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Background: Falls in hospitalised patients remain an ongoing challenge for healthcare systems internationally. Limited research exists on the perspectives of older people on falls risk, cause and care. Objectives: This study explored the experiences of patients and their families after a fall in a healthcare facility. Methods: Semi‐structured interviews were conducted with patients and families to explore the experience of having a fall. Data were analysed thematically. Results: The themes that emerged from the 14 interviews included the following: explanations; physical environment; communication; experiences of care; perceptions of risk; ageism; feelings towards the fall; and independence and dignity. Conclusions: This research emphasises the diversity in older people's experiences after experiencing a fall. Falls prevention should be incorporated as one part of healthy, dignified ageing. Implications for practice: Falls prevention and management strategies should be multifactorial, including enhanced communication with the patient and their families. When engaging in education and awareness, falls prevention should be positioned as one component of independent and dignified healthy ageing. [ABSTRACT FROM AUTHOR]

Introduction: Medication reconciliation (MedRec) reduces the risk of preventable medication-related adverse events (ADEs). A best possible medication discharge plan (BPMDP) is a revised list of medications a patient will take when discharged from hospital; a pharmacist review ensures accuracy. For many hospitals, on-site pharmacists are non-existent. Extension of a visual presence via a mobile robotic platform with real-time audiovisual communication by pharmacists to conduct MedRec remains unstudied. This study explored patient perceptions of a pharmacist-led BPMDP using a telepresence robot. Time requirements, unintentional discharge medication discrepancies (UMD), programme inefficiencies/ barriers and facilitators involved in pharmacist review of the discharge medication list and patient interviews were also described. Methods: This prospective cohort study enrolled adult patients admitted to a 12-bed community hospital at high risk of an ADE. Remote pharmacists reviewed the discharge prescription list, identified/resolved UMDs, and interviewed/counselled patients using a telepresence robot. Thereafter, patients completed an anonymous satisfaction questionnaire. Prescriber discharge UMDs were classified, and barriers/inefficiencies and facilitators were documented. Results: Nine patients completed an interview, with a 75% interview agreement rate. All patients were comfortable with the robot and 76% felt their care was better. With a median of 11 discharge medications/patient, the UMD rate was 78%; 71% had omitted medications, 43% involved a cardiovascular medication, 88% were due to a hospital system cause, and 43% were specifically due to an inaccurate best possible admission medication history. Median times for interview preparation, interview and UMD/drug therapy problem resolution were 45, 15 and 10 min, respectively. Conclusion: Using a telepresence robot to provide pharmacist-led BPMDPs is acceptable to patients and an innovative, effective solution to identify/resolve UMDs. [ABSTRACT FROM AUTHOR]

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Objectives: The aim of this study was to develop and test, for the first time, a multivariate diagnostic classifier of attention deficit hyperactivity disorder (ADHD) based on EEG coherence measures and chronological age. Setting: The participants were recruited in two specialised centres and three schools in Reykjavik. Participants: The data are from a large cross- sectional cohort of 310 patients with ADHD and 351 controls, covering an age range from 5.8 to 14 years. ADHD was diagnosed according to the Diagnostic and Statistical Manual of Mental Disorders fourth edition (DSM-IV) criteria using the K-SADS-PL semistructured interview. Participants in the control group were reported to be free of any mental or developmental disorders by their parents and had a score of less than 1.5 SDs above the age-appropriate norm on the ADHD Rating Scale-IV. Other than moderate or severe intellectual disability, no additional exclusion criteria were applied in order that the cohort reflected the typical cross section of patients with ADHD. Results: Diagnostic classifiers were developed using statistical pattern recognition for the entire age range and for specific age ranges and were tested using cross-validation and by application to a separate cohort of recordings not used in the development process. The age-specific classification approach was more accurate (76% accuracy in the independent test cohort; 81% cross-validation accuracy) than the age- independent version (76%; 73%). Chronological age was found to be an important classification feature. Conclusions: The novel application of EEG-based classification methods presented here can offer significant benefit to the clinician by improving both the accuracy of initial diagnosis and ongoing monitoring of children and adolescents with ADHD. The most accurate possible diagnosis at a single point in time can be obtained by the age-specific classifiers, but the age-independent classifiers are also useful as they enable longitudinal monitoring of brain function. [ABSTRACT FROM AUTHOR]