The impact of the COVID-19 pandemic on 397 631 elective dental admissions among the under-25s in England: a retrospective study.

BACKGROUND: COVID-19 caused widespread disruptions to health services worldwide, including reductions in elective surgery. Tooth extractions are among the most common reasons for elective surgery among children and young people (CYP). It is unclear how COVID-19 affected elective dental surgeries in hospitals over multiple pandemic waves at a national level. METHODS: Elective dental tooth extraction admissions were selected using Hospital Episode Statistics. Admission trends for the first 14 pandemic months were compared with the previous five years and results were stratified by age (under-11s, 11-16s, 17-24s). RESULTS: The most socioeconomically deprived CYP comprised the largest proportion of elective dental tooth extraction admissions. In April 2020, admissions dropped by >95%. In absolute terms, the biggest reduction was in April (11-16s: -1339 admissions, 95% CI -1411 to -1267; 17-24s: -1600, -1678 to -1521) and May 2020 (under-11s: -2857, -2962 to -2752). Admissions differed by socioeconomic deprivation for the under-11s (P < 0.0001), driven by fewer admissions than expected by the most deprived and more by the most affluent during the pandemic. CONCLUSION: Elective tooth extractions dropped most in April 2020, remaining below pre-pandemic levels throughout the study. Despite being the most likely to be admitted, the most deprived under-11s had the largest reductions in admissions relative to other groups.

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.

Impact of the COVID-19 pandemic on the clinical management trends for acute appendicitis among the under-25s: a retrospective study.

OBJECTIVE: To describe the COVID-19 pandemic's impact on acute appendicitis management on children and young people (CYP). DESIGN: Retrospective cohort study. SETTING: All English National Health Service hospitals. PATIENTS: Acute appendicitis admissions (all, simple, complex) by CYP (under-5s, 5-9s, 10-24s). EXPOSURE: Study pandemic period: February 2020-March 2021. Comparator pre-pandemic period: February 2015-January 2020. MAIN OUTCOME MEASURES: Monthly appendicectomy and laparoscopic appendicectomy rate trends and absolute differences between pandemic month and the pre-pandemic average. Proportions of appendicitis admissions comprising complex appendicitis by hospital with or without specialist paediatric centres were compared. RESULTS: 101 462 acute appendicitis admissions were analysed. Appendicectomy rates fell most in April 2020 for the 5-9s (-18.4% (95% CI -26.8% to -10.0%)) and 10-24s (-28.4% (-38.9% to -18.0%)), driven by reductions in appendicectomies for simple appendicitis. This was equivalent to -54 procedures (-68.4 to -39.6) and -512 (-555.9 to -467.3) for the 5-9s and 10-24s, respectively. Laparoscopic appendicectomies fell in April 2020 for the 5-9s (-15.5% (-23.2% to -7.8%)) and 10-24s (-44.8% (-57.9% to -31.6%) across all types, which was equivalent to -43 (-56.1 to 30.3) and -643 (-692.5 to -593.1) procedures for the 5-9s and 10-24s, respectively. A larger proportion of complex appendicitis admissions were treated within trusts with specialist paediatric centres during the pandemic. CONCLUSIONS: For CYP across English hospitals, a sharp recovery followed a steep reduction in appendicectomy rates in April 2020, due to concerns with COVID-19 transmission. This builds on smaller-sized studies reporting the immediate short-term impacts.

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.

Treating insomnia in people who are incarcerated: a feasibility study of a multicomponent treatment pathway.

Around 60% of people who are incarcerated have insomnia; 6-10 times more prevalent than the general population. Yet, there is no standardized, evidence-based approach to insomnia treatment in prison. We assessed the feasibility of a treatment pathway for insomnia in a high-secure prison to inform a future randomized controlled trial (RCT) and initial efficacy data for sleep and mental health outcomes. We used a within-participants pre-post design. The stepped-care pathway included: self-management with peer support, environmental aids, and cognitive behavioral therapy for insomnia (CBTi). Assessment measures for insomnia, well-being, mood, anxiety, suicidality, overall health, sleepiness, fatigue, and cognitive functioning were administered at baseline and pathway exit. Feasibility criteria included eligibility to participate, CBTi uptake, and assessment completion. Forty-two adult males who are incarcerated were approached of which 95.2% were eligible. Of those deemed eligible, most participated (36/40, 90.0%). Most who completed baseline completed post-assessments (28/36, 77.8%) and of these, most showed improvements in their subjective sleep (27/28, 96.4%). Large reductions were found from pre- to posttreatment in insomnia severity (d = -1.81, 95% CI: 8.3 to 12.9) and 57.0% reported no clinically significant insomnia symptoms at post-assessment. There was no overall change in actigraphy-measured sleep. Large treatment benefits were found for depression, anxiety, well-being, and cognitive functioning, with a medium benefit on suicidal ideation. The treatment pathway for insomnia in prison was feasible and may be an effective treatment for insomnia in people who are incarcerated, with additional promising benefits for mental health. A pragmatic RCT across different prison populations is warranted. This paper is part of the Sleep and Circadian Health in the Justice System Collection.

A service evaluation of passive remote monitoring technology for patients in a high-secure forensic psychiatric hospital: a qualitative study.

BACKGROUND: Technology has the potential to remotely monitor patient safety in real-time that helps staff and without disturbing the patient. However, staff and patients' perspectives on using passive remote monitoring within an inpatient setting is lacking. The study aim was to explore stakeholders' perspectives about using Oxehealth passive monitoring technology within a high-secure forensic psychiatric hospital in the UK as part of a wider mixed-methods service evaluation. METHODS: Semi-structured interviews were conducted with staff and patients with experience of using Oxehealth technology face-to-face within a private room in Broadmoor Hospital. We applied thematic analysis to the data of each participant group separately. Themes and sub-themes were integrated, finalised, and presented in a thematic map. Design, management, and analysis was meaningfully informed by both staff and patients. RESULTS: Twenty-four participants were interviewed (n = 12 staff, n = 12 patients). There were seven main themes: detecting deterioration and improving health and safety, "big brother syndrome", privacy and dignity, knowledge and understanding, acceptance, barriers to use and practice issues and future changes needed. Oxehealth technology was considered acceptable to both staff and patients if the technology was used to detect deterioration and improve patient's safety providing patient's privacy was not invaded. However, overall acceptance was lower when knowledge and understanding of the technology and its camera was limited. Most patients could not understand why both physical checks through bedroom windows, and Oxehealth was needed to monitor patients, whilst staff felt Oxehealth should not replace physical checks of patients as reassures staff on patient safety. CONCLUSIONS: Oxehealth technology is considered viable and acceptable by most staff and patients but there is still some concern about its possible intrusive nature. However, more support and education for new patients and staff to better understand how Oxehealth works in the short- and long-term could be introduced to further improve acceptability. A feasibility study or pilot trial to compare the impact of Oxehealth with and without physical checks may be needed.

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.

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.

Characteristics associated with influenza vaccination uptake in pregnancy: a retrospective cohort study.

BACKGROUND: Pregnant women are at increased risk from influenza, yet maternal influenza vaccination levels remain suboptimal. AIM: To estimate associations between sociodemographic and health characteristics and seasonal influenza vaccination uptake among pregnant women, and to understand trends over time to inform interventions to improve vaccine coverage. DESIGN AND SETTING: Retrospective cohort study using linked electronic health records of women in North West London with a pregnancy overlapping an influenza season between September 2010 and February 2020. METHOD: A multivariable mixed-effects logistic regression model was used to identify associations between characteristics of interest and the primary outcome of influenza vaccination. RESULTS: In total, 451 954 pregnancies, among 260 744 women, were included. In 85 376 (18.9%) pregnancies women were vaccinated against seasonal influenza. Uptake increased from 8.4% in 2010/11 to 26.4% in 2017/18, dropping again to 21.1% in 2019/20. Uptake was lowest among women aged 15-19 years (11.9%; reference category) or ≥40 years (15.2%; odds ratio [OR] 1.17, 95% confidence interval [CI] = 1.10 to 1.24); of Black (14.1%; OR 0.55, 95% CI = 0.53 to 0.57) or unknown ethnicity (9.9%; OR 0.42, 95% CI = 0.39 to 0.46); who lived in more deprived areas (OR least versus most deprived [reference category] 1.16, 95% CI = 1.11 to 1.21); or with no known risk factors for severe influenza. CONCLUSION: Seasonal influenza vaccine uptake in pregnant women increased in the decade before the COVID-19 pandemic, but remained suboptimal. Targeted approaches are recommended to reducing inequalities in access to vaccination and should focus on women of Black ethnicity, younger and older women, and women living in deprived areas.

Patient outcomes following emergency admission to hospital for COVID-19 compared with influenza: retrospective cohort study.

BACKGROUND: We examine differences in posthospitalisation outcomes, and health system resource use, for patients hospitalised with COVID-19 during the UK's first pandemic wave in 2020, and influenza during 2018 and 2019. METHODS: This retrospective cohort study used routinely collected primary and secondary care data. Outcomes, measured for 90 days follow-up after discharge were length of stay in hospital, mortality, emergency readmission and primary care activity. RESULTS: The study included 5132 patients admitted to hospital as an emergency, with COVID-19 and influenza cohorts comprising 3799 and 1333 patients respectively. Patients in the COVID-19 cohort were more likely to stay in hospital longer than 10 days (OR 3.91, 95% CI 3.14 to 4.65); and more likely to die in hospital (OR 11.85, 95% CI 8.58 to 16.86) and within 90 days of discharge (OR 7.92, 95% CI 6.20 to 10.25). For those who survived, rates of emergency readmission within 90 days were comparable between COVID-19 and influenza cohorts (OR 1.07, 95% CI 0.89 to 1.29), while primary care activity was greater among the COVID-19 cohort (incidence rate ratio 1.30, 95% CI 1.23 to 1.37). CONCLUSIONS: Patients admitted for COVID-19 were more likely to die, more likely to stay in hospital for over 10 days and interact more with primary care after discharge, than patients admitted for influenza. However, readmission rates were similar for both groups. These findings, while situated in the context of the first wave of COVID-19, with the associated pressures on the health system, can inform health service planning for subsequent waves of COVID-19, and show that patients with COVID-19 interact more with healthcare services as well as having poorer outcomes than those with influenza.

Impact of COVID-19 on outpatient appointments in children and young people in England: an observational study.

OBJECTIVES: To describe the impact of the COVID-19 pandemic on outpatient appointments for children and young people. SETTING: All National Health Service (public) hospitals in England. PARTICIPANTS: All people in England aged <25 years. OUTCOME MEASURES: Outpatient department attendance numbers, rates and modes (face to face vs telephone) by age group, sex and socioeconomic deprivation. RESULTS: Compared with the average for January 2017 to December 2019, there was a 3.8 million appointment shortfall (23.5%) for the under-25 population in England between March 2020 and February 2021, despite a total rise in phone appointments of 2.6 million during that time. This was true for each age group, sex and deprivation fifth, but there were smaller decreases in face to face and total appointments for babies under 1 year. For all ages combined, around one in six first and one in four follow-up appointments were by phone in the most recent period. The proportion of appointments attended was high, at over 95% for telephone and over 90% for face-to-face appointments for all ages. CONCLUSIONS: COVID-19 led to a dramatic fall in total outpatient appointments and a large rise in the proportion of those appointments conducted by telephone. The impact that this has had on patient outcomes is still unknown. The differential impact of COVID-19 on outpatient activity in different sociodemographic groups may also inform design of paediatric outpatient services in the post-COVID period.

Factors associated with, and variations in, COVID-19 hospital death rates in England's first two waves: observational study.

OBJECTIVES: To assess patient-level and hospital-level predictors of death and variation in death rates following admission for COVID-19 in England's first two waves after accounting for random variation. To quantify the correlation between hospitals' first and second wave death rates. DESIGN: Observational study using administrative data. SETTING: Acute non-specialist hospitals in England. PARTICIPANTS: All patients admitted with a primary diagnosis of COVID-19. PRIMARY AND SECONDARY OUTCOMES: In-hospital death. RESULTS: Hospital Episode Statistics (HES) data were extracted for all acute hospitals in England for COVID-19 admissions from March 2020 to March 2021. In wave 1 (March to July 2020), there were 74 484 admissions and 21 883 deaths (crude rate 29.4%); in wave 2 (August 2020 to March 2021), there were 165 642 admissions and 36 040 deaths (21.8%). Wave 2 patients were younger, with more hypertension and obesity but lower rates of other comorbidities. Mortality improved for all ages; in wave 2, it peaked in December 2020 at 24.2% (lower than wave 1's peak) but halved by March 2021. In multiple multilevel modelling combining HES with hospital-level data from Situational Reports, wave 2 and wave 1 variables significantly associated with death were mostly the same. The median odds ratio for wave 1 was just 1.05 and for wave 2 was 1.07. At 99.8% control limits, 3% of hospitals were high and 7% were low funnel plot outliers in wave 1; these figures were 9% and 12% for wave 2. Four hospitals were (low) outliers in both waves. The correlation between hospitals' adjusted mortality rates between waves was 0.45 (p<0.0001). Length of stay was similar in each wave. CONCLUSIONS: England's first two COVID-19 waves were similar regarding predictors and moderate interhospital variation. Despite the challenges, variation in death rates and length of stay between hospitals was modest and might be accounted for by unobserved patient factors.

The Association Between Sleep Disturbance and Suicidality in Psychiatric Inpatients Transitioning to the Community: Protocol for an Ecological Momentary Assessment Study.

BACKGROUND: Patients are at high risk of suicidal behavior and death by suicide immediately following discharge from inpatient psychiatric hospitals. Furthermore, there is a high prevalence of sleep problems in inpatient settings, which is associated with worse outcomes following hospitalization. However, it is unknown whether poor sleep is associated with suicidality following initial hospital discharge. OBJECTIVE: Our study objective is to describe a protocol for an ecological momentary assessment (EMA) study that aims to examine the relationship between sleep and suicidality in discharged patients. METHODS: Our study will use an EMA design based on a wearable device to examine the sleep-suicide relationship during the transition from acute inpatient care to the community. Prospectively discharged inpatients 18 to 35 years old with mental disorders (N=50) will be assessed for eligibility and recruited across 2 sites. Data on suicidal ideation, behavior, and imagery; nonsuicidal self-harm and imagery; defeat, entrapment, and hopelessness; affect; and sleep will be collected on the Pro-Diary V wrist-worn electronic watch for up to 14 days. Objective sleep and daytime activity will be measured using the inbuilt MotionWare software. Questionnaires will be administered face-to-face at baseline and follow up, and data will also be collected on the acceptability and feasibility of using the Pro-Diary V watch to monitor the transition following discharge. The study has been, and will continue to be, coproduced with young people with experience of being in an inpatient setting and suicidality. RESULTS: South Birmingham Research Ethics Committee (21/WM/0128) approved the study on June 28, 2021. We expect to see a relationship between poor sleep and postdischarge suicidality. Results will be available in 2022. CONCLUSIONS: This protocol describes the first coproduced EMA study to examine the relationship between sleep and suicidality and to apply the integrated motivational volitional model in young patients transitioning from a psychiatric hospital to the community. We expect our findings will inform coproduction in suicidology research and clarify the role of digital monitoring of suicidality and sleep before and after initial hospital discharge. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): PRR1-10.2196/33817.

Population-level impact of a pulse oximetry remote monitoring programme on mortality and healthcare utilisation in the people with COVID-19 in England: a national analysis using a stepped wedge design.

BACKGROUND: To identify the population-level impact of a national pulse oximetry remote monitoring programme for COVID-19 (COVID Oximetry @home (CO@h)) in England on mortality and health service use. METHODS: We conducted a retrospective cohort study using a stepped wedge pre-implementation and post-implementation design, including all 106 Clinical Commissioning Groups (CCGs) in England implementing a local CO@h programme. All symptomatic people with a positive COVID-19 PCR test result from 1 October 2020 to 3 May 2021, and who were aged ≥65 years or identified as clinically extremely vulnerable were included. Care home residents were excluded. A pre-intervention period before implementation of the CO@h programme in each CCG was compared with a post-intervention period after implementation. Five outcome measures within 28 days of a positive COVID-19 test: (i) death from any cause; (ii) any ED attendance; (iii) any emergency hospital admission; (iv) critical care admission and (v) total length of hospital stay. RESULTS: 217 650 people were eligible and included in the analysis. Total enrolment onto the programme was low, with enrolment data received for only 5527 (2.5%) of the eligible population. The period of implementation of the programme was not associated with mortality or length of hospital stay. The period of implementation was associated with increased health service utilisation with a 12% increase in the odds of ED attendance (95% CI: 6% to 18%) and emergency hospital admission (95% CI: 5% to 20%) and a 24% increase in the odds of critical care admission in those admitted (95% CI: 5% to 47%). In a secondary analysis of CO@h sites with at least 10% or 20% of eligible people enrolled, there was no significant association with any outcome measure. CONCLUSION: At a population level, there was no association with mortality before and after the implementation period of the CO@h programme, and small increases in health service utilisation were observed. However, lower than expected enrolment is likely to have diluted the effects of the programme at a population level.

Effectiveness and safety of pulse oximetry in remote patient monitoring of patients with COVID-19: a systematic review.

The COVID-19 pandemic has led health systems to increase the use of tools for monitoring and triaging patients remotely. In this systematic review, we aim to assess the effectiveness and safety of pulse oximetry in remote patient monitoring (RPM) of patients at home with COVID-19. We searched five databases (MEDLINE, Embase, Global Health, medRxiv, and bioRxiv) from database inception to April 15, 2021, and included feasibility studies, clinical trials, and observational studies, including preprints. We found 561 studies, of which 13 were included in our narrative synthesis. These 13 studies were all observational cohorts and involved a total of 2908 participants. A meta-analysis was not feasible owing to the heterogeneity of the outcomes reported in the included studies. Our systematic review substantiates the safety and potential of pulse oximetry for monitoring patients at home with COVID-19, identifying the risk of deterioration and the need for advanced care. The use of pulse oximetry can potentially save hospital resources for patients who might benefit the most from care escalation; however, we could not identify explicit evidence for the effect of RPM with pulse oximetry on health outcomes compared with other monitoring models such as virtual wards, regular monitoring consultations, and online or paper diaries to monitor changes in symptoms and vital signs. Based on our findings, we make 11 recommendations across the three Donabedian model domains and highlight three specific measurements for setting up an RPM system with pulse oximetry.

Factors associated with accessing long-term adult social care in people aged 75 and over: a retrospective cohort study.

BACKGROUND: An ageing population and limited resources have put strain on state provision of adult social care (ASC) in England. With social care needs predicted to double over the next 20 years, there is a need for new approaches to inform service planning and development, including through predictive models of demand. OBJECTIVE: Describe risk factors for long-term ASC in two inner London boroughs and develop a risk prediction model for long-term ASC. METHODS: Pseudonymised person-level data from an integrated care dataset were analysed. We used multivariable logistic regression to model associations of demographic factors, and baseline aspects of health status and health service use, with accessing long-term ASC over 12 months. RESULTS: The cohort comprised 13,394 residents, aged ≥75 years with no prior history of ASC at baseline. Of these, 1.7% became ASC clients over 12 months. Residents were more likely to access ASC if they were older or living in areas with high socioeconomic deprivation. Those with preexisting mental health or neurological conditions, or more intense prior health service use during the baseline period, were also more likely to access ASC. A prognostic model derived from risk factors had limited predictive power. CONCLUSIONS: Our findings reinforce evidence on known risk factors for residents aged 75 or over, yet even with linked routinely collected health and social care data, it was not possible to make accurate predictions of long-term ASC use for individuals. We propose that a paradigm shift towards more relational, personalised approaches, is needed.

The use of, and outcomes for, inflammatory bowel disease services during the Covid-19 pandemic: a nationwide observational study.

BACKGROUND: Inflammatory bowel disease (IBD) services have been particularly affected by the Covid-19 pandemic. Delays in referral to secondary care and access to investigations and surgery have been exacerbated. AIMS: To investigate the use of and outcomes for emergency IBD care during the Covid-19 pandemic. METHODS: Nationwide observational study using administrative data for England (2015-2020) comparing cohorts admitted from 1 January 2015, to 31 January 2020 (pre-pandemic) and from 1 February 2020, to 31 January 2021 (pandemic). Autoregressive integrated moving average forecast models were run to estimate the counterfactual IBD admissions and procedures for February 2020 to January 2021. RESULTS: Large decreases in attendances to hospital for emergency treatment were observed for both acute ulcerative colitis (UC, 16.4%) and acute Crohn's disease (CD, 8.7%). The prevalence of concomitant Covid-19 during the same episode was low [391/16 494 (2.4%) and 349/15 613 (2.2%), respectively]. No significant difference in 30-day mortality was observed. A shorter median length of stay by 1 day for acute IBD admissions was observed (P < 0.0001). A higher rate of emergency readmission within 28 days for acute UC was observed (14.1% vs 13.4%, P = 0.012). All IBD procedures and investigations showed decreases in volume from February 2020 to January 2021 compared with counterfactual estimates. The largest absolute deficit was in endoscopy (17 544 fewer procedures, 35.2% reduction). CONCLUSION: There is likely a significant burden of untreated IBD in the community. Patients with IBD may experience clinical harm or protracted decreases in quality of life if care is not prioritised.