Comparing natural language processing representations of coded disease sequences for prediction in electronic health records.

OBJECTIVE: Natural language processing (NLP) algorithms are increasingly being applied to obtain unsupervised representations of electronic health record (EHR) data, but their comparative performance at predicting clinical endpoints remains unclear. Our objective was to compare the performance of unsupervised representations of sequences of disease codes generated by bag-of-words versus sequence-based NLP algorithms at predicting clinically relevant outcomes. MATERIALS AND METHODS: This cohort study used primary care EHRs from 6 286 233 people with Multiple Long-Term Conditions in England. For each patient, an unsupervised vector representation of their time-ordered sequences of diseases was generated using 2 input strategies (212 disease categories versus 9462 diagnostic codes) and different NLP algorithms (Latent Dirichlet Allocation, doc2vec, and 2 transformer models designed for EHRs). We also developed a transformer architecture, named EHR-BERT, incorporating sociodemographic information. We compared the performance of each of these representations (without fine-tuning) as inputs into a logistic classifier to predict 1-year mortality, healthcare use, and new disease diagnosis. RESULTS: Patient representations generated by sequence-based algorithms performed consistently better than bag-of-words methods in predicting clinical endpoints, with the highest performance for EHR-BERT across all tasks, although the absolute improvement was small. Representations generated using disease categories perform similarly to those using diagnostic codes as inputs, suggesting models can equally manage smaller or larger vocabularies for prediction of these outcomes. DISCUSSION AND CONCLUSION: Patient representations produced by sequence-based NLP algorithms from sequences of disease codes demonstrate improved predictive content for patient outcomes compared with representations generated by co-occurrence-based algorithms. This suggests transformer models may be useful for generating multi-purpose representations, even without fine-tuning.

Assigning disease clusters to people: A cohort study of the implications for understanding health outcomes in people with multiple long-term conditions.

Background: Identifying clusters of co-occurring diseases may help characterise distinct phenotypes of Multiple Long-Term Conditions (MLTC). Understanding the associations of disease clusters with health-related outcomes requires a strategy to assign clusters to people, but it is unclear how the performance of strategies compare. Aims: First, to compare the performance of methods of assigning disease clusters to people at explaining mortality, emergency department attendances and hospital admissions over one year. Second, to identify the extent of variation in the associations with each outcome between and within clusters. Methods: We conducted a cohort study of primary care electronic health records in England, including adults with MLTC. Seven strategies were tested to assign patients to fifteen disease clusters representing 212 LTCs, identified from our previous work. We tested the performance of each strategy at explaining associations with the three outcomes over 1 year using logistic regression and compared to a strategy using the individual LTCs. Results: 6,286,233 patients with MLTC were included. Of the seven strategies tested, a strategy assigning the count of conditions within each cluster performed best at explaining all three outcomes but was inferior to using information on the individual LTCs. There was a larger range of effect sizes for the individual LTCs within the same cluster than there was between the clusters. Conclusion: Strategies of assigning clusters of co-occurring diseases to people were less effective at explaining health-related outcomes than a person's individual diseases. Furthermore, clusters did not represent consistent relationships of the LTCs within them, which might limit their application in clinical research.

The impact of the 2022 spring COVID-19 booster vaccination programme on hospital occupancy in England: An interrupted time series analysis.

Regular booster vaccination programmes help protect the most vulnerable from COVID-19 and limit pressure on health systems. Existing studies find booster doses to be effective in preventing hospital admissions and deaths but focus on individual effects, failing to consider the population impact of incomplete vaccination coverage and seasonal patterns in disease transmission. We estimated the effectiveness of the 2022 spring booster vaccination programme, available for those aged 75 years and older, residents in care homes, and adults with weakened immune systems, on COVID-19 hospital bed occupancy in England. Booster vaccine coverage in the eligible population increased rapidly in the months after rollout (from 21st March 2022), flattening out just below 80% by July 2022. We used interrupted time series analysis to estimate a 23.7% overall reduction in the rate of hospital occupancy for COVID-19 following the programme, with a statistically significant benefit in the 6-12 weeks following rollout. In the absence of the programme, we calculate that a total of 380,104 additional hospital bed-days would have been occupied by patients with COVID-19 from 4th April to 31st August 2022 (95% CI: -122,842 to 1,034,590). The programme delayed and shortened the duration of the peak while not reducing its magnitude. In sensitivity analyses adjusting the start of the post-intervention period or removing the rate of COVID-19 infection in the over 60s from the model, the effect of the spring booster programme on hospital bed occupancy remained similar. Our findings suggest that timing is a critical consideration in the implementation of COVID-19 booster programmes and that policymakers cannot rely on intermittent booster vaccination of high-risk groups alone to mitigate anticipated peaks in hospital pressure due to COVID-19 epidemics.

Effect of timeframes to define long term conditions and sociodemographic factors on prevalence of multimorbidity using disease code frequency in primary care electronic health records: retrospective study.

Objective: To determine the extent to which the choice of timeframe used to define a long term condition affects the prevalence of multimorbidity and whether this varies with sociodemographic factors. Design: Retrospective study of disease code frequency in primary care electronic health records. Data sources: Routinely collected, general practice, electronic health record data from the Clinical Practice Research Datalink Aurum were used. Main outcome measures: Adults (≥18 years) in England who were registered in the database on 1 January 2020 were included. Multimorbidity was defined as the presence of two or more conditions from a set of 212 long term conditions. Multimorbidity prevalence was compared using five definitions. Any disease code recorded in the electronic health records for 212 conditions was used as the reference definition. Additionally, alternative definitions for 41 conditions requiring multiple codes (where a single disease code could indicate an acute condition) or a single code for the remaining 171 conditions were as follows: two codes at least three months apart; two codes at least 12 months apart; three codes within any 12 month period; and any code in the past 12 months. Mixed effects regression was used to calculate the expected change in multimorbidity status and number of long term conditions according to each definition and associations with patient age, gender, ethnic group, and socioeconomic deprivation. Results: 9 718 573 people were included in the study, of whom 7 183 662 (73.9%) met the definition of multimorbidity where a single code was sufficient to define a long term condition. Variation was substantial in the prevalence according to timeframe used, ranging from 41.4% (n=4 023 023) for three codes in any 12 month period, to 55.2% (n=5 366 285) for two codes at least three months apart. Younger people (eg, 50-75% probability for 18-29 years v 1-10% for ≥80 years), people of some minority ethnic groups (eg, people in the Other ethnic group had higher probability than the South Asian ethnic group), and people living in areas of lower socioeconomic deprivation were more likely to be re-classified as not multimorbid when using definitions requiring multiple codes. Conclusions: Choice of timeframe to define long term conditions has a substantial effect on the prevalence of multimorbidity in this nationally representative sample. Different timeframes affect prevalence for some people more than others, highlighting the need to consider the impact of bias in the choice of method when defining multimorbidity.

Patient portal registration and healthcare utilisation in general practices in England: a longitudinal cohort study.

BACKGROUND: Patient portals introduced in most of England's general practices since 2015 have the potential to improve healthcare efficiency. There is a paucity of information on the use of patient portals within the NHS general practices and the potential impact on healthcare utilisation. AIM: To investigate the association between patient portal registration and care utilisation (measured by the number of general practice consultations) among general practice patients. DESIGN & SETTING: A longitudinal analysis using electronic health record data from the Clinical Practice Research Datalink (CPRD). METHOD: We analysed patients registered for patient portals (n = 284 666), aggregating their consultations 1 year before and 1 year after registration. We ran a multilevel negative binomial regression model to examine patient portal registration's association with face-to-face and remote consultations. RESULTS: Patients who registered to the portal had a small decrease in the total number of face-to-face consultations after registering to the patient portal (incidence rate ratio = 0.93, 95% confidence interval [CI] = 0.93 to 0.94). Patients who registered to the portal had an increase in the total number of remote consultations after registering to the portal (incidence rate ratio = 1.16, 95% CI = 1.15 to 1.18). CONCLUSION: The study found minor changes in consultation numbers post-patient portal registration, notably with an increase in remote consultations. While causality between portal registration and consultation number remains unclear, the potential link between patient portal use and healthcare utilisation warrants further investigation, especially within the NHS, where portal impacts are not well-studied. Detailed portal utilisation data could clarify this relationship.

Validating a framework to guide the implementation of high-quality virtual primary care: an international eDelphi study protocol.

BACKGROUND: There is an urgent need to support primary care organisations in implementing safe and high-quality virtual consultations. We have previously performed qualitative research to capture the views of 1600 primary care physicians across 20 countries on the main benefits and challenges of using virtual consultations. Subsequently, a prototype of a framework to guide the implementation of high-quality virtual primary care was developed. AIM: To explore general practitioners' perspectives on the appropriateness and relevance of each component of the framework's prototype, to further refine it and optimise its practical use in primary care facilities. METHODS AND ANALYSIS: Participants will be primary care physicians with active experience providing virtual care, recruited through convenience and snowball sampling. This study will use a systematic and iterative online Delphi research approach (eDelphi), with a minimum of three rounds. A pre-round will be used to circulate items for initial feedback and adjustment. In subsequent rounds, participants will be asked to rate the relevance of the framework's components. Consensus will be defined as >70% of participants agreeing/strongly agreeing or disagreeing/strongly disagreeing with a component. Data will be collected using structured online questionnaires. The primary outcome of the study will be a list of the essential components to be incorporated in the final version of the framework. ETHICS AND DISSEMINATION: The study has received ethical approval conceded by the Imperial College London Science, Engineering and Technology Research Ethics Committee (SETREC) (reference no .6559176/2023). Anonymous results will be made available to the public, academic organisations and policymakers.

Attendance at remote versus in-person outpatient appointments in an NHS Trust.

INTRODUCTION: With the growing use of remote appointments within the National Health Service, there is a need to understand potential barriers of access to care for some patients. In this observational study, we examined missed appointments rates, comparing remote and in-person appointments among different patient groups. METHODS: We analysed adult outpatient appointments at Imperial College Healthcare NHS Trust in Northwest London in 2021. Rates of missed appointments per patient were compared between remote versus in-person appointments using negative binomial regression models. Models were stratified by appointment type (first or a follow-up). RESULTS: There were 874,659 outpatient appointments for 189,882 patients, 29.5% of whom missed at least one appointment. Missed rates were 12.5% for remote first appointments and 9.2% for in-person first appointments. Remote and in-person follow-up appointments were missed at similar rates (10.4% and 10.7%, respectively). For remote and in-person appointments, younger patients, residents of more deprived areas, and patients of Black, Mixed and 'other' ethnicities missed more appointments. Male patients missed more in-person appointments, particularly at younger ages, but gender differences were minimal for remote appointments. Patients with long-term conditions (LTCs) missed more first appointments, whether in-person or remote. In follow-up appointments, patients with LTCs missed more in-person appointments but fewer remote appointments. DISCUSSION: Remote first appointments were missed more often than in-person first appointments, follow-up appointments had similar attendance rates for both modalities. Sociodemographic differences in outpatient appointment attendance were largely similar between in-person and remote appointments, indicating no widening of inequalities in attendance due to appointment modality.

Cross-sectional analyses of online appointment booking and repeat prescription ordering user characteristics in general practices of England in the years 2018-2020.

OBJECTIVES: To explore the characteristics of the General Practice Patient Survey (GPPS) respondents using the different functionalities of the online services in the context of England's National Health Service General Practices. We hypothesised that respondents who are older, with lower socioeconomic status and non-white ethnicity would be less likely to use online services, while long-term conditions might increase their usage. DESIGN: Cross-sectional study using respondent-level data from the GPPS in England of the years 2018, 2019 and 2020. We assessed the association between online services use and respondent characteristics using two-level mixed-effects logistic regression. PARTICIPANTS: Survey respondents of the GPPS 2018-2020. PRIMARY OUTCOME MEASURES: Online appointment booking and online repeat prescription ordering. RESULTS: 1 807 049 survey respondents were included in this study. 15% (n=263 938) used online appointment booking in the previous 12 months, and 19% (n=339 449) had ordered a repeat prescription in the previous 12 months. Respondents with a long-term condition, on regular multiple medications, who have deafness or hearing loss and who are from the lowest deprivation quintile were more likely to have used online services. Male respondents (compared with females) and respondents with black and other ethnicity compared with white ethnicity were less likely to use online services. Respondents over 85 years old were less likely to use online appointment booking and online repeat prescription ordering compared with the younger age groups. CONCLUSIONS: Specific groups of respondents were more likely to use online services such as patients with long-term conditions or those with deafness or hearing loss. While online services could provide efficiency to patients and practices it is essential that alternatives continue to be provided to those that cannot use or choose not to use online services. Understanding the different patients' needs could inform solutions to increase the uptake and use of the services.

Identifying potential biases in code sequences in primary care electronic healthcare records: a retrospective cohort study of the determinants of code frequency.

OBJECTIVES: To determine whether the frequency of diagnostic codes for long-term conditions (LTCs) in primary care electronic healthcare records (EHRs) is associated with (1) disease coding incentives, (2) General Practice (GP), (3) patient sociodemographic characteristics and (4) calendar year of diagnosis. DESIGN: Retrospective cohort study. SETTING: GPs in England from 2015 to 2022 contributing to the Clinical Practice Research Datalink Aurum dataset. PARTICIPANTS: All patients registered to a GP with at least one incident LTC diagnosed between 1 January 2015 and 31 December 2019. PRIMARY AND SECONDARY OUTCOME MEASURES: The number of diagnostic codes for an LTC in (1) the first and (2) the second year following diagnosis, stratified by inclusion in the Quality and Outcomes Framework (QOF) financial incentive programme. RESULTS: 3 113 724 patients were included, with 7 723 365 incident LTCs. Conditions included in QOF had higher rates of annual coding than conditions not included in QOF (1.03 vs 0.32 per year, p<0.0001). There was significant variation in code frequency by GP which was not explained by patient sociodemographics. We found significant associations with patient sociodemographics, with a trend towards higher coding rates in people living in areas of higher deprivation for both QOF and non-QOF conditions. Code frequency was lower for conditions with follow-up time in 2020, associated with the onset of the COVID-19 pandemic. CONCLUSIONS: The frequency of diagnostic codes for newly diagnosed LTCs is influenced by factors including patient sociodemographics, disease inclusion in QOF, GP practice and the impact of the COVID-19 pandemic. Natural language processing or other methods using temporally ordered code sequences should account for these factors to minimise potential bias.

The impacts of social restrictions during the COVID-19 pandemic on the physical activity levels of over 50-year olds: The CHARIOT COVID-19 Rapid Response (CCRR) cohort study.

OBJECTIVES: To quantify the associations between shielding status and loneliness at the start of the COVID-19 pandemic, and physical activity (PA) levels throughout the pandemic. METHODS: Demographic, health and lifestyle characteristics of 7748 cognitively healthy adults aged >50, and living in London, were surveyed from April 2020 to March 2021. The International Physical Activity Questionnaire (IPAQ) short-form assessed PA before COVID-19 restrictions, and up to 6 times over 11 months. Linear mixed models investigated associations between shielding status and loneliness at the onset of the pandemic, with PA over time. RESULTS: Participants who felt 'often lonely' at the outset of the pandemic completed an average of 522 and 547 fewer Metabolic Equivalent of Task (MET) minutes/week during the pandemic (95% CI: -809, -236, p<0.001) (95% CI: -818, -275, p<0.001) than those who felt 'never lonely' in univariable and multivariable models adjusted for demographic factors respectively. Those who felt 'sometimes lonely' completed 112 fewer MET minutes/week (95% CI: -219, -5, p = 0.041) than those who felt 'never lonely' following adjustment for demographic factors. Participants who were shielding at the outset of the pandemic completed an average of 352 fewer MET minutes/week during the pandemic than those who were not (95% CI: -432, -273; p<0.001) in univariable models and 228 fewer MET minutes/week (95% CI: -307, -150, p<0.001) following adjustment for demographic factors. No significant associations were found after further adjustment for health and lifestyle factors. CONCLUSIONS: Those shielding or lonely at pandemic onset were likely to have completed low levels of PA during the pandemic. These associations are influenced by co-morbidities and health status.

The Impact of Virtual Consultations on the Quality of Primary Care: Systematic Review.

BACKGROUND: The adoption of virtual consultations, catalyzed by the COVID-19 pandemic, has transformed the delivery of primary care services. Owing to their rapid global proliferation, there is a need to comprehensively evaluate the impact of virtual consultations on all aspects of care quality. OBJECTIVE: This study aims to evaluate the impact of virtual consultations on the quality of primary care. METHODS: A total of 6 databases were searched. Studies that evaluated the impact of virtual consultations, for any disease, were included. Title and abstract screening and full-text screening were performed by 2 pairs of investigators. Risk of bias was assessed using the Mixed Methods Appraisal Tool. A narrative synthesis of the results was performed. RESULTS: In total, 30 studies (5,469,333 participants) were included in this review. Our findings suggest that virtual consultations are equally effective to or more effective than face-to-face care for the management of certain conditions, including mental illness, excessive smoking, and alcohol consumption. Overall, 4 studies indicated positive impacts on some aspects of patient-centeredness; however, a negative impact was noted on patients' perceived autonomy support (ie, the degree to which people perceive those in positions of authority to be autonomy supportive). Virtual consultations may reduce waiting times, lower patient costs, and reduce rates of follow-up in secondary and tertiary care settings. Evidence for the impact on clinical safety is extremely limited. Evidence regarding equity was considerably mixed. Overall, it appears that virtual care is more likely to be used by younger, female patients, with disparities among other subgroups depending on contextual factors. CONCLUSIONS: Our systematic review demonstrated that virtual consultations may be as effective as face-to-face care and have a potentially positive impact on the efficiency and timeliness of care; however, there is a considerable lack of evidence on the impacts on patient safety, equity, and patient-centeredness, highlighting areas where future research efforts should be devoted. Capitalizing on real-world data, as well as clinical trials, is crucial to ensure that the use of virtual consultations is tailored according to patient needs and is inclusive of the intended end users. Data collection methods that are bespoke to the primary care context and account for patient characteristics are necessary to generate a stronger evidence base to inform future virtual care policies.

Global blood pressure screening during the COVID-19 pandemic: results from the May Measurement Month 2021 campaign.

BACKGROUND: Raised blood pressure (BP) remains the biggest risk factor contributing to the global burden of disease and mortality, despite the COVID-19 pandemic. May Measurement Month (MMM), an annual global screening campaign aims to highlight the importance of BP measurement by evaluating global awareness, treatment and control rates among adults with hypertension. In 2021, we assessed the global burden of these rates during the COVID-19 pandemic. METHODS: Screening sites were set up in 54 countries between May and November 2021 and screenees were recruited by convenience sampling. Three sitting BPs were measured, and a questionnaire completed including demographic, lifestyle and clinical data. Hypertension was defined as a systolic BP at least 140 mmHg and/or a diastolic BP at least 90 mmHg (using the mean of the second and third readings) or taking antihypertensive medication. Multiple imputation was used to impute the average BP when readings were missing. RESULTS: Of the 642 057 screenees, 225 882 (35.2%) were classified as hypertensive, of whom 56.8% were aware, and 50.3% were on antihypertensive medication. Of those on treatment, 53.9% had controlled BP (<140/90 mmHg). Awareness, treatment and control rates were lower than those reported in MMM campaigns before the COVID-19 pandemic. Minimal changes were apparent among those testing positive for, or being vaccinated against COVID-19. Of those on antihypertensive medication, 94.7% reported no change in their treatment because of the COVID-19 pandemic. CONCLUSION: The high yield of untreated or inadequately treated hypertension in MMM 2021 confirms the need for systematic BP screening where it does not currently exist.

Factors associated with enrolment into a national COVID-19 pulse oximetry remote monitoring programme in England: a retrospective observational study.

BACKGROUND: Hypoxaemia is an important predictor of severity in individuals with COVID-19 and can present without symptoms. The COVID Oximetry @home (CO@h) programme was implemented across England in November, 2020, providing pulse oximeters to higher-risk people with COVID-19 to enable early detection of deterioration and the need for escalation of care. We aimed to describe the clinical and demographic characteristics of individuals enrolled onto the programme and to assess whether there were any inequalities in enrolment. METHODS: This retrospective observational study was based on data from a cohort of people resident in England recorded as having a positive COVID-19 test between Oct 1, 2020, and May 3, 2021. The proportion of participants enrolled onto the CO@h programmes in the 7 days before and 28 days after a positive COVID-19 test was calculated for each clinical commissioning group (CCG) in England. Two-level hierarchical multivariable logistic regression with random intercepts for each CCG was run to identify factors predictive of being enrolled onto the CO@h programme. FINDINGS: CO@h programme sites were reported by NHS England as becoming operational between Nov 21 and Dec 31, 2020. 1 227 405 people resident in 72 CCGs had a positive COVID-19 test between the date of programme implementation and May 3, 2021, of whom 19 932 (1·6%) were enrolled onto the CO@h programme. Of those enrolled, 14 441 (72·5%) were aged 50 years or older or were identified as clinically extremely vulnerable (ie, having a high-risk medical condition). Higher odds of enrolment onto the CO@h programme were found in older individuals (adjusted odds ratio 2·21 [95% CI 2·19-2·23], p<0·001, for those aged 50-64 years; 3·48 [3·33-3·63], p<0·001, for those aged 65-79 years; and 2·50 [2·34-2·68], p<0·001, for those aged ≥80 years), in individuals of non-White ethnicity (1·35 [1·28-1·43], p<0·001, for Asian individuals; 1·13 [1·04-1·22], p=0·005, for Black individuals; and 1·17 [1·03-1·32], p=0·015, for those of mixed ethnicity), in those who were overweight (1·31 [1·26-1·37], p<0·001) or obese (1·69 [1·63-1·77], p<0·001), or in those identified as clinically extremely vulnerable (1·58 [1·51-1·65], p<0·001), and lower odds were reported in those from the least socioeconomically deprived areas compared with those from the most socioeconomically deprived areas (0·75 [0·69-0·81]; p<0·001). INTERPRETATION: Nationally, uptake of the CO@h programme was low, with clinical judgment used to determine eligibility. Preferential enrolment onto the pulse oximetry monitoring programme was observed in people known to be at the highest risk of developing severe COVID-19. FUNDING: NHS England, National Institute for Health Research, and The Wellcome Trust.

Evaluating the impact of a pulse oximetry remote monitoring programme on mortality and healthcare utilisation in patients with COVID-19 assessed in emergency departments in England: a retrospective matched cohort study.

BACKGROUND: To identify the impact of enrolment onto a national pulse oximetry remote monitoring programme for COVID-19 (COVID-19 Oximetry @home; CO@h) on health service use and mortality in patients attending Emergency Departments (EDs). METHODS: We conducted a retrospective matched cohort study of patients enrolled onto the CO@h pathway from EDs in England. We included all patients with a positive COVID-19 test from 1 October 2020 to 3 May 2021 who attended ED from 3 days before to 10 days after the date of the test. All patients who were admitted or died on the same or following day to the first ED attendance within the time window were excluded. In the primary analysis, participants enrolled onto CO@h were matched using demographic and clinical criteria to participants who were not enrolled. Five outcome measures were examined within 28 days of first ED attendance: (1) Death from any cause; (2) Any subsequent ED attendance; (3) Any emergency hospital admission; (4) Critical care admission; and (5) Length of stay. RESULTS: 15 621 participants were included in the primary analysis, of whom 639 were enrolled onto CO@h and 14 982 were controls. Odds of death were 52% lower in those enrolled (95% CI 7% to 75%) compared with those not enrolled onto CO@h. Odds of any ED attendance or admission were 37% (95% CI 16% to 63%) and 59% (95% CI 32% to 91%) higher, respectively, in those enrolled. Of those admitted, those enrolled had 53% (95% CI 7% to 76%) lower odds of critical care admission. There was no significant impact on length of stay. CONCLUSIONS: These findings indicate that for patients assessed in ED, pulse oximetry remote monitoring may be a clinically effective and safe model for early detection of hypoxia and escalation. However, possible selection biases might limit the generalisability to other populations.

Stagnating rates of blood pressure control in Australia: insights from opportunistic screening of 10 046 participants of the May Measurement Month campaigns.

BACKGROUND: Raised blood pressure (BP) remains the single most important modifiable risk factor contributing to cardiovascular and all-cause mortality in Australia and worldwide. May Measurement Month , a global BP measurement and screening campaign initiated by the International Society of Hypertension and carried out in Australia since its inception in 2017, aimed at obtaining standardized BP measurements from members of the community to increase awareness of high BP and its associated risks. METHOD: Adults participants (≥18 years) were recruited through opportunistic sampling across Australia during the month of May in 2017, 2018 and 2019. Trained volunteers recorded BP readings in a standardized manner and collected data on demographic, lifestyle factors and comorbidities. Hypertension was defined as SBP of at least 140 mmHg, or DBP of at least 90 mmHg, or taking antihypertensive medication. Data were collated centrally and analysis was carried out using regression models to evaluate the associations between BP and participant characteristics. RESULTS: A total of 10 046 participants were screened, of whom 3097 (31.0%) had hypertension, only 48.5% were aware of their condition and 44.4% were taking antihypertensive medication. Of those taking antihypertensive medication, 53.2% were controlled to less than 140/90 mmHg, whereas the remaining 46.8% of participants had BP of at least 140/90 mmHg suggestive of inadequately treated hypertension. CONCLUSION: Consecutive data obtained over a 3-year period in Australia demonstrated stagnating awareness, treatment and control rates with the latter two being substantially lower than global rates and those in other high-income countries. Concerted efforts from all stakeholders will be required to help overcome the unacceptably poor rates of BP treatment and control in Australia.

Home oxygen monitoring and therapy: learning from the pandemic.

PURPOSE OF REVIEW: Home oxygen monitoring and therapy have been increasingly used in the management of patients with chronic diseases. The COVID-19 pandemic has prompted the rapid uptake of remote monitoring programmes to support people with COVID-19 at home. This review discusses the recent evidence and learning in home oxygen monitoring and therapy from the pandemic. RECENT FINDINGS: Many home oxygen monitoring programmes were established around the world during the pandemic, mostly in high-income countries to support early detection of hypoxaemia and/or early hospital discharge. The characteristics of these programmes vary widely in the type of monitoring (self-monitoring or clinician-monitoring) and the patient risk groups targeted. There is a lack of evidence for benefits on clinical outcomes, including mortality, and on reductions in healthcare utilisation or cost-effectiveness, but programmes are viewed positively by patients. Recent studies have highlighted the potential bias in pulse oximetry in people with darker skin. SUMMARY: Recent evidence indicates that home oxygen monitoring therapy programmes are feasible in acute disease, but further research is needed to establish whether they improve patient outcomes, are cost-effective and to understand their equity impact.

May Measurement Month 2018: an analysis of blood pressure screening results from Benin.

Hypertension is the strongest cardiovascular risk factor worldwide. May Measurement Month (MMM) is an international campaign for blood pressure (BP) screening initiated by the International Society of Hypertension. This work aims to estimate the proportion and the levels of awareness, treatment, and control of hypertension in participants of the MMM survey in Benin in 2018. A cross-sectional survey focused on people aged ≥18 years was conducted in May 2018 in nine rural and urban areas in Benin. A sampling of volunteers was done. BP was measured following the MMM protocol. Hypertension was defined as a systolic BP ≥140 mm Hg and/or a diastolic BP ≥90 mm Hg (mean of the second and third readings) and/or taking antihypertensive medication. Linear regression was used to identify BP associations. A total of 2035 people were screened, including 55.9% women. The mean age was 44.2 ± 15.9 years. The percentage with hypertension was 35.4%. Of 721 participants with hypertension, 56.2% were aware of their diagnosis, 39.7% were on antihypertensive medication, and 13.6% were controlled (<140/90 mmHg). The results confirm the significant proportion of hypertension in Benin. Education programs on risk factors, early detection, and better management strategies should be developed.