Intranasal corticosteroid users in The Netherlands: A drug utilization study.

Background: To improve (patient-tailored) instructions for intranasal corticosteroid (INC) administration, we need to gain insight into specific characteristics of INC users and comedication use. Objective: We examined INC prescriptions obtained from the Dutch InterAction Database to gain insight into the prevalence and incidence rates, INC use in previous years, and comedication. Methods: We retrospectively examined INC prescriptions written between January 1, 2015, and December 31, 2019. Prevalence and incidence rates were stratified by age and sex. The use of INCs in previous years and comedication were analyzed. Results: In 2019, a total of 172,563 INC prescriptions were written and dispensed to 75,048 individuals. Also in 2019, the prevalence and incidence of INC users were 68.9 and 25.6 per 1000 individuals, respectively. INCs were used by all age groups. More than half of INC users in 2019 did not receive a prescription in 2018, almost a quarter received a prescription in 5 consecutive years, 28% used an INC in combination with an inhaler, 29% used an INC together with a systemic antihistamine, 9% used an INC along with ocular medication, and 1% used an INC with an intranasal antihistamine. Several corticosteroid-containing drugs were being used in combination with INCs by 2% to 16% of those studied. Conclusion: This study gives insights into opportunities for patient-tailored instructions. INCs are used by various age groups and by new or intermittent users as well as by continuous users. On the bases of these results, patient-tailored instructions can be developed and subsequently studied to determine whether the instructions affect treatment adherence and efficacy. The insights gained about comedication provide opportunities for improved evaluation of the INC administration technique. Taken together, these suggestions might lead to a more patient-tailored approach, which might in turn lead to improved treatment with INCs.

Dynamics of HIV PrEP use and coverage during and after COVID-19 in Germany.

BACKGROUND: Pre-exposure prophylaxis (PrEP) with oral emtricitabine/tenofovir disoproxil (FTC/TDF) proved highly efficient in preventing HIV. Since 09/2019, FTC/TDF-PrEP is covered by health insurances in Germany, if prescribed by licensed specialists. However, methods to longitudinally monitor progress in PrEP implementation in Germany are lacking. METHODS: Utilizing anonymous FTC/TDF prescription data from 2017-2021, we developed a mathematical model to disentangle HIV-treatment from PrEP prescriptions, as well as to translate PrEP prescriptions into number of PrEP users. We used the model to estimate past- and future PrEP uptake dynamics, to predict coverage of PrEP needs and to quantify the impact of COVID-19 on PrEP uptake on a national and regional level. RESULTS: We identified significant (p<0.01) decelerating effects of the first- and second COVID-19-lockdown on PrEP uptake in 04/2020 and 12/2020. We estimated 26,159 (CI: 25,751-26,571) PrEP users by 12/2021, corresponding to 33% PrEP coverage of people in need. We projected 64,794 (CI: 62,956-66,557) PrEP users by 12/2030, corresponding to 81% PrEP coverage. We identified profound regional differences, with high PrEP coverage and uptake in metropoles and low coverage in more rural regions. CONCLUSIONS: Our approach presents a comprehensive solution to monitor and forecast PrEP implementation from anonymous data and highlighted that the COVID-19 pandemic significantly decelerated PrEP uptake in Germany. Moreover, slow PrEP uptake in rural areas indicate that structural barriers in PrEP care, education or information exist that may hamper the goal of ending the AIDS epidemic by 2030.

Antibiotic use in pediatric acute care hospitals: an analysis of antibiotic consumption data from Germany, 2013-2020.

BACKGROUND: Antimicrobial stewardship (AMS) programs are effective tools for improving antibiotic prescription quality. Their implementation requires the regular surveillance of antibiotic consumption at the patient and institutional level. Our study captured and analyzed antibiotic consumption density (ACD) for hospitalized pediatric patients. METHOD: We collected antibacterial drug consumption data for 2020 from hospital pharmacies at 113 pediatric departments of acute care hospitals in Germany. ACD was calculated as defined daily dose (DDD, WHO/ATC Index 2019) per 100 patient days (pd). In addition, we analyzed the trends in antibiotic use during 2013-2020. RESULTS: In 2020, median ACD across all participating hospitals was 26.7 DDD/100 pd, (range: 10.1-79.2 DDD/100 pd). It was higher at university vs. non-university hospitals (38.6 vs. 25.2 DDD/100 pd, p < 0.0001). The highest use densities were seen on oncology wards and intensive care units at university hospitals (67.3 vs. 38.4 DDD/100 pd). During 2013-2020, overall ACD declined (- 10%) and cephalosporin prescriptions also decreased (- 36%). In 2020, cephalosporins nevertheless remained the most commonly dispensed class of antibiotics. Interhospital variability in cephalosporin/penicillin ratio was substantial. Antibiotics belonging to WHO AWaRe "Watch" and "Reserve" categories, including broad-spectrum penicillins (+ 31%), linezolid (+ 121%), and glycopeptides (+ 43%), increased over time. CONCLUSION: Significant heterogeneity in ACD and prescription of different antibiotic classes as well as high prescription rates for cephalosporins and an increased use of reserve antibiotics indicate improvable antibiotic prescribing quality. AMS programs should urgently prioritize these issues to reduce antimicrobial resistance.

The relationship between palliative radiotherapy and opioid prescribing patterns among patients with metastatic cancer.

BACKGROUND: While randomized trials have established that palliative radiotherapy, especially to bone, can improve qualitative measures of pain, its quantitative relationship to opioid prescribing patterns has remained underexplored. We aimed to identify the association of palliative radiotherapy on opioid prescriptions received among patients with metastatic cancer. METHODS: The Virginia Commonwealth University Institutional Review Board approved retrospective analysis extracted prescription data from all adult patients with metastatic cancer who underwent outpatient palliative external beam radiation therapy at Virginia Commonwealth University Health System from 2008-2018. Institutional prescribing data were used to calculate the average opioid oral morphine milligram equivalent (MME) dose 30, 60 and 90 days both before and after radiotherapy. Univariate and bivariate ordinary least squares (OLS) regression models were used to estimate the relationship of MME changes with clinical, radiation-related, and demographic patient factors. RESULTS: A total of 182 patients met inclusion criteria. Overall, patients required higher opioid doses after radiotherapy, with mean MME 30, 60, and 90 days prior to radiotherapy of 24.6, 20.2, and 16.8 mg, respectively; which increased to 62.9, 77.7 and 82.4 mg post-radiation therapy (P<0.01). Multivariate OLS models predicting the change of MME 60 days pre- and post-radiation treatment showed that younger age and comorbid depression predicted increased MME after radiotherapy. CONCLUSIONS: Patients with metastatic cancer face a relatively high opioid burden, which increases over time, even among those who receive palliative radiation therapy. Patients who are younger and have comorbid depression may have a higher risk of increased opioid burden after radiotherapy.

Outpatient fluoroquinolone use in relation to European Medicines Agency's recommendation: An Estonian nationwide drug utilization study.

PURPOSE: To determine possible changes in prescribing of fluoroquinolones in relation to the European Medicines Agency's (EMA) recommendation in October 2018. METHODS: We conducted a nationwide time-series study on outpatient use of fluoroquinolones during January 2016-June 2021 in Estonia. Joinpoint regression was used to identify change points over time. Several subgroup analyses by prescriber specialty, indication group, risk factors for tendon injury, aortic aneurysm/dissection or heart valve regurgitation/incompetence and the prescribing of other antibiotics were performed. RESULTS: During the study period 236 989 prescriptions of fluoroquinolones were dispensed to 142 659 persons. The number of episodes per month declined from 3780 (2.9/1000 inhabitants) to 2570 (1.9/1000 inhabitants). We identified three change points with four different trend segments: from January 2016 to November 2018 monthly percent change (MPC) -0.4%, from November 2018 to June 2019 MPC -2.5%, from June 2019 to July 2020 MPC 1.7% and from July 2020 to June 2021 MPC -3.3%. Prescribing for indications which were removed or restricted by EMA's recommendation comprised a small proportion of all fluoroquinolone episodes -2.8% and 6.3%, respectively. The risk factors for tendon injury and for cardiac disorders (aortic aneurysm/dissection or heart valve regurgitation/incompetence) were present in 46.4% and 57.8% episodes of fluoroquinolone users, respectively. No changes in the trend of prescribing to users with risk factors was detected. CONCLUSIONS: The EMA's recommendation may have contributed to the greater decline in the use of fluoroquinolones. However, there is still a high proportion of users with predisposing factors for tendon injury and serious cardiac disorders.

Identifying High-Risk Comorbidities Associated with Opioid Use Patterns Using Electronic Health Record Prescription Data.

Introduction: Opioid use disorders (OUDs) constitute a major public health issue, and we urgently need alternative methods for characterizing risk for OUD. Electronic health records (EHRs) are useful tools for understanding complex medical phenotypes but have been underutilized for OUD because of challenges related to underdiagnosis, binary diagnostic frameworks, and minimally characterized reference groups. As a first step in addressing these challenges, a new paradigm is warranted that characterizes risk for opioid prescription misuse on a continuous scale of severity, i.e., as a continuum. Methods: Across sites within the PsycheMERGE network, we extracted prescription opioid data and diagnoses that co-occur with OUD (including psychiatric and substance use disorders, pain-related diagnoses, HIV, and hepatitis C) for over 2.6 million patients across three health registries (Vanderbilt University Medical Center, Mass General Brigham, Geisinger) between 2005 and 2018. We defined three groups based on levels of opioid exposure: no prescriptions, minimal exposure, and chronic exposure and then compared the comorbidity profiles of these groups to the full registries and to those with OUD diagnostic codes. Results: Our results confirm that EHR data reflects known higher prevalence of substance use disorders, psychiatric disorders, medical, and pain diagnoses in patients with OUD diagnoses and chronic opioid use. Comorbidity profiles that distinguish opioid exposure are strikingly consistent across large health systems, indicating the phenotypes described in this new quantitative framework are robust to health systems differences. Conclusion: This work indicates that EHR prescription opioid data can serve as a platform to characterize complex risk markers for OUD using existing data.

PrAna: an R package to calculate and visualize England NHS primary care prescribing data.

BACKGROUND: The objective of this work to calculate prescribed quantity of an active pharmaceutical ingredient (API) in prescription medications for human use, to facilitate research on the prediction of amount of API released to the environment and create an open-data tool to facilitate spatiotemporal and long-term prescription trends for wider usage. DESIGN: We have developed an R package, PrAna to calculate the prescribed quantity (in kg) of an APIs by postcode using England's national level prescription data provided by National Health Service, for the years 2015-2018. Datasets generated using PrAna can be visualized in a real-time interactive web-based tool, PrAnaViz to explore spatiotemporal and long-term trends. The visualisations can be customised by selecting month, year, API, and region. RESULTS: PrAnaViz's targeted API approach is demonstrated with the visualisation of prescribed quantities of 14 APIs in the Bath and North East Somerset (BANES) region during 2018. Once the APIs list is loaded, the back end retrieves relevant data and populates the graphs based on user-defined data features in real-time. These plots include the prescribed quantity of APIs over a year, by month, and individual API by month, general practice, postcode, and medicinal form. The non-targeted API approach is demonstrated with the visualisation of clarithromycin prescribed quantities at different postcodes in the BANES region. CONCLUSION: PrAna and PrAnaViz enables the analysis of spatio-temporal and long-term trends with prescribed quantities of different APIs by postcode. This can be used as a support tool for policymakers, academics and researchers in public healthcare, and environmental scientist to monitor different group of pharmaceuticals emitted to the environment and for prospective risk assessment of pharmaceuticals in the environment.

Claims-based measures of prescription opioid utilization: A practical guide for researchers.

BACKGROUND: Given the increased attention to the opioid epidemic and the role of inappropriate prescribing, there has been a marked increase in the number of studies using claims data to study opioid use and policies designed to curb misuse. Our objective is to review the medical literature for recent studies that use claims data to construct opioid use measures and to develop a guide for researchers using these measures. METHODS: We searched for articles relating to opioid use measured in health insurance claims data using a defined set of search terms for the years 2014-2020. Original research articles based in the United States that used claims-based measures of opioid utilization were included and information on the study population and measures of any opioid use, quantity of opioid use, new opioid use, chronic opioid use, multiple providers, and overlapping prescriptions was abstracted. RESULTS: A total of 164 articles met inclusion criteria. Any opioid use was the most commonly included measure, defined by 85 studies. This was followed by quantity of opioids (68 studies), chronic opioid use (53 studies), overlapping prescriptions (28 studies), and multiple providers (8 studies). Each measure contained multiple, distinct definitions with considerable variation in how each was operationalized. CONCLUSIONS: Claims-based opioid utilization measures are commonly used in research, but definitions vary significantly from study to study. Researchers should carefully consider which opioid utilization measures and definitions are most appropriate for their study and recognize how different definitions may influence study results.

Assessing polypharmacy in the older population: Comparison of a self-reported and prescription based method.

PURPOSE: To explore differences in the prevalence and determinants of polypharmacy in the older general population in Belgium between self-reported and prescription based estimates and assess the relative merits of each data source. METHODS: Data were used from participants aged ≥65 years of the Belgian national health survey 2013 (n = 1950). Detailed information was asked on the use of medicines in the past 24 h and linked with prescription data from the Belgian compulsory health insurance (BCHI). Agreement between polypharmacy (use or prescription ≥5 medicines) and excessive polypharmacy (≥10 medicines) between both sources was assessed with kappa statistics. Multinomial logistic regression was used to study determinants of moderate (5-9 medicines) and excessive polypharmacy (≥10 medicines) and over- and underestimation of prescription based compared to self-reported polypharmacy. RESULTS: Self-reported and prescription based polypharmacy prevalence estimates were respectively 27% and 32%. Overall agreement was moderate, but better in men (kappa 0.60) than in women (0.45). Determinants of moderate polypharmacy did not vary substantially by source of outcome indicator, but restrictions in activities of daily living (ADL), living in an institution and a history of a hospital admission was associated with self-reported based excessive polypharmacy only. CONCLUSIONS: Surveys and prescription data measure polypharmacy from a different perspective, but overall conclusions in terms of prevalence and determinants of polypharmacy do not differ substantially by data source. Linking survey data with prescription data can combine the strengths of both data sources resulting in a better tool to explore polypharmacy at population level.

Using Prescription and Wastewater Data to Estimate the Correction Factors of Atenolol, Carbamazepine, and Naproxen for Wastewater-Based Epidemiology Applications.

The correction factor (CF) is a critical parameter in wastewater-based epidemiology (WBE) that significantly influences the accuracy of the final consumption estimates. However, most CFs have been derived from a few old pharmacokinetic studies and should be re-evaluated and refined to improve the accuracy of the WBE approach. This study aimed to review and estimate the CFs for atenolol, carbamazepine, and naproxen for WBE using the daily mass loads of those pharmaceuticals in wastewater and their corresponding dispensed prescription data in Australia. Influent wastewater samples were collected from wastewater treatment plants serving approximately 24% of the Australian population and annual national dispensed prescription data. The estimated CFs for atenolol and carbamazepine are 1.37 (95% CI: 1.17-1.66) and 8.69 (95% CI: 7.66-10.03), respectively. Due to significant over-the-counter sales of naproxen, a reliable CF could not be estimated based on prescription statistics. Using an independent dataset of 186 and 149 wastewater samples collected in an urban catchment in 2011 and 2012, WBE results calculated using the new CFs matched well with the dispensed data for atenolol and carbamazepine in the catchment area.

Showcasing the potential of wastewater-based epidemiology to track pharmaceuticals consumption in cities: Comparison against prescription data collected at fine spatial resolution.

While the extent of pharmaceutical consumption within a society/community is of high relevance to its health, economy and general wellbeing, this data is often not readily available. Herein, we strengthen a wastewater-based epidemiology (WBE) approach as a way to track the consumption of pharmaceuticals within the sampled community. This method is less laborious than established questionnaire or databases approaches and allows a higher temporal and spatial resolution. The WBE approach was conducted by sampling influent wastewater from two wastewater treatment plants of different size. A total of 39 targeted compounds were quantified by liquid chromatography coupled with tandem mass spectrometry. The number of prescriptions and the defined daily doses for each prescription was obtained from the reference database of The Catalan Health System to validate the wastewater-based approach. The wastewater sampling and the data inquiry were both executed during the same period (October 2019) and standardised for comparison to treatments per 1,000 inhabitants per day. The back-calculation parameters were improved from previous studies by including the faecal excretion rate of the pharmaceuticals. For prescription only pharmaceuticals, where prescription numbers are expected to be a good estimate of consumption, our WBE approach agreed with 27 out of 32 (<0.7 order of magnitude). Common over-the-counter pharmaceuticals such as acetaminophen, ibuprofen and naproxen showed much higher values for treatments per day per 1,000 inhabitant in wastewater than prescribed, reflecting the usefulness of WBE in obtaining an estimate of the total consumption i.e. with and without a prescription.

The fentanyl phase of the opioid epidemic in Cuyahoga County, Ohio, United States.

Since late 2014, fentanyl has become the major driver of opioid mortality in the United States. However, a descriptive analysis of fentanyl victims is limited. We studied the 2016 fentanyl and heroin overdose deaths and compared them to previously studied heroin-associated fatalities from 2012 over a wide range of demographic and investigative variables, including overdose scene findings, toxicology results, and prescription drug history. We observed a significant increase in fentanyl-related deaths (n = 421, 2016) versus heroin deaths (n = 160, 2012) but the baseline demographics between both cohorts remained similar. Victims were predominantly of ages 35-64 years (60%-64%), White (83%-85%), and male (73%-76%). 2016 fentanyl decedents were more likely to have naloxone administered upon overdose, and the majority still had a positive prescription history for a controlled substance. Toxicology data showed a decrease in mean morphine and 6-monoacetylmorphine concentrations when cointoxication with fentanyl occurred. Our study emphasizes the medical examiner's role as a public health data source and bridge between different stakeholders combating the opioid epidemic.

Detecting potential signals of adverse drug events from prescription data.

Adverse drug events (ADEs) may occur and lead to severe consequences for the public, even though clinical trials are conducted in the stage of pre-market. Computational methods are still needed to fulfil the task of pharmacosurveillance. In post-market surveillance, the spontaneous reporting system (SRS) has been widely used to detect suspicious associations between medicines and ADEs. However, the passive mechanism of SRS leads to the hysteresis in ADE detection by SRS based methods, not mentioning the acknowledged problem of under-reporting and duplicate reporting in SRS. Therefore, there is a growing demand for other complementary methods utilising different types of healthcare data to assist with global pharmacosurveillance. Among those data sources, prescription data is of proved usefulness for pharmacosurveillance. However, few works have used prescription data for signalling ADEs. In this paper, we propose a data-driven method to discover medicines that are responsible for a given ADE purely from prescription data. Our method uses a logistic regression model to evaluate the associations between up to hundreds of suspected medicines and an ADE spontaneously and selects the medicines possessing the most significant associations via Lasso regularisation. To prepare data for training the logistic regression model, we adapt the design of the case-crossover study to construct case time and control time windows for the extraction of medicine use information. While the case time window can be readily determined, we propose several criteria to select the suitable control time windows providing the maximum power of comparisons. In order to address confounding situations, we have considered diverse factors in medicine utilisation in terms of the temporal effect of medicine and the frequency of prescription, as well as the individual effect of patients on the occurrence of an ADE. To assess the performance of the proposed method, we conducted a case study with a real-world prescription dataset. Validated by the existing domain knowledge, our method successfully traced a wide range of medicines that are potentially responsible for the ADE. Further experiments were also carried out according to a recognised gold standard, our method achieved a sensitivity of 65.9% and specificity of 96.2%.

Antihypertensive prescription patterns and cardiovascular risk in patients with newly diagnosed hypertension- an analysis of statutory health insurance data in Germany.

PURPOSE: Hypertension is the most important risk factor for disease and premature death. Treatment strategies adjusted for cardiovascular risk have been proposed in guidelines, but real-life treatment strategies for patients with newly diagnosed hypertension in Germany are largely unknown. The aim of the study was to analyse initial drug treatment strategies and associated risk status in patients with newly diagnosed hypertension. MATERIAL AND METHODS: In the representative research database of the public health insurance system in Germany (2077899 individuals) we identified patients with newly diagnosed hypertension in 2012 and analysed co-existing cardiovascular co-morbidities and hypertension-mediated organ damage by ICD-codes as qualifiers for high risk. Health insurance billing datasets for redeemed prescriptions were analysed at several time points using ATC-codes. RESULTS: The incidence of hypertension was 2.6%, 33.6% of the patients were at high risk at diagnosis, mainly due to cardiovascular co-morbidities. Most patients initially received monotherapy (55.4%), of which ACE inhibitors (43.8%) or beta-blockers (32.4%) were the leading drug classes, while 21.7% of patients received no drug therapy during the first year. The treatment strategies of low and high-risk patients resembled each other - high-risk patients also received mostly monotherapy during the first year after diagnosis (53.4%), while 13.7% remained without drug therapy. Combination therapy was the most frequent treatment strategy one year after hypertension diagnosis (40.6%) and in the long term (68.4%). CONCLUSION: Initial treatment strategies may not always be stratified according to cardiovascular risk. The majority of patients with hypertension receives initial monotherapy independent of their individual risk. However, combination therapy represents the major form of therapy in the long-term.

Unmasking the Actual COVID-19 Case Count.

This report presents a novel approach to estimate the total number of COVID-19 cases in the United States, including undocumented infections, by combining the Centers for Disease Control and Prevention's influenza-like illness surveillance data with aggregated prescription data. We estimated that the cumulative number of COVID-19 cases in the United States by 4 April 2020 was > 2.5 million.

Valproic acid prescription trends among females of childbearing age in Estonia: A 14-year nationwide prescription database study.

PURPOSE: Valproic acid (VPA) is a widely used anticonvulsant that is effective against most seizure types. Due to its teratogenic effects, its use should be avoided among females of childbearing age, unless other treatments are ineffective or not tolerated. This study aimed to determine the prevalence of VPA use in 2005-2018 in Estonia, with special attention to females of childbearing age. METHODS: In this retrospective nationwide population-based cohort study, outpatient prescription data from the national health insurance provider were used. Annual sex- and age-specific prevalence rates were calculated, and changes therein during the study period were evaluated. RESULTS: The annual rates of VPA use among females of childbearing age increased significantly in 2005-2014. After 2014, the increasing trend stopped; in 2014-2018, the prevalence rates declined slightly [prevalence rate ratio (PRR), 0.94; P = 0.136]. In males of the same age, the increasing trend continued (PRR, 1.08: P = 0.028). Among neurologists, the rate of VPA prescription to females aged <15 and 15-44 years decreased during 2014-2018 (PRR, 0.74; P < 0.001 and PRR 0.72; P < 0.001, respectively); no change in prescription frequency was seen among psychiatrists during this period. CONCLUSIONS: The increasing trend in VPA usage among females of childbearing age in Estonia stopped after 2014, when the European Medicines Agency's strengthened restrictions on VPA use in females were communicated extensively in Estonia. The level of awareness of VPA's harmful effects during pregnancy is lower in the psychiatric community.

Adherence to long-term therapies in cystic fibrosis: a French cross-sectional study linking prescribing, dispensing, and hospitalization data.

BACKGROUND: Cystic fibrosis (CF) is a life-shortening genetic condition that usually affects several organs and involves significant treatment burden. Adherence to medication is important for successful CF management. OBJECTIVE: To describe medication adherence according to age, therapeutic class, and pharmaceutical form in adults and children followed in four regional CF centers in France. METHODS: We conducted a cross-sectional study with non-transplanted patients followed in two adult and two pediatric centers during 2015 who were covered by the French National Health Insurance (NHI). Sociodemographic, clinical, hospitalization, and prescription data were collected from patient medical records. Medication dispensations were extracted from the regional French NHI database. Adherence was calculated over 12 months using continuous medication availability (CMA) accounting for dose adjustments and hospitalizations. Drug-specific CMA was computed in R with the AdhereR package for each medication prescribed more than 3 months, which was averaged to obtain a composite CMA score (cCMA) for all treatments and per therapeutic class as well as pharmaceutical form for each patient. RESULTS: A total of 228 patients were included. The number of chronic medications increased with age (r=0.50, p<0.001): a median of 7 medications per patient were prescribed. The mean±SD cCMA was significantly different between age groups (p=0.0098): it was 0.71±0.20 for the 0-5 years age group, 0.73±0.16 for 6-11 years, 0.64±0.17 for 12-17 years, 0.57±0.23 for 18-25 years, and 0.65±0.20 for the over 25 years age group. cCMA varied significantly according to pharmaceutical forms: the mean±SD cCMA was 0.70±0.21 for oral medications and 0.54±0.28 for inhaled medications (p<0.001). CONCLUSION: This study suggests that adherence to medication regimens in CF patients remains suboptimal and varies substantially between age groups and pharmaceutical forms. These variations in adherence should be considered when developing effective strategies to improve adherence.

Antimicrobial prescription data in Danish national database validated against treatment records in organic pig farms and analysed for associations with lesions found at slaughter.

BACKGROUND: Antimicrobial use (AMU) in livestock is a debated topic, mainly due to the risk of associated development of antimicrobial resistance. There is focus on reducing AMU in the Danish pig production, which accounts for the largest proportion of AMU for animals in Denmark. Due to special restriction on AMU in organic pig production, the AMU in organic pig production is lower than in conventional pig production. There is concern that reduced AMU could jeopardize animal health and welfare, if it reflects insufficient treatment of sick animals, which might be reflected by the prevalence and types of lesions found at meat inspection. However, little is known about the associations between AMU and meat inspection findings in pigs from organic farms. Furthermore, excess amount of antimicrobial product after a treatment cannot be re-prescribed in organic pig herds. The initial prescription is recorded in the national database VetStat, but the unused amount is not deducted leading to uncertainty when reporting AMU. The objectives of this study were to 1) describe AMU patterns based on prescription data for organic pig production and compare with those of the conventional pig production for year 2016, 2) study the associations between herd-level AMU prescription data and meat inspection data for organic pig herds and 3) validate herd-level AMU prescription data in VetStat against treatment records collected on-farm in organic Danish pig herds. RESULTS AND CONCLUSIONS: Gastrointestinal indications account for the largest proportion of AMU in both organic pig herds (65 and 54% of treatment doses for weaners and finishers, respectively) and conventional pig herds (80 and 68% of doses for weaners and finishers, respectively). A larger proportion is prescribed for respiratory indications in organic than conventional weaners and arthropathic indications in finishers. No associations between AMU and meat inspection data were found. This needs further investigation as the prevalence of lesions at slaughter was slightly (non-significantly) higher in herds with no registered AMU than with AMU prescriptions. Only 8 out of 31 herds had recorded their AMU sufficiently detailed to compare, and using VetStat as a proxy for AMU led to 9-88% overestimation of the actual use in 7 out of these 8 herds and 120% underestimation in one herd.

Improving the accuracy of medication adherence measures using linked prescription and dispensation data: findings from the ESOSVAL cohort of patients treated with osteoporosis drugs.

Objective: We compare estimates of proportion of days covered (PDC) based on dispensation-only data versus linked prescription and dispensation information, and we analyse their differences in a real-world cohort of patients with osteoporosis.Methods: Prospective cohort study. We compared four alternative measures of PDC, using dispensation-only data: a) with a fixed assessment interval; b) censoring the assessment interval at the moment of the last refill; and using linked prescription and dispensation data: c) considering a minimum prescription gap of three months to interpret interruption by the physician; and d) considering any prescription gap.Results: The mean PDC at 12 months for new users was 63.1% using dispensation-only data and a fixed interval, 86.0% using dispensation-only data and a last-refill interval, 81% using linked dispensation and prescription data and censoring any period without prescription, and 78.3% when using linked prescription and dispensation data and censoring periods of at least 3 months. For experienced users, the figures were 80.0%, 88.9%, 83% and 81%, respectively. Overall, dispensation-based measures presented issues of patient misclassification.Conclusions: Linked prescription and dispensation data allows for more precise PDC estimates than dispensation-only data, as both primary non-adherence and early non-adherence periods, and fully non-adherent patients, are all identified and accounted for.

A systematic review finds inconsistency in the measures used to estimate adherence and persistence to multiple cardiometabolic medications.

OBJECTIVES: We reviewed measures used to estimate adherence and persistence to multiple cardiometabolic medications from prescription data, particularly for blood pressure-lowering, lipid-lowering, and/or glucose-lowering medication, and give guidance on which measures to choose. STUDY DESIGN AND SETTING: A literature search of Medline, Embase, and PsycINFO databases was conducted to identify studies assessing medication adherence and/or persistence for patients using multiple cardiometabolic medications. Two reviewers performed the study selection process independently. RESULTS: From the 54 studies assessing adherence, only 36 (67%) clearly described the measures used. Five measures for adherence were identified, including adherence to "all," to "any," to "both" medication, "average adherence," and "highest/lowest adherence". From the 22 studies assessing persistence, only six (27%) clearly described the measures used. Three measures for persistence were identified, including persistence with "all," with "both," and with "any" medication. Less than half of the studies explicitly considered medication switches when relevant. CONCLUSION: From the identified measures, the "any medication" measure is most suitable for identifying patients in need of an intervention, whereas the "all medication" measure is useful for assessing the effect of interventions. More attention is needed for adequate measurement definitions when reporting on and interpreting adherence or persistence estimates to multiple medications.