Cohort profile: CROSS-TRACKS: a population-based open cohort across healthcare sectors in Denmark.

PURPOSE: This paper describes the open cohort CROSS-TRACKS, which comprises population-based data from primary care, secondary care and national registries to study patient pathways and transitions across sectors while adjusting for sociodemographic characteristics. PARTICIPANTS: A total of 221 283 individuals resided in the four Danish municipalities that constituted the catchment area of Horsens Regional Hospital in 2012-2018. A total of 96% of the population used primary care, 35% received at least one transfer payment and 66% was in contact with a hospital at least once in the period. Additional clinical information is available for hospital contacts (eg, alcohol intake, smoking status, body mass index and blood pressure). A total of 23% (n=8191) of individuals aged ≥65 years had at least one potentially preventable hospital admission, and 73% (n=5941) of these individuals had more than one. FINDINGS TO DATE: The cohort is currently used for research projects in epidemiology and artificial intelligence. These projects comprise a prediction model for potentially preventable hospital admissions, a clinical decision support system based on artificial intelligence, prevention of medication errors in the transition between sectors, health behaviour and sociodemographic characteristics of men and women prior to fertility treatment, and a recently published study applying machine learning methods for early detection of sepsis. FUTURE PLANS: The CROSS-TRACKS cohort will be expanded to comprise the entire Central Denmark Region consisting of 1.3 million residents. The cohort can provide new knowledge on how to best organise interventions across healthcare sectors and prevent potentially preventable hospital admissions. Such knowledge would benefit both the individual citizen and society as a whole.

Validity and Reliability Evaluation of Four Commercial Activity Trackers' Step Counting Performance.

INTRODUCTION: Activity trackers are useful tools for physical rehabilitation purposes. Most available activity trackers are designed for fitness and wellness use, lacking in both accuracy and precision at lower speeds. Validity and reliability at all clinically relevant speeds are crucial selection criteria for use in clinical practice. The aim of this study was to assess the validity and reliability of four consumer-based activity trackers at clinical relevant walking speeds for patient groups undergoing rehabilitation. METHODS: The four commercial activity trackers Fitbit Surge (FS), Fitbit Charge HR (FC), Microsoft Band 2 (MB), and A&D 101NFC Activity Monitor (A&D) were evaluated at 2, 4, 4.5, and 5.5 km/h. Twenty healthy participants aged 25.6 ± 2 years walked on a treadmill at the four velocities in two trials of 100 steps each. Mean average percentage error (MAPE), intraclass correlation coefficient (ICC), and Bland-Altman 95% limits of agreement were calculated to assess validity and reliability. RESULTS: MAPE levels were between -8% and -6% for FS, -15% and 0% for MB, 7% and 21% for FC, and -53% and 1% for AD. The biggest inaccuracies were seen at 2 km/h, where AD underestimated by 53%. The highest accuracy was predominantly found with MB and AD, which overestimated ≤2% at velocities ≥4 km/h. ICC was moderate (0.73) for FS, good (0.88) for MB, moderate (0.52) for FC, and excellent (0.98) for AD. CONCLUSIONS: MB, FS, and AD accurately counted steps, when participants walked with velocities corresponding to a brisk walk (≥4 km/h). Walking at lower speeds (≤2 km/h) was not counted accurately. Thus, the four evaluated activity trackers are not useful for patient groups walking at lower speeds during rehabilitation, nor for counting indoor walking.