Nancy Winslade

A Randomized Trial of the Effectiveness of On-demand versus Computer-triggered Drug Decision Support in Primary Care

OBJECTIVES Prescribing alerts generated by computerized drug decision support (CDDS) may prevent drug-related morbidity. However, the vast majority of alerts are ignored because of clinical irrelevance. The ability to customize commercial alert systems should improve physician acceptance because the physician can select the circumstances and types of drug alerts that are viewed. We tested the effectiveness of two approaches to medication alert customization to reduce prevalence of prescribing problems: on-physician-demand versus computer-triggered decision support. Physicians in each study condition were able to preset levels that triggered alerts. DESIGN This was a cluster trial with 28 primary care physicians randomized to either automated or on-demand CDDS in the MOXXI drug management system for 3,449 of their patients seen over the next 6 months. MEASUREMENTS The CDDS generated alerts for prescribing problems that could be customized by severity level. Prescribing problems included dosing errors, drug-drug, age, allergy, and disease interactions. Physicians randomized to on-demand activated the drug review when they considered it clinically relevant, whereas physicians randomized to computer-triggered decision support viewed all alerts for electronic prescriptions in accordance with the severity level they selected for both prevalent and incident problems. Data from administrative claims and MOXXI were used to measure the difference in the prevalence of prescribing problems at the end of follow-up. RESULTS During follow-up, 50% of the physicians receiving computer-triggered alerts modified the alert threshold (n = 7), and 21% of the physicians in the alert-on-demand group modified the alert level (n = 3). In the on-demand group 4,445 prescribing problems were identified, 41 (0.9%) were seen by requested drug review, and in 31 problems (75.6%) the prescription was revised. In comparison, 668 (10.3%) of the 6,505 prescribing problems in the computer-triggered group were seen, and 81 (12.1%) were revised. The majority of alerts were ignored because the benefit was judged greater than the risk, the interaction was known, or the interaction was considered clinically not important (computer-triggered: 75.8% of 585 ignored alerts; on-demand: 90% of 10 ignored alerts). At the end of follow-up, there was a significant reduction in therapeutic duplication problems in the computer-triggered group (odds ratio 0.55; p = 0.02) but no difference in the overall prevalence of prescribing problems. CONCLUSION Customization of computer-triggered alert systems is more useful in detecting and resolving prescribing problems than on-demand review, but neither approach was effective in reducing prescribing problems. New strategies are needed to maximize the use of drug decision support systems to reduce drug-related morbidity.

Risk of Injury Associated with Opioid Use in Older Adults

OBJECTIVES: To estimate the dose‐related risk of injuries in older adults associated with the use of low‐, medium‐, and high‐potency opioids.

Doctor scores on national qualifying examinations predict quality of care in future practice

Objectives  This study aimed to determine if national licensing examinations that measure medical knowledge (QE1) and clinical skills (QE2) predict the quality of care delivered by doctors in future practice.

Drug, Patient, and Physician Characteristics Associated With Off-label Prescribing in Primary Care

BACKGROUND Off-label prescribing may lead to adverse drug events. Little is known about its prevalence and determinants resulting from challenges in documenting treatment indication. METHODS We used the Medical Office of the XXI Century electronic health record network in Quebec, Canada, where documentation of treatment indication is mandatory. One hundred thirteen primary care physicians wrote 253 347 electronic prescriptions for 50 823 patients from January 2005 through December 2009. Each drug indication was classified as on-label or off-label according to the Health Canada drug database. We identified off-label uses lacking strong scientific evidence. Alternating logistic regression was used to estimate the association between off-label use and drug, patient, and physician characteristics. RESULTS The prevalence of off-label use was 11.0%; of the off-label prescriptions, 79.0% lacked strong scientific evidence. Off-label use was highest for central nervous system drugs (26.3%), including anticonvulsants (66.6%), antipsychotics (43.8%), and antidepressants (33.4%). Drugs with 3 or 4 approved indications were associated with less off-label use compared with drugs with 1 or 2 approved indications (6.7% vs 15.7%; adjusted odds ratio [AOR], 0.44; 95% CI, 0.41-0.48). Drugs approved after 1995 were prescribed off-label less often than were drugs approved before 1981 (8.0% vs 17.0%; AOR, 0.46; 95% CI, 0.42-0.50). Patients with a Charlson Comorbidity Index of 1 or higher had lower off-label use than did patients with an index of 0 (9.6% vs 11.7%; AOR, 0.94; 95% CI, 0.91-0.97). Physicians with evidence-based orientation were less likely to prescribe off-label (AOR, 0.93; 95% CI, 0.88-0.99), a 7% reduction per 5 points in the evidence section of the Evidence-Practicality-Conformity Scale. CONCLUSIONS Off-label prescribing is common and varies by drug, patient, and physician characteristics. Electronic prescribing should document treatment indication to monitor off-label use.

Association of Off-label Drug Use and Adverse Drug Events in an Adult Population

IMPORTANCE Off-label use of prescription drugs has been identified as an important contributor to preventable adverse drug events (ADEs) in children. Despite concerns regarding adverse outcomes, to date, no systematic investigation of the effects of off-label drug use in adult populations has been performed. OBJECTIVE To monitor and evaluate off-label use of prescription drugs and its effect on ADEs in an adult population. DESIGN, SETTING, AND PARTICIPANTS A cohort of 46,021 patients who received 151,305 incident prescribed drugs was assembled from primary care clinics in Quebec, Canada, using the Medical Office of the XXIst Century electronic health record, which supports documentation of treatment indications and treatment outcomes. Prescriptions dispensed from January 1, 2005, through December 30, 2009, were followed up from the date of the prescription to the date the drug use was discontinued, the end of treatment, or the end of follow-up (December 30, 2010). Data were analyzed from January 5, 2012, to March 15, 2015. EXPOSURES Off-label prescription drug use with and without strong scientific evidence. MAIN OUTCOMES AND MEASURES Adverse drug events in off-label use with and without strong scientific evidence. Analysis used multivariate marginal Cox proportional hazards regression for clustered data with the drug as the unit of analysis. RESULTS A total of 3484 ADEs were found in the 46,021 study patients, with an incidence rate of 13.2 per 10,000 person-months. The rate of ADEs for off-label use (19.7 per 10,000 person-months) was higher than that for on-label use (12.5 per 10,000 person-months) (adjusted hazard ratio [AHR], 1.44; 95% CI, 1.30-1.60). Off-label use lacking strong scientific evidence had a higher ADE rate (21.7 per 10,000 person-months) compared with on-label use (AHR, 1.54; 95% CI, 1.37-1.72). However, off-label use with strong scientific evidence had the same risk for ADEs as on-label use (AHR, 1.10; 95% CI, 0.88-1.38). The risks for ADEs were higher for drugs approved from 1981 to 1995 (14.4 per 10,000 person-months; AHR, 1.62; 95% CI, 1.45-1.80) and for those used by women (14.3 per 10,000 person-months; AHR, 1.17; 95% CI, 1.06-1.28), patients receiving 5 to 7 drugs (12.1 per 10,000 person-months; AHR, 3.23; 95% CI, 2.66-3.92), and patients receiving cardiovascular drugs (15.9 per 10,000 person-months; AHR, 3.30; 95% CI, 2.67-4.08) and anti-infectives (66.2 per 10,000 person-months; AHR, 6.33; 95% CI, 4.58-8.76). Patients with a 1-unit increase in the continuity of care index had a 19% increase in ADEs (AHR, 1.19; 95% CI, 1.12-1.26). CONCLUSIONS AND RELEVANCE Off-label use of prescription drugs is associated with ADEs. Caution should be exercised in prescribing drugs for off-label uses that lack strong scientific evidence. Future electronic health records should be designed to enable postmarket surveillance of treatment indications and treatment outcomes to monitor the safety of on- and off-label uses of drugs.

Influence of Physicians' Management and Communication Ability on Patients' Persistence With Antihypertensive Medication

BACKGROUND Less than 75% of people prescribed antihypertensive medication are still using treatment after 6 months. Physicians determine treatment, educate patients, manage side effects, and influence patient knowledge and motivation. Although physician communication ability likely influences persistence, little is known about the importance of medical management skills, even though these abilities can be enhanced through educational and practice interventions. The purpose of this study was to determine whether a physicians medical management and communication ability influence persistence with antihypertensive treatment. METHODS This was a population-based study of 13,205 hypertensive patients who started antihypertensive medication prescribed by a cohort of 645 physicians entering practice in Quebec, Canada, between 1993 and 2007. Medical Council of Canada licensing examination scores were used to assess medical management and communication ability. Population-based prescription and medical services databases were used to assess starting therapy, treatment changes, comorbidity, and persistence with antihypertensive treatment in the first 6 months. RESULTS Within 6 months after starting treatment, 2926 patients (22.2%) had discontinued all antihypertensive medication. The risk of nonpersistence was reduced for patients who were treated by physicians with better medical management (odds ratio per 2-SD increase in score, 0.74; 95% confidence interval, 0.63-0.87) and communication (0.88; 0.78-1.00) ability and with early therapy changes (odds ratio, 0.45; 95% confidence interval, 0.37-0.54), more follow-up visits, and nondiuretics as the initial choice of therapy. Medical management ability was responsible for preventing 15.8% (95% confidence interval, 7.5%-23.3%) of nonpersistence. CONCLUSION Better clinical decision-making and data collection skills and early modifications in therapy improve persistence with antihypertensive therapy.

The effectiveness of a new generation of computerized drug alerts in reducing the risk of injury from drug side effects: a cluster randomized trial

Context Computerized drug alerts for psychotropic drugs are expected to reduce fall-related injuries in older adults. However, physicians over-ride most alerts because they believe the benefit of the drugs exceeds the risk. Objective To determine whether computerized prescribing decision support with patient-specific risk estimates would increase physician response to psychotropic drug alerts and reduce injury risk in older people. Design Cluster randomized controlled trial of 81 family physicians and 5628 of their patients aged 65 and older who were prescribed psychotropic medication. Intervention Intervention physicians received information about patient-specific risk of injury computed at the time of each visit using statistical models of non-modifiable risk factors and psychotropic drug doses. Risk thermometers presented changes in absolute and relative risk with each change in drug treatment. Control physicians received commercial drug alerts. Main outcome measures Injury risk at the end of follow-up based on psychotropic drug doses and non-modifiable risk factors. Electronic health records and provincial insurance administrative data were used to measure outcomes. Results Mean patient age was 75.2 years. Baseline risk of injury was 3.94 per 100 patients per year. Intermediate-acting benzodiazepines (56.2%) were the most common psychotropic drug. Intervention physicians reviewed therapy in 83.3% of visits and modified therapy in 24.6%. The intervention reduced the risk of injury by 1.7 injuries per 1000 patients (95% CI 0.2/1000 to 3.2/1000; p=0.02). The effect of the intervention was greater for patients with higher baseline risks of injury (p<0.03). Conclusion Patient-specific risk estimates provide an effective method of reducing the risk of injury for high-risk older people. Trial registration number clinicaltrials.gov Identifier: NCT00818285.

Increasing the Detection and Response to Adherence Problems with Cardiovascular Medication in Primary Care through Computerized Drug Management Systems: A Randomized Controlled Trial

Background. Adherence with antihypertensive and lipid-lowering therapy is poor, resulting in an almost 2-fold increase in hospitalization. Treatment side effects, cost, and complexity are common reasons for nonadherence, and physicians are often unaware of these potentially modifiable problems. Objective. To determine if a cardiovascular medication tracking and nonadherence alert system, incorporated into a computerized health record system, would increase drug profile review by primary care physicians, increase the likelihood of therapy change, and improve adherence with antihypertensive and lipid-lowering drugs. Methods. There were 2293 primary care patients prescribed lipid-lowering or antihypertensive drugs who were randomized to the adherence tracking and alert system or active medication list alone to determine if the intervention increased drug profile review, changes in cardiovascular drug treatment, and refill adherence in the first 6 months. An intention to treat analysis was conducted using generalized estimating equations to account for clustering within physician. Results. Overall, medication adherence was below 80% for 36.3% of patients using lipid-lowering drugs and 40.8% of patients using antihypertensives at the start of the trial. There was a significant increase in drug profile review in the intervention compared to the control group (44.5% v. 35.5%; P < 0.001), a nonsignificant increase in drug discontinuations due to side effects (2.3% v. 2.0%; P = 0.61), and a reduction in therapy increases (28.5% v. 29.1%; P = 0.86). There was no significant change in refill adherence after 6 months of follow-up. Conclusion. An adherence tracking and alert system increases drug review but not therapy changes or adherence in prevalent users of cardiovascular drug treatment. Targeting incident users where adverse treatment effects are more common and combining adherence tracking and alert tools with motivational interventions provided by multidisciplinary primary care teams may improve the effectiveness of the intervention.

Detection of Adverse Drug Events and Other Treatment Outcomes Using an Electronic Prescribing System

AbstractBackground: Current pharmacosurveillance methods do not provide timely information on drug safety and effectiveness. Real-time surveillance using electronic prescribing systems could address this problem; however, the data collected using these systems has not been validated. We investigated the accuracy of using orders for drug discontinuation and dose change in an electronic prescribing system as a potential source of information for drug safety and effectiveness. Objectives: To determine the accuracy of an electronic prescribing and drug management system in documenting orders for discontinuation and dose changes of prescription drug treatment, and in identifying the reasons for the drug discontinuation and dose change. Study design and setting: We prospectively assessed the accuracy of electronic prescription orders for drug discontinuation and dose change by comparing them with treatment changes documented by physician-facilitated medical chart review (gold standard). Validity was evaluated in 620 patients of 22 community-based primary care physicians in addition to the reasons for these treatment changes. Results: A total of 141 (41.7%) drug discontinuation orders and 197 (58.3%) changes in drug doses were identified by chart review, the majority of which were for cardiovascular and CNS drugs. Ineffective treatment (30.8%), adjusting dose to optimize treatment (25.1%) and adverse drug reactions (21.9%) were the most common reasons for treatment change. The sensitivity of the electronic prescribing system in identifying physician-initiated drug discontinuations and dose changes was 67.0% (95% CI 54.1, 77.7) and the specificity was 99.7% (95% CI 99.5, 99.9). The positive and negative predictive values of electronic treatment discontinuation and change orders were 97.3% (95% CI 95.6, 98.7) and 95.8% (95% CI 92.9, 97.7), respectively. Conclusion: An electronic prescribing and drug management system documents drug discontinuation and dose-change orders with high specificity and moderate sensitivity. Ineffective treatment, dose optimization and adverse drug reactions were the most common reasons for drug discontinuation or dose changes. The electronic prescribing system offers a new method for augmenting pharmacosurveillance.

Enhancing pharmacosurveillance with systematic collection of treatment indication in electronic prescribing: a validation study in Canada.

AbstractBackground: Adverse drug reaction reports used in pharmacosurveillance often lack complete information on treatment indication that is important for benefit-risk analyses and clinical and regulatory decision making. A systematic documentation of treatment indication using electronic prescribing applications provides an opportunity to develop new pharmacosurveillance tools that will allow evaluation of drugs by weighing benefits and risks for specific indications, and evaluate off-label prescribing. In addition, interfacing indications with reminders and clinical guidelines can enhance clinical decision making. We investigated the validity of treatment indications documented using an electronic prescribing system at the time of prescribing. Objectives: To determine the sensitivity and positive predictive value (PPV) of an electronic prescribing system in documenting treatment indications at the time of drug prescribing, and to investigate the use of treatment indication data to evaluate off-label prescribing in primary-care practice. Study Design and Setting: We prospectively assessed the validity of documenting treatment indication using an electronic prescribing system by comparing it with treatment indications documented by physician-facilitated medical chart review (‘gold standard’). Sensitivity and PPV were evaluated in 338 patients of 22 community-based primary-care physicians in Quebec, Canada, in 2006. Results: The sensitivity of the electronic prescribing system in documenting treatment indication was 98.5% (95% CI 96.5, 99.5) and the PPV of the system in accurately identifying the treatment indication was 97.0% (95% CI 94.2, 98.6). The treatment indication data collected using this system allowed assessment of off-label prescribing. Conclusions: The electronic prescribing system offers a valid method for documenting treatment indication at the time of prescribing. Our results provide strong evidence to support incorporating mandatory recording of treatment indication in integrated electronic prescribing systems to provide a critical piece of information for the evaluation of safety and effectiveness of drugs.