Detection of serious adverse drug reactions using diagnostic codes in the International Statistical Classification of Diseases and Related Health Problems.

Introduction The detection, characterization, and communication of information about drug toxicity are integral to medicine and drug regulation in all medical fields. Although the challenges we face in HIV may appear uniquely daunting, they are not essentially different. Over the first two decades of the HIV epidemic, the importance of drug safety monitoring was overshadowed by the need to develop potent therapies capable of arresting a fatal disease process. It is now clear, however, that the treatment successes achieved mainly through highly active antiretroviral therapy (HAART) are tempered significantly by drug toxicity [1–3]. These toxicities often occur in patients who have been exposed to multiple drugs for prolonged periods of time, thus the monitoring of long-term toxicities necessitates efforts extending beyond the usual follow-up of many cohorts and nearly all clinical trials. This review focuses on drug safety monitoring of HIV treatments and, in particular, the strengths and limitations of the available approaches for detecting and characterizing long-term toxicities. To understand the challenges specific to the monitoring of long-term toxicities, it is critical to understand the interconnected functions of both pharmacovigilance and pharmacoepidemiology. The purpose of pharmacovigilance is to detect previously unknown adverse drug effects. Pharmacovigilance sets the stage for formal pharmacoepidemiology studies, which involve control groups and are meant to refute or confirm and quantify drug safety risks. Risk management follows. Findings are communicated to patients and providers, while governments, manufacturers, and professional groups devise ways to change medical practice in order to avoid further toxicities. These processes are illustrated schematically in Figure 1. (A broader definition places all steps under the umbrella of pharmacovigilance, but in this review, we will refer to pharmacovigilance and pharmacoepidemiology as distinct concepts).Fig. 1.: Process of pharmacovigilance and pharmacoepidemiology.From a regulatory standpoint, safety monitoring of pharmaceuticals occurs in two phases – (1) before and (2) after a drug is approved. Leading up to approval, clinical trials provide data on predefined efficacy questions, frequent adverse events and immediate safety. Following approval, during postmarketing surveillance, safety information is derived primarily from spontaneous reporting systems supported by regulatory authorities in every industrialized country; further information may be generated by large post-marketing (Phase III and IV) clinical studies. The current system of drug safety assessment faces significant constraints, many of which are explained below. Despite these challenges, enhanced understanding of toxicities associated with use of antiretroviral medications can be expected to improve HIV care in several ways. Patients will be provided with information leading to more accurate expectations, perhaps decreasing disappointment and frustration when chronic, low-grade toxicities occur [4]. More realistic expectations may increase a feeling of trust and teamwork between patient and provider, which could lead to greater adherence [5]. Furthermore, better evidence regarding long-term toxicities will improve advice given to patients by clinicians about timing of initial therapy, choice of regimen, and drug substitutions or discontinuations. Better safety data may also lead to insights into the mechanism of toxicity and can eventually assist in drug development, in screening patients at high risk for toxicity, and in developing useful strategies for toxicity monitoring and management. For the purposes of this review, the term adverse event (AE) is defined as any untoward medical occurrence in a subject who has been administered a pharmaceutical product. The drug may or may not be causally related to the AE – in the cases where it is, the event is termed an adverse drug reaction (ADR). Indeed, sorting out the role of the drug in causing the AE is the goal of pharmacoepidemiology and drug safety monitoring. Available systems for monitoring the safety of HIV treatments – signal detection and hypothesis testing Signal detection Several systems currently are available for the detection of HIV-related AEs. They include pre- and post-approval clinical trials, spontaneous reporting systems such as the US Food and Drug Administration's (FDA) Adverse Event Reporting System and similar arrangements in the European Union and other industrialized countries, automated databases such as those compiled by Health Maintenance Organizations (HMOs), and observational cohorts. Randomized clinical trials Because individuals are first exposed to pharmaceutical products in the setting of clinical trials, these trials comprise a potentially valuable early source of toxicity data especially for relatively common ADRs with short-term onset. An example of one such toxicity is abacavir hypersensitivity reaction, which affects approximately 5% of individuals given the drug [6]. Randomized clinical trials (RCTs), however, have several limitations as signal generators. Pre-marketing studies usually recruit small, homogenous patient populations for study – typically fewer than 3000 exposed individuals. In this case, even if no serious ADRs are detected, one can only be confident that the rate of events is not greater than 3 per 3000, often referred to as the 'rule of 3' [7]. Thus, detection of relatively infrequent ADRs such as lactic acidosis is unlikely. Furthermore, individuals with significant comorbidities (e.g., hepatitis B and C) are commonly excluded, making detection of ADRs in these groups impossible. Similarly, ADRs may occur only in selected patient subsets that are insufficiently recruited and included in these trials. For example, female sex is associated with development of cutaneous rash caused by nevirapine [8]. Trials carried out largely in a male population could potentially miss or at least underestimate the occurrence of this reaction. Similarly, under-representation of ethnic minorities in clinical trials adds to this problem. Another limitation of RCTs (both pre- and post-approval) for the detection of long-term ADRs in HIV is the relatively short follow-up time of clinical trials. Indeed, increasing the follow-up of RCTs increases the cost and complexity of these studies. Moreover, the validity of the results often diminishes as losses to follow-up increase. However, several trials with extended follow-up are currently ongoing, including ACTG 384, the FIRST study, INITIO, and SMART, demonstrating that although difficult, long-term RCTs are feasible. Yet another limitation is the possibility that certain ADRs occurring in RCTs are under-reported. 'Minor' ADRs such as mood disorders or sleep disturbances may go undetected unless specifically targeted in data collection. These low-grade toxicities, however, may have substantial effects on adherence, which has been shown to affect several HIV-related outcomes [9,10]. Other ADRs, such as lipodystrophy, may not be classified in a standardized way, leading to poor detection in RCTs [11]. Homogenous patient populations, small sample sizes, and short durations of follow-up therefore significantly limit the use of RCTs for the detection of uncommon and late-onset toxicities. Spontaneous reporting systems After approval, the major mechanism of post-marketing surveillance is spontaneous reporting systems. This mechanism, used in both the United States and Europe, helps to identify ADRs that may not have been revealed during pre-approval trials. Completely passive in design, the identification of ADRs begins with the collection of spontaneous AE reports made by health professionals and patients and is typified by the FDA's MedWatch system [12]. Major strengths are the large scale (indeed, they potentially include all patients in clinical care in those countries with these systems) and the diversity of the population potentially included over long periods of time. Significant limitations do, however, exist. In the US, no federal laws or regulations require health care providers to report AEs related to pharmaceuticals, and it is estimated that the FDA receives reports on less than 1% of suspected serious drug-related events [13]. In many cases, physicians may feel an event is too trivial or too well known to report [14]. Other reasons for under-reporting may include physician guilt about harming a patient, fear of potential litigation, ambition to collect and publish cases, lack of awareness that an ADR has occurred, and lack of knowledge of how to report AEs via the available system [15]. A further limitation probably relates to lack of time and/or unwillingness to become involved in follow-up documentation or verification of reported AEs. Because of these limitations, the actual number of patients with a particular AE (the numerator of the AE rate) is unknown. Once reports are received, AEs are grouped into aggregate categories (i.e. a 'rash' may be further separated into 'maculopapular rash' or 'bullous eruption', etc.) based on standardized medical terminology dictionaries, such as MedDRA (Medical Dictionary for Drug Regulatory Activities) [16]. Some AE reports, however, may not be easily assigned to a single specific category. Moreover, terminology used in standardized medical dictionaries, despite ongoing efforts at harmonization, is often not consistent across international systems, adding further complexity to the process. After categorization, further challenges arise from the need to systematically identify and characterize those AEs that are observed to a greater rate than expected. The process of identification, based on pattern recognition, involves the use of prior knowledge and scientific inference to separate consistent, replicable 'signals' from a background of database 'noise' [17]. Given that any large surveillance system will produce many interesting but perhaps biased patterns of AEs and disease, it becomes vital that carefully reviewed associations be followed by formal pharmacoepidemiology studies in order to further evaluate cause and effect. This is particularly true in the case of HIV, where causal associations between drug and AE are often complicated by the multiplicity of treatments, any one of which might account for the toxicity, and by the possibility that the disease itself, apart from any treatment, may be the culprit. Indeed, the process of signal detection produces case reports and case series; observational and/or interventional studies that utilize control groups are critical in order to formally define risk. Automated databases Automated databases, originally developed to support computerized billing systems, are another potential resource for detecting antiretroviral toxicity. Automated databases provide large numbers of patients followed longitudinally through various health-care encounters and sequences of drug use. Necessarily smaller in their population coverage than nationwide spontaneous reporting systems, they nonetheless offer more complete ascertainment of serious events in the persons included in the database. Furthermore, some large systems (most notably in the UK, but also found in continental Europe and in the United States) were initially created as computerized medical records, and may, depending on local privacy laws, be used for individual record review or for population studies. The most common uses of these data historically have been to provide quantitative evaluation of signals generated elsewhere. They also provide a strong platform for building active surveillance systems. Another strength of automated databases is the relative heterogeneity of patients exposed to drug. Furthermore, prescription information may be available, providing one way of assessing duration of drug exposure. The longitudinal nature of the data is particularly valuable when the goal is to detect long-term toxicities. A partial list of automated databases available for the detection of ADRs in HIV is given in Table 1. Note that certain databases not included in the table, such as the General Practice Research Database in the UK and the Saskatchewan database in Canada, although large, currently have limited utility in HIV due to their relatively small numbers of HIV-infected patients included. A helpful discussion of the use of these specific databases for pharmacoepidmiologic purposes is contained in Part III of the book Pharmacoepidemiology [7].Table 1: Automated databases available for study of adverse events in HIV.However, in order for an AE to be coded in an automated database it must be recognized. The tendency of providers to recognize AEs as ADRs may in turn relate to diagnostic suspicion and/or other biases that over or underestimate the true association of a drug and a specific toxicity. In some cases, AEs may not be recognized at all. All of these issues may limit the ability to accurately identify and study toxicities using these sources. In some cases, billing codes (e.g. International Classification of Disease (ICD) codes) may capture the events with adequate sensitivity and specificity. However, the target event might be spread across many codes (e.g. upper gastrointestinal bleeding could be coded as upper gastrointestinal bleeding not otherwise specified, hematemesis, melena, or acute duodenal ulcer with bleeding), be buried under a rubric that contains numerous other entities, or correspond to an evolving syndrome for which no code yet exists, such as lipodystrophy syndrome [11]. Case ascertainment in this setting often requires multiple different aggregations of codes as different definitions of the same disease [18]. Chart review of suspected cases is almost always required. Alternatively, if linkage to the medical record is possible, some ADRs, such as anemia, may be ascertained via laboratory data. In general, those clinical entities that bring patients to the attention of caregivers, result in a quick and coded diagnosis, and can be supported or confirmed by a laboratory test (or chart review) are candidates for study using these sources. Specific ADRs, listed according to ease of study using these databases, are given in Table 2.Table 2: Adverse events according to ease of study using automated databases (aspects leading to ease or difficulty).Ad hoc cohort studies For epidemiologists, a cohort is simply a group of people followed over time during which health events are observed. In this sense of the term, the automated databases of the previous section can be used to form epidemiologic cohorts. The usable databases are circumscribed, however, by the kinds of data that are routinely captured. Ad hoc cohort studies, in which the data collection is specified in advance and implemented according to standard procedures, an in detection of ADRs when the and the diagnostic go beyond the occurs in automated The follow-up time of cohorts often that of clinical trials the of term and toxicities. data collection is ADRs such as and mood disorders can be may also be useful for of specific patient such as and drug – groups that are often from clinical trials and in automated A partial list of cohorts to HIV treatment is given in Table Note that the and duration of patient populations, data and number of list of cohorts available for study of adverse events associated with testing After a signal is through pharmacovigilance further is by way of hypothesis testing and formal studies. In particular, it is to both and quantify risk. is critical to to or the of the risk is critical to the importance of the ADR relative to other ADRs and other of and Spontaneous reporting systems Spontaneous reporting systems offer for formal hypothesis The significant under-reporting and lack of adequate data on number of patients exposed to a drug – as in the section – not ascertainment of the numerator (the number of people with an the thus making the of of AEs impossible. They are a valuable source of information between drugs or drug only in the of events that appear commonly in association with one drug or and almost in their Automated databases Automated databases have a potentially useful role in hypothesis Once an ADR is by spontaneous can an automated database for cases, and in order to for the use of automated databases for studies of ADRs in HIV requires several although database populations may be in the only a small of patients will have HIV, sample and the to detect only prescription information is – data on and are this information is based on prescription – it is not known if the was most automated databases are based on information – if a patient or they may be from the database. information on such as and adherence patterns are often not This limitation may result in the of significant regarding patient for treatment, and ascertainment is usually from care as only databases are to vital available source for this information is the but the has a time of approximately Ad hoc cohort studies Once an AE is large, patient cohorts can be used to associations of AEs with drugs or drug A major of cohorts over automated databases is that specific treatment and information can be more ascertained by than can be from medical For some HIV such as drug and observational cohort studies may be the only way to numbers of patients to safety Furthermore, the longitudinal nature of the data in many cohorts is particularly useful in the of duration of treatment on development of toxicity. Some such as the and the HIV also provide valuable and control Furthermore, to toxicity may be and – these data can in into the of major with the study of HIV drug toxicity, even in hoc is the lack of definitions for various ADRs This is particularly true for certain ADRs, such as lipodystrophy syndrome [11]. Furthermore, of case definitions the ability of cohorts to increase by Although individual cohorts may be large, for such as the number of case patients may This potentially useful has been to example of such is the study – a observational cohort study the association of with It involves cohorts patients who are followed for at least This study the way can increase sample and to detect infrequent but ADRs that otherwise be or to Another critical when cohorts as a source of toxicity data is that cohort studies are more to be by and than are clinical trials, where helps exposed and groups more Furthermore, issues of and the of may the ability of to identify less but significant All of these increase the time and for data which to and need for from both and Randomized clinical trials for the purposes of associations between antiretroviral drugs and long-term toxicities, RCTs are the However, currently RCTs have a on safety than on efficacy and this is true for both the and post-approval This is that the for specific of AEs could be by the control of known and unknown by the of multiple treatments and common in HIV, the of to two (or groups valuable insights into safety. example of a clinical to patients for an extended of time is or the This study to the long-term clinical of different strategies of antiretroviral therapy, and up beyond Other include the or and with 3 of and the Trials Randomized which will to ways to efficacy and toxicity of and will patients for These studies the and resource nature of the for these the use of HIV medications – from reporting to risk management In order to improve the use of HIV treatments to be by all groups involved to information on safety a major of HIV This result in a of to and scientific to the study of HIV-related AEs to this goal to into efforts specifically to improve all of drug including AE detection, and risk management. an that safety outcomes to their is to this is an understanding that in the of drug safety can in of critical is an understanding of the limitations of current knowledge of antiretroviral toxicities – is known and is This can be as a drug safety as shown in Figure derived from and The goal of pharmacovigilance in HIV be to the of the small as as The This to the most to the and study of ADRs – duration of follow-up (the and of the event (the The small in the upper the frequent in which more study and risk management of ADRs The the of the the unknown of those ADRs that occur and less post-marketing reporting of potential ADRs through spontaneous reporting systems is for enhanced understanding of long-term toxicities in pattern through is one way reporting of AEs may be In order to on ADRs be in both medical and as well as via for AE reporting Given a greater understanding of pattern recognition, will providers report more way to increase the of this may be to develop a specifically at AE This all of the from patient to Furthermore, an active the of ways to improve reporting be A limited example of this active in the UK, where spontaneous reporting is based on the This system an for clinicians to report suspected ADRs to the UK from this system that the of into the pharmacovigilance the number of reports received, which were of to those from In have been included as of AEs in the UK Furthermore, a system of the HIV drugs is an example of at In other as in where reporting of AEs has been for and regulatory steps have been to increase the of will need to be A but often of the surveillance is the Indeed, several long-term toxicities, including were initially recognized by HIV-infected individuals. 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Methods and systems to detect adverse drug reactions in hospitals.

A Machine-Learning Algorithm to Optimise Automated Adverse Drug Reaction Detection from Clinical Coding.

In order to detect adverse events in patients at pharmacies, a questionnaire was developed to evaluate adverse drug reactions that may come from the use of pharmaceuticals. The questionnaire enabled pharmacists to assume possible adverse drug reactions while they dispense a prescription but was designed not to make patients sensitive. An investigation method was developed to detect adverse drug reactions that may be attributable to drug treatment by leading patient natural complaints while pharmacists provide drug treatment guidance to patients. This investigation was conducted at six pharmacies. As a result, 26.6% of the adverse drug reactions that can be associated with the question items ticked by at least five patients who had received the same drug were not indicated in the precautionary statements of the drugs. This suggests that this investigation may possibly contribute to detection of unknown adverse drug reactions. Furthermore, some of the patients who ticked question items related to prodromal symptoms of serious adverse drug reactions had received drug therapies that were known to be associated with those adverse drug reactions. This also suggests that the investigation may possibly contribute to detection of serious adverse drug reactions. It was considered to be more effective to focus on detection of serious adverse drug reactions with the use of the questionnaire in the future, which is more important than safety precautions. The accuracy in judging adverse drug reactions can be enhanced by asking patients with chronic diseases to respond to the questionnaire every time a prescription is dispensed.

BackgroundOlder inpatients with dementia are at an increased risk of an adverse drug reaction (ADR) during hospitalization.ObjectiveTo quantify the prevalence of ADRs in older inpatients according to dementia status and ADR definition approach and to identify risk factors of ADRs during hospitalization.MethodsThis was a retrospective cohort study of 2000 inpatients aged ≥ 75 years admitted consecutively to six Sydney hospitals (1 July 2016 to 31 May 2017). Dementia was defined by diagnosis in electronic medical records. ADRs were defined according to two approaches: the International Statistical Classification of Diseases and Related Health Problems, Tenth Revision, Australian Modification (ICD-10-AM) and classification by a research pharmacist (subset cohort, n = 600). A binary logistic regression was conducted to determine risk factors of ADRs.ResultsAmong 2000 patients, 25.9% (n = 517) were reported to have dementia. ADRs defined by ICD-10-AM were identified in 8.3% (n = 43) and 14.6% (n = 217) of inpatients with and without dementia respectively (p < 0.001). A total of 13.0% (n = 260) and 12.5% (n = 75) of patients had ADRs defined by ICD-10-AM and a research pharmacist, respectively. Key risk factors of ADRs were longer hospital stay [odds ratio (OR) 1.01, 95% confidence interval (CI) 1.01, 1.02) and a greater number of regular potentially inappropriate medicines (PIMs) on admission (OR 1.17, 95% CI 1.00, 1.38).ConclusionsADRs were more prevalent among inpatients without dementia and when assessed by a research pharmacist. Our findings underline the need for improved ADR detection in older inpatients.

What is already known about this subject. Studies conducted primarily in developed countries have shown that adverse drug reactions (ADRs) are a significant cause of hospital admission, prolong hospital stay and consequently increase the cost of disease management in patients. Cardiovascular medicines, hypoglycaemic agents, nonsteroidal anti-inflammatory drugs and antibiotics are the most frequently implicated medicines in these studies. A large proportion of these ADRs have been shown to be preventable through improved drug prescribing, administration and monitoring for adverse effects. What this paper adds. This is the first Sub-Saharan African study in the HIV/AIDS era that describes the contribution of ADRs to patient morbidity, hospitalisation and mortality. Cardiovascular medicines and antiretroviral therapy contributed the most to community-acquired ADRs at the time of hospital admission while medicines used for opportunistic infections (such as antifungals, antibiotics and antituberculosis medicines were most frequently implicated in hospital acquired ADRs. ADRs in HIV-infected patients were less likely to be preventable. To describe the frequency, nature and preventability of community-acquired and hospital-acquired adverse drug reactions (ADRs) in a South African hospital serving a community with a high prevalence of human immunodeficiency virus (HIV)/ acquired immunodeficiency syndrome. A 3-month prospective observational study of 665 adults admitted to two medical wards. Forty-one (6.3%) patients were admitted as a result of an ADR and 41 (6.3%) developed an ADR in hospital. Many of the ADRs (46.2%) were considered preventable, although less likely to be preventable in HIV-infected patients than in those with negative or unknown HIV status (community-acquired ADRs 2/24 vs. 35/42; P < 0.0001; hospital-acquired ADRs 3/25 vs. 14/26; P = 0.003). Patients admitted with ADRs were older than patients not admitted with an ADR (median 53 vs. 42 years, P = 0.003), but 60% of community-acquired ADRs at hospital admission were in patients <60 years old. Among patients <60 years old, those HIV infected were more likely to be admitted with an ADR [odds ratio (OR) 2.32, 95% confidence interval (CI) 1.17, 4.61; P = 0.017]. Among HIV-infected patients, those receiving antiretroviral therapy (ART) were more likely to be admitted with an ADR than those not receiving ART (OR 10.34, 95% CI 4.50, 23.77; P < 0.0001). No ART-related ADRs were fatal. Antibiotics and drugs used for opportunistic infections were implicated in two-thirds of hospital-acquired ADRs. ADRs are an important, often preventable cause of hospitalizations and inpatient morbidity in South Africa, particularly among the elderly and HIV-infected. Although ART-related injury contributed to hospital admissions, many HIV-related admissions were among patients not receiving ART, and many ADRs were associated with medicines used for managing opportunistic infections.

Spontaneous reporting of adverse drug reactions (ADRs) is essential for the post-marketing safety evaluation of drugs. Therefore, good monitoring of ADRs is vital for strengthening drug supervision, management, and guiding rational drug use. Chinese medical institutions are the primary source of ADR case reports, but the proportion of the reports in grade IIIA hospitals is still low due to serious under-reporting. The 3rd Affiliated Hospital of Chengdu Medical College, Chengdu Pidu District People's Hospital, also has such a problem. To improve the quantity and quality of ADR reports and enhance the level of pharmacovigilance in hospitals, the Third Affiliated Hospital of Chengdu Medical College, People's Hospital of Chengdu Pidu District experienced 10years to gradually establish a management model to improve the medical staff's reporting rate of spontaneous reporting of ADRs. The management model is led by clinical pharmacists and combines the PDCA with Teach-back methods. The purpose of this paper is to introduce the management model and discuss its advantages and shortcomings of this model. This study was conducted at the Third Affiliated Hospital of Chengdu Medical College-Chengdu Pidu District People's Hospital. From 2016, the daily management of reporting, auditing, and data improvement of adverse drug reactions in the hospital was carried out by clinical pharmacists, who used the PDCA method combined with the Teach-back method to continuously improve the reporting program of ADRs in the hospital during 2016-2021. Then, the proportion of spontaneous reports of total, new, and serious ADRs was compared before and after the intervention. Also, we performed a time series analysis using an autoregressive moving average model to assess changes in the total number of spontaneous ADR reports before the intervention (2013-2015), the first intervention (2016-2018), and the second intervention (2019-2021). After the combined PDCA and Teach-back method intervention, the median number of reported ADRs per year increased from 50 (range 37-55) in the pre-intervention period to 88 (range 83-162) in the first intervention period and to 374 in the second (range 312-566). Breakpoint regression analysis of the spontaneous reporting rate of ADRs showed that the instantaneous increase after the first intervention was not statistically significant (P = 0.526). However, the reporting rate of ADRs increased at a month-by-month growth rate during the second intervention compared to the first intervention. Its spontaneous reporting rate improved 1.034 times (P = 0.002). After the second intervention, the spontaneous reporting rate of ADRs transiently increased 6.111-fold (P < 0.001), and the month-to-month growth rate increased 1.024-fold (P < 0.001) again. The management model that combines the PDCA and the Teach-back method significantly improves the reporting rate of adverse drug reactions.

Objective.—To estimate the incidence of serious and fatal adverse drug reactions (ADR) in hospital patients.Data Sources.—Four electronic databases were searched from 1966 to 1996.Study Selection.—Of 153, we selected 39 prospective studies from US hospitals.Data Extraction.—Data extracted independently by 2 investigators were analyzed by a random-effects model. To obtain the overall incidence of ADRs in hospitalized patients, we combined the incidence of ADRs occurring while in the hospital plus the incidence of ADRs causing admission to hospital. We excluded errors in drug administration, noncompliance, overdose, drug abuse, therapeutic failures, and possible ADRs. Serious ADRs were defined as those that required hospitalization, were permanently disabling, or resulted in death.Data Synthesis.—The overall incidence of serious ADRs was 6.7% (95% confidence interval [CI], 5.2%-8.2%) and of fatal ADRs was 0.32% (95% CI, 0.23%-0.41%) of hospitalized patients. We estimated that in 1994 overall 2216000 (1721000-2711000) hospitalized patients had serious ADRs and 106000 (76000-137000) had fatal ADRs, making these reactions between the fourth and sixth leading cause of death.Conclusions.—The incidence of serious and fatal ADRs in US hospitals was found to be extremely high. While our results must be viewed with circumspection because of heterogeneity among studies and small biases in the samples, these data nevertheless suggest that ADRs represent an important clinical issue.

Previous studies are limited in sample size and number of sites for the detection and characterization of adverse drug reactions (ADRs) in ambulatory care and hospital settings. To determine the prevalence and distribution of suspected ADRs according to demographic characteristics and drug classes for ambulatory care and hospitalized patients. A cross-sectional evaluation of administrative data from 2002-2005, containing a maximum of 20 million Medicare and commercially insured patients in a year, was completed. Individuals with one or more claims suggesting an ADR were identified, using International Classification of Diseases, 9th Revision, Clinical Modification (ICD-9-CM) criteria referred to as a "suspected ADR." Frequency of ICD-9-CM codes consistent with suspected ADRs for the 4 years was calculated for hospital and ambulatory care settings, based on age ranges, comorbidities, and drug classes. Between 2002 and 2005, the average annual prevalence of suspected ADRs was 0.5%, with a total of 249,633 suspected ADRs during the 4 years. The mean age of hospitalized patients experiencing a suspected ADR was 12 years older than that of ambulatory care patients and 20 years older than that of the general database population. Diseases of the circulatory and endocrine/nutritional/metabolic systems rank among the top 5 comorbid conditions in hospitalized patients who had a suspected ADR. Injury and poisoning was the primary comorbidity in ambulatory patients. High-risk medications frequently associated with suspected ADRs in both settings were antineoplastic and anticoagulant agents. Other drug classes commonly associated with suspected ADRs in hospitalized patients were antihypertensives and diuretics. For the ambulatory care setting, drug classes frequently associated with suspected ADRs were antirheumatic and antiarteriosclerotic agents. ADR detection, using administrative data, revealed differences in age, comorbidities, and drug classifications between ambulatory care and hospital settings. The results can be used to develop focused prevention strategies and targeted surveillance for individuals most at risk for developing ADRs.

To implement and measure the effects of automatic computerized laboratory signals (ALS) as a detection support tool of adverse drug reactions (ADRs) in hospital. This was a prospective observational study of a total of 192 patients (199 sequential medical admissions) during a 2-month period in a 34-bed medical ward at the Hadassah University Hospital, Jerusalem, Israel. The study involved the routine (daily) distribution to staff physicians of lists of automatic signals generated from computerized laboratory data as potential indicators of ADRs. Patient charts were reviewed by the clinical pharmacology team for ADRs and to see whether these were recognized by the staff physicians. Seventy-one ADRs were detected in 64 of the 199 (32%) admissions. Twenty-seven per cent of the ADRs were serious, 9% of the admissions were due to ADRs. Two hundred and ninety-five ALS were generated involving 69% of the admissions. Sixty-one per cent of the ADRs were identified by ALS. ALS were present in 58% of the ADR negative admissions. Eighty-five per cent of the ADRs were recognized as such and 19% of the ALS-positive ADRs were not recognized by the staff physicians. The routine implementation of ALS doubled the number of ADRs recognized by the physicians while patients were hospitalized in the medical ward. The use of the system appeared valid, simple and potentially cost-effective.

To estimate the incidence of serious and fatal adverse drug reactions (ADR) in hospital patients. Four electronic databases were searched from 1966 to 1996. Of 153, we selected 39 prospective studies from US hospitals. Data extracted independently by 2 investigators were analyzed by a random-effects model. To obtain the overall incidence of ADRs in hospitalized patients, we combined the incidence of ADRs occurring while in the hospital plus the incidence of ADRs causing admission to hospital. We excluded errors in drug administration, noncompliance, overdose, drug abuse, therapeutic failures, and possible ADRs. Serious ADRs were defined as those that required hospitalization, were permanently disabling, or resulted in death. The overall incidence of serious ADRs was 6.7% (95% confidence interval [CI], 5.2%-8.2%) and of fatal ADRs was 0.32% (95% CI, 0.23%-0.41%) of hospitalized patients. We estimated that in 1994 overall 2216000 (1721000-2711000) hospitalized patients had serious ADRs and 106000 (76000-137000) had fatal ADRs, making these reactions between the fourth and sixth leading cause of death. The incidence of serious and fatal ADRs in US hospitals was found to be extremely high. While our results must be viewed with circumspection because of heterogeneity among studies and small biases in the samples, these data nevertheless suggest that ADRs represent an important clinical issue.

There is evidence that different methods used to identify and quantify adverse drug reactions (ADR) in hospitals are not exhaustive (spontaneous reporting or computerized medical databases). The combination of these different sources of data could improve knowledge about ADR frequency in hospitals. The aim of this study was to estimate the incidence of serious ADRs handled in medical wards of a French university hospital using data from the Programme de Medicalization des Systemes d'Information (PMSI) and spontaneous reports recorded in the French Pharmacovigilance Database. The study period was the first semester of 2001. From PMSI, all hospitalization summaries including an ICD-10th code related to a potential ADR were selected. From the French Pharmacovigilance Database, all serious ADRs which occurred during the study period and were reported by physicians working in the University Hospital were collected. After identification of common cases, the capture-recapture method was applied in order to estimate the real number of ADRs occurring during the first semester of 2001. From PMSI, we identified 274 different hospital stays related to an ADR. Out of 241 reports selected from the French Pharmacovigilance Database, we retained 151 ADRs for analysis. Fifty-two ADRs were common in the two databases, giving an estimated number of serious ADRs of 796 [95% confidence interval (CI) 638, 954], corresponding to 2.9% of inpatients (95% CI 2.3, 3.5). This study shows the lack of exhaustiveness of ADR reporting whatever the sources of data and underlines the interest of merging data from different databases to identify fully the real impact of ADR in hospitals.

Incidence and costs of adverse drug reactions during hospitalisation: computerised monitoring versus stimulated spontaneous reporting.

The aim of this study was to assess an automated detection method of serious adverse reactions induced by oral targeted therapy (OTT) in patients with cancer, performed in the French Diagnosis Related Groups (DRG) database. Patients with cancer of the Poitiers hospital who started an OTT between 2014 and 2015 were included. This study focused on adverse drug reaction which required inpatient hospitalization (ADRh ). All diagnoses coded in the DRG database for hospital stays that occurred within 3 months after OTT initiation were collected (potential ADRh ). Filters (exclusion criteria) were automatically applied on potential ADRh to exclude diagnoses that were not adverse drug reactions (false positives). A pharmacovigilance review was carried out to identify ADRh in the medical records (reported ADRh ). The sensitivity and specificity of the detection method were estimated for each filter combinations by comparison between potential and reported ADRh . This study included 129 patients. The medical records review led to identify 19 ADRh (all coded in the DRG database) in 14 patients. To maintain a 100% sensitivity of the method detection, the best specificity obtained was 58.3% (95% IC: [55.2-61.4]).The use of restrictive filters ('drug' in the diagnostic label, specific diagnosis code for adverse cancer drug reaction) resulted in a 97.8% specificity (95% IC: [96.6-98.5]) with a 38.2% sensitivity (95% IC: [23.9-55.0]). Our method has detected the third of ADRh with an excellent specificity. Complementary experimentations in pharmacovigilance centers are necessary to evaluate the interest of this tool in routine in addition to spontaneous reporting.

The Protecting Canadians from Unsafe Drugs Act will eventually require institutions to report all serious adverse drug reactions (ADRs), although the proposed regulations do not yet define what will need to be reported and by whom. Knowledge about the occurrence of serious ADRs in the hospital setting is needed to optimize the effectiveness of reporting and to determine the potential implications of mandatory reporting. To quantify and characterize suspected serious ADRs in patients admitted to a general medicine service, to assess the likelihood of causality, and to determine inter-rater agreement for identification of ADRs and assessment of their likelihood. This prospective observational study involved 60 consecutive patients admitted to a general medicine service at a tertiary care teaching centre starting on March 28, 2016. The primary outcome was the number of serious ADRs, defined by Health Canada as ADRs that result in hospital admission, congenital malformation, persistent or significant disability or incapacity, or death; that are life-threatening; or that require significant intervention to prevent one of these outcomes. Medical records were reviewed independently by pairs of pharmacists for serious ADRs, and the likelihood of causality was assessed using the World Health Organization-Uppsala Monitoring Centre system. Inter-rater agreement was calculated using the kappa score, and disagreements were resolved by discussion and consensus. Twenty-three serious ADRs occurred in the sample of 60 patients. The proportion of patients experiencing a serious ADR that contributed to the original hospital admission was 19/60 (32%, 95% confidence interval [CI] 20%-43%), and 4 patients (7%, 95% CI 0%-13%) experienced a serious ADR during their hospital stay. Inter-rater agreement for occurrence of serious ADRs was moderate (kappa 0.58, 95% CI 0.35-0.76). Reportable serious ADRs were common among patients admitted to a general medicine service. Canadian hospitals would face difficulties reporting all serious ADRs because of the frequency of their occurrence and the subjectivity of their identification.