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OBJECTIVES: To evaluate the FeelBetter machine learning system's ability to accurately identify older patients with multimorbidity at Brigham and Women's Hospital at highest risk of medication-associated emergency department (ED) visits and hospitalizations, and to assess the system's ability to provide accurate medication recommendations for these patients. STUDY DESIGN: Retrospective cohort study. METHODS: The system uses medications, demographics, diagnoses, laboratory results, health care utilization patterns, and costs to stratify patients' risk of ED visits and hospitalizations. Patients were assigned 1 of 22 risk levels based on their system-generated risk percentile of either ED visits or hospitalizations. Logistic regression models were used to estimate the odds of ED visits and hospitalizations associated with each successive risk level compared with the 45th to 50th percentiles. After stratification, 100 high-risk (95th-100th percentiles) and 100 medium-risk (45th-55th percentiles) patients were randomly selected for generation of medication recommendations. Two clinical pharmacists reviewed the system-generated medication recommendations for these patients. RESULTS: Logistic regression models predicting 3-month utilization showed that compared with the 45th to 50th percentiles, patients in the top 1% risk percentile had ORs of 7.9 and 17.3 for ED visits and hospitalizations, respectively. The first 5 high-priority medications on each patient's medication list were associated with a mean (SD) of 6.65 (4.09) warnings. Of 1290 warnings reviewed, 1151 (89.2%) were assessed as correct. CONCLUSIONS: The FeelBetter system effectively stratifies older patients with multimorbidity at risk of ED use and hospitalizations. Medication recommendations provided by the system are largely accurate and can potentially be beneficial for patient care.
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Serviço Hospitalar de Emergência , Hospitalização , Aprendizado de Máquina , Multimorbidade , Humanos , Feminino , Idoso , Estudos Retrospectivos , Masculino , Hospitalização/estatística & dados numéricos , Serviço Hospitalar de Emergência/estatística & dados numéricos , Idoso de 80 Anos ou mais , Medição de Risco , Efeitos Colaterais e Reações Adversas Relacionados a Medicamentos/epidemiologia , Efeitos Colaterais e Reações Adversas Relacionados a Medicamentos/prevenção & controle , Modelos LogísticosRESUMO
BACKGROUND: Limited data exist regarding adverse drug events (ADEs) in the outpatient setting. The objective of this study was to determine the incidence, severity, and preventability of ADEs in the outpatient setting and identify potential prevention strategies. METHODS: We conducted an analysis of ADEs identified in a retrospective electronic health records review of outpatient encounters in 2018 at 13 outpatient sites in Massachusetts that included 13 416 outpatient encounters in 3323 patients. Triggers were identified in the medical record including medications, consultations, laboratory results, and others. If a trigger was detected, a further in-depth review was conducted by nurses and adjudicated by physicians to examine the relevant information in the medical record. Patients were included in the study if they were at least 18 years of age with at least one outpatient encounter with a physician, nurse practitioner or physician's assistant in that calendar year. Patients were excluded from the study if the outpatient encounter occurred in outpatient surgery, psychiatry, rehabilitation, and paediatrics. RESULTS: In all, 5% of patients experienced an ADE over the 1-year period. We identified 198 ADEs among 170 patients, who had a mean age of 60. Most patients experienced one ADE (87%), 10% experienced two ADEs and 3% experienced three or more ADEs. The most frequent drug classes resulting in ADEs were cardiovascular (25%), central nervous system (14%), and anti-infective agents (14%). Severity was ranked as significant in 85%, 14% were serious, 1% were life-threatening, and there were no fatal ADEs. Of the ADEs, 22% were classified as preventable and 78% were not preventable. We identified 246 potential prevention strategies, and 23% of ADEs had more than one prevention strategy possibility. CONCLUSIONS: Despite efforts to prioritise patient safety, medication-related harms are still frequent. These results underscore the need for further patient safety improvement in the outpatient setting.
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INTRODUCTION: A risk factor for a potentially fatal ventricular arrhythmia Torsade de Pointes is a prolongation in the heart rate-corrected QT interval (QTc) ≥ 500 milliseconds (ms) or an increase of ≥ 60 ms from a patient's baseline value, which can cause sudden cardiac death. The Tisdale risk score calculator uses clinical variables to predict which hospitalized patients are at the highest risk for QTc prolongation. OBJECTIVE: To determine the rate of overridden QTc drug-drug interaction (DDI)-related clinical decision support (CDS) alerts per patient admission and the prevalence by Tisdale risk score category of these overridden alerts. Secondary outcome was to determine the rate of drug-induced QTc prolongation (diQTP) associated with overrides. METHODS: Our organization's enterprise data warehouse was used to retrospectively access QTc DDI alerts presented for patients aged ≥ 18 years who were admitted to Brigham and Women's Hospital during 2022. The QTc DDI CDS alerts were included if shown to a physician, fellow, resident, physician assistant, or nurse practitioner when entering the order in inpatient areas for patients with a length of stay of at least 2 days. Variables collected for the Tisdale calculator included age, sex, whether patient was on a loop diuretic, potassium level, admission QTc value, admitting diagnosis of acute myocardial infarction, sepsis, or heart failure, and number of QTc-prolonging drugs given to the patient. RESULTS: A total of 2649 patients with 3033 patient admissions had 18,432 QTc DDI alerts presented that were overridden. An average of 3 unique QTc DDI alerts were presented per patient admission and the alerts were overridden an average of 6 times per patient admission. Overall, 6% of patient admissions were low risk (score ≤ 6), 64% moderate risk (score 7-10), and 30% high risk (score ≥ 11) of QTc prolongation. The most common QTc DDI alerts overridden resulting in an diQTP were quetiapine and propofol (11%) and amiodarone and haloperidol (7%). The diQTP occurred in 883 of patient admissions (29%) and was more frequent in those with higher risk score, with 46% of patient admissions with diQTP in high risk, 23% in moderate risk, and 8% in low risk. CONCLUSION: Use of the Tisdale calculator to assess patient-specific risk of QT prolongation combined with CDS may improve overall alert quality and acceptance rate, which may decrease the diQTP rate.
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Objective: To evaluate the ability of DynaMedex, an evidence-based drug and disease Point of Care Information (POCI) resource, in answering clinical queries using keyword searches. Methods: Real-world disease-related questions compiled from clinicians at an academic medical center, DynaMedex search query data, and medical board review resources were categorized into five clinical categories (complications & prognosis, diagnosis & clinical presentation, epidemiology, prevention & screening/monitoring, and treatment) and six specialties (cardiology, endocrinology, hematology-oncology, infectious disease, internal medicine, and neurology). A total of 265 disease-related questions were evaluated by pharmacist reviewers based on if an answer was found (yes, no), whether the answer was relevant (yes, no), difficulty in finding the answer (easy, not easy), cited best evidence available (yes, no), clinical practice guidelines included (yes, no), and level of detail provided (detailed, limited details). Results: An answer was found for 259/265 questions (98%). Both reviewers found an answer for 241 questions (91%), neither found the answer for 6 questions (2%), and only one reviewer found an answer for 18 questions (7%). Both reviewers found a relevant answer 97% of the time when an answer was found. Of all relevant answers found, 68% were easy to find, 97% cited best quality of evidence available, 72% included clinical guidelines, and 95% were detailed. Recommendations for areas of resource improvement were identified. Conclusions: The resource enabled reviewers to answer most questions easily with the best quality of evidence available, providing detailed answers and clinical guidelines, with a high level of replication of results across users.
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Sistemas Automatizados de Assistência Junto ao Leito , Humanos , Medicina Baseada em EvidênciasRESUMO
BACKGROUND: Despite considerable emphasis on delivering safe care, substantial patient harm occurs. Although most care occurs in the outpatient setting, knowledge of outpatient adverse events (AEs) remains limited. OBJECTIVE: To measure AEs in the outpatient setting. DESIGN: Retrospective review of the electronic health record (EHR). SETTING: 11 outpatient sites in Massachusetts in 2018. PATIENTS: 3103 patients who received outpatient care. MEASUREMENTS: Using a trigger method, nurse reviewers identified possible AEs and physicians adjudicated them, ranked severity, and assessed preventability. Generalized estimating equations were used to assess the association of having at least 1 AE with age, sex, race, and primary insurance. Variation in AE rates was analyzed across sites. RESULTS: The 3103 patients (mean age, 52 years) were more often female (59.8%), White (75.1%), English speakers (90.8%), and privately insured (70.4%) and had a mean of 4 outpatient encounters in 2018. Overall, 7.0% (95% CI, 4.6% to 9.3%) of patients had at least 1 AE (8.6 events per 100 patients annually). Adverse drug events were the most common AE (63.8%), followed by health care-associated infections (14.8%) and surgical or procedural events (14.2%). Severity was serious in 17.4% of AEs, life-threatening in 2.1%, and never fatal. Overall, 23.2% of AEs were preventable. Having at least 1 AE was less often associated with ages 18 to 44 years than with ages 65 to 84 years (standardized risk difference, -0.05 [CI, -0.09 to -0.02]) and more often associated with Black race than with Asian race (standardized risk difference, 0.09 [CI, 0.01 to 0.17]). Across study sites, 1.8% to 23.6% of patients had at least 1 AE and clinical category of AEs varied substantially. LIMITATION: Retrospective EHR review may miss AEs. CONCLUSION: Outpatient harm was relatively common and often serious. Adverse drug events were most frequent. Rates were higher among older adults. Interventions to curtail outpatient harm are urgently needed. PRIMARY FUNDING SOURCE: Controlled Risk Insurance Company and the Risk Management Foundation of the Harvard Medical Institutions.
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Assistência Ambulatorial , Registros Eletrônicos de Saúde , Segurança do Paciente , Humanos , Feminino , Pessoa de Meia-Idade , Masculino , Estudos Retrospectivos , Adulto , Idoso , Massachusetts , Adolescente , Adulto JovemRESUMO
[This corrects the article DOI: 10.2196/43960.].
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BACKGROUND: Evidence-based point-of-care information (POCI) tools can facilitate patient safety and care by helping clinicians to answer disease state and drug information questions in less time and with less effort. However, these tools may also be visually challenging to navigate or lack the comprehensiveness needed to sufficiently address a medical issue. OBJECTIVE: This study aimed to collect clinicians' feedback and directly observe their use of the combined POCI tool DynaMed and Micromedex with Watson, now known as DynaMedex. EBSCO partnered with IBM Watson Health, now known as Merative, to develop the combined tool as a resource for clinicians. We aimed to identify areas for refinement based on participant feedback and examine participant perceptions to inform further development. METHODS: Participants (N=43) within varying clinical roles and specialties were recruited from Brigham and Women's Hospital and Massachusetts General Hospital in Boston, Massachusetts, United States, between August 10, 2021, and December 16, 2021, to take part in usability sessions aimed at evaluating the efficiency and effectiveness of, as well as satisfaction with, the DynaMed and Micromedex with Watson tool. Usability testing methods, including think aloud and observations of user behavior, were used to identify challenges regarding the combined tool. Data collection included measurements of time on task; task ease; satisfaction with the answer; posttest feedback on likes, dislikes, and perceived reliability of the tool; and interest in recommending the tool to a colleague. RESULTS: On a 7-point Likert scale, pharmacists rated ease (mean 5.98, SD 1.38) and satisfaction (mean 6.31, SD 1.34) with the combined POCI tool higher than the physicians, nurse practitioner, and physician's assistants (ease: mean 5.57, SD 1.64, and satisfaction: mean 5.82, SD 1.60). Pharmacists spent longer (mean 2 minutes, 26 seconds, SD 1 minute, 41 seconds) on average finding an answer to their question than the physicians, nurse practitioner, and physician's assistants (mean 1 minute, 40 seconds, SD 1 minute, 23 seconds). CONCLUSIONS: Overall, the tool performed well, but this usability evaluation identified multiple opportunities for improvement that would help inexperienced users.
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BACKGROUND: Adverse events during hospitalization are a major cause of patient harm, as documented in the 1991 Harvard Medical Practice Study. Patient safety has changed substantially in the decades since that study was conducted, and a more current assessment of harm during hospitalization is warranted. METHODS: We conducted a retrospective cohort study to assess the frequency, preventability, and severity of patient harm in a random sample of admissions from 11 Massachusetts hospitals during the 2018 calendar year. The occurrence of adverse events was assessed with the use of a trigger method (identification of information in a medical record that was previously shown to be associated with adverse events) and from review of medical records. Trained nurses reviewed records and identified admissions with possible adverse events that were then adjudicated by physicians, who confirmed the presence and characteristics of the adverse events. RESULTS: In a random sample of 2809 admissions, we identified at least one adverse event in 23.6%. Among 978 adverse events, 222 (22.7%) were judged to be preventable and 316 (32.3%) had a severity level of serious (i.e., caused harm that resulted in substantial intervention or prolonged recovery) or higher. A preventable adverse event occurred in 191 (6.8%) of all admissions, and a preventable adverse event with a severity level of serious or higher occurred in 29 (1.0%). There were seven deaths, one of which was deemed to be preventable. Adverse drug events were the most common adverse events (accounting for 39.0% of all events), followed by surgical or other procedural events (30.4%), patient-care events (which were defined as events associated with nursing care, including falls and pressure ulcers) (15.0%), and health care-associated infections (11.9%). CONCLUSIONS: Adverse events were identified in nearly one in four admissions, and approximately one fourth of the events were preventable. These findings underscore the importance of patient safety and the need for continuing improvement. (Funded by the Controlled Risk Insurance Company and the Risk Management Foundation of the Harvard Medical Institutions.).
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Atenção à Saúde , Hospitalização , Erros Médicos , Dano ao Paciente , Segurança do Paciente , Humanos , Atenção à Saúde/normas , Atenção à Saúde/estatística & dados numéricos , Efeitos Colaterais e Reações Adversas Relacionados a Medicamentos/epidemiologia , Efeitos Colaterais e Reações Adversas Relacionados a Medicamentos/prevenção & controle , Hospitalização/estatística & dados numéricos , Pacientes Internados , Erros Médicos/prevenção & controle , Erros Médicos/estatística & dados numéricos , Segurança do Paciente/normas , Estudos Retrospectivos , Dano ao Paciente/prevenção & controle , Dano ao Paciente/estatística & dados numéricosRESUMO
PURPOSE: To identify current challenges in detection of medication-related symptoms, and review technology-based opportunities to increase the patient-centeredness of postmarketing pharmacosurveillance to promote more accountable, safer, patient-friendly, and equitable medication prescribing. SUMMARY: Pharmacists have an important role to play in detection and evaluation of adverse drug reactions (ADRs). The pharmacist's role in medication management should extend beyond simply dispensing drugs, and this article delineates the rationale and proactive approaches for pharmacist detection and assessment of ADRs. We describe a stepwise approach for assessment, best practices, and lessons learned from a pharmacist-led randomized trial, the CEDAR (Calling for Detection of Adverse Drug Reactions) project. CONCLUSION: Health systems need to be redesigned to more fully utilize health information technologies and pharmacists in detecting and responding to ADRs.
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Efeitos Colaterais e Reações Adversas Relacionados a Medicamentos , Informática Médica , Humanos , Farmacêuticos , Efeitos Colaterais e Reações Adversas Relacionados a Medicamentos/diagnóstico , Efeitos Colaterais e Reações Adversas Relacionados a Medicamentos/epidemiologia , Efeitos Colaterais e Reações Adversas Relacionados a Medicamentos/prevenção & controle , Prescrições de Medicamentos , Papel ProfissionalRESUMO
Pharmacovigilance improves patient safety by detecting and preventing adverse drug events. However, challenges exist that limit adverse drug event detection, resulting in many adverse drug events being underreported or inaccurately reported. One challenge includes having access to large data sets from various sources including electronic health records and wearable medical devices. Artificial intelligence, including machine learning methods, such as natural language processing and deep learning, can detect and extract information about adverse drug events, thus automating the pharmacovigilance process and improving the surveillance of known and documented adverse drug events. In addition, with the increased demand for telehealth services, for managing both acute and chronic diseases, artificial intelligence methods can play a role in detecting and preventing adverse drug events. In this review, we discuss two use cases of how artificial intelligence methods may be useful to improve the quality of pharmacovigilance and the role of artificial intelligence in telehealth practices.
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Efeitos Colaterais e Reações Adversas Relacionados a Medicamentos , Telemedicina , Sistemas de Notificação de Reações Adversas a Medicamentos , Inteligência Artificial , Efeitos Colaterais e Reações Adversas Relacionados a Medicamentos/epidemiologia , Efeitos Colaterais e Reações Adversas Relacionados a Medicamentos/prevenção & controle , Humanos , Processamento de Linguagem Natural , FarmacovigilânciaRESUMO
Adverse drug events (ADEs) represent one of the most prevalent types of health-care-related harm, and there is substantial room for improvement in the way that they are currently predicted and detected. We conducted a scoping review to identify key use cases in which artificial intelligence (AI) could be leveraged to reduce the frequency of ADEs. We focused on modern machine learning techniques and natural language processing. 78 articles were included in the scoping review. Studies were heterogeneous and applied various AI techniques covering a wide range of medications and ADEs. We identified several key use cases in which AI could contribute to reducing the frequency and consequences of ADEs, through prediction to prevent ADEs and early detection to mitigate the effects. Most studies (73 [94%] of 78) assessed technical algorithm performance, and few studies evaluated the use of AI in clinical settings. Most articles (58 [74%] of 78) were published within the past 5 years, highlighting an emerging area of study. Availability of new types of data, such as genetic information, and access to unstructured clinical notes might further advance the field.
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Inteligência Artificial , Efeitos Colaterais e Reações Adversas Relacionados a Medicamentos/prevenção & controle , Aprendizado de Máquina , HumanosRESUMO
AIMS: Implementation of guideline-directed medical therapy (GDMT) for heart failure with reduced ejection fraction (HFrEF) remains incomplete. Non-cardiovascular hospitalization may present opportunities for GDMT optimization. We assessed the efficacy and durability of a virtual, multidisciplinary 'GDMT Team' on medical therapy prescription for HFrEF. METHODS AND RESULTS: Consecutive hospitalizations in patients with HFrEF (ejection fraction ≤40%) were prospectively identified from 3 February to 1 March 2020 (usual care group) and 2 March to 28 August 2020 (intervention group). Patients with critical illness, de novo heart failure, and systolic blood pressure <90 mmHg in the preceeding 24 hs prior to enrollment were excluded. In the intervention group, a pharmacist-physician GDMT Team provided optimization suggestions to treating teams based on an evidence-based algorithm. The primary outcome was a GDMT optimization score, the sum of positive (+1 for new initiations or up-titrations) and negative therapeutic changes (-1 for discontinuations or down-titrations) at hospital discharge. Serious in-hospital safety events were assessed. Among 278 consecutive encounters with HFrEF, 118 met eligibility criteria; 29 (25%) received usual care and 89 (75%) received the GDMT Team intervention. Among usual care encounters, there were no changes in GDMT prescription during hospitalization. In the intervention group, ß-blocker (72% to 88%; P = 0.01), angiotensin receptor-neprilysin inhibitor (6% to 17%; P = 0.03), mineralocorticoid receptor antagonist (16% to 29%; P = 0.05), and triple therapy (9% to 26%; P < 0.01) prescriptions increased during hospitalization. After adjustment for clinically relevant covariates, the GDMT Team was associated with an increase in GDMT optimization score (+0.58; 95% confidence interval +0.09 to +1.07; P = 0.02). There were no serious in-hospital adverse events. CONCLUSIONS: Non-cardiovascular hospitalizations are a potentially safe and effective setting for GDMT optimization. A virtual GDMT Team was associated with improved heart failure therapeutic optimization. This implementation strategy warrants testing in a prospective randomized controlled trial.
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Insuficiência Cardíaca , Insuficiência Cardíaca/tratamento farmacológico , Humanos , Antagonistas de Receptores de Mineralocorticoides , Projetos Piloto , Estudos Prospectivos , Volume SistólicoRESUMO
INTRODUCTION: Medication-related harm represents a significant issue for patient safety and quality of care. One strategy to avoid preventable adverse drug events is to utilize patient-specific factors such as pharmacogenomics (PGx) to individualize therapy. OBJECTIVE: We measured the number of patients enrolled in a health-system biobank with actionable PGx results who received relevant medications and assessed the incidence of adverse drug events (ADEs) that might have been prevented had the PGx results been used to inform prescribing. METHODS: Patients with actionable PGx results in the following four genes with Clinical Pharmacogenetics Implementation Consortium (CPIC) guidelines were identified: HLA-A*31:01, HLA-B*15:02, TPMT, and VKORC1. The patients who received interacting medications (carbamazepine, oxcarbazepine, thiopurines, or warfarin) were identified, and electronic health records were reviewed to determine the incidence of potentially preventable ADEs. RESULTS: Of 36,424 patients with PGx results, 2327 (6.4%) were HLA-A*31:01 positive; 3543 (9.7%) were HLA-B*15:02 positive; 2893 (7.9%) were TPMT intermediate metabolizers; and 4249 (11.7%) were homozygous for the VKORC1 c.1639 G>A variant. Among patients positive for one of the HLA variants who received carbamazepine or oxcarbazepine (n = 92), four (4.3%) experienced a rash that warranted drug discontinuation. Among the TPMT intermediate metabolizers who received a thiopurine (n = 56), 11 (19.6%) experienced severe myelosuppression that warranted drug discontinuation. Among patients homozygous for the VKORC1 c.1639 G>A variant who received warfarin (n = 379), 85 (22.4%) experienced active bleeding and/or international normalized ratio (INR) > 5 that warranted drug discontinuation or dose reduction. CONCLUSION: Patients with actionable PGx results from a health-system biobank who received relevant medications experienced predictable ADEs. These ADEs may have been prevented if the patients' PGx results were available in the electronic health record with clinical decision support prior to prescribing.
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Efeitos Colaterais e Reações Adversas Relacionados a Medicamentos , Farmacogenética , Bancos de Espécimes Biológicos , Efeitos Colaterais e Reações Adversas Relacionados a Medicamentos/epidemiologia , Efeitos Colaterais e Reações Adversas Relacionados a Medicamentos/genética , Efeitos Colaterais e Reações Adversas Relacionados a Medicamentos/prevenção & controle , Antígenos HLA-A , Antígenos HLA-B/genética , Humanos , Oxcarbazepina , Farmacogenética/métodos , Vitamina K Epóxido Redutases , Varfarina/efeitos adversosRESUMO
OBJECTIVE: To assess the appropriateness of medication-related clinical decision support (CDS) alerts associated with renal insufficiency and the potential/actual harm from overriding the alerts. MATERIALS AND METHODS: Override rate frequency was recorded for all inpatients who had a renal CDS alert trigger between 05/2017 and 04/2018. Two random samples of 300 for each of 2 types of medication-related CDS alerts associated with renal insufficiency-"dose change" and "avoid medication"-were evaluated by 2 independent reviewers using predetermined criteria for appropriateness of alert trigger, appropriateness of override, and patient harm. RESULTS: We identified 37 100 "dose change" and 5095 "avoid medication" alerts in the population evaluated, and 100% of each were overridden. Dose change triggers were classified as 12.5% appropriate and overrides of these alerts classified as 90.5% appropriate. Avoid medication triggers were classified as 29.6% appropriate and overrides 76.5% appropriate. We identified 5 adverse drug events, and, of these, 4 of the 5 were due to inappropriately overridden alerts. CONCLUSION: Alerts were nearly always presented inappropriately and were all overridden during the 1-year period studied. Alert fatigue resulting from receiving too many poor-quality alerts may result in failure to recognize errors that could lead to patient harm. Although medication-related CDS alerts associated with renal insufficiency had previously been found to be the most clinically beneficial alerts in a legacy system, in this system they were ineffective. These findings underscore the need for improvements in alert design, implementation, and monitoring of alert performance to make alerts more patient-specific and clinically appropriate.
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Fadiga de Alarmes do Pessoal de Saúde , Sistemas de Apoio a Decisões Clínicas , Registros Eletrônicos de Saúde , Sistemas de Registro de Ordens Médicas , Insuficiência Renal/tratamento farmacológico , Centros Médicos Acadêmicos , Boston , Efeitos Colaterais e Reações Adversas Relacionados a Medicamentos/epidemiologia , Humanos , Pacientes Internados , Erros de Medicação/estatística & dados numéricos , Qualidade da Assistência à SaúdeRESUMO
OBJECTIVE: The study sought to determine frequency and appropriateness of overrides of high-priority drug-drug interaction (DDI) alerts and whether adverse drug events (ADEs) were associated with overrides in a newly implemented electronic health record. MATERIALS AND METHODS: We conducted a retrospective study of overridden high-priority DDI alerts occurring from April 1, 2016, to March 31, 2017, from inpatient and outpatient settings at an academic health center. We studied highest-severity DDIs that were previously designated as "hard stops" and additional high-priority DDIs identified from clinical experience and literature review. All highest-severity alert overrides (n = 193) plus a stratified random sample of additional overrides (n = 371) were evaluated for override appropriateness, using predetermined criteria. Charts were reviewed to identify ADEs for overrides that resulted in medication administration. A chi-square test was used to compare ADE rate by override appropriateness. RESULTS: Of 16 011 alerts presented to providers, 15 318 (95.7%) were overridden, including 193 (87.3%) of the highest-severity DDIs and 15 125 (95.8%) of additional DDIs. Override appropriateness was 45.4% overall, 0.5% for highest-severity DDIs and 68.7% for additional DDIs. For alerts that resulted in medication administration (n = 423, 75.0%), 29 ADEs were identified (6.9%, 5.1 per 100 overrides). The rate of ADEs was higher with inappropriate vs appropriate overrides (9.4% vs 4.3%; P = .038). CONCLUSIONS: The override rate was nearly 90% for even the highest-severity DDI alerts, indicating that stronger suggestions should be made for these alerts, while other alerts should be evaluated for potential suppression.
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Sistemas de Apoio a Decisões Clínicas , Interações Medicamentosas , Efeitos Colaterais e Reações Adversas Relacionados a Medicamentos , Registros Eletrônicos de Saúde , Sistemas de Registro de Ordens Médicas , Centros Médicos Acadêmicos , Distribuição de Qui-Quadrado , Quimioterapia Assistida por Computador , Efeitos Colaterais e Reações Adversas Relacionados a Medicamentos/epidemiologia , Efeitos Colaterais e Reações Adversas Relacionados a Medicamentos/prevenção & controle , Feminino , Humanos , Masculino , Erros de Medicação/prevenção & controle , Estudos RetrospectivosRESUMO
PURPOSE: To examine the extent to which outpatient clinicians currently document drug indications in prescription instructions. METHODS: Free-text sigs were extracted from all outpatient prescriptions generated by the computerized prescriber order entry system of a major academic institution during a 5-year period. Natural language processing was used to identify drug indications. The data set was analyzed to determine the rates at which prescribers included indications. It was stratified by provider specialty, drug class, and specific medications, to determine how often these indications were in prescriptions for as-needed (PRN) versus non-PRN medications. RESULTS: During the study period, 4,356,086 prescriptions were ordered. Indications were included in 322,961 orders (7.41%). From these orders, 249,262 indications (77.18%) were written for PRN orders. Although internal medicine prescribers generated the highest number of medication orders, they included indications in only 6.26% of their prescriptions, whereas orthopedic surgery providers had the highest rate of documenting indications (33.41%). Pain was the most common indication, accounting for 30.35% of all documented indications. The drug class with the highest number of sigs-containing indications was narcotic analgesics. Non-PRN chronic medication prescriptions rarely included the indication. CONCLUSION: Prescribers rarely included drug indications in electronic free-text prescription instructions, and, when they did, it was mostly for PRN uses such as pain.
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Assistência Ambulatorial/estatística & dados numéricos , Prescrições de Medicamentos/estatística & dados numéricos , Sistemas de Registro de Ordens Médicas/estatística & dados numéricos , Assistência Ambulatorial/normas , Conjuntos de Dados como Assunto , Prescrições de Medicamentos/normas , Humanos , Sistemas de Registro de Ordens Médicas/normas , Erros de Medicação/prevenção & controle , Processamento de Linguagem NaturalRESUMO
OBJECTIVE: The study sought to determine availability and use of structured override reasons for drug-drug interaction (DDI) alerts in electronic health records. MATERIALS AND METHODS: We collected data on DDI alerts and override reasons from 10 clinical sites across the United States using a variety of electronic health records. We used a multistage iterative card sort method to categorize the override reasons from all sites and identified best practices. RESULTS: Our methodology established 177 unique override reasons across the 10 sites. The number of coded override reasons at each site ranged from 3 to 100. Many sites offered override reasons not relevant to DDIs. Twelve categories of override reasons were identified. Three categories accounted for 78% of all overrides: "will monitor or take precautions," "not clinically significant," and "benefit outweighs risk." DISCUSSION: We found wide variability in override reasons between sites and many opportunities to improve alerts. Some override reasons were irrelevant to DDIs. Many override reasons attested to a future action (eg, decreasing a dose or ordering monitoring tests), which requires an additional step after the alert is overridden, unless the alert is made actionable. Some override reasons deferred to another party, although override reasons often are not visible to other users. Many override reasons stated that the alert was inaccurate, suggesting that specificity of alerts could be improved. CONCLUSIONS: Organizations should improve the options available to providers who choose to override DDI alerts. DDI alerting systems should be actionable and alerts should be tailored to the patient and drug pairs.
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Registros Eletrônicos de Saúde , Sistemas de Registro de Ordens Médicas , Erros de Medicação/prevenção & controle , Idoso , Interações Medicamentosas , Prescrição Eletrônica , Feminino , Humanos , Masculino , Pessoa de Meia-IdadeRESUMO
Importance: The indication (reason for use) for a medication is rarely included on prescriptions despite repeated recommendations to do so. One barrier has been the way existing electronic prescribing systems have been designed. Objective: To evaluate, in comparison with the prescribing modules of 2 leading electronic health record prescribing systems, the efficiency, error rate, and satisfaction with a new computerized provider order entry prototype for the outpatient setting that allows clinicians to initiate prescribing using the indication. Design, Setting, and Participants: This quality improvement study used usability tests requiring internal medicine physicians, residents, and physician assistants to enter prescriptions electronically, including indication, for 8 clinical scenarios. The tool order assignments were randomized and prescribers were asked to use the prototype for 4 of the scenarios and their usual system for the other 4. Time on task, number of clicks, and order details were captured. User satisfaction was measured using posttask ratings and a validated system usability scale. The study participants practiced in 2 health systems' outpatient practices. Usability tests were conducted between April and October of 2017. Main Outcomes and Measures: Usability (efficiency, error rate, and satisfaction) of indications-based computerized provider order entry prototype vs the electronic prescribing interface of 2 electronic health record vendors. Results: Thirty-two participants (17 attending physicians, 13 residents, and 2 physician assistants) used the prototype to complete 256 usability test scenarios. The mean (SD) time on task was 1.78 (1.17) minutes. For the 20 participants who used vendor 1's system, it took a mean (SD) of 3.37 (1.90) minutes to complete a prescription, and for the 12 participants using vendor 2's system, it took a mean (SD) of 2.93 (1.52) minutes. Across all scenarios, when comparing number of clicks, for those participants using the prototype and vendor 1, there was a statistically significant difference from the mean (SD) number of clicks needed (18.39 [12.62] vs 46.50 [27.29]; difference, 28.11; 95% CI, 21.47-34.75; P < .001). For those using the prototype and vendor 2, there was also a statistically significant difference in number of clicks (20.10 [11.52] vs 38.25 [19.77]; difference, 18.14; 95% CI, 11.59-24.70; P < .001). A blinded review of the order details revealed medication errors (eg, drug-allergy interactions) in 38 of 128 prescribing sessions using a vendor system vs 7 of 128 with the prototype. Conclusions and Relevance: Reengineering prescribing to start with the drug indication allowed indications to be captured in an easy and useful way, which may be associated with saved time and effort, reduced medication errors, and increased clinician satisfaction.
Assuntos
Prescrição Eletrônica , Modelos Teóricos , Melhoria de Qualidade , Assistência Ambulatorial , Pessoal de Saúde , Humanos , Sistemas de Registro de Ordens Médicas , Erros de Medicação/estatística & dados numéricos , Inovação OrganizacionalRESUMO
BACKGROUND: Medication adverse events are important and common yet are often not identified by clinicians. We evaluated an automated telephone surveillance system coupled with transfer to a live pharmacist to screen potentially drug-related symptoms after newly starting medications for four common primary care conditions: hypertension, diabetes, depression, and insomnia. METHODS: Cluster randomized trial with automated calls to eligible patients at 1 and 4 months after starting target drugs from intervention primary care clinics compared to propensity-matched patients from control clinics. Primary and secondary outcomes were physician documentation of any adverse effects associated with newly prescribed target medication, and whether the medication was discontinued and, if yes, whether the reason for stopping was an adverse effect. RESULTS: Of 4876 eligible intervention clinic patients who were contacted using automated calls, 776 (15.1%) responded and participated in the automated call. Based on positive symptom responses or request to speak to a pharmacist, 320 patients were transferred to the pharmacist and discussed 1021 potentially drug-related symptoms. Of these, 188 (18.5%) were assessed as probably and 479 (47.1%) as possibly related to the medication. Compared to a propensity-matched cohort of control clinic patients, intervention patients were significantly more likely to have adverse effects documented in the medical record by a physician (277 vs. 164 adverse effects, p < 0.0001, and 177 vs. 122 patients discontinued with documented adverse effects, p < 0.0001). DISCUSSION: Systematic automated telephone outreach monitoring coupled with real-time phone referral to a pharmacist identified a substantial number of previously unidentified potentially drug-related symptoms, many of which were validated as probably or possibly related to the drug by the pharmacist or their physicians. Multiple challenges were encountered using the interactive voice response (IVR) automated calling system, suggesting that other approaches may need to be considered and evaluated. TRIAL REGISTRATION: ClinicalTrials.gov : NCT02087293.
Assuntos
Telefone Celular , Aconselhamento/métodos , Efeitos Colaterais e Reações Adversas Relacionados a Medicamentos/terapia , Programas de Rastreamento/métodos , Farmacêuticos , Papel Profissional , Adolescente , Adulto , Idoso , Idoso de 80 Anos ou mais , Estudos de Coortes , Efeitos Colaterais e Reações Adversas Relacionados a Medicamentos/diagnóstico , Efeitos Colaterais e Reações Adversas Relacionados a Medicamentos/psicologia , Registros Eletrônicos de Saúde , Feminino , Humanos , Masculino , Programas de Rastreamento/psicologia , Pessoa de Meia-Idade , Farmacêuticos/psicologia , Papel Profissional/psicologia , Adulto JovemRESUMO
INTRODUCTION: Medication-related clinical decision support (CDS) alerts have been shown to be effective at reducing adverse drug events (ADEs). However, these alerts are frequently overridden, with limited data linking these overrides to harm. Dose-range checking alerts are a type of CDS alert that could have a significant impact on morbidity and mortality, especially in the intensive care unit (ICU) setting. METHODS: We performed a single-center, prospective, observational study of adult ICUs from September 2016 to April 2017. Targeted overridden alerts were triggered when doses greater than or equal to 5% over the maximum dose were prescribed. The primary outcome was the appropriateness of the override, determined by two independent reviewers, using pre-specified criteria formulated by a multidisciplinary group. Overrides which resulted in medication administration were then evaluated for ADEs by chart review. RESULTS: The override rate of high dose-range alerts in the ICU was 93.0% (total n = 1525) during the study period. A total of 1418 overridden alerts from 755 unique patients were evaluated for appropriateness (appropriateness rate 88.8%). The most common medication associated with high dose-range alerts was insulin regular infusion (n = 262, 18.5%). The rates of ADEs for the appropriately and inappropriately overridden alerts per 100 overridden alerts were 1.3 and 5.0, respectively (p < 0.001). CONCLUSIONS: Overriding high dose-range CDS alerts was found to be common and often appropriate, suggesting that more intelligent dose checking is needed. Some alerts were clearly inappropriately presented to the provider. Inappropriate overrides were associated with an increased risk of ADEs, compared to appropriately overridden alerts.