Smart diapers for nursing home residents with dementia: a pilot study

Huion, Anja; Decalf, Veerle; Kumps, Candy; Witte, Nico De; Everaert, Karel

doi:10.1080/17843286.2018.1511279

Cited by 16 publications

(15 citation statements)

References 13 publications

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“…To the best of our knowledge, this study is the first to investigate the feasibility of a smart diaper system in an acute care hospital. The only previous study was conducted with 18 people with dementia living in nursing homes and estimated the saturation of diaper capacity indirectly rather than measuring the volume of urine [ 36 ]. The study reported that the saturation errors between the smart diaper system and FVCs were –26% to 39% in the regular diaper (450 mL) with 51 urination records, and –34% to 30% in the super diaper (1000 mL) with 46 records, respectively.…”

Section: Discussionmentioning

confidence: 99%

A Smart Diaper System Using Bluetooth and Smartphones to Automatically Detect Urination and Volume of Voiding: Prospective Observational Pilot Study in an Acute Care Hospital

Cho¹,

Choi²,

Kim³

et al. 2021

J Med Internet Res

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Background Caregivers of patients who wear conventional diapers are required to check for voiding every hour because prolonged wearing of wet diapers causes health problems including diaper dermatitis and urinary tract infections. However, frequent checking is labor intensive and disturbs patients’ and caregivers’ sleep. Furthermore, assessing patients’ urine output with diapers in an acute care setting is difficult. Recently, a smart diaper system with wetness detection technology was developed to solve these issues. Objective We aimed to evaluate the applicability of the smart diaper system for urinary detection, its accuracy in measuring voiding volume, and its effect on incontinence-associated dermatitis (IAD) occurrence in an acute care hospital. Methods This prospective, observational, single-arm pilot study was conducted at a single tertiary hospital. We recruited 35 participants aged ≥50 years who were wearing diapers due to incontinence between August and November 2020. When the smart diaper becomes wet, the smart diaper system notifies the caregiver to change the diaper and measures voiding volume automatically. Caregivers were instructed to record the weight of wet diapers on frequency volume charts (FVCs). We determined the voiding detection rate of the smart diaper system and compared the urine volume as automatically calculated by the smart diaper system with the volume recorded on FVCs. Agreement between the two measurements was estimated using a Bland-Altman plot. We also checked for the occurrence or aggravation of IAD and bed sores. Results A total of 30 participants completed the protocol and 390 episodes of urination were recorded. There were 108 records (27.7%) on both the FVCs and the smart diaper system, 258 (66.2%) on the FVCs alone, 18 (4.6%) on the smart diaper system alone, and 6 (1.5%) on the FVCs with sensing device lost. The detection rate of the smart diaper system was 32.8% (126/384). When analyzing records concurrently listed in both the FVCs and the smart diaper system, linear regression showed a strong correlation between the two measurements (R2=0.88, P<.001). The Bland-Altman assessment showed good agreement between the two measurements, with a mean difference of –4.2 mL and 95% limits of agreement of –96.7 mL and 88.3 mL. New occurrence and aggravation of IAD and bed sores were not observed. Bed sores improved in one participant. Conclusions The smart diaper system showed acceptable accuracy for measuring urine volume and it could replace conventional FVCs in acute setting hospitals. Furthermore, the smart diaper system has the potential advantage of preventing IAD development and bed sore worsening. However, the detection rate of the smart diaper system was lower than expected. Detection rate polarization among participants was observed, and improvements in the user interface and convenience are needed for older individuals who are unfamiliar with the smart diaper system.

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Section: Discussionmentioning

confidence: 99%

A Smart Diaper System Using Bluetooth and Smartphones to Automatically Detect Urination and Volume of Voiding: Prospective Observational Pilot Study in an Acute Care Hospital

Cho¹,

Choi²,

Kim³

et al. 2021

J Med Internet Res

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“…Thus, given the high healthcare resource utilization and costs associated with anticholinergic burden, efforts to reduce the levels of anticholinergic burden could result in decreased utilization and costs, specifically among LSNH residents with OAB. Additionally, the use of pads and diapers would avoid contributing to anticholinergic burden in the LSNH population with OAB [11,12]; however, it is unclear whether their use would result in a net reduction economic burden and warrants further investigation.…”

Section: Discussionmentioning

confidence: 99%

“…Among residents with dementia and those who are relatively immobile, behavioral strategies may be less successful and the use of pads and diapers may be preferred. Both behavioral strategies and the use of pads and diapers avoid contributing to polypharmacy among patients; however, it may add to the economic burden of the condition [11,12]. OAB pharmacotherapy is primarily comprised of antimuscarinic agents, which are part of the class of oral anticholinergic medications [13]; however, anticholinergics are associated with several central and peripheral adverse effects.…”

Section: Data Sourcementioning

confidence: 99%

The Costs and Healthcare Resource Utilization Associated with Anticholinergic Burden in Long-Stay Nursing Home Residents with Overactive Bladder in the US

Chatterjee

Walker

Kimura

et al. 2021

PharmacoEconomics Open

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Background Overactive bladder (OAB) is a prevalent condition commonly treated with anticholinergic medications. The extent to which anticholinergic burden is associated with costs and healthcare resource use (HCRU) in the long-stay nursing home (LSNH) setting is currently unknown. Objectives This research evaluated the impact of anticholinergic burden on HCRU and related costs among LSNH residents with OAB. Methods This was a cohort study based on 2013-2015 Minimum Data Set-linked Medicare claims data involving LSNH residents aged ≥ 65 years with OAB and having Parts A, B and D coverage 6 months pre-and ≥ 12 months post-nursing home admission date (index date). Cumulative anticholinergic burden was determined using the Anticholinergic Cognitive Burden scale and defined daily dose. Direct medical costs related to HCRU were examined. HCRU included inpatient, outpatient, emergency room (ER), and physician office visits. Costs and HCRU associated with levels of anticholinergic burden were evaluated using generalized linear models. Results A total of 123,308 LSNH residents with OAB were included in this study. Most residents (87.2%) had some level (12.8%, none; 18.0%, low; 41.9%, moderate; and 27.3%, high) of cumulative anticholinergic burden. Results indicate that all types of resource utilization were higher among those with any level of anticholinergic burden than those with no burden. The outpatient, ER, and physician costs tended to be higher with increasing anticholinergic burden. Conclusions Costs and HCRU patterns reflected increasing trends with anticholinergic burden. Targeted efforts towards reducing anticholinergic burden among LSNH residents with OAB may result in decreases in costs and HCRU.

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“…Wireless Communications and Mobile Computing smartwatch-based communication system for nursing homes [23], which improve communication between residents and caregivers, thus reducing staff response time and improving residents' safety; or an experimental smart diaper [24] as an indicator of saturation for diaper change in people with dementia living in nursing homes. On the other hand, there are rehabilitation assistance projects, such as a new electroinformatics assistive medical system [25] used for the communication with neuromotor disabled patients, which allows bidirectional communication through using an interface with a software application by using different types of sensors including switch-type sensors or eye tracking devices; a system for monitoring and rehabilitation services for elderly [26], based on mobile and wearable technologies ready to be used in residential long-term care facilities to reduce the risk of depression and social isolation; a telecare and telerehabilitation system using computer vision techniques [27]; or a software application for tablet device [3] to support social connections and reducing responsive behaviours of people with dementia while in a care setting, such as nursing homes.…”

Section: Motivationsmentioning

confidence: 99%

Smart Nursing Homes: Self‐Management Architecture Based on IoT and Machine Learning for Rural Areas

Flores-Martín

Rojo

Moguel

et al. 2021

Wireless Communications and Mobile Computing

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The rate of world population aging is increasing. This situation directly affects all countries socially and economically, increasing their compromise and effort to improve the living conditions of this sector of society. In environments with large influxes of elderly people, such as nursing homes, the use of technology has shown promise in improving their quality of life. The use of smart devices allows people to automate everyday tasks and learn from them to predict future actions. Additionally, smartphones capture a wealth of information that allows to adapt to nearby actuators according to people’s preferences and even detects anomalies in their behaviour. Current works are proposing new frameworks to detect these behaviours and act accordingly. However, these works are not focused on managing multidevice environments where sensor and smartphone data are considered to automate environments with elderly people or to learn from them. Also, most of these works require a permanent Internet connection, so the full benefit of smart devices is not completely achieved. In this work, we present an architecture that takes the data from sensors and smartphones in order to adapt the behaviour of the actuators of the environment. In addition, it uses this data to learn from the environment to predict actions or to extrapolate the actions that should be executed according to similar behaviours. The architecture is implemented through a use case based on a nursing home located in a rural area. Thanks to this work, the quality of life of the elderly is improved in a simple, affordable, and transparent way for them.

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Smart diapers for nursing home residents with dementia: a pilot study

Abstract: This study indicates that the sensor detects and notifies wetness but is not sensitive enough for using it as an indicator for diaper change in people with severe dementia.

Cited by 16 publications

References 13 publications

A Smart Diaper System Using Bluetooth and Smartphones to Automatically Detect Urination and Volume of Voiding: Prospective Observational Pilot Study in an Acute Care Hospital

A Smart Diaper System Using Bluetooth and Smartphones to Automatically Detect Urination and Volume of Voiding: Prospective Observational Pilot Study in an Acute Care Hospital

The Costs and Healthcare Resource Utilization Associated with Anticholinergic Burden in Long-Stay Nursing Home Residents with Overactive Bladder in the US

Smart Nursing Homes: Self‐Management Architecture Based on IoT and Machine Learning for Rural Areas

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