The glarma Package for Observation-Driven Time Series Regression of Counts

We review the theory and application of generalized linear autoregressive moving average observation-driven models for time series of counts with explanatory variables and describe the estimation of these models using the R package glarma. Forecasting, diagnostic and graphical methods are also illustrated by several examples

Interprofessional collaboration between educational psychologists and speech and language therapists in the UK: facilitators and barriers

In the UK, speech and language therapists (SLTs) and educational psychologists (EPs) are professionals who support children with speech, language and communication needs (SLCN). Legislative and socio-economic changes within the UK and continuing concern about poor outcomes for children with SLCN provided the impetus for a focus on interprofessional collaboration between these two groups. An online survey was distributed to qualified EPs and SLTs in the UK enquiring about facilitators and barriers to collaboration. Responses from 125 EPs and 182 SLTs were content analysed. Responses indicated that communication and working environments were key factors impacting interprofessional collaboration. Relationships and commitment to joint working were also cited as facilitators. Challenges related to reduced resourcing, staffing and changes to working environments as a result of austerity. A framework illustrating possible inter-relationships between factors is presented, indicating hypothesised pathways that could underpin planning for development and change. In summary, despite positive moves towards shared policy and guidance for children with SLCN, findings suggest that a continued focus on maximising effective interprofessional collaboration is crucial to ensure that assessment and early intervention are available to support children with speech, language and communication needs

Usability and Feasibility of PIERS on the Move: An mHealth App for Pre-Eclampsia Triage.

BACKGROUND: Pre-eclampsia is one of the leading causes of maternal death and morbidity in low-resource countries due to delays in case identification and a shortage of health workers trained to manage the disorder. Pre-eclampsia Integrated Estimate of RiSk (PIERS) on the Move (PotM) is a low cost, easy-to-use, mobile health (mHealth) platform that has been created to aid health workers in making decisions around the management of hypertensive pregnant women. PotM combines two previously successful innovations into a mHealth app: the miniPIERS risk assessment model and the Phone Oximeter. OBJECTIVE: The aim of this study was to assess the usability of PotM (with mid-level health workers) for iteratively refining the system. METHODS: Development of the PotM user interface involved usability testing with target end-users in South Africa. Users were asked to complete clinical scenario tasks, speaking aloud to give feedback on the interface and then complete a questionnaire. The tool was then evaluated in a pilot clinical evaluation in Tygerberg Hospital, Cape Town. RESULTS: After ethical approval and informed consent, 37 nurses and midwives evaluated the tool. During Study 1, major issues in the functionality of the touch-screen keyboard and date scroll wheels were identified (total errors n=212); during Study 2 major improvements in navigation of the app were suggested (total errors n=144). Overall, users felt the app was usable using the Computer Systems Usability Questionnaire; median (range) values for Study 1 = 2 (1-6) and Study 2 = 1 (1-7). To demonstrate feasibility, PotM was used by one research nurse for the pilot clinical study. In total, more than 500 evaluations were performed on more than 200 patients. The median (interquartile range) time to complete an evaluation was 4 min 55 sec (3 min 25 sec to 6 min 56 sec). CONCLUSIONS: By including target end-users in the design and evaluation of PotM, we have developed an app that can be easily integrated into health care settings in low- and middle-income countries. Usability problems were often related to mobile phone features (eg, scroll wheels, touch screen use). Larger scale evaluation of the clinical impact of this tool is underway

Attention-deficit hyperactivity disorder diagnoses and prescriptions in UK primary care, 2000–2018: population-based cohort study

Background Rates of diagnosed attention-deficit hyperactivity disorder (ADHD) may be increasing in the UK. Aims Estimate incidence and prevalence of ADHD diagnoses and ADHD prescriptions in UK adults and children in primary care. Method We conducted a cohort study using IQVIA Medical Research Data, a UK primary care database. Rates of ADHD diagnoses and ADHD prescriptions were calculated between 2000 and 2018 for individuals aged 3–99 years, analysed by age, gender, social deprivation status and calendar year. Results Of 7 655 931 individuals, 35 877 (0.5%) had ADHD diagnoses; 18 518 (0.2%) received ADHD medication prescriptions. Diagnoses and prescription rates were greater in men versus women, children versus adults, and deprivation status (nearly double in most deprived versus least deprived quintile). By 2018, the proportion of ADHD diagnoses was 255 per 10 000 (95% CI 247–263) in boys and 67.7 per 10 000 (95% CI 63.5–71.9) in girls; for adults, it was 74.3 per 10 000 (95% CI 72.3–76.2) in men and 20 per 10 000 (95%CI 19.0–21.0) in women. Corresponding figures for prescriptions were 156 per 10 000 (95% CI 150–163) in boys, 36.8 per 10 000 (95% CI 33.8–40.0) in girls, 13.3 per 10 000 (95% CI 12.5–14.1) in men and 4.5 per 10 000 (95% CI 4.1–5.0) in women. Except among 3- to 5-year-olds, the incidence and prevalence of ADHD diagnoses and prescriptions have increased from 2000 to 2018 in all age groups. The absolute increase was highest in children, but the relative increase was largest among adults (e.g. among men aged 18–29 years, approximately 20-fold and nearly 50-fold increases in diagnoses and prescriptions, respectively). Conclusions The incidence and prevalence of both ADHD diagnoses and medication are highest among children. Proportionally, rates increased most among adults during 2000–2018. ADHD diagnoses and prescriptions are associated with socioeconomic deprivation

Assessment of neonatal respiratory rate variability

Accurate measurement of respiratory rate (RR) in neonates is challenging due to high neonatal RR variability (RRV). There is growing evidence that RRV measurement could inform and guide neonatal care. We sought to quantify neonatal RRV during a clinical study in which we compared multiparameter continuous physiological monitoring (MCPM) devices. Measurements of capnography-recorded exhaled carbon dioxide across 60-s epochs were collected from neonates admitted to the neonatal unit at Aga Khan University-Nairobi hospital. Breaths were manually counted from capnograms and using an automated signal detection algorithm which also calculated mean and median RR for each epoch. Outcome measures were between- and within-neonate RRV, between- and within-epoch RRV, and 95% limits of agreement, bias, and root-mean-square deviation. Twenty-seven neonates were included, with 130 epochs analysed. Mean manual breath count (MBC) was 48 breaths per minute. Median RRV ranged from 11.5% (interquartile range (IQR) 6.8–18.9%) to 28.1% (IQR 23.5–36.7%). Bias and limits of agreement for MBC vs algorithm-derived breath count, MBC vs algorithm-derived median breath rate, MBC vs algorithm-derived mean breath rate were − 0.5 (− 2.7, 1.66), − 3.16 (− 12.12, 5.8), and − 3.99 (− 11.3, 3.32), respectively. The marked RRV highlights the challenge of performing accurate RR measurements in neonates. More research is required to optimize the use of RRV to improve care. When evaluating MCPM devices, accuracy thresholds should be less stringent in newborns due to increased RRV. Lastly, median RR, which discounts the impact of extreme outliers, may be more reflective of the underlying physiological control of breathing