs/HCAs were satisfied with the interventions despite the time required (35/45 min/patient). In case vignettes, GPs/HCAs needed help using the CDSS. The study made no patients feel uneasy. Intra-rater/inter-rater reliability for MAI was excellent. Inclusion criteria were challenging and potentially inadequate, and should therefore be adjusted. Outcome measures on pain, functionality and self-reported adherence were unfeasible due to frequent missing values, an incorrect manual or potentially invalid results.

CONCLUSIONS

Intervention and trial design were feasible. The pilot study revealed important limitations that influenced the design and conduct of the main study, thus highlighting the value of piloting complex interventions.

TRIAL REGISTRATION NUMBER

ISRCTN99691973; Results.

The Safety of Drug Therapy in Children

BACKGROUND

1.7% of children taking medication on an outpatient basis in Germany have at least one adverse drug reaction (ADR). The corresponding figure for hospitalized children is estimated at 10% .

METHODS

This review is based on pertinent literature retrieved by a selective search in PubMed.

RESULTS

According to reports submitted to the Drug Commission of the German Medical Association (Arzneimittelkommission der deutschen Ärzteschaft, AkdÄ), serious ADRs can arise, for example, after the administration of dimenhydrinate, α-adrenergic nose drops, enemas containing phosphate, ACE inhibitors, angiotensin-2-receptor antagonists (sartans), and methylphenidate. The causes of ADRs include overdoses, drug administration despite contraindications, and inadequate monitoring of long-term treatment. Errors can also be made in communication, labeling, and drug administration. The risk of ADRs is especially high in off-label use. Computerized physician order entry systems, individual packaging and labeling of single doses, and the use of bar codes for patient and drug identification can help prevent such errors.

CONCLUSION

The process of drug administration should be optimized through suitable interventions and electronic support, with due consideration of local circumstances. Clinical trials on children should be encouraged as a means of improving drug safety, and additional financial incentives should be created for trials concerning drugs that are off-patent. Physicians and pharmacists should take care to report adverse reactions as they are required to do by professional code, particularly in the case of new drugs, off-label use, or medication errors. A recognized national standard for dosing that can be implemented in computerized physician order entry systems is needed so that evidence-based pediatric dosages can be calculated.

Delirium and sleep disturbances in the intensive care unit: can we do better?

PURPOSE OF REVIEW

Delirium in the ICU affects as many as 60-80% of mechanically ventilated patients and a smaller but substantial percentage of other critically ill patients. Poor sleep quality has been consistently observed in critically ill patients. These problems are associated with worse ICU outcomes and, in many cases, delirium and poor sleep quality may be related. This review will summarize the recent literature relevant to both the problems and provide a potential pathway toward improvement.

RECENT FINDINGS

Many cases of delirium and the poor sleep experienced by ICU patients may be iatrogenic. How critical care practitioners prescribe sedatives and analgesics and, perhaps more broadly, how all medications are administered to critically ill patients, may be at the root of some of these problems. Reducing the administration of some commonly used ICU medications, especially some sedatives and anticholinergic medications, and keeping patients more awake and actively engaged in their care during the day may lead to better outcomes.

SUMMARY

It is our responsibility to apply the best available, evidence-based medicine to our practice. Adherence to new guidelines for the treatment of pain, agitation, and delirium may be the best pathway toward reducing delirium, improving sleep quality, and improving related outcomes.

How to improve prescription of inhaled salbutamol by providing standardised feedback on administration: a controlled intervention pilot study with follow-up

Background

The effectiveness of inhaled salbutamol in routine care depends particularly on prescribed dosage and applied inhalation technique. To achieve maximum effectiveness and to prevent drug-related problems, prescription and administration need to work in concert.

Methods

We performed a controlled intervention pilot study with 4 consecutive groups in a general paediatric unit and assessed problems in salbutamol prescribing and administration. Control group [i]: Routine care without additional support. First intervention group [ii]: We carried out a teaching session for nurses aimed at preventing problems in inhalation technique. Independently from this, a pharmacist counselled physicians on problems in salbutamol prescribing. Second intervention group [iii]: Additionally to the first intervention, physicians received standardised feedback on the inhalation technique. Follow-up group [iv]: Subsequently, without any delay after the second intervention group had been completed, sustainability of the measures was assessed. We performed the chi-square test to calculate the level of significance with p ≤ 0.05 to indicate a statistically significant difference for the primary outcome. As we performed multiple testing, an adjusted p ≤ 0.01 according to Bonferroni correction was considered as significant.

Results

We included a total of 225 patients. By counselling the physicians, we reduced the number of patients with problems from 55% to 43% (control [i] vs. first intervention [ii], n.s.). With additional feedback to physicians, this number was further reduced to 25% ([i] vs. [iii], p < 0.001). In the follow-up [iv], the number rose again to 48% (p < 0.01 compared to feedback group).

Conclusions

Teaching nurses, counselling physicians, and providing feedback on the quality of inhalation technique effectively reduced problems in salbutamol treatment. However, for success to be sustained, continuous support needs to be provided.

Trial registration

German Clinical Trials register: DRKS00006792.

Practices and preferences for detecting chronic medication toxicity: a pilot cross-sectional survey of health care providers focusing on decision support systems

RATIONALE, AIMS, AND OBJECTIVES

Adverse drug reactions (ADRs) are a critical concern: they are costly, both in dollars and in diminishing patients' quality of life. ADRs that occur due to prolonged exposure to a pharmaceutical agent (adverse drug reactions of long latency, ADRLLs) may be easier to prevent than acute ADRs, as ADRLLs inherently require continued medication exposures. This pilot study used glucocorticoid-induced osteoporosis (GIO) as an example ADRLL. The aims were to survey health care providers' current practices in avoiding ADRLLs and the perceived utility of decisional support systems (DSS) to aid them in preventing GIO.

METHODS

We administered an anonymous, cross-sectional survey to health care providers (fellows, doctor assistants, nurse practitioners and attending doctors) focusing on their methods to monitor for and prevent ADRLLs. The questionnaire also gauged usage of electronic medical records (EMRs) and each provider's perceived utility of specific DSS-based approaches to monitoring for GIO. Data were interpreted using descriptive statistics and histograms.

RESULTS

A majority of the 33 responding providers (84.8%) reported that their primary ADRLL avoidance technique is simply remembering that a patient is on chronic glucocorticoids. The most favourably perceived DSS options included tracking medications on a flow sheet (84.8%) and digital tracking of cumulative glucocorticoid exposure with real-time prompts (83.9%).

CONCLUSIONS

Surveyed providers reported that additional DSS implementation may help in the avoidance of ADRLLs such as GIO. Providers ranked both digital and non-digital DSS favourably, but a computerized approach is appealing in that it may be integrated into extant EMR systems.

Analysis of potential drug-drug interactions in medical intensive care unit patients

OBJECTIVE

To describe the frequency and type of potential drug-drug interactions (pDDIs) in a general intensive care unit (ICU) and to make recommendations to improve the management of these pDDIs.

DESIGN

Retrospective observational study.

SETTING

General ICU of a tertiary care hospital.

SUBJECTS

All patients admitted for more than 24 hours between May 2009 and December 2010 who were prescribed at least one medication.

MEASUREMENT AND MAIN RESULTS

Based on the G-Standaard, the Dutch national drug database, pDDIs were identified and classified into categories of potential clinical outcome and management advice. In total, 35,784 medication episodes were identified, resulting in 2887 pDDIs (8.1%). These 2887 pDDIs occurred in 1659 patients for a mean frequency of 1.7 (95% confidence interval [CI] 1.6-1.9) pDDIs per patient. Overall, 54% of the patients experienced at least one pDDI with pDDIs present during 27% of all ICU admission days. All pDDIs could be reconstructed using 81 of the 358 (23%) relevant unique pDDI pairs described in the G-Standaard. The most frequently occurring potential clinical consequence was an increased risk of side effects or toxicity (91% of the pDDIs) such as electrolyte disturbances and masking of hypoglycemia. The most important advised management strategy was monitoring (81%), consisting of monitoring of laboratory values (52%), clinical monitoring of toxicity or effectiveness (48%), or monitoring of physical parameters such as electrocardiogram and blood pressure (11%).

CONCLUSION

Potential drug-drug interactions occur in 54% of all ICU patients, which is two times more than the rate seen in patients on general wards. A limited set of 20 pDDI pairs is responsible for more than 90% of all pDDIs. Therefore, it is worthwhile to develop guidelines for the management of these specific pDDIs. As the vast majority of the interactions can be managed by monitoring, advanced clinical decision support systems linking laboratory data to prescription data may be an effective risk management strategy.

Systematic review of clinical decision support interventions with potential for inpatient cost reduction

Background

Healthcare costs are increasing rapidly and at an unsustainable rate in many countries, and inpatient hospitalizations are a significant driver of these costs. Clinical decision support (CDS) represents a promising approach to not only improve care but to reduce costs in the inpatient setting. The purpose of this study was to systematically review trials of CDS interventions with the potential to reduce inpatient costs, so as to identify promising interventions for more widespread implementation and to inform future research in this area.

Methods

To identify relevant studies, MEDLINE was searched up to July 2013. CDS intervention studies with the potential to reduce inpatient healthcare costs were identified through titles and abstracts, and full text articles were reviewed to make a final determination on inclusion. Relevant characteristics of the studies were extracted and summarized.

Results

Following a screening of 7,663 articles, 78 manuscripts were included. 78.2% of studies were controlled before-after studies, and 15.4% were randomized controlled trials. 53.8% of the studies were focused on pharmacotherapy. The majority of manuscripts were published during or after 2008. 70.5% of the studies resulted in statistically and clinically significant improvements in an explicit financial measure or a proxy financial measure. Only 12.8% of the studies directly measured the financial impact of an intervention, whereas the financial impact was inferred in the remainder of studies. Data on cost effectiveness was available for only one study.

Conclusions

Significantly more research is required on the impact of clinical decision support on inpatient costs. In particular, there is a remarkable gap in the availability of cost effectiveness studies required by policy makers and decision makers in healthcare systems.

Computerized decision support in adult and pediatric critical care

Computerized decision support (CDS) is the most advanced form of clinical decision support available and has evolved with innovative technologies to provide meaningful assistance to medical professionals. Critical care clinicians are in unique environments where vast amounts of data are collected on individual patients, and where expedient and accurate decisions are paramount to the delivery of quality healthcare. Many CDS tools are in use today among adult and pediatric intensive care units as diagnostic aides, safety alerts, computerized protocols, and automated recommendations for management. Some CDS use have significantly decreased adverse events and improved costs when carefully implemented and properly operated. CDS tools integrated into electronic health records are also valuable to researchers providing rapid identification of eligible patients, streamlining data-gathering and analysis, and providing cohorts for study of rare and chronic diseases through data-warehousing. Although the need for human judgment in the daily care of critically ill patients has limited the study and realization of meaningful improvements in overall patient outcomes, CDS tools continue to evolve and integrate into the daily workflow of clinicians, and will likely provide advancements over time. Through novel technologies, CDS tools have vast potential for progression and will significantly impact the field of critical care and clinical research in the future.

Assessing cardiovascular drug safety for clinical decision-making

Optimal therapeutic decision-making requires integration of patient-specific and therapy-specific information at the point of care, particularly when treating patients with complex cardiovascular conditions. The formidable task for the prescriber is to synthesize information about all therapeutic options and match the best treatment with the characteristics of the individual patient. Computerized decision support systems have been developed with the goal of integrating such information and presenting the acceptable therapeutic options on the basis of their effectiveness, often with limited consideration of their safety for a specific patient. Assessing the safety of therapies relative to each patient is difficult, and sometimes impossible, because the evidence required to make such an assessment is either imperfect or does not exist. In addition, many of the alerts sent to prescribers by decision-support systems are not perceived as credible, and 'alert fatigue' causes warnings to be ignored putting patients at risk of harm. The CredibleMeds.org and BrugadaDrugs.org websites are prototypes for evidence-based sources of safety information that rank drugs for their risk of a specific form of drug toxicity-in these cases, drug-induced arrhythmias. Broad incorporation of this type of information in electronic prescribing algorithms and clinical decision support could speed the evolution of safe personalized medicine.

Agreement between ICU clinicians and electrophysiology cardiologists on the decision to initiate a QTc-interval prolonging medication in critically ill patients with potential risk factors for torsade de pointes: a comparative, case-based evaluation

STUDY OBJECTIVES

To measure concordance between different intensive care unit (ICU) clinicians and a consensus group of electrophysiology (EP) cardiologists for use of a common rate-corrected QT interval (QTc)-prolonging medication in cases containing different potential risk factor(s) for torsade de pointes (TdP).

DESIGN

Prospective case-based evaluation.

SETTING

Academic medical center with 320 beds.

SUBJECTS

Medical house staff (MDs) and ICU nurses (RNs) from one center and select critical care pharmacists (PHs).

INTERVENTION

Completion of a survey containing 10 hypothetical ICU cases in which patients had agitated delirium for which a psychiatrist recommended intravenous haloperidol 5 mg every 6 hours. Each case contained different potential risk factor(s) for TdP in specific combinations. A group of five EP cardiologists agreed that haloperidol use was safe in five cases and not safe in five cases.

MEASUREMENTS AND MAIN RESULTS

For each case, participants were asked to document whether they would administer haloperidol, to provide a rationale for their decision, and to state their level of confidence in that decision. Most clinicians (92 of 115 [80%]) invited to participate completed the cases. Among the five cases where EP cardiologists agreed that haloperidol was not safe, 29% of respondents felt that haloperidol was safe. Conversely, in the five cases where EP cardiologists felt haloperidol was safe, 21% of respondents believed that it was not safe. Overall respondent-EP cardiologist agreement for haloperidol use across the 10 cases was moderate (κ = 0.51). MDs and PHs were in agreement with the EP cardiologists more than RNs (p=0.03). Interprofessional variability existed for the TdP risk factors each best identified. Clinician confidence correlated with EP cardiologist concordance for MDs (p=0.002) and PHs (p=0.0002), but not for RNs (p=0.69).

CONCLUSION

When evaluating use of a QTc interval-prolonging medication, ICU clinicians often fail to identify the TdP risk factors that EP cardiologists feel should prevent its use. Clinician-EP cardiologist concordance varies by the specific risk factor(s) for TdP and the ICU professional conducting the assessment.

Exploiting online discussions to discover unrecognized drug side effects

BACKGROUND

Drugs can treat human diseases through chemical interactions between the ingredients and intended targets in the human body. However, the ingredients could unexpectedly interact with off-targets, which may cause adverse drug side effects. Notifying patients and physicians of potential drug effects is an important step in improving healthcare quality and delivery.

OBJECTIVE

With the increasing popularity of Web 2.0 applications, more and more patients start discussing drug side effects in many online sources. These online discussions form a valuable source for mining interesting knowledge about side effects. The main goal of this paper is to investigate the feasibility of exploiting these discussions to discover unrecognized drug side effects.

METHODS

We propose methods that can 1) build a knowledge base for drug side effects by automatically integrating the information related to drug side effects from different sources; and 2) monitor online discussions about drugs and discover potential unrecognized drug side effects.

RESULTS

Experiment results show that the online discussions indeed provide useful information discovering unrecognized drug side effects. We find that the integrated knowledge base contains more information than individual online sources. Moreover, both proposed detection methods can identify the side effects related to the four recently recalled drugs, and the information from online discussions makes it possible to make the detection much earlier than official announcements. Finally, the proposed generative modeling method is shown to be more effective than the discriminative method.

CONCLUSIONS

We find that it is possible to monitor online discussions to detect unrecognized drug side effects. The developed system is expected to serve as a complementary tool for drug companies and FDA to receive feedbacks from the patients, and it has the potentials to expedite the discovery process of unrecognized drug side effects and to improve the quality of healthcare.

Drug interactions--principles, examples and clinical consequences

BACKGROUND

Drug interactions can have desired, reduced or unwanted effects. The probability of interactions increases with the number of drugs taken. The high rate of prescribed drugs in elderly patients (65-year-old patients take an average of 5 drugs) increases the likelihood of drug interactions and thus the risk that drugs themselves can be the cause of hospitalization. According to meta-analyses, up to 7% of hospitalizations are drug-related.

METHODS

Selective literature review.

RESULTS

Drug interactions occur on pharmacodynamic and pharmacokinetic levels. Examples of pharmacodynamic interactions are simultaneous administration of a NSAID and phenprocoumon (additive interaction), or of aspirin and ibuprofen (antagonistic interaction). Pharmacokinetic interactions occur at the levels of absorption (e.g., levothyroxine and neutralizing antacids), elimination (e.g., digoxin and macrolides), and metabolism, as in the competition for cytochrome P450 enzymes (e.g., SSRIs and certain beta-blockers).

CONCLUSION

The systematic knowledge of drug interaction, in particular on the level of absorption, elimination, transport and drug metabolism may help to prevent adverse effects. Predicting pharmacodynamic interactions often demands a deeper understanding of the mechanisms of effect. Electronic prescribing systems are helpful.

Examining the evidence of the impact of health information technology in primary care: an argument for participatory research with health professionals and patients

PURPOSE

Health information technology represents a promising avenue to improve health care delivery. How can we use lessons learnt from existing health information technologies in primary care to inform the optimal design of newer developments such as personal health records?

METHODS

The results of systematic literature reviews about the impact of different information systems on health outcomes in primary care are critically discussed in a narrative synthesis, with a focus on their implications for the development of personal health records.

RESULTS

Given the proliferation of systematic reviews and randomized controlled trials, high quality evidence for health information technology in primary care is accumulating with mixed results. The heterogeneity of systems being compared and the quality of research can no longer account for these findings. One potential explanation may be that systems originally designed for acute care settings are being implemented in primary care. Early studies evaluating personal health records suggest that targeting patient outcomes directly and adapting systems to patients' needs may be part of the solution.

CONCLUSION

In order to develop personal health records for primary care, studies are needed that involve the users, namely patients and primary care health professionals, in the design and evaluation of these systems from their inception. Participatory research is a recommended methodological approach.

Impact of the drug-drug interaction database SFINX on prevalence of potentially serious drug-drug interactions in primary health care

PURPOSE

To investigate the impact of the integration of the drug-drug interaction database SFINX into primary health care records on the prevalence of potentially serious drug-drug interactions.

METHODS

The study was a controlled before-and-after study on the prevalence of potential drug-drug interactions before and after the implementation of SFINX at 15 primary healthcare centres compared with 5 centres not receiving the intervention. Data on dispensed prescriptions from health care centres were retrieved from the Swedish prescribed drug register and analysed for September-December 2006 (pre-intervention) and September-December 2007 (post-intervention). All drugs dispensed during each 4 month period were regarded as potentially interacting.

RESULTS

Use of SFINX was associated with a 17% decrease, to 1.81 × 10(-3) from 2.15 × 10(-3) interactions per prescribed drug-drug pair, in the prevalence of potentially serious drug-drug interactions (p = 0.042), whereas no significant effect was observed in the control group. The change in prevalence of potentially serious drug-drug interactions did not differ significantly between the two study groups. The majority of drug-drug interactions identified were related to chelate formation.

CONCLUSION

Prescriptions resulting in potentially serious drug-drug interactions were significantly reduced after integration of the drug-drug interaction database SFINX into electronic health records in primary care. Further studies are needed to demonstrate the effectiveness of drug-drug interaction warning systems.

Drug-drug interactions in the medical intensive care unit: an assessment of frequency, severity and the medications involved

OBJECTIVES

Mortality and morbidity are increased in patients experiencing drug-drug interactions (DDIs). Critically ill patients are at an increased risk of adverse events from DDIs due to the large number of medications that they take and their changes in organ function. Currently, there is a lack of literature describing DDIs in the intensive care unit (ICU). The purpose of this study is to evaluate frequency, severity and drug combinations involved in DDIs occurring in a medical ICU (MICU).

METHODS

This was a 4-week, prospective, observational study that was conducted in the MICU of an academic medical centre. Lexi-Interact and Micromedex interaction databases were utilized daily to screen patients' medication profiles for DDIs, and severity was assessed using each database's severity rating scale.

KEY FINDINGS

Of 240 patient medication profiles evaluated, 457 DDIs were identified. The rate of DDIs was 190.4 DDIs/100 patient days with 297 of these interactions being unique drug pairs. About 25% (114/457) were considered major DDIs. The most commonly involved medications were antihypertensive medications (106/457) and anticoagulants/antiplatelet agents (80/457).

CONCLUSIONS

DDIs occur frequently in the MICU. Severity and drug combinations related to DDIs in the MICU differ from DDIs published in other ICU settings. When developing a DDI alerting system, patient characteristics and location should be considered.