Impact of implementing alerts about medication black-box warnings in electronic health records

Effectiveness of clinical decision support in controlling inappropriate red blood cell and platelet transfusions, speciality specific responses and behavioural change

BACKGROUND

Electronic clinical decision support (CDS) within Electronic Health Records has been used to improve patient safety, including reducing unnecessary blood product transfusions. We assessed the effectiveness of CDS in controlling inappropriate red blood cell (RBC) and platelet transfusion in a large acute hospital and how speciality specific behaviours changed in response.

METHODS

We used segmented linear regression of interrupted time series models to analyse the instantaneous and long term effect of introducing blood product electronic warnings to prescribers. We studied the impact on transfusions for patients in critical care (CC), haematology/oncology (HO) and elsewhere.

RESULTS

In non-CC or HO, there was significant and sustained decrease in the numbers of RBC transfusions after introduction of alerts. In CC the alerts reduced transfusions but this was not sustained, and in HO there was no impact on RBC transfusion. For platelet transfusions outside of CC and HO, the introduction of alerts stopped a rising trend of administration of platelets above recommended targets. In CC, alerts reduced platelet transfusions, but in HO alerts had little impact on clinician prescribing.

CONCLUSION

The findings suggest that CDS can result in immediate change in user behaviour which is more obvious outside specialist settings of CC and HO. It is important that this is then sustained. In CC and HO, blood transfusion practices differ. CDS thus needs to take specific circumstances into account. In this case there are acceptable reasons to transfuse outside of these crude targets and CDS should take these into account.

Electronic health record alerts for acute kidney injury: multicenter, randomized clinical trial

OBJECTIVE

To determine whether electronic health record alerts for acute kidney injury would improve patient outcomes of mortality, dialysis, and progression of acute kidney injury.

DESIGN

Double blinded, multicenter, parallel, randomized controlled trial.

SETTING

Six hospitals (four teaching and two non-teaching) in the Yale New Haven Health System in Connecticut and Rhode Island, US, ranging from small community hospitals to large tertiary care centers.

PARTICIPANTS

6030 adult inpatients with acute kidney injury, as defined by the Kidney Disease: Improving Global Outcomes (KDIGO) creatinine criteria.

INTERVENTIONS

An electronic health record based "pop-up" alert for acute kidney injury with an associated acute kidney injury order set upon provider opening of the patient's medical record.

MAIN OUTCOME MEASURES

A composite of progression of acute kidney injury, receipt of dialysis, or death within 14 days of randomization. Prespecified secondary outcomes included outcomes at each hospital and frequency of various care practices for acute kidney injury.

RESULTS

6030 patients were randomized over 22 months. The primary outcome occurred in 653 (21.3%) of 3059 patients with an alert and in 622 (20.9%) of 2971 patients receiving usual care (relative risk 1.02, 95% confidence interval 0.93 to 1.13, P=0.67). Analysis by each hospital showed worse outcomes in the two non-teaching hospitals (n=765, 13%), where alerts were associated with a higher risk of the primary outcome (relative risk 1.49, 95% confidence interval 1.12 to 1.98, P=0.006). More deaths occurred at these centers (15.6% in the alert group v 8.6% in the usual care group, P=0.003). Certain acute kidney injury care practices were increased in the alert group but did not appear to mediate these outcomes.

CONCLUSIONS

Alerts did not reduce the risk of our primary outcome among patients in hospital with acute kidney injury. The heterogeneity of effect across clinical centers should lead to a re-evaluation of existing alerting systems for acute kidney injury.

TRIAL REGISTRATION

ClinicalTrials.gov NCT02753751.

Translation of evidence into kidney transplant clinical practice: managing drug-lab interactions by a context-aware clinical decision support system

BACKGROUND

Drug-laboratory (lab) interactions (DLIs) are a common source of preventable medication errors. Clinical decision support systems (CDSSs) are promising tools to decrease such errors by improving prescription quality in terms of lab values. However, alert fatigue counteracts their impact. We aimed to develop a novel user-friendly, evidence-based, clinical context-aware CDSS to alert nephrologists about DLIs clinically important lab values in prescriptions of kidney recipients.

METHODS

For the most frequently prescribed medications identified by a prospective cross-sectional study in a kidney transplant clinic, DLI-rules were extracted using main pharmacology references and clinical inputs from clinicians. A CDSS was then developed linking a computerized prescription system and lab records. The system performance was tested using data of both fictitious and real patients. The "Questionnaire for User Interface Satisfaction" was used to measure user satisfaction of the human-computer interface.

RESULTS

Among 27 study medications, 17 needed adjustments regarding renal function, 15 required considerations based on hepatic function, 8 had drug-pregnancy interactions, and 13 required baselines or follow-up lab monitoring. Using IF & THEN rules and the contents of associated alert, a DLI-alerting CDSS was designed. To avoid alert fatigue, the alert appearance was considered as interruptive only when medications with serious risks were contraindicated or needed to be discontinued or adjusted. Other alerts appeared in a non-interruptive mode with visual clues on the prescription window for easy, intuitive notice. When the system was used for real 100 patients, it correctly detected 260 DLIs and displayed 249 monitoring, seven hepatic, four pregnancy, and none renal alerts. The system delivered patient-specific recommendations based on individual lab values in real-time. Clinicians were highly satisfied with the usability of the system.

CONCLUSIONS

To our knowledge, this is the first study of a comprehensive DLI-CDSS for kidney transplant care. By alerting on considerations in renal and hepatic dysfunctions, maternal and fetal toxicity, or required lab monitoring, this system can potentially improve medication safety in kidney recipients. Our experience provides a strong foundation for designing specialized systems to promote individualized transplant follow-up care.

The critical need for clinical decision support systems for identification and management of teratogenic medications

OBJECTIVES

To describe the critical need for clinical decision support systems to identify and manage use of potentially teratogenic medications in women of reproductive potential in the United States.

DATA SOURCES

Medline, CINAHL Plus, Academic Search Complete, International Pharmaceutical Abstracts, and the Cochrane Library databases were searched on November 1, 2018, with the key words (teratogen* OR birth defect OR Category D OR Category X OR (pregnancy or pregnant)) AND (clinical decision support OR decision support OR electronic record) to identify primary literature published in peer-reviewed journals describing clinical decision support systems implemented in outpatient settings in the United States to promote safe prescribing and clinician counseling for teratogenic medications. A hand search of the reference lists of relevant articles, including review articles, found through this search strategy was also performed.

SUMMARY

Despite the great potential for clinical decision support to assist clinicians in minimizing inadvertent fetal exposure to potentially teratogenic medications, there were only seven primary articles meeting the criteria. The results of these studies have shown some evidence of effectiveness yet had several notable limitations. No published clinical decision system showed great success. An eighth article, published in 2017, details the design of an intervention that had been implemented but not yet evaluated.

CONCLUSION

There is a relative paucity of data regarding clinical decision support systems focused on teratogenic medications in the outpatient setting in the United States. Additional clinical decision support systems in this area need to be developed.

Comprehensive process model of clinical information interaction in primary care: results of a "best-fit" framework synthesis

Objective

To describe a new, comprehensive process model of clinical information interaction in primary care (Clinical Information Interaction Model, or CIIM) based on a systematic synthesis of published research.

Materials and Methods

We used the "best fit" framework synthesis approach. Searches were performed in PubMed, Embase, the Cumulative Index to Nursing and Allied Health Literature (CINAHL), PsycINFO, Library and Information Science Abstracts, Library, Information Science and Technology Abstracts, and Engineering Village. Two authors reviewed articles according to inclusion and exclusion criteria. Data abstraction and content analysis of 443 published papers were used to create a model in which every element was supported by empirical research.

Results

The CIIM documents how primary care clinicians interact with information as they make point-of-care clinical decisions. The model highlights 3 major process components: (1) context, (2) activity (usual and contingent), and (3) influence. Usual activities include information processing, source-user interaction, information evaluation, selection of information, information use, clinical reasoning, and clinical decisions. Clinician characteristics, patient behaviors, and other professionals influence the process.

Discussion

The CIIM depicts the complete process of information interaction, enabling a grasp of relationships previously difficult to discern. The CIIM suggests potentially helpful functionality for clinical decision support systems (CDSSs) to support primary care, including a greater focus on information processing and use. The CIIM also documents the role of influence in clinical information interaction; influencers may affect the success of CDSS implementations.

Conclusion

The CIIM offers a new framework for achieving CDSS workflow integration and new directions for CDSS design that can support the work of diverse primary care clinicians.

The Impact of US FDA and Health Canada Warnings Related to the Safety of High-dose Simvastatin

Introduction

Between 2010 and 2012, the US Food and Drug Administration and Health Canada issued warnings to healthcare professionals emphasizing the increased risk of muscle problems with high-dose simvastatin.

Objective

To measure the impact of the Health Canada safety warning regarding dose-dependent adverse effects of simvastatin on prescribing of low, medium, and high doses of simvastatin.

Methods

An interrupted time-series design was used to evaluate the impact of a Health Canada safety warning on 7 November 2012 regarding the safety of high-dose simvastatin. Monthly prescription records were analyzed for beneficiaries of the Nova Scotia Seniors’ Pharmacare Program aged 65 years or older who had received > 1 prescription of simvastatin between 1 January 1997 and 31 March 2015. Autoregressive Integrated Moving Average models were used to test changes in the proportion of beneficiaries dispensed a low dose (< 40 mg), medium dose (40 mg to < 80 mg), or high dose (≥ 80 mg) of simvastatin over time.

Results

There were 219 monthly periods, of which 29 periods occurred after the Health Canada warning. On average during the pre-warning periods there were 2944 simvastatin users per month, of whom 71% were dispensed a low dose, 26% a medium dose, and 2% a high dose. The proportion of beneficiaries dispensed low-dose simvastatin increased by 0.9% (one-sided p value 0.035; 90% CI 0.07–1.65), the proportion dispensed medium-dose simvastatin decreased by 0.7% (one-sided p value 0.0496; 90% CI −1.48 to −0), and there was no significant change in the proportion dispensed high-dose simvastatin (−0.15% change, one-sided p value 0.205; 90% CI −0.45 to 0.15).

Conclusions

The Health Canada Health Care Professional warning had a small effect on increasing the proportion of beneficiaries dispensed low and medium doses of simvastatin but not high doses of simvastatin. Nevertheless, there remain seniors in Nova Scotia receiving high-dose simvastatin for whom the benefit/risk potential may need to be re-evaluated.

Trends in Use of High-Intensity Statin Therapy After Myocardial Infarction, 2011 to 2014

BACKGROUND

Data prior to 2011 suggest that a low percentage of patients hospitalized for acute coronary syndromes filled high-intensity statin prescriptions upon discharge. Black-box warnings, generic availability of atorvastatin, and updated guidelines may have resulted in a change in high-intensity statin use.

OBJECTIVES

The aim of this study was to examine trends and predictors of high-intensity statin use following hospital discharge for myocardial infarction (MI) between 2011 and 2014.

METHODS

Secular trends in high-intensity statin use following hospital discharge for MI were analyzed among patients 19 to 64 years of age with commercial health insurance in the MarketScan database (n = 42,893) and 66 to 75 years of age with U.S. government health insurance through Medicare (n = 75,096). Patients filling statin prescriptions within 30 days of discharge were included. High-intensity statins included atorvastatin 40 or 80 mg and rosuvastatin 20 or 40 mg.

RESULTS

The percentage of beneficiaries whose first statin prescriptions filled following hospital discharge for MI were for high-intensity doses increased from 33.5% in January through March 2011 to 71.7% in October through November 2014 in MarketScan and from 24.8% to 57.5% in Medicare. Increases in high-intensity statin use following hospital discharge occurred over this period among patients initiating treatment (30.6% to 72.0% in MarketScan and 21.1% to 58.8% in Medicare) and those taking low- or moderate-intensity statins prior to hospitalization (from 27.8% to 62.3% in MarketScan and from 12.6% to 45.1% in Medicare). In 2014, factors associated with filling high-intensity statin prescriptions included male sex, filling beta-blocker and antiplatelet agent prescriptions, and attending cardiac rehabilitation within 30 days following discharge.

CONCLUSIONS

The use of high-intensity statins following hospitalization for MI increased progressively from 2011 through 2014.

Prospective Assessment of Inpatient Boxed Warning Prescriber Adherence

OBJECTIVE

To evaluate medication boxed warning nonadherence in the inpatient setting.

METHODS

This was a prospective cohort quality improvement project approved by our institution's Total Quality Council. General medicine and ICU patients 18 years and older were included if they were cared for by a prescriber-led multidisciplinary team that included a pharmacist. Patients were evaluated for medication orders with an actionable boxed warning; if boxed warning nonadherence occurred, the physician's reason was determined. Patients with boxed warning nonadherence were monitored for adverse drug reactions until discharge.

RESULTS

A total of 393 patients (224 general medicine and 169 ICU) were evaluated for nonadherence to 149 actionable boxed warnings. There were 293 drugs (175 general medicine and 118 ICU) with boxed warnings prescribed, and more than 50% of these were medications restarted from home. A total of 23 boxed warning nonadherences occurred in general medicine patients, and NSAIDs accounted for 81% of these events. ICU patients experienced 11 boxed warning nonadherences, with nearly 54% from anti-infectives and immunosuppressants. Antipsychotics were the most commonly ordered boxed warning medication class in ICU patients. Reasons for nonadherence included knowledge deficit and an acceptable risk-to-benefit ratio. Two adverse drug reactions occurred from boxed warning nonadherences, both because of a drug-drug interaction.

CONCLUSIONS

Boxed warning nonadherence is a concern in the inpatient setting, specifically with NSAID use in general medicine patients and antipsychotic use in ICU patients. More than half of boxed warning nonadherence occurred in medications restarted from home, which emphasizes the need for medication evaluation during transitions of care.

Information Technology-Based Interventions to Improve Drug-Drug Interaction Outcomes: A Systematic Review on Features and Effects

The purpose of this systematic review was to identify features and effects of information technology (IT)-based interventions on outcomes related to drug-drug interactions (DDI outcomes). A literature search was conducted in Medline, EMBASE, and the Cochrane Library for published English-language studies. Studies were included if a main outcome was related to DDIs, the intervention involved an IT-based system, and the study design was experimental or observational with controls. Study characteristics, including features and effects of IT-based interventions, were extracted. Nineteen studies comprising five randomized controlled trials (RCT), five non-randomized controlled trials (NRCT) and nine observational studies with controls (OWC) were included. Sixty-four percent of prescriber-directed interventions, and all non-prescriber interventions, were effective. Each of the following characteristics corresponded to groups of studies of which a majority were effective: automatic provision of recommendations within the providers' workflow, intervention at the time of decision-making, integration into other systems, and requiring the reason for not following the recommendations. Only two studies measured clinical outcomes: an RCT that showed no significant improvement and an OWC that showed improvement, but did not statistically assess the effect. Most studies that measured surrogate outcomes (e.g. potential DDIs) and other outcomes (e.g. adherence to alerts) showed improvements. IT-based interventions improve surrogate clinical outcomes and adherence to DDI alerts. However, there is lack of robust evidence about their effectiveness on clinical outcomes. It is recommended that researchers consider the identified features of effective interventions in the design of interventions and evaluate the effectiveness on DDI outcomes, particularly clinical outcomes.

Co-Prescribing of Potentially Interacting Drugs during Warfarin Therapy - A Population-Based Register Study

We analysed the occurrence of co-prescribing of potentially interacting drugs during warfarin therapy in the community-dwelling population of Finland. We identified drugs having interaction potential with warfarin using the Swedish Finnish INteraction X-referencing drug-drug interaction database (SFINX) and obtained data on drug purchases from the nationwide Prescription Register. We defined warfarin users as persons purchasing warfarin in 2010 (n = 148,536) and followed them from their first prescription in 2010 until the end of the calendar year. Co-prescribing was defined as at least 1-day overlap between warfarin and interacting drug episodes. In addition, we identified persons who initiated warfarin therapy between 1 January 2007 and 30 September 2010 (n = 110,299) and followed these incident users for a 3-month period since warfarin initiation. Overall, 74.4% of warfarin users were co-prescribed interacting drugs. Co-prescribing covered 46.4% of the total person-years of warfarin exposure. Interacting drugs that should be avoided with warfarin were co-prescribed for 13.4% of warfarin users. The majority of the co-prescriptions were for drugs that are not contraindicated during warfarin therapy but require special consideration. Among incident users, 57.1% purchased potentially interacting drugs during the 3-month period after initiation, while 9.0% purchased interacting drugs that should be avoided with warfarin. To conclude, the occurrence of co-prescribing of potentially interacting drugs was high during warfarin therapy. Our findings highlight the importance of close monitoring of warfarin therapy and the need for further studies on the clinical consequences of co-prescribing of interacting drugs with warfarin.

Factors associated with ordering laboratory monitoring of high-risk medications

BACKGROUND

Knowledge about factors associated with provider ordering of appropriate testing is limited.

OBJECTIVE

To determine physician factors associated with ordering recommended laboratory monitoring tests for high-risk medications.

METHODS

Retrospective cohort study of patients prescribed a high-risk medication requiring laboratory monitoring in a large multispecialty group practice between 1 January 2008 and 31 December 2008. Analyses are based on administrative claims and electronic medical records. The outcome is a physician order for each recommended laboratory test for each prescribed medication. Key predictor variables are physician characteristics, including age, gender, specialty training, years since completing training, and prescribing volume. Additional variables are patient characteristics such as age, gender, comorbidity burden, whether the medication requiring monitoring is new or chronic, and drug-test characteristics such as inclusion in black box warnings. We used multivariable logistic regression, accounting for clustering of drugs within patients and patients within providers.

RESULTS

Physician orders for laboratory testing varied across drug-test pairs and ranged from 9% (Primidone-Phenobarbital level) to 97% (Azathioprine-CBC), with half of the drug-test pairs in the 85-91% ordered range. Test ordering was associated with higher provider prescribing volume for study drugs and specialist status (primary care providers were less likely to order tests than specialists). Patients with higher comorbidity burden and older patients were more likely to have appropriate tests ordered. Drug-test combinations with black box warnings were more likely to have tests ordered.

CONCLUSIONS

Interventions to improve laboratory monitoring should focus on areas with the greatest potential for improvement: providers with lower frequencies of prescribing medications with monitoring recommendations and those prescribing these medications for healthier and younger patients; patients with less interaction with the health care system are at particular risk of not having tests ordered. Black box warnings were associated with higher ordering rates and may be a tool to increase appropriate test ordering.

Impact of clinical decision support on receipt of antibiotic prescriptions for acute bronchitis and upper respiratory tract infection

OBJECTIVE

Antibiotics are commonly recognized as non-indicated for acute bronchitis and upper respiratory tract infection (URI), yet their widespread use persists. Clinical decision support in the form of electronic warnings is hypothesized to prevent non-indicated prescriptions. The purpose of this study was to identify the effect of clinical decision support on a common type of non-indicated prescription.

MATERIALS AND METHODS

Using National Ambulatory Medical Care Survey data from 2006 to 2010, ambulatory visits with a primary diagnosis of acute bronchitis or URI and orders for antibiotic prescriptions were identified. Visits were classified on the basis of clinician report of decision-support use. Generalized estimating equations were used to assess the effect of decision support on likelihood of antibiotic prescription receipt, controlling for patient, provider, and practice characteristics.

RESULTS

Clinician use of decision support increased sharply between 2006 (16% of visits) and 2010 (55%). Antibiotic prescribing for acute bronchitis and URI increased from ∼35% of visits in 2006 to ∼45% by 2010. Use of decision support was associated with a 19% lower likelihood of receiving an antibiotic prescription, controlling for patient, provider, and practice characteristics.

DISCUSSION

In spite of the increased use of decision-support systems and the relatively fewer non-indicated antibiotic prescriptions resulting from the use of decision support, a secular upward trend in non-indicated antibiotic prescribing offset these improvements.

CONCLUSIONS

The overall effect of decision support suggests an important role for technology in reducing non-indicated prescriptions. Decision support alone may not be sufficient to eliminate non-indicated prescriptions given secular trends.

Using the computer in the clinical consultation; setting the stage, reviewing, recording, and taking actions: multi-channel video study

BACKGROUND AND OBJECTIVE

Electronic patient record (EPR) systems are widely used. This study explores the context and use of systems to provide insights into improving their use in clinical practice.

METHODS

We used video to observe 163 consultations by 16 clinicians using four EPR brands. We made a visual study of the consultation room and coded interactions between clinician, patient, and computer. Few patients (6.9%, n=12) declined to participate.

RESULTS

Patients looked at the computer twice as much (47.6 s vs 20.6 s, p<0.001) when it was within their gaze. A quarter of consultations were interrupted (27.6%, n=45); and in half the clinician left the room (12.3%, n=20). The core consultation takes about 87% of the total session time; 5% of time is spent pre-consultation, reading the record and calling the patient in; and 8% of time is spent post-consultation, largely entering notes. Consultations with more than one person and where prescribing took place were longer (R(2) adj=22.5%, p<0.001). The core consultation can be divided into 61% of direct clinician-patient interaction, of which 15% is examination, 25% computer use with no patient involvement, and 14% simultaneous clinician-computer-patient interplay. The proportions of computer use are similar between consultations (mean=40.6%, SD=13.7%). There was more data coding in problem-orientated EPR systems, though clinicians often used vague codes.

CONCLUSIONS

The EPR system is used for a consistent proportion of the consultation and should be designed to facilitate multi-tasking. Clinicians who want to promote screen sharing should change their consulting room layout.

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.

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.

Baseline and follow-up laboratory monitoring of cardiovascular medications

BACKGROUND

Laboratory monitoring of medications is typically used to establish safety prior to drug initiation and to detect drug-related injury following initiation. It is unclear whether black box warnings (BBWs) as well as evidence- and consensus-based clinical guidelines increase the likelihood of appropriate monitoring.

OBJECTIVE

To determine the proportion of patients newly initiated on selected cardiovascular medications with baseline assessment and follow-up laboratory monitoring and compare the prevalence of laboratory testing for drugs with and without BBWs and guidelines.

METHODS

This cross-sectional study included patients aged 18 years or older from a large multispecialty group practice who were prescribed a cardiovascular medication (angiotensin converting enzyme inhibitors, angiotensin II receptor blockers, amiodarone, digoxin, lipid-lowering agents, diuretics, and potassium supplements) between January 1 and July 31, 2008. The primary outcome measure was laboratory test ordering for baseline assessment and follow-up monitoring of newly initiated cardiovascular medications.

RESULTS

The number of new users of each study drug ranged from 49 to 1757 during the study period. Baseline laboratory test ordering across study drugs ranged from 37.4% to 94.8%, and follow-up laboratory test ordering ranged from 20.0% to 77.2%. Laboratory tests for drugs with baseline laboratory assessment recommendations in BBWs were more commonly ordered than for drugs without BBWs (86.4% vs 78.0%, p < 0.001). Drugs with follow-up monitoring recommendations in clinical guidelines had a lower prevalence of monitoring (33.1% vs 50.7%, p < 0.001).

CONCLUSIONS

Baseline assessment of cardiovascular medication monitoring is variable. Quality measurement of adherence to BBW recommendations may improve monitoring.