Mobile devices and wearable technology for measuring patient outcomes after surgery: a systematic review
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SUBMITTER: Knight S
PROVIDER: S-EPMC8590052 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:BackgroundDiabetes mellitus is a metabolic disorder that affects hundreds of millions of people worldwide and causes several million deaths every year. Such a dramatic scenario puts some pressure on administrations, care services, and the scientific community to seek novel solutions that may help control and deal effectively with this condition and its consequences.ObjectiveThis study aims to review the literature on the use of modern mobile and wearable technology for monitoring parameters that condition the development or evolution of diabetes mellitus.MethodsA systematic review of articles published between January 2010 and July 2020 was performed according to the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines. Manuscripts were identified through searching the databases Web of Science, Scopus, and PubMed as well as through hand searching. Manuscripts were included if they involved the measurement of diabetes-related parameters such as blood glucose level, performed physical activity, or feet condition via wearable or mobile devices. The quality of the included studies was assessed using the Newcastle-Ottawa Scale.ResultsThe search yielded 1981 articles. A total of 26 publications met the eligibility criteria and were included in the review. Studies predominantly used wearable devices to monitor diabetes-related parameters. The accelerometer was by far the most used sensor, followed by the glucose monitor and heart rate monitor. Most studies applied some type of processing to the collected data, mainly consisting of statistical analysis or machine learning for activity recognition, finding associations among health outcomes, and diagnosing conditions related to diabetes. Few studies have focused on type 2 diabetes, even when this is the most prevalent type and the only preventable one. None of the studies focused on common diabetes complications. Clinical trials were fairly limited or nonexistent in most of the studies, with a common lack of detail about cohorts and case selection, comparability, and outcomes. Explicit endorsement by ethics committees or review boards was missing in most studies. Privacy or security issues were seldom addressed, and even if they were addressed, they were addressed at a rather insufficient level.ConclusionsThe use of mobile and wearable devices for the monitoring of diabetes-related parameters shows early promise. Its development can benefit patients with diabetes, health care professionals, and researchers. However, this field is still in its early stages. Future work must pay special attention to privacy and security issues, the use of new emerging sensor technologies, the combination of mobile and clinical data, and the development of validated clinical trials.
| S-EPMC8212630 | biostudies-literature
Project description:BACKGROUND:Individuals of all ages are becoming more health conscious, and wearable technology devices (eg, Fitbit and Apple Watch) are becoming increasingly popular in encouraging healthy lifestyles. OBJECTIVE:The aim of this paper was to explore how consumers use wearable devices. METHODS:A retrospective review was done on the top-rated verified purchase reviews of the Fitbit One posted on Amazon.com between January 2014 and August 2018. Relevant themes were identified by qualitatively analyzing open-ended reviews. RESULTS:On retrieval, there were 9369 reviews with 7706 positive reviews and 1663 critical reviews. The top 100 positive and top 100 critical comments were subsequently analyzed. Four major themes were identified: sleep hygiene ("charts when you actually fall asleep, when you wake up during the night, when you're restless--and gives you a cumulative time of "actual sleep" as well as weekly averages."), motivation ("25 lbs lost after 8 months - best motivator ever!"), accountability ("platform to connect with people you know and set little competitions or group…fun accountability if you set a goal with a friend/family."), and discretion ("able to be clipped to my bra without being seen."). Alternatively, negative reviewers felt that the wearable device's various tracking functions, specifically steps and sleep, were inaccurate. CONCLUSIONS:Wearable technology devices are an affordable, user-friendly application that can support all individuals throughout their everyday lives and potentially be implemented into medical surveillance, noninvasive medical care, and mobile health and wellness monitoring. This study is the first to explore wearable technology device use among consumers, and further studies are needed to examine the limitless possibilities of wearable devices in health care.
| S-EPMC7199133 | biostudies-literature
Project description:BackgroundConsumer-wearable activity trackers are small electronic devices that record fitness and health-related measures.ObjectiveThe purpose of this systematic review was to examine the validity and reliability of commercial wearables in measuring step count, heart rate, and energy expenditure.MethodsWe identified devices to be included in the review. Database searches were conducted in PubMed, Embase, and SPORTDiscus, and only articles published in the English language up to May 2019 were considered. Studies were excluded if they did not identify the device used and if they did not examine the validity or reliability of the device. Studies involving the general population and all special populations were included. We operationalized validity as criterion validity (as compared with other measures) and construct validity (degree to which the device is measuring what it claims). Reliability measures focused on intradevice and interdevice reliability.ResultsWe included 158 publications examining nine different commercial wearable device brands. Fitbit was by far the most studied brand. In laboratory-based settings, Fitbit, Apple Watch, and Samsung appeared to measure steps accurately. Heart rate measurement was more variable, with Apple Watch and Garmin being the most accurate and Fitbit tending toward underestimation. For energy expenditure, no brand was accurate. We also examined validity between devices within a specific brand.ConclusionsCommercial wearable devices are accurate for measuring steps and heart rate in laboratory-based settings, but this varies by the manufacturer and device type. Devices are constantly being upgraded and redesigned to new models, suggesting the need for more current reviews and research.
| S-EPMC7509623 | biostudies-literature
Project description:IntroductionSarcopenia is a highly prevalent muscle dysfunction among older adults and is associated with adverse events. The periodic monitoring enables an early screening of patients at risk and control of the progression of muscle impairment. Wearable devices have been used as clinical support for sarcopenia detection. Therefore, this review aims to identify how wearable devices have been used to screen sarcopenia.Methods and analysesSearches will be conducted from August 2023 on PubMed, CINHAL, Embase, Web of Science and SciELO databases. We will include cross-sectional and/or baseline data from prospective studies reporting the use of wearable devices to investigate sarcopenia. Studies that discuss only the development of algorithms or applications for the assessment of sarcopenia or unavailable full texts will be excluded. The main reviewer will conduct the initial search and exclusion of duplicates, while two independent reviewers will select studies, extract data and assess the methodological quality using the Appraisal tool for Cross-sectional Studies.Ethics and disseminationNo previous ethical approval is required for this review. The findings of this review will be submitted to a scientific journal and disclosed at international scientific conferences.Prospero registration numberCRD42022356040.
| S-EPMC10314455 | biostudies-literature
Project description:BackgroundRecent events in health care reform have brought national attention to integrating patient experiences and expectations into quality metrics. Few studies have comprehensively evaluated the effect of patient expectations on patient-reported outcomes (PROs) after surgery. The purpose of this study is to systematically review the available literature describing the relationship between patient expectations and postoperative PROs.MethodsWe performed a search of the literature published before November 1, 2012. Articles were included in the review if (1) primary data were presented, (2) patient expectations regarding a surgical procedure were measured, (3) PROs were measured, and (4) the relationship between patient expectations and PROs was specifically examined. PROs were categorized into 5 subgroups: Satisfaction, quality of life (QOL), disability, mood disorder, and pain. We examined each study to determine the relationship between patient expectations and PROs as well as study quality.ResultsFrom the initial literature search yielding 1,708 studies, 60 articles were included. Fulfillment of expectations was associated with improved PROs among 24 studies. Positive expectations were correlated with improved PROs for 28 studies (47%), and poorer PROs for 9 studies (15%). Eighteen studies reported that fulfillment of expectations was correlated with improved patient satisfaction, and 10 studies identified that positive expectations were correlated with improved postoperative. Finally, patients with positive preoperative expectations reported less pain (8 studies) and disability (15 studies) compared with patients with negative preoperative expectations.ConclusionPatient expectations are inconsistently correlated with PROs after surgery, and there is no accepted method to capture perioperative expectations. Future efforts to rigorously measure expectations and explore their influence on postoperative outcomes can inform clinicians and policymakers seeking to integrate PROs into measures of surgical quality.
| S-EPMC4170731 | biostudies-literature
Project description:BackgroundHigh levels of sedentary behaviour (SB) are associated with negative health consequences. Technology enhanced solutions such as mobile applications, activity monitors, prompting software, texts, emails and websites are being harnessed to reduce SB. The aim of this paper is to evaluate the effectiveness of such technology enhanced interventions aimed at reducing SB in healthy adults and to examine the behaviour change techniques (BCTs) used.MethodsFive electronic databases were searched to identify randomised-controlled trials (RCTs), published up to June 2016. Interventions using computer, mobile or wearable technologies to facilitate a reduction in SB, using a measure of sedentary time as an outcome, were eligible for inclusion. Risk of bias was assessed using the Cochrane Collaboration's tool and interventions were coded using the BCT Taxonomy (v1).ResultsMeta-analysis of 15/17 RCTs suggested that computer, mobile and wearable technology tools resulted in a mean reduction of -41.28 min per day (min/day) of sitting time (95% CI -60.99, -21.58, I2 = 77%, n = 1402), in favour of the intervention group at end point follow-up. The pooled effects showed mean reductions at short (≤ 3 months), medium (>3 to 6 months), and long-term follow-up (>6 months) of -42.42 min/day, -37.23 min/day and -1.65 min/day, respectively. Overall, 16/17 studies were deemed as having a high or unclear risk of bias, and 1/17 was judged to be at a low risk of bias. A total of 46 BCTs (14 unique) were coded for the computer, mobile and wearable components of the interventions. The most frequently coded were "prompts and cues", "self-monitoring of behaviour", "social support (unspecified)" and "goal setting (behaviour)".ConclusionInterventions using computer, mobile and wearable technologies can be effective in reducing SB. Effectiveness appeared most prominent in the short-term and lessened over time. A range of BCTs have been implemented in these interventions. Future studies need to improve reporting of BCTs within interventions and address the methodological flaws identified within the review through the use of more rigorously controlled study designs with longer-term follow-ups, objective measures of SB and the incorporation of strategies to reduce attrition.Trial registrationThe review protocol was registered with PROSPERO: CRD42016038187.
| S-EPMC5553917 | biostudies-literature
Project description:ObjectiveTo systematically review studies assessing the effects of health information technology (health IT) on patient safety outcomes.Materials and methodsThe authors employed the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) statement methods. MEDLINE, Cumulative Index to Nursing Allied Health (CINAHL), EMBASE, and Cochrane Library databases, from 2001 to June 2012, were searched. Descriptive and comparative studies were included that involved use of health IT in a clinical setting and measured effects on patient safety outcomes.ResultsData on setting, subjects, information technology implemented, and type of patient safety outcomes were all abstracted. The quality of the studies was evaluated by 2 independent reviewers (scored from 0 to 10). A total of 69 studies met inclusion criteria. Quality scores ranged from 1 to 9. There were 25 (36%) studies that found benefit of health IT on direct patient safety outcomes for the primary outcome measured, 43 (62%) studies that either had non-significant or mixed findings, and 1 (1%) study for which health IT had a detrimental effect. Neither the quality of the studies nor the rate of randomized control trials performed changed over time. Most studies that demonstrated a positive benefit of health IT on direct patient safety outcomes were inpatient, single-center, and either cohort or observational trials studying clinical decision support or computerized provider order entry.Discussion and conclusionMany areas of health IT application remain understudied and the majority of studies have non-significant or mixed findings. Our study suggests that larger, higher quality studies need to be conducted, particularly in the long-term care and ambulatory care settings.
| S-EPMC6375119 | biostudies-literature
Project description:Objective:To review and analyze the literature to determine whether wearable technologies can predict health outcomes. Materials and methods:We queried Ovid Medline 1946 -, Embase 1947 -, Scopus 1823 -, the Cochrane Library, clinicaltrials.gov 1997 - April 17, 2018, and IEEE Xplore Digital Library and Engineering Village through April 18, 2018, for studies utilizing wearable technology in clinical outcome prediction. Studies were deemed relevant to the research question if they involved human subjects, used wearable technology that tracked a health-related parameter, and incorporated data from wearable technology into a predictive model of mortality, readmission, and/or emergency department (ED) visits. Results:Eight unique studies were directly related to the research question, and all were of at least moderate quality. Six studies developed models for readmission and two for mortality. In each of the eight studies, data obtained from wearable technology were predictive of or significantly associated with the tracked outcome. Discussion:Only eight unique studies incorporated wearable technology data into predictive models. The eight studies were of moderate quality or higher and thereby provide proof of concept for the use of wearable technology in developing models that predict clinical outcomes. Conclusion:Wearable technology has significant potential to assist in predicting clinical outcomes, but needs further study. Well-designed clinical trials that incorporate data from wearable technology into clinical outcome prediction models are required to realize the opportunities of this advancing technology.
| S-EPMC7263786 | biostudies-literature
Project description:BackgroundWearable biometric monitoring devices (BMDs) have the potential to transform the conduct of randomized controlled trials (RCTs) by shifting the collection of outcome data from single measurements at predefined time points to dense continuous measurements.MethodsMethodological systematic review to understand how recent RCTs used BMDs to measure outcomes and to describe the reporting of these RCTs. Electronic search was performed in the Cochrane Central Register of Controlled Trials, PubMed, and EMBASE and completed a page-by-page hand search in five leading medical journals between January 1, 2018, and December 31, 2018. Three reviewers independently extracted all primary and secondary outcomes collected using BMDs, and assessed (1) the definitions used to summarize BMD outcome data; (2) whether the validity, reliability, and responsiveness of sensors was reported; (3) the discrepancy with outcomes prespecified in public clinical trial registries; and (4) the methods used to manage missing and incomplete BMD outcome data.ResultsOf the 4562 records screened, 75 RCTs were eligible. Among them, 24% tested a pharmacological intervention and 57% used an inertial measurement sensor to measure physical activity. Included trials involved 464 outcomes (average of 6 [SD = 8] outcomes per trial). In total, 35 trials used a BMD to measure a primary outcome. Several issues affected the value and transparency of trials using BMDs to measure outcomes. First, the definition of outcomes used in the trials was highly heterogeneous (e.g., 21 diabetes trials had 266 outcomes and 153 had different unique definitions to measure diabetes control), which limited the combination and comparison of results. Second, information on the validity, reliability, and responsiveness of sensors used was lacking in 74% of trials. Third, half (53%) of the outcomes measured with BMDs had not been prespecified, with a high risk of outcome reporting bias. Finally, reporting on the management of incomplete outcome data (e.g., due to suboptimal compliance with the BMD) was absent in 68% of RCTs.ConclusionsUse of BMDs to measure outcomes is becoming the norm rather than the exception in many fields. Yet, trialists need to account for several methodological issues when specifying and conducting RCTs using these novel tools.
| S-EPMC7646072 | biostudies-literature
Project description:We sought to determine the feasibility of using wearable accelerometer devices for determining delirium effects on patients' physical activity patterns and detecting delirium and delirium subtype.Data sourcesPubMed, Embase, and Web of Science.Study selectionScreening was performed using predefined search terms to identify original research studies using accelerometer devices for studying physical activity in relation to delirium.Data extractionKey data were extracted from the selected articles.Data synthesisAmong the 14 studies identified, there were a total of 315 patients who wore accelerometer devices to record movements related to delirium. Eight studies (57.1%) used accelerometer devices to compare the activity of delirious and nondelirious patients. Delirious patients had lower activity levels, lower restlessness index, higher number of daytime immobility minutes, lower mean activity levels during the day, and higher mean activity levels at night. Delirious patients also had lower actual sleep time, lower sleep efficiency, fewer nighttime minutes resting, fewer minutes resting over 24 hours, and smaller change in activity from day to night. Six studies (42.9%) evaluated the feasibility of using accelerometer devices for detection of delirium and its subtype. Variables including number of postural changes during daytime, frequency of ultrashort, short, and continuous movements were significantly different among the nondelirium and the three delirium subtypes.ConclusionsThe results from the studies using accelerometer devices in studying delirium demonstrate that accelerometer devices can potentially detect the differences between delirious and nondelirious patients, detect delirium, and determine delirium subtype. We suggest the following directions as the next steps for future studies using accelerometer devices for predicting delirium: benchmark studies with longer data collection, larger and more diverse population size, incorporating related factors (e.g., medications), and evaluating delirium subtype and severity.
| S-EPMC7063934 | biostudies-literature