Adverse drug reactions in hospital and ambulatory care settings identified using a large administrative database

Exploring the prevalence and characteristics of adverse drug events among older adults in South Korea using a national health insurance database

Background: Adverse drug events (ADEs) in the elderly frequently occur because of their multiple chronic diseases and complexity of drug therapy. To better understand adverse drug events, the prevalence and characteristics of adverse drug events in elderly South Korean patients were assessed.

Methods: The National Health Insurance databases for 2015 and 2016 were used for the analysis. We included patients aged ≥65 years that had at least one claim with the diagnosis codes ‘drug-induced,’ ‘poisoning by drug,’ and ‘vaccine-associated’ each year for the base-case analysis. To minimize the underestimation of adverse drug event prevalence, we also used an extended definition analysis by adding the ‘adverse drug event very likely’ codes. We estimated the prevalence of adverse drug events by sex, age group, and type of insurance and examined the frequent types of adverse drug events in 2015 and 2016.

Results: In the base-case analysis, adverse drug event prevalence in individuals aged 65 years and older was 2.75% in 2015 and 2.77% in 2016. With advanced age, the prevalence of adverse drug event tended to increase, peaking in the age group of 75–79 years. In addition, the adverse drug event prevalence was higher in females and Medical Aid enrollees. The most frequently occurring adverse drug event was ‘allergy, unspecified,’ followed by ‘other drug-induced secondary parkinsonism,’ and ‘generalized skin eruption due to drugs and medicaments.’ When we examined the extended definition analysis, the prevalence of adverse drug events was 4.47% in 2015 and 4.52% in 2016, which significantly increased from those estimated in the base-case analysis.

Conclusion: Among the older adults, the prevalence of adverse drug event was higher in advanced age, females, and Medical Aid enrollees. In particular, allergy and drug-induced secondary parkinsonism frequently occurred. This study provides evidence that health policies addressing the prevention and management of adverse drug events should be a priority for the most vulnerable elderly patients.

[Deaths from adverse drug events in Brazil: Mortality Information System as a source of information]

Adverse drug events (ADEs) are harmful events caused by medication, and some of which can lead to death. Death records are an important source of information when using codes from the 10th revision of the International Classification of Diseases (ICD-10) suggestive of ADE. This study aimed to identify the ADEs registered in Brazililian Mortality Information System (SIM), analyzing data distribution by year, age group, and type of event. This is an ecological study with retrospective data collection, identifying ADEs in the SIM, using the ICD-10 codes. The study included deaths that occurred in Brazil from 2008 to 2016. An increase in the number of deaths associated with ADE was observed from 2008 to 2016, with a mortality rate per 1 million inhabitants ranging from 8.70 to 14.40 in the period. Most events corresponded to mental and behavioral disorders due to the use of psychotropic drugs. Most deaths (12,311) related to ADE codes were identified in several chapters of the ICD-10. Chapter XX, about adverse events, allowed the identification of a smaller number of deaths (4,893). Higher event rates were observed among individuals aged 60 years and over (39.8/1 million) and children younger than one year (22.0/1 million). The identification of ADE-related deaths on the SIM is an important strategy for addressing undesirable drug-related events. Deaths related to the use of psychotropic drugs were the most frequent ADE-related deaths and the elderly were the age group most affected by ADEs.

Hospitalizations and adverse drug events in the Brazilian unified health system: a ten-year retrospective analysis of routine data

OBJECTIVE

To describe the frequency and characteristics of hospitalizations for/with adverse drug events in the Brazilian unified health system routine data.

METHODS

Nationwide retrospective study using data obtained from a period of ten years from the Brazil Hospital Information System (SIH-SUS), an administrative database that registers hospitalizations in the unified health system. We selected hospitalizations with primary and/or secondary diagnosis related to adverse drug events according to a list of validated International Classification Disease 10th edition (ICD-10) codes. These events were described according to year, age group, sex, length of hospital stay, mortality, hospital costs, Brazilian geographical region, and category of ICD-10 codes. Crude hospitalization rates of adverse drug events per 100,000 inhabitants were obtained and Joinpoint Regression was used to analyze temporal changes in these rates along the years. The most frequent ICD-10 codes were also identified.

RESULTS

Over ten years, 603,663 hospitalizations in Brazil were found in the database, out of which 2.5% of the patients died. Though 2009 had the highest prevalence of hospitalization per 100,000 inhabitants (32.57), no significant annual change in rates was found for the entire period. All age groups and sexes presented a jointpoint in temporal series; however, only women had a significative increase trend. The most frequent codes were from the chapter of mental and behavioral disorders (F19.2, F19.0, and F19.5 codes).

CONCLUSIONS

The database methodology can be useful to estimate frequencies of adverse drug events and perform characterization nationwide and to help monitor morbidity along the years.

Allergic Reactions Captured by Voluntary Reporting

BACKGROUND

The epidemiology of hospital adverse reactions (ARs), particularly allergic reactions, or hypersensitivity reactions (HSRs), is poorly defined. To determine priorities for allergy safety in healthcare, we identified and described safety reports of allergic reactions.

METHODS

We searched the safety report database of a large academic medical center from April 2006 to March 2016 using 101 complete, truncated, and/or misspelled key words related to allergic symptoms, treatments, and culprits (e.g., medications, foods). Patient and event data were summarized for ARs and two types of ARs, HSRs and side effects/toxicities.

RESULTS

Among 9111 key word search-identified events, 876 (10%) were ARs, of which 436 (5%) were HSRs and the remaining 440 (5%) were side effect reactions or toxicities. Whereas the most common HSRs were simple cutaneous reactions (83%), the following severe immediate HSRs were also identified: shortness of breath (16%), anaphylaxis (14%), and angioedema (12%). Most HSRs were caused by drugs (81%), with antibiotics (26%), particularly β-lactams (11%), and vancomycin (8%), commonly implicated. Other causes of drug HSRs included contrast agents (24%), chemotherapeutics (7%), and opioids (6%). Nondrug HSRs were from blood products (8%), latex (3%), and devices (3%). Food reactions were rarely identified (1%).

CONCLUSIONS

We identified ARs, HSRs, and side effects/toxicities, contained in a decade of safety reports at an academic medical center. Allergy safety in the healthcare setting should target approaches to common and severe reactions, with a focus on the safe administration of β-lactams, vancomycin, contrast agents, chemotherapeutics, and opioids. Priority nondrug HSR culprits include blood products, latex, and devices.

Hospitalizations and deaths related to adverse drug events worldwide: Systematic review of studies with national coverage

PURPOSE

Adverse drug events are related to negative outcomes in healthcare, including hospitalization, increased duration of hospital stay and death. The aim of this study was to conduct a systematic review to evaluate hospitalizations and deaths related to adverse drug events worldwide, reported in studies with national coverage.

METHODS

The protocol was registered in PROSPERO (CRD42020157008). We performed a systematic search on Medline, Embase, CINAHL, LILACS, and the Cochrane Library (until March 2020) using pre-specified terms. We included published studies that reported data on hospitalizations and/or deaths related to adverse drug events from a national perspective and the use of secondary data as a source of information. Two reviewers independently extracted and synthesized data. The quality of the studies was assessed using an adapted version of the Joanna Briggs Institute critical appraisal checklist for prevalence studies. Narrative summaries of findings were undertaken.

RESULTS

Among 59,336 citations, 62 studies were included for data extraction and synthesis. Among these studies, 41 studies included the outcome of hospitalization, 16 included the death outcome, and five included both outcomes. Administrative databases regarding discharges and registries of vital statistics were the most common sources of information. The relative frequency of hospitalizations ranged from 0.03% to 7.3%, and from 9.7 to 383.0/100,000 population, whereas mortality rate ranged from 0.1 to 7.88/100,000 population.

CONCLUSION

Our study highlights information about adverse drug events using large administrative databases in a national scenario and provides an overview of databases and methods implemented to detect adverse drug events.

Development and Validation of a Deep Learning Model for Detection of Allergic Reactions Using Safety Event Reports Across Hospitals

IMPORTANCE

Although critical to patient safety, health care-related allergic reactions are challenging to identify and monitor.

OBJECTIVE

To develop a deep learning model to identify allergic reactions in the free-text narrative of hospital safety reports and evaluate its generalizability, efficiency, productivity, and interpretability.

DESIGN, SETTING, AND PARTICIPANTS

This cross-sectional study analyzed hospital safety reports filed between May 2004 and January 2019 at Brigham and Women's Hospital and between April 2006 and June 2018 at Massachusetts General Hospital in Boston. Training and validating a deep learning model involved extracting safety reports using 101 expert-curated keywords from Massachusetts General Hospital (data set I). The model was then evaluated on 3 data sets: reports without keywords (data set II), reports from a different time frame (data set III), and reports from a different hospital (Brigham and Women's Hospital; data set IV). Statistical analyses were performed between March 1, 2019, and July 18, 2020.

MAIN OUTCOMES AND MEASURES

The area under the receiver operating characteristic curve and area under the precision-recall curve were used on data set I. The precision at top-k was used on data sets II to IV.

RESULTS

A total of 299 028 safety reports with 172 854 patients were included. Of these patients, 86 544 were women (50.1%) and the median (interquartile range [IQR]) age was 59.7 (43.8-71.6) years. The deep learning model achieved an area under the receiver operating characteristic curve of 0.979 (95% CI, 0.973-0.985) and an area under the precision-recall curve of 0.809 (95% CI, 0.773-0.845). The model achieved precisions at the top 100 model-identified cases of 0.930 in data set II, 0.960 in data set III, and 0.990 in data set IV. Compared with the keyword-search approach, the deep learning model reduced the number of cases for manual review by 63.8% and identified 24.2% more cases of confirmed allergic reactions. The model highlighted important words (eg, rash, hives, and Benadryl) in prediction and extended the list of expert-curated keywords through an attention layer.

CONCLUSIONS AND RELEVANCE

This study showed that a deep learning model can accurately and efficiently identify allergic reactions using free-text narratives written by a variety of health care professionals. This model could be used to improve allergy care, potentially enabling real-time event surveillance and guidance for medical errors and system improvement.

Anticoagulants' Safety and Effectiveness in General Practice: A Nationwide Prospective Cohort Study

PURPOSE

Most real-world studies on anticoagulants have been based on health insurance databases or performed in secondary care. The aim of this study was to compare safety and effectiveness between patients treated with vitamin K antagonists (VKAs) and patients treated with direct oral anticoagulants (DOACs) in a general practice setting.

METHODS

The CACAO study (Comparison of Accidents and their Circumstances with Oral Anticoagulants) is a multicenter prospective cohort study conducted among ambulatory patients taking an oral anticoagulant. Participants were patients from the study's cross-sectional phase receiving oral anticoagulants because of nonvalvular atrial fibrillation, for secondary prevention of venous thromboembolism, or both. They were followed as usual for 1 year by their general practitioners, who collected data on changes in therapy, thromboembolic events, bleeding, and deaths. All events were adjudicated by an independent committee. We used a propensity score and a Cox regression model to derive hazard ratios.

RESULTS

Between April and December 2014, a total of 3,082 patients were included. At 1 year, 42 patients (1.7%) had experienced an arterial or venous event; 151 (6.1%) had experienced bleeding, including 47 (1.9%) who experienced major bleeding; and 105 (4.1%) had died. There was no significant difference between the VKA and DOAC groups regarding arterial or venous events, or major bleeding. The VKA group had a lower risk of overall bleeding (hazard ratio = 0.65; 95% CI, 0.43-0.98) but twice the risk of death (hazard ratio = 1.98; 95% CI, 1.15-3.42).

CONCLUSIONS

VKAs and DOACs had fairly similar safety and effectiveness in general practice. The substantially higher incidence of deaths with VKAs is consistent with known data from health insurance databases and calls for further research to understand its cause.

Areas of improvement in anticoagulant safety. Data from the CACAO study, a cohort in general practice

Background

Real-world studies on anticoagulants are mostly performed on health insurance databases, limited to reported events, and sometimes far from every-day issues in family practice. We assess the presence of data for safe monitoring of oral anticoagulants in general practice, and compare patients’ knowledge of taking an anticoagulant between vitamin K antagonists (VKA) and direct anticoagulants (DOAC), and the general practitioner’s perception of their adherence to anticoagulation.

Methods

The CACAO study is a national cohort study, conducted by general practitioners on ambulatory patients under oral anticoagulant. In the first phase, investigators provided safety data available from medical records at inclusion. They also evaluated patients’ knowledge about anticoagulation and graded their perception of patients’ adherence.

Results

Between April and December 2014, 463 general practitioners included 7154 patients. Renal and hepatic function tests were respectively unavailable in 109 (7.5%) and 359 (24.7%) DOAC patients. Among patients with atrial fibrillation, 345 patients (6.9%) had a questionable indication of anticoagulant (CHA2DS2-Vasc<2). One hundred and thirty-three VKA patients (2.3%) and 70 DOAC patients (4.9%) answered they took no anticoagulant (p<0.0001). According to general practitioners’ perception, 430 patients (6.1%) were classified as “not very” or “not adherent”, with no difference between groups.

Conclusions

Our results highlight the efforts needed to improve anticoagulant safety in daily practice: decreasing the rate of unknown biological data in patients with DOACs or the rate of patients with VKA with no strong indication of anticoagulation, and improving patient knowledge with regard to their anticoagulant. Patients’ adherence seems highly over-estimated by the general practitioners.

Clinical trial registration

ClinicalTrials.gov NCT02376777

How safe is primary care? A systematic review

IMPORTANCE

Improving patient safety is at the forefront of policy and practice. While considerable progress has been made in understanding the frequency, causes and consequences of error in hospitals, less is known about the safety of primary care.

OBJECTIVE

We investigated how often patient safety incidents occur in primary care and how often these were associated with patient harm.

EVIDENCE REVIEW

We searched 18 databases and contacted international experts to identify published and unpublished studies available between 1 January 1980 and 31 July 2014. Patient safety incidents of any type were eligible. Eligible studies were critically appraised using validated instruments and data were descriptively and narratively synthesised.

FINDINGS

Nine systematic reviews and 100 primary studies were included. Studies reported between <1 and 24 patient safety incidents per 100 consultations. The median from population-based record review studies was 2-3 incidents for every 100 consultations/records reviewed. It was estimated that around 4% of these incidents may be associated with severe harm, defined as significantly impacting on a patient's well-being, including long-term physical or psychological issues or death (range <1% to 44% of incidents). Incidents relating to diagnosis and prescribing were most likely to result in severe harm.

CONCLUSIONS AND RELEVANCE

Millions of people throughout the world use primary care services on any given day. This review suggests that safety incidents are relatively common, but most do not result in serious harm that reaches the patient. Diagnostic and prescribing incidents are the most likely to result in avoidable harm.

SYSTEMATIC REVIEW REGISTRATION

This systematic review is registered with the International Prospective Register of Systematic Reviews (PROSPERO CRD42012002304).

A Multicenter Evaluation of Off-Label Medication Use and Associated Adverse Drug Reactions in Adult Medical ICUs

OBJECTIVE

Prior research indicates that off-label use is common in the ICU; however, the safety of off-label use has not been assessed. The study objective was to determine the prevalence of adverse drug reactions associated with off-label use and evaluate off-label use as a risk factor for the development of adverse drug reactions in an adult ICU population.

DESIGN

Multicenter, observational study

SETTING

: Medical ICUs at three academic medical centers.

PATIENTS

Adult patients (age ≥ 18 yr old) receiving medication therapy.

INTERVENTIONS

All administered medications were evaluated for Food and Drug Administration-approved or off-label use. Patients were assessed daily for the development of an adverse drug reaction through active surveillance. Three adverse drug reaction assessment instruments were used to determine the probability of an adverse drug reaction resulting from drug therapy. Severity and harm of the adverse drug reaction were also assessed. Cox proportional hazard regression was used to identify a set of covariates that influenced the rate of adverse drug reactions.

MEASUREMENTS AND MAIN RESULTS

Overall, 1,654 patient-days (327 patients) and 16,391 medications were evaluated, with 43% of medications being used off-label. One hundred and sixteen adverse drug reactions were categorized dichotomously (Food and Drug Administration or off-label), with 56% and 44% being associated with Food and Drug Administration-approved and off-label use, respectively. The number of adverse drug reactions for medications administered and the number of harmful and severe adverse drug reactions did not differ for medications used for Food and Drug Administration-approved or off-label use (0.74% vs 0.67%; p = 0.336; 33 vs 31 events, p = 0.567; 24 vs 24 events, p = 0.276). Age, sex, number of high-risk medications, number of off-label medications, and severity of illness score were included in the Cox proportional hazard regression. It was found that the rate of adverse drug reactions increases by 8% for every one additional off-label medication (hazard ratio = 1.08; 95% CI, 1.018-1.154).

CONCLUSION

Although adverse drug reactions do not occur more frequently with off-label use, adverse drug reaction risk increases with each additional off-label medication used.

Exploring in-hospital adverse drug events using ICD-10 codes

OBJECTIVE

Adverse drug events (ADEs) during hospital admissions are a widespread problem associated with adverse patient outcomes. The 'external cause' codes in the International Statistical Classification of Diseases and Related Health Problems 10th Revision (ICD-10) provide opportunities for identifying the incidence of ADEs acquired during hospital stays that may assist in targeting interventions to decrease their occurrence. The aim of the present study was to use routine administrative data to identify ADEs acquired during hospital admissions in a suburban healthcare network in Melbourne, Australia.

METHODS

Thirty-nine secondary diagnosis fields of hospital discharge data for a 1-year period were reviewed for 'diagnoses not present on admission' and assigned to the Classification of Hospital Acquired Diagnoses (CHADx) subclasses. Discharges with one or more ADE subclass were extracted for retrospective analysis.

RESULTS

From 57205 hospital discharges, 7891 discharges (13.8%) had at least one CHADx, and 402 discharges (0.7%) had an ADE recorded. The highest proportion of ADEs was due to administration of analgesics (27%) and systemic antibiotics (23%). Other major contributors were anticoagulation (13%), anaesthesia (9%) and medications with cardiovascular side-effects (9%).

CONCLUSION

Hospital data coded in ICD-10 can be used to identify ADEs that occur during hospital stays and also clinical conditions, therapeutic drug classes and treating units where these occur. Using the CHADx algorithm on administrative datasets provides a consistent and economical method for such ADE monitoring.

Pilot testing of checklists to discern adverse drug reactions and adverse drug events

OBJECTIVES

To estimate the prevalence of patient-reported adverse drug events (ADEs)/adverse drug reactions (ADRs) in the community pharmacy setting and determine the prevalence relative to pharmacist judgment.

DATA SOURCES

The 2009 version of the Pharmacy Times top 200 drugs was used to identify the prescription medications most commonly used within the ambulatory population during 2008. All ADEs/ADRs for each medication were obtained by combining the ADEs/ADRs listed in Drug Facts and Comparisons, Lexi-Comp, and Micromedex.

METHODS

Checklists for each pharmacologic class within the top 200 medications (n = 51) were developed, with questions about the five most common ADEs/ADRs in each class. Ten community pharmacies administered the checklists. Patients requesting a prescription refill for a medication listed in the top 200 were asked to complete a class-specific checklist to determine ADEs/ADRs experienced in the previous 4 weeks. Upon completion, pharmacists engaged in routine counseling procedures, including a discussion of patient-reported ADEs/ADRs. Pharmacists indicated if they believed, based on their clinical judgment, whether the ADE/ADR reported was related to the medication.

RESULTS

2,057 checklists were completed, with a total of 10,285 potential ADEs/ADRs. Patients reported 2,185 ADEs/ADRs (21.24%), with 755 (7.3%) definitively confirmed by the pharmacist as being related to their medication.

CONCLUSION

Use of these checklists resulted in the identification of previously unrecognized ADEs/ADRs in the community setting. Routine use of these short, patient-completed checklists may assist pharmacists in earlier identification of ADEs/ADRs, which can have a positive impact on patient safety across settings.

Developing an expert panel process to refine health outcome definitions in observational data

OBJECTIVES

Drug safety surveillance using observational data requires valid adverse event, or health outcome of interest (HOI) measurement. The objectives of this study were to develop a method to review HOI definitions in claims databases using (1) web-based digital tools to present de-identified patient data, (2) a systematic expert panel review process, and (3) a data collection process enabling analysis of concepts-of-interest that influence panelists' determination of HOI.

METHODS

De-identified patient data were presented via an interactive web-based dashboard to enable case review and determine if specific HOIs were present or absent. Criteria for determining HOIs and their severity were provided to each panelist. Using a modified Delphi method, six panelist pairs independently reviewed approximately 200 cases across each of three HOIs (acute liver injury, acute kidney injury, and acute myocardial infarction) such that panelist pairs independently reviewed the same cases. Panelists completed an assessment within the dashboard for each case that included their assessment of the presence or absence of the HOI, HOI severity (if present), and data contributing to their decision. Discrepancies within panelist pairs were resolved during a consensus process.

RESULTS

Dashboard development was iterative, focusing on data presentation and recording panelists' assessments. Panelists reported quickly learning how to use the dashboard. The assessment module was used consistently. The dashboard was reliable, enabling an efficient review process for panelists. Modifications were made to the dashboard and review process when necessary to facilitate case review. Our methods should be applied to other health outcomes of interest to further refine the dashboard and case review process.

CONCLUSION

The expert review process was effective and was supported by the web-based dashboard. Our methods for case review and classification can be applied to future methods for case identification in observational data sources.

Expert panel assessment of acute liver injury identification in observational data

BACKGROUND

Observational data are useful for studying drug safety; however, to be effective, accurate outcome measurement is paramount.

OBJECTIVES

This study compared alternative outcome definitions for acute liver injury (ALI) and explored opportunities for improving ALI identification in observational data.

METHODS

The Truven MarketScan® Lab Database (MSLR) was used to identify patients meeting at least 1 of 4 ALI definitions, including definitions based on diagnosis codes, laboratory measures, or combinations of diagnoses, procedures, and/or laboratory measures. Expert panelists reviewed patient data using a Web dashboard. Panelists determined whether they believed the patient had ALI and identified factors influencing their decision. Logistic regression models explored which factors were influential in case determination.

RESULTS

Overall, only 37 of 208 reviewed patients (17.8%) were classified as cases. The diagnosis-based definition yielded no positive cases and the laboratory-based definition yielded the most positive cases (31 of 60). The most influential factors in case classification were occurrence of procedures after the index date (OR = 13.2, 95% CI = 5.3-32.9), no occurrence of drug treatments before the index date (OR = 4.6; 95% CI = 1.6-13.2), occurrence of drug treatments before the index date (OR = 0.3; 95% CI = 0.1-0.6), and no drug treatments after the index date (OR = 0.2; 95% CI = 0.0-0.5).

CONCLUSIONS

Comparing ALI definitions illustrated tradeoffs between the number of plausible cases identified and the likelihood of cases being classified as positive. Future research should refine ALI case definitions, considering the import of laboratory results, procedures, and drugs in defining a case.

An algorithm to detect adverse drug reactions in the neonatal intensive care unit

Critically ill newborns in neonatal intensive care units (NICUs) are at greater risk of developing adverse drug reactions (ADRs). Differentiation of ADRs from reactions associated with organ dysfunction/immaturity is difficult. Current ADR algorithm scoring was established arbitrarily without validation in infants. The study objective was to develop a valid and reliable algorithm to identify ADRs in the NICU. Algorithm development began with a 24-item questionnaire for data collection on 100 previously suspected ADRs. Five pediatric pharmacologists independently rated cases as definite, probable, possible, and unlikely ADRs. Consensus "gold standard" was reached via teleconference. Logistic regression and iterative C programs were used to derive the scoring system. For validation, 50 prospectively collected ADR cases were assessed by 3 clinicians using the new algorithm and the Naranjo algorithm. Weighted kappa and intraclass correlation coefficient (ICC) were used to compare validity and reliability of algorithms. The new algorithm consists of 13 items. Kappa and ICC of the new algorithm were 0.76 and 0.62 versus 0.31 and 0.43 for the Naranjo algorithm. The new algorithm developed using actual patient data is more valid and reliable than the Naranjo algorithm for identifying ADRs in the NICU population. Because of the relatively small and nonrandom samples, further refinement and additional testing are needed.

Readmission risk factors after hospital discharge among the elderly

Hospital readmission rates among the elderly are attracting increasing attention. Readmission is costly, especially as proposed new guidelines could deny reimbursement for readmissions. Identifying key factors at discharge that can serve as prognostic indicators for readmission is an important step toward developing and targeting interventions to reduce hospital readmissions rates. Published literature has listed predominantly demographic, clinical, and health care utilization characteristics to describe the factors that put the elderly at risk. However, additional factors are proposed that include social, clinical, individual-level, environmental, and system-level factors. Multimodal interventions have been tested and some reduction in readmissions has been shown. Whether these additional factors might lead to a further reduction remains unclear. In addition to possible factors at discharge, factors identified after the patient has been discharged also must be identified and addressed. The patient safety literature characterizes factors that put the elderly at risk for adverse drug events, which function as antecedent factors for readmission and likely include the environmental and system-level factors. Synthesizing these factors from the readmission and patient safety literature provides the basis to develop a more comprehensive conceptual framework to identify research gaps aimed at reducing hospital readmissions among the elderly.

Adverse Drug Reactions in Elderly Hospitalized Patients: A 12-Year Population-Based Retrospective Cohort Study

BACKGROUND:

Although research has identified some risk factors for first-time adverse drug reactions (ADRs), little is known about the risks associated with the number of ADRs. Modeling ADR counts is relatively complex because of the rarity of the events, requiring careful consideration of appropriate models that best present the observed data.

OBJECTIVE:

To determine the incidence of ADRs among elderly hospitalized patients, assess patient-related risk factors for the number of ADRs, and review drug classes commonly responsible for ADRs.

METHODS:

This retrospective cohort study used a population-based large administrative database on hospital separations from all acute care hospitals in the Canadian province of Newfoundland and Labrador. Patients aged 65 years or older with at least 1 hospital admission from April 1, 1995, to March 31, 2007, were included. Comorbidities, Charlson Comorbidity Index (CCI), and sociodemographic factors were assessed as predictors of ADR counts. A zero-inflated negative binomial regression model was used for analysis.

RESULTS:

The study cohort contained 64,446 patients. The incidence of ADRs was 15.2 per 1000 person-years (95% CI 14.8 to 15.7). Of those having an ADR, 15.4% had recurrent ADRs. The most common drug category implicated in ADRs was cardiovascular agents (17.7%). A dose-response relationship was found between CCI and ADR counts (rate ratio [RR] 1.67, 95% CI 1.41 to 1.98 for CCI 2-3; RR 2.38, 95% CI 1.98 to 2.87 for CCI 4-5; and RR 3.83, 95% CI 3.21-4.57 for CCI ≥6). Comorbid conditions including congestive heart failure (RR 1.58, 95% CI 1.33 to 1.89), diabetes (RR 2.42, 95% CI 1.64 to 3.56), and cancer (RR 3.12, 95% CI 2.58 to 3.76) were strong predictors. Rural areas (RR 1.22, 95% CI 1.01 to 1.46) were associated with increased risk for ADRs, whereas age and sex had no effect.

CONCLUSIONS:

Comorbidity from chronic diseases and severity of illness, rather than individual characteristics (advancing age and sex), increased the likelihood of ADRs. Changes in the delivery of care focusing on the monitoring of prescribed drugs in elderly patients with comorbidities could mitigate ADRs.

Deriving rules and assertions from pharmacogenomics knowledge resources in support of patient drug metabolism efficacy predictions

OBJECTIVE

Pharmacogenomics evaluations of variability in drug metabolic processes may be useful for making individual drug response predictions. We present an approach to deriving 'phenotype scores' based on existing pharmacogenomics knowledge and a patient's genomics data. Pharmacogenomics plays an important role in the bioactivation of tamoxifen, a prodrug administered to patients for breast cancer treatment. Tamoxifen is therefore considered a model for many drugs requiring bioactivation. We investigate whether this knowledge-based approach can be applied to produce a phenotype score that is predictive of the endoxifen/N-desmethyltamoxifen (NDM) plasma concentration ratio in patients taking tamoxifen.

MATERIALS AND METHODS

We implement a knowledge-based model for calculating phenotype scores from patient-specific genotype data. These data include allelic variants of genes encoding enzymes involved in the bioactivation of tamoxifen. We performed quantile linear regression to evaluate whether six phenotype scoring algorithms are predictive of patient endoxifen/NDM plasma concentration ratio, and validate our scoring methods.

RESULTS

Our model illustrates a knowledge-based approach to predict drug metabolism efficacy given patient genomics data. Results showed that for one phenotype scoring algorithm, scores were weakly correlated with patient endoxifen/NDM plasma concentration ratios. This algorithm performed better than simple metrics for variation in individual and multiple genes.

DISCUSSION

We discuss advantages of the model, challenges to its implementation in a personalized medicine context, and provide example future directions.

CONCLUSIONS

We demonstrate the utility of our model in a tamoxifen case study context. We also provide evidence that more complicated polygenic models are needed to represent heterogeneity in clinical outcomes.

Analysis of risk factors for adverse drug events in critically ill patients*

OBJECTIVES

An evaluation of risk factors for adverse drug events in critically ill patients has not been previously studied. The purpose of this original study was to determine risk factors for adverse drug events in critically ill adult patients.

DESIGN

This retrospective case-control study includes patients who were admitted to the intensive care unit during a 7.5-yr period.

SETTING

Academic medical center with 647 beds that contains approximately 120 intensive care unit beds.

PATIENTS

Patients in the case group experienced an adverse drug event as documented in the hospital's database. The control group comprised the next two patients admitted to the same intensive care unit by the same admitting service.

INTERVENTIONS

None.

MEASUREMENTS AND MAIN RESULTS

Twenty-nine suspected risk factors identified from the literature were evaluated, including patient characteristics, drug characteristics, and laboratory values using a multiple logistic regression. A sample of 1101 cases and controls (54% male), with a mean age of 59.4 ± 17.5 yrs, were identified. In 367 cases, there was a total of 499 documented adverse drug events. Patients with kidney injury, thrombocytopenia, and those admitted emergently were 16-times, 3-times, and 2-times more likely to have an adverse drug event, respectively. Patients who were administered intravenous medications had a 3% higher risk of having an adverse drug event for each drug dispensed. Overall, the case group received more drugs per intensive care unit day and more drugs per intensive care unit stay.

CONCLUSIONS

Several patient and drug-related characteristics contribute to the risk of adverse drug events in critically ill patients. Diligent monitoring of factors that can influence the pharmacokinetic properties for existing drug therapies is necessary. Drug regimens should be evaluated daily for minimization. Based on previous studies, pharmacists as part of the interdisciplinary team could help to manage these risks.

Drug-nutrient interactions: a broad view with implications for practice

The relevance of drug?nutrient interactions in daily practice continues to grow with the widespread use of medication. Interactions can involve a single nutrient, multiple nutrients, food in general, or nutrition status. Mechanistically, drug?nutrient interactions occur because of altered intestinal transport and metabolism, or systemic distribution, metabolism and excretion, as well as additive or antagonistic effects. Optimal patient care includes identifying, evaluating, and managing these interactions. This task can be supported by a systematic approach for categorizing interactions and rating their clinical significance. This review provides such a broad framework using recent examples, as well as some classic drug?nutrient interactions. Pertinent definitions are presented, as is a suggested approach for clinicians. This important and expanding subject will benefit tremendously from further clinician involvement.

Polypharmacy and food-drug interactions among older persons: a review

Polypharmacy is generally defined as the use of 5 or more prescription medications on a regular basis. The average number of prescribed and over-the-counter medications used by community-dwelling older adults per day in the United States is 6 medications, and the number used by institutionalized older persons is 9 medications. Almost all medications affect nutriture, either directly or indirectly, and nutriture affects drug disposition and effect. This review will highlight the issues surrounding polypharmacy, food-drug interactions, and the consequences of these interactions for the older adult.

Underreporting of recognized adverse drug reactions by primary care physicians: an exploratory study

PURPOSE

This study evaluated the magnitude of underreporting of adverse drug reactions (ADRs) and investigated possible reporting patterns according to patient characteristics and the type of reaction based on the integration of information obtained from primary care electronic medical records (EMRs) and the Spanish Pharmacovigilance System.

METHODS

This investigation was a descriptive retrospective study analysing ADRs recorded in 2005 in the EMRs from six health centers in Zaragoza (Aragon, Spain) with a covered population of 126,838 subjects. The associations between the probability of reporting and the reaction and drug type were studied using logistic regression models adjusted by age and sex.

RESULTS

The total number of ADRs recorded in the EMRs was 543, of which 65.7% were reported to the Spanish Pharmacovigilance System. Positive associations were found between the probability of reporting an ADR and advanced age of patients (OR for ≥76 years = 2.0; 95%CI 1.1-3.6), involvement of the reproductive system (OR = 7.9; 95%CI 1.02-60.2) and involvement of psychiatric disorders (OR = 4.0; 95%CI 1.4-11.6). Negative associations were found between reporting an ADR and early age of patients (OR for 0-14 years = 0.2; 95%CI 0.1-0.6) and the use of antimicrobial drugs (OR = 0.6; 95%CI 0.4-0.9).

CONCLUSIONS

This study tackles an important public health problem directly related to patients' safety and highlights the utility of EMRs for investigating the current significance of ADR underreporting. It also makes us think that primary care physicians seem to have selective reporting patterns based on their familiarity with the reaction type and the drug causing the reaction as well as on the age of patients.

Intensive insulin therapy in critically ill hospitalized patients: making it safe and effective

Intensive insulin therapy (IIT) for hyperglycemia in critically ill patients has become a standard practice. Target levels for glycemia have fluctuated since 2000, as evidence initially indicated that tight glycemic control to so-called normoglycemia (80-110 mg/dl) leads to the lowest morbidity and mortality without hypoglycemic complications. Subsequent studies have demonstrated minimal clinical benefit combined with greater hypoglycemic morbidity and mortality with tight glycemic control in this population. The consensus glycemic targets were then liberalized to the mid 100s (mg/dl). Handheld POC blood glucose (BG) monitors have migrated from the outpatient setting to the hospital environment because they save time and money for managing critically ill patients who require IIT. These devices are less accurate than hospital-grade POC blood analyzers or central laboratory analyzers. Three questions must be answered to understand the role of IIT for defined populations of critically ill patients: (1) How safe is IIT, with various glycemic targets, from the risk of hypoglycemia? (2) How tightly must BG be controlled for this approach to be effective? (3) What role does the accuracy of BG measurements play in affecting the safety of this method? For each state of impaired glucose regulation seen in the hospital, such as hyperglycemia, hypoglycemia, or glucose variability, the benefits, risks, and goals of treatment, including IIT, might differ. With improved accuracy of BG monitors, IIT might be rendered even more intensive than at present, because patients will be less likely to receive inadvertent overdosages of insulin. Greater doses of insulin, but with dosing based on more accurate glucose levels, might result in less hypoglycemia, less hyperglycemia, and less glycemic variability.