Mapping English GP prescribing data: a tool for monitoring health-service inequalities

Interactive Visualization Applications in Population Health and Health Services Research: Systematic Scoping Review

BACKGROUND

Simple visualizations in health research data, such as scatter plots, heat maps, and bar charts, typically present relationships between 2 variables. Interactive visualization methods allow for multiple related facets such as numerous risk factors to be studied simultaneously, leading to data insights through exploring trends and patterns from complex big health care data. The technique presents a powerful tool that can be used in combination with statistical analysis for knowledge discovery, hypothesis generation and testing, and decision support.

OBJECTIVE

The primary objective of this scoping review is to describe and summarize the evidence of interactive visualization applications, methods, and tools being used in population health and health services research (HSR) and their subdomains in the last 15 years, from January 1, 2005, to March 30, 2019. Our secondary objective is to describe the use cases, metrics, frameworks used, settings, target audience, goals, and co-design of applications.

METHODS

We adapted standard scoping review guidelines with a peer-reviewed search strategy: 2 independent researchers at each stage of screening and abstraction, with a third independent researcher to arbitrate conflicts and validate findings. A comprehensive abstraction platform was built to capture the data from diverse bodies of literature, primarily from the computer science and health care sectors. After screening 11,310 articles, we present findings from 56 applications from interrelated areas of population health and HSR, as well as their subdomains such as epidemiologic surveillance, health resource planning, access, and use and costs among diverse clinical and demographic populations.

RESULTS

In this companion review to our earlier systematic synthesis of the literature on visual analytics applications, we present findings in 6 major themes of interactive visualization applications developed for 8 major problem categories. We found a wide application of interactive visualization methods, the major ones being epidemiologic surveillance for infectious disease, resource planning, health service monitoring and quality, and studying medication use patterns. The data sources included mostly secondary administrative and electronic medical record data. In addition, at least two-thirds of the applications involved participatory co-design approaches while introducing a distinct category, embedded research, within co-design initiatives. These applications were in response to an identified need for data-driven insights into knowledge generation and decision support. We further discuss the opportunities stemming from the use of interactive visualization methods in studying global health; inequities, including social determinants of health; and other related areas. We also allude to the challenges in the uptake of these methods.

CONCLUSIONS

Visualization in health has strong historical roots, with an upward trend in the use of these methods in population health and HSR. Such applications are being fast used by academic and health care agencies for knowledge discovery, hypotheses generation, and decision support.

INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID)

RR2-10.2196/14019.

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.

Environmental DNA reveals links between abundance and composition of airborne grass pollen and respiratory health

Grass (Poaceae) pollen is the most important outdoor aeroallergen,¹ exacerbating a range of respiratory conditions, including allergic asthma and rhinitis ("hay fever").^2-5 Understanding the relationships between respiratory diseases and airborne grass pollen with a view to improving forecasting has broad public health and socioeconomic relevance. It is estimated that there are over 400 million people with allergic rhinitis⁶ and over 300 million with asthma, globally,⁷ often comorbidly.⁸ In the UK, allergic asthma has an annual cost of around US$ 2.8 billion (2017).⁹ The relative contributions of the >11,000 (worldwide) grass species (C. Osborne et al., 2011, Botany Conference, abstract) to respiratory health have been unresolved,¹⁰ as grass pollen cannot be readily discriminated using standard microscopy.¹¹ Instead, here we used novel environmental DNA (eDNA) sampling and qPCR^12-15 to measure the relative abundances of airborne pollen from common grass species during two grass pollen seasons (2016 and 2017) across the UK. We quantitatively demonstrate discrete spatiotemporal patterns in airborne grass pollen assemblages. Using a series of generalized additive models (GAMs), we explore the relationship between the incidences of airborne pollen and severe asthma exacerbations (sub-weekly) and prescribing rates of drugs for respiratory allergies (monthly). Our results indicate that a subset of grass species may have disproportionate influence on these population-scale respiratory health responses during peak grass pollen concentrations. The work demonstrates the need for sensitive and detailed biomonitoring of harmful aeroallergens in order to investigate and mitigate their impacts on human health.

Outbreak of Severe Vomiting in Dogs Associated with a Canine Enteric Coronavirus, United Kingdom

The lack of population health surveillance for companion animal populations leaves them vulnerable to the effects of novel diseases without means of early detection. We present evidence on the effectiveness of a system that enabled early detection and rapid response a canine gastroenteritis outbreak in the United Kingdom. In January 2020, prolific vomiting among dogs was sporadically reported in the United Kingdom. Electronic health records from a nationwide sentinel network of veterinary practices confirmed a significant increase in dogs with signs of gastroenteric disease. Male dogs and dogs living with other vomiting dogs were more likely to be affected. Diet and vaccination status were not associated with the disease; however, a canine enteric coronavirus was significantly associated with illness. The system we describe potentially fills a gap in surveillance in neglected populations and could provide a blueprint for other countries.

Micropollutant fluxes in urban environment - A catchment perspective

This study provided a holistic understanding of the sources, fate and behaviour of 142 compounds of emerging concern (CECs) throughout a river catchment impacted by 5 major urban areas. Of the incoming 169.3 kg d^-1 of CECs entering the WwTWs, 167.9 kg d^-1 were present in the liquid phase of influent and 1.4 kg d^-1 were present in the solid phase (solid particulate matter, SPM). Analysis of SPM was important to determine accurate loads of incoming antidepressants and antifungal compounds, which are primarily found in the solid phase. Furthermore, these classes and the plasticiser, bisphenol A (BPA) were the highest contributors to CEC load in digested solids. Population normalised loads showed little variation across the catchment at 154 ± 12 mg d^-1 inhabitant^-1 indicating that population size is the main driver of CECs in the studied catchment. Across the catchment 154.6 kg d^-1 were removed from the liquid phase during treatment processes. CECs discharged into surface waters from individual WwTWs contributed between 0.19 kg d^-1 at WwTW A to 7.3 kg d^-1 at WwTW E, which correlated strongly with the respective contributing populations. Spatial and temporal variations of individual CECs and their respective classes were found in WwTW influent (both solid (influent_SPM) and liquid phases (influent_AQ)) throughout the catchment, showing that different urban areas impact the catchment in different ways, with key variables being lifestyle, use of over-the-counter pharmaceuticals and industrial activity. Understanding of both spatial and temporal variation of CECs at the catchment level helped to identify possible instances of direct disposal, as in the case of carbamazepine. Analysis of surface waters throughout the catchment showed increasing mass loads of CECs from upstream of WwTW A to downstream at WwTW D, showing clear individual contributions from WwTWs. Many CECs were ubiquitous throughout the river water in the catchment. Daily loads ranged from 0.005 g d^-1 (ketamine, WwTW A) up to 1890.3 g d^-1 (metformin, WwTW C) for the 84/138 CECs that were detected downstream of the WwTWs. For metformin this represents the equivalent of ∼1,890 tablets (1,000 mg per tablet) dissolved in the river water downstream of WwTW C.

Availability, access, analysis and dissemination of small-area data

In this era of 'big data', there is growing recognition of the value of environmental, health, social and demographic data for research. Open government data initiatives are growing in number and in terms of content. Remote sensing data are finding widespread use in environmental research, including in low- and middle-income settings. While our ability to study environment and health associations across countries and continents grows, data protection rules and greater patient control over the use of their data present new challenges to using health data in research. Innovative tools that circumvent the need for the physical sharing of data by supporting non-disclosive sharing of information, or that permit spatial analysis without researchers needing access to underlying patient data can be used to support analyses while protecting data confidentiality. User-friendly visualizations, allowing small-area data to be seen and understood by non-expert audiences, are revolutionizing public and researcher interactions with data. The UK Small Area Health Statistics Unit's Environment and Health Atlas for England and Wales, and the US National Environmental Public Health Tracking Network offer good examples. Open data facilitates user-generated outputs, and 'mash-ups', and user-generated inputs from social media, mobile devices and wearable tech are new data streams that will find utility in future studies, and bring novel dimensions with respect to ethical use of small-area data.

Spatiotemporal modelling of pregabalin prescribing in England with effect of deprivation

OBJECTIVE

This paper aims to understand spatial and temporal trends in pregabalin prescribing and the relationship with deprivation across England at both general practice and clinical commissioning group (CCG) levels.

DESIGN

A set of 207 independent generalised additive models are employed to model the spatiotemporal trend of pregabalin prescribed and dispensed per 1000 population, adjusting for deprivation. The response variable is pregabalin prescribed in milligrams, with weighted Index of Multiple Deprivation (IMD), geographical location and time as predictors. The set of active prescribing facilities grouped within CCG is the unit of analysis.

SETTING

National Health Service open prescribing data; all general practices in England, UK between January 2015 and June 2017.

POPULATION

All patients registered to general practices in England, UK.

RESULTS

Adjusting for deprivation, a North-South divide is shown in terms of prescribing trends, with the North of England showing increasing prescribing rates during the study period on average, while in the South of England rates are on average decreasing. Approximately 60% of general practices showed increasing prescribing rate, with the highest being 4.03 (1.75 for the most decreasing). There were no apparent spatial patterns in baseline prescription rates at the CCG level. Weighted IMD score proved to be statistically significant in 138 of 207 CCGs. Two-thirds of CCGs showed more pregabalin prescribed in areas of greater deprivation. Whether the prescribing rate is high due to high baseline prescription rate or increasing rates needs to be specifically looked at.

CONCLUSIONS

The spatial temporal modelling demonstrated that the North of England has a significantly higher chance to see increase in pregablin prescriptions compared with the South, adjusted for weighted IMD. Weighted IMD has shown positive impact on pregabalin prescriptions for 138 CCGs.

bench4gis: Benchmarking Privacy-aware Geocoding with Open Big Data

Geocoding, the process of translating addresses to geographic coordinates, is a relatively straight-forward and well-studied process, but limitations due to privacy concerns may restrict usage of geographic data. The impact of these limitations are further compounded by the scale of the data, and in turn, also limits viable geocoding strategies. For example, healthcare data is protected by patient privacy laws in addition to possible institutional regulations that restrict external transmission and sharing of data. This results in the implementation of "in-house" geocoding solutions where data is processed behind an organization's firewall; quality assurance for these implementations is problematic because sensitive data cannot be used to externally validate results. In this paper, we present our software framework called bench4gis which benchmarks privacy-aware geocoding solutions by leveraging open big data as surrogate data for quality assurance; the scale of open big data sets for address data can ensure that results are geographically meaningful for the locale of the implementing institution.

New approaches to pharmacosurveillance for monitoring prescription frequency, diversity, and co-prescription in a large sentinel network of companion animal veterinary practices in the United Kingdom, 2014-2016

Pharmaceutical agents (PAs) are commonly prescribed in companion animal practice in the United Kingdom. However, little is known about PA prescription on a population-level, particularly with respect to PAs authorised for human use alone prescribed via the veterinary cascade; this raises important questions regarding the efficacy and safety of PAs prescribed to companion animals. This study explored new approaches for describing PA prescription, diversity and co-prescription in dogs, cats and rabbits utilising electronic health records (EHRs) from a sentinel network of 457 companion animal-treating veterinary sites throughout the UK over a 2-year period (2014-2016). A novel text mining-based identification and classification methodology was utilised to semi-automatically map practitioner-defined product descriptions recorded in 918,333 EHRs from 413,870 dogs encompassing 1,242,270 prescriptions; 352,730 EHRs from 200,541 cats encompassing 491,554 prescriptions, and 22,526 EHRS from 13,398 rabbits encompassing 18,490 prescriptions respectively. PA prescription as a percentage of booked consultations was 65.4% (95% confidence interval, CI, 64.6-66.3) in dogs; in cats it was 69.1% (95% CI, 67.9-70.2) and in rabbits, 56.3% (95% CI, 54.7-57.8). Vaccines were the most commonly prescribed PAs in all three species, with antibiotics, antimycotics, and parasiticides also commonly prescribed. PA prescription utilising products authorised for human use only (hence, 'human-authorised') comprised 5.1% (95% CI, 4.7-5.5) of total canine prescription events; in cats it was 2.8% (95% CI, 2.6-3.0), and in rabbits, 7.8% (95% CI, 6.5-9.0). The most commonly prescribed human-authorised PA in dogs was metronidazole (antibiotic); in cats and rabbits it was ranitidine (H2 histamine receptor antagonist). Using a new approach utilising the Simpson's Diversity Index (an ecological measure of relative animal, plant etc. species abundance), we identified differences in prescription based on presenting complaint and species, with rabbits generally exposed to a less diverse range of PAs than dogs or cats, potentially reflecting the paucity of authorised PAs for use in rabbits. Finally, through a novel application of network analysis, we demonstrated the existence of three major co-prescription groups (preventive health; treatment of disease, and euthanasia); a trend commonly observed in practice. This study represents the first time PA prescription has been described across all pharmaceutical families in a large population of companion animals, encompassing PAs authorised for both veterinary and human-only use. These data form a baseline against which future studies could be compared, and provides some useful tools for understanding PA comparative efficacy and risks when prescribed in the varied setting of clinical practice.

More green space is related to less antidepressant prescription rates in the Netherlands: A Bayesian geoadditive quantile regression approach

BACKGROUND

Exposure to green space seems to be beneficial for self-reported mental health. In this study we used an objective health indicator, namely antidepressant prescription rates. Current studies rely exclusively upon mean regression models assuming linear associations. It is, however, plausible that the presence of green space is non-linearly related with different quantiles of the outcome antidepressant prescription rates. These restrictions may contribute to inconsistent findings.

OBJECTIVE

Our aim was: a) to assess antidepressant prescription rates in relation to green space, and b) to analyze how the relationship varies non-linearly across different quantiles of antidepressant prescription rates.

METHODS

We used cross-sectional data for the year 2014 at a municipality level in the Netherlands. Ecological Bayesian geoadditive quantile regressions were fitted for the 15%, 50%, and 85% quantiles to estimate green space-prescription rate correlations, controlling for physical activity levels, socio-demographics, urbanicity, etc. RESULTS: The results suggested that green space was overall inversely and non-linearly associated with antidepressant prescription rates. More important, the associations differed across the quantiles, although the variation was modest. Significant non-linearities were apparent: The associations were slightly positive in the lower quantile and strongly negative in the upper one.

CONCLUSION

Our findings imply that an increased availability of green space within a municipality may contribute to a reduction in the number of antidepressant prescriptions dispensed. Green space is thus a central health and community asset, whilst a minimum level of 28% needs to be established for health gains. The highest effectiveness occurred at a municipality surface percentage higher than 79%. This inverse dose-dependent relation has important implications for setting future community-level health and planning policies.

ADHD in the United Kingdom: Regional and Socioeconomic Variations in Incidence Rates Amongst Children and Adolescents (2004-2013)

OBJECTIVE

To describe the incidence and distribution of ADHD within the United Kingdom, and to examine whether there was any association between ADHD incidence and socioeconomic deprivation.

METHOD

The study used data from the Clinical Practice Research Datalink (CPRD). Patients diagnosed with ADHD before the age of 19 between January 1, 2004 and December 31, 2013 were stratified according to the region in which their general practice was based. Practice Index of Multiple Deprivation (IMD) score was used as a surrogate measure of patients' deprivation status.

RESULTS

ADHD incidence was relatively stable between 2004 and 2013, but peaked in the last 2 years studied. Statistically significant ( p ≤ .05) differences in incidence were observed between U.K. regions. In almost every year studied, incidence rates were highest among the most deprived patients and lowest among the least deprived patients.

CONCLUSION

In the United Kingdom, ADHD may be associated with socioeconomic deprivation.

Organisation of services for managing ADHD

There is considerable variation in practice, both between and with different countries in the management of attention deficit hyperactivity disorder (ADHD). Whilst there is no one optimal model of service organisation there are general principles of care that can be introduced to reduce this variability. There are frequent debates and discussions about which professional group is best placed to manage ADHD at different points in the life cycle. Who delivers care is however less important than ensuring that training schemes provide adequate exposure, training and experience to both the core and non-core skills required to provide a comprehensive package of care. Most evidence-based guidelines recommend a multi-modal, multi-professional and multi-agency approach. Many also promote the use of both stepped care and shared care approaches for the management of ADHD. As most of those with ADHD continue to have ADHD-related problems into adulthood, it is important to consider how best to transition care into adulthood and think about who should deliver care to adults with ADHD. Young people with ADHD should generally be transferred to adult mental health services if they continue to have significant symptoms of ADHD or other coexisting conditions that require treatment. Unfortunately services for adults with ADHD remain relatively scarce across much of the world and some adult psychiatrists remain unsure of the diagnosis and uncertain about the appropriate use of ADHD medications in adults, but there is a strong case for increased services for adults. ADHD is on the one hand easy to treat; it is much more difficult to treat well. Although optimised care for ADHD requires routine measurement of outcomes, this often does not happen in routine clinical practice. Focusing on optimising symptoms and minimising adverse effects can significantly improve both short- and long-term outcomes.