991 resultados para Healthcare monitoring


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The health system is one sector dealing with a deluge of complex data. Many healthcare organisations struggle to utilise these volumes of health data effectively and efficiently. Also, there are many healthcare organisations, which still have stand-alone systems, not integrated for management of information and decision-making. This shows, there is a need for an effective system to capture, collate and distribute this health data. Therefore, implementing the data warehouse concept in healthcare is potentially one of the solutions to integrate health data. Data warehousing has been used to support business intelligence and decision-making in many other sectors such as the engineering, defence and retail sectors. The research problem that is going to be addressed is, "how can data warehousing assist the decision-making process in healthcare". To address this problem the researcher has narrowed an investigation focusing on a cardiac surgery unit. This research used the cardiac surgery unit at the Prince Charles Hospital (TPCH) as the case study. The cardiac surgery unit at TPCH uses a stand-alone database of patient clinical data, which supports clinical audit, service management and research functions. However, much of the time, the interaction between the cardiac surgery unit information system with other units is minimal. There is a limited and basic two-way interaction with other clinical and administrative databases at TPCH which support decision-making processes. The aims of this research are to investigate what decision-making issues are faced by the healthcare professionals with the current information systems and how decision-making might be improved within this healthcare setting by implementing an aligned data warehouse model or models. As a part of the research the researcher will propose and develop a suitable data warehouse prototype based on the cardiac surgery unit needs and integrating the Intensive Care Unit database, Clinical Costing unit database (Transition II) and Quality and Safety unit database [electronic discharge summary (e-DS)]. The goal is to improve the current decision-making processes. The main objectives of this research are to improve access to integrated clinical and financial data, providing potentially better information for decision-making for both improved from the questionnaire and by referring to the literature, the results indicate a centralised data warehouse model for the cardiac surgery unit at this stage. A centralised data warehouse model addresses current needs and can also be upgraded to an enterprise wide warehouse model or federated data warehouse model as discussed in the many consulted publications. The data warehouse prototype was able to be developed using SAS enterprise data integration studio 4.2 and the data was analysed using SAS enterprise edition 4.3. In the final stage, the data warehouse prototype was evaluated by collecting feedback from the end users. This was achieved by using output created from the data warehouse prototype as examples of the data desired and possible in a data warehouse environment. According to the feedback collected from the end users, implementation of a data warehouse was seen to be a useful tool to inform management options, provide a more complete representation of factors related to a decision scenario and potentially reduce information product development time. However, there are many constraints exist in this research. For example the technical issues such as data incompatibilities, integration of the cardiac surgery database and e-DS database servers and also, Queensland Health information restrictions (Queensland Health information related policies, patient data confidentiality and ethics requirements), limited availability of support from IT technical staff and time restrictions. These factors have influenced the process for the warehouse model development, necessitating an incremental approach. This highlights the presence of many practical barriers to data warehousing and integration at the clinical service level. Limitations included the use of a small convenience sample of survey respondents, and a single site case report study design. As mentioned previously, the proposed data warehouse is a prototype and was developed using only four database repositories. Despite this constraint, the research demonstrates that by implementing a data warehouse at the service level, decision-making is supported and data quality issues related to access and availability can be reduced, providing many benefits. Output reports produced from the data warehouse prototype demonstrated usefulness for the improvement of decision-making in the management of clinical services, and quality and safety monitoring for better clinical care. However, in the future, the centralised model selected can be upgraded to an enterprise wide architecture by integrating with additional hospital units’ databases.

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Quality oriented management systems and methods have become the dominant business and governance paradigm. From this perspective, satisfying customers’ expectations by supplying reliable, good quality products and services is the key factor for an organization and even government. During recent decades, Statistical Quality Control (SQC) methods have been developed as the technical core of quality management and continuous improvement philosophy and now are being applied widely to improve the quality of products and services in industrial and business sectors. Recently SQC tools, in particular quality control charts, have been used in healthcare surveillance. In some cases, these tools have been modified and developed to better suit the health sector characteristics and needs. It seems that some of the work in the healthcare area has evolved independently of the development of industrial statistical process control methods. Therefore analysing and comparing paradigms and the characteristics of quality control charts and techniques across the different sectors presents some opportunities for transferring knowledge and future development in each sectors. Meanwhile considering capabilities of Bayesian approach particularly Bayesian hierarchical models and computational techniques in which all uncertainty are expressed as a structure of probability, facilitates decision making and cost-effectiveness analyses. Therefore, this research investigates the use of quality improvement cycle in a health vii setting using clinical data from a hospital. The need of clinical data for monitoring purposes is investigated in two aspects. A framework and appropriate tools from the industrial context are proposed and applied to evaluate and improve data quality in available datasets and data flow; then a data capturing algorithm using Bayesian decision making methods is developed to determine economical sample size for statistical analyses within the quality improvement cycle. Following ensuring clinical data quality, some characteristics of control charts in the health context including the necessity of monitoring attribute data and correlated quality characteristics are considered. To this end, multivariate control charts from an industrial context are adapted to monitor radiation delivered to patients undergoing diagnostic coronary angiogram and various risk-adjusted control charts are constructed and investigated in monitoring binary outcomes of clinical interventions as well as postintervention survival time. Meanwhile, adoption of a Bayesian approach is proposed as a new framework in estimation of change point following control chart’s signal. This estimate aims to facilitate root causes efforts in quality improvement cycle since it cuts the search for the potential causes of detected changes to a tighter time-frame prior to the signal. This approach enables us to obtain highly informative estimates for change point parameters since probability distribution based results are obtained. Using Bayesian hierarchical models and Markov chain Monte Carlo computational methods, Bayesian estimators of the time and the magnitude of various change scenarios including step change, linear trend and multiple change in a Poisson process are developed and investigated. The benefits of change point investigation is revisited and promoted in monitoring hospital outcomes where the developed Bayesian estimator reports the true time of the shifts, compared to priori known causes, detected by control charts in monitoring rate of excess usage of blood products and major adverse events during and after cardiac surgery in a local hospital. The development of the Bayesian change point estimators are then followed in a healthcare surveillances for processes in which pre-intervention characteristics of patients are viii affecting the outcomes. In this setting, at first, the Bayesian estimator is extended to capture the patient mix, covariates, through risk models underlying risk-adjusted control charts. Variations of the estimator are developed to estimate the true time of step changes and linear trends in odds ratio of intensive care unit outcomes in a local hospital. Secondly, the Bayesian estimator is extended to identify the time of a shift in mean survival time after a clinical intervention which is being monitored by riskadjusted survival time control charts. In this context, the survival time after a clinical intervention is also affected by patient mix and the survival function is constructed using survival prediction model. The simulation study undertaken in each research component and obtained results highly recommend the developed Bayesian estimators as a strong alternative in change point estimation within quality improvement cycle in healthcare surveillances as well as industrial and business contexts. The superiority of the proposed Bayesian framework and estimators are enhanced when probability quantification, flexibility and generalizability of the developed model are also considered. The empirical results and simulations indicate that the Bayesian estimators are a strong alternative in change point estimation within quality improvement cycle in healthcare surveillances. The superiority of the proposed Bayesian framework and estimators are enhanced when probability quantification, flexibility and generalizability of the developed model are also considered. The advantages of the Bayesian approach seen in general context of quality control may also be extended in the industrial and business domains where quality monitoring was initially developed.

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As a result of growing evidence regarding the effects of environmental characteristics on the health and wellbeing of people in healthcare facilities (HCFs), more emphasis is being placed on, and more attention being paid to, the consequences of design choices in HCFs. Therefore, we have critically reviewed the implications of key indoor physical design parameters, in relation to their potential impact on human health and wellbeing. In addition, we discussed these findings within the context of the relevant guidelines and standards for the design of HCFs. A total of 810 abstracts, which met the inclusion criteria, were identified through a Pubmed search, and these covered journal articles, guidelines, books, reports and monographs in the studied area. Of these, 231 full publications were selected for this review. According to the literature, the most beneficial design elements were: single-bed patient rooms, safe and easily cleaned surface materials, sound-absorbing ceiling tiles, adequate and sufficient ventilation, thermal comfort, natural daylight, control over temperature and lighting, views, exposure and access to nature, and appropriate equipment, tools and furniture. The effects of some design elements, such as lighting (e.g. artificial lighting levels) and layout (e.g. decentralized versus centralized nurses’ stations), on staff and patients vary, and “the best design practice” for each HCF should always be formulated in co-operation with different user groups and a multi-professional design team. The relevant guidelines and standards should also be considered in future design, construction and renovations, in order to produce more favourable physical indoor environments in HCFs.

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Understanding the physical characteristics of the indoor environment that affect human health and wellbeing is the key requirement underpinning the beneficial design of a healthcare facility (HCF). We reviewed and summarised physical factors of the indoor environment reported to affect human health and wellbeing in HCFs. Research materials included articles identified in a Pubmed search, guidelines, books, reports and monographs, as well as the bibliographies of review articles in the area studied. Of these, 209 publications were selected for this review. According to the literature, there is evidence that the following physical factors of the indoor environment affect the health and wellbeing of human beings in an HCF: safety, ventilation and HVAC systems, thermal environment, acoustic environment, interior layout and room type, windows (including daylight and views), nature and gardens, lighting, colour, floor covering, furniture and its placement, ergonomics, wayfinding, artworks and music. Some of these, in themselves, directly promote or hinder health and wellbeing, but the physical factors may also have numerous indirect impacts by influencing the behaviour, actions, and interactions of patients, their families and the staff members. The findings of this research enable a good understanding of the different physical factors of the indoor environment on health and wellbeing and provide a practical resource for those responsible for the design and operate the facilities as well as researchers investigating these factors. However, more studies are needed in order to inform the design of optimally beneficial indoor environments in HCFs for all user groups.

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Remote monitoring for heart failure has been evaluated in numerous systematic reviews. The aim of this meta-review was to appraise their quality and synthesise results. We electronically searched online databases, performed a forward citation search and hand-searched bibliographies. Systematic reviews of remote monitoring interventions that were used for surveillance of heart failure patients were included. Seven (41%) systematic reviews pooled results for meta-analysis. Eight (47%) considered all non-invasive remote monitoring strategies. Five (29%) focused on telemonitoring. Four (24%) included both non-invasive and invasive technologies. According to AMSTAR criteria, ten (58%) systematic reviews were of poor methodological quality. In high quality reviews, the relative risk of mortality in patients who received remote monitoring ranged from 0.53 (95% CI=0.29-0.96) to 0.88 (95% CI=0.76-1.01). High quality reviews also reported that remote monitoring reduced the relative risk of all-cause (0.52; 95% CI=0.28-0.96 to 0.96; 95% CI=0.90–1.03) and heart failure-related hospitalizations (0.72; 95% CI=0.64–0.81 to RR 0.79; 95% CI=0.67-0.94) and, as a consequence, healthcare costs. As the high quality reviews reported that remote monitoring reduced hospitalizations, mortality and healthcare costs, research efforts should now be directed towards optimising these interventions in preparation for more widespread implementation.

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Background/aims: Remote monitoring for heart failure has not only been evaluated in a large number of randomised controlled trials, but also in many systematic reviews and meta-analyses. The aim of this meta-review was to identify, appraise and synthesise existing systematic reviews that have evaluated the effects of remote monitoring in heart failure. Methods: Using a Cochrane methodology, we electronically searched all relevant online databases and search engines, performed a forward citation search as well as hand-searched bibliographies. Only fully published systematic reviews of invasive and/or non-invasive remote monitoring interventions were included. Two reviewers independently extracted data. Results: Sixty-five publications from 3333 citations were identified. Seventeen fulfilled the inclusion and exclusion criteria. Quality varied with A Measurement Tool to Assess Systematic Reviews (AMSTAR scores) ranging from 2 to 11 (mean 5.88). Seven reviews (41%) pooled results from individual studies for meta-analysis. Eight (47%) considered all non-invasive remote monitoring strategies. Four (24%) focused specifically on telemonitoring. Four (24%) included studies investigating both non-invasive and invasive technologies. Population characteristics of the included studies were not reported consistently. Mortality and hospitalisations were the most frequently reported outcomes 12 (70%). Only five reviews (29%) reported healthcare costs and compliance. A high degree of heterogeneity was reported in many of the meta-analyses. Conclusions: These results should be considered in context of two negative RCTs of remote monitoring for heart failure that have been published since the meta-analyses (TIM-HF and Tele-HF). However, high quality reviews demonstrated improved mortality, quality of life, reduction in hospitalisations and healthcare costs.

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The care processes of healthcare providers are typically considered as human-centric, flexible, evolving, complex and multi-disciplinary. Consequently, acquiring an insight in the dynamics of these care processes can be an arduous task. A novel event log based approach for extracting valuable medical and organizational information on past executions of the care processes is presented in this study. Care processes are analyzed with the help of a preferential set of process mining techniques in order to discover recurring patterns, analyze and characterize process variants and identify adverse medical events.

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The key requirements for enabling real-time remote healthcare service on a mobile platform, in the present day heterogeneous wireless access network environment, are uninterrupted and continuous access to the online patient vital medical data, monitor the physical condition of the patient through video streaming, and so on. For an application, this continuity has to be sufficiently transparent both from a performance perspective as well as a Quality of Experience (QoE) perspective. While mobility protocols (MIPv6, HIP, SCTP, DSMIP, PMIP, and SIP) strive to provide both and do so, limited or non-availability (deployment) of these protocols on provider networks and server side infrastructure has impeded adoption of mobility on end user platforms. Add to this, the cumbersome OS configuration procedures required to enable mobility protocol support on end user devices and the user's enthusiasm to add this support is lost. Considering the lack of proper mobility implementations that meet the remote healthcare requirements above, we propose SeaMo+ that comprises a light-weight application layer framework, termed as the Virtual Real-time Multimedia Service (VRMS) for mobile devices to provide an uninterrupted real-time multimedia information access to the mobile user. VRMS is easy to configure, platform independent, and does not require additional network infrastructure unlike other existing schemes. We illustrate the working of SeaMo+ in two realistic remote patient monitoring application scenarios.

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Thomas, R., Spink, S., Durbin, J. & Urquhart, C. (2005). NHS Wales user needs study including knowledgebase tools report. Report for Informing Healthcare Strategy implementation programme. Aberystwyth: Department of Information Studies, University of Wales Aberystwyth. Sponsorship: Informing Healthcare, NHS Wales

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The aging population in many countries brings into focus rising healthcare costs and pressure on conventional healthcare services. Pervasive healthcare has emerged as a viable solution capable of providing a technology-driven approach to alleviate such problems by allowing healthcare to move from the hospital-centred care to self-care, mobile care, and at-home care. The state-of-the-art studies in this field, however, lack a systematic approach for providing comprehensive pervasive healthcare solutions from data collection to data interpretation and from data analysis to data delivery. In this thesis we introduce a Context-aware Real-time Assistant (CARA) architecture that integrates novel approaches with state-of-the-art technology solutions to provide a full-scale pervasive healthcare solution with the emphasis on context awareness to help maintaining the well-being of elderly people. CARA collects information about and around the individual in a home environment, and enables accurately recognition and continuously monitoring activities of daily living. It employs an innovative reasoning engine to provide accurate real-time interpretation of the context and current situation assessment. Being mindful of the use of the system for sensitive personal applications, CARA includes several mechanisms to make the sophisticated intelligent components as transparent and accountable as possible, it also includes a novel cloud-based component for more effective data analysis. To deliver the automated real-time services, CARA supports interactive video and medical sensor based remote consultation. Our proposal has been validated in three application domains that are rich in pervasive contexts and real-time scenarios: (i) Mobile-based Activity Recognition, (ii) Intelligent Healthcare Decision Support Systems and (iii) Home-based Remote Monitoring Systems.

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Background: On-going surveillance of behaviours during pregnancy is an important but overlooked population health activity that is particularly lacking in Ireland. Few, if any, nationally representative estimates of most maternal behaviours and experiences are available. While on-going surveillance of maternal behaviours has not been a priority thus far in European countries including Ireland, on-going surveillance was identified as a key priority in the United States (US) during the 1980’s when the Pregnancy Risk Assessment Monitoring System (PRAMS), was established. Today, PRAMS is the only surveillance programme of maternal behaviours and experiences world-wide. Although on-going prevalence estimates are required in Ireland, studies which examine the offspring health effects of maternal behaviours are also required, since various questions regarding maternal exposures and their offspring health effects remain unanswered. Gestational alcohol consumption is one such important maternal exposure which is common in pregnancy, though its offspring health effects are unclear, particularly at lower or moderate levels. Thus, guidelines internationally have not reached consensus on safe alcohol recommendations for pregnant women. The aims of this thesis are to implement the PRAMS in Ireland (PRAMS Ireland), to describe the prevalence of health behaviours around the time of pregnancy in Ireland and to examine the effect of health behaviours on pregnancy and child outcomes (specifically the relationship between alcohol use during pregnancy and infant and child growth). Structure: In Chapter 1, a brief background and rationale for the work, as well as the thesis aims and objective is provided. A detailed description of the design and implementation of PRAMS Ireland is described in Chapter 2. Chapter 3 and Chapter 4 describe the methodological results of the implementation of the PRAMS Ireland pilot study and PRAMS Ireland main study. In Chapter 5, a comparison of alcohol prevalence in two Irish studies (PRAMS Ireland and Growing up in Ireland (GUI)) and one multi-centre prospective cohort study, Screening for Pregnancy Endpoints (SCOPE) Study is detailed. Chapter 6 describes findings on adherence to National Clinical Guidelines on health behaviours and nutrition around the time of pregnancy in PRAMS Ireland. Findings on exposure to alcohol use in pregnancy and infant growth outcomes are described in Chapter 7 and Chapter 8. The results of analysis conducted to examine the impact of gestational alcohol use on offspring growth trajectories to age ten are described in Chapter 9. Finally, a discussion of the findings, strengths and limitations of the thesis, direction for future research, policy, practice and public health implications are discussed in Chapter 10.Results: Implementation of PRAMS: PRAMS may be an effective system for the surveillance of health behaviours around the time of pregnancy in the Irish context. PRAMS Ireland had high response rates (67% and 61% response rates in the pilot and main study respectively), high item completion rates and valid prevalence estimates for many health behaviours. Examining prevalence of health behaviours: We found high levels of alcohol consumption before and during pregnancy, poor adherence to healthy diets and high levels of smoking before and during pregnancy among women in Ireland. Socially disadvantaged women had higher rates of deleterious health behaviours before pregnancy, although women with the most deleterious behaviour profiles before pregnancy appeared to experience the greatest gain in protective health behaviours during pregnancy. The impact of alcohol use on infant and offspring growth: We found that low and moderate levels of alcohol use did not impact on birth outcomes or offspring growth whereas heavy alcohol consumption resulted in reduced birth length and birth weight; however, this finding was not consistently observed across all studies. Selection, reporting and confounding biases which are common in observational research could be masking harmful effects. Conclusion: PRAMS is a valid and feasible method of surveillance of health behaviours around the time of pregnancy in Ireland. A surveillance program of maternal behaviours and experiences is immediately warranted due to high levels of deleterious health behaviours around the time of pregnancy in Ireland. Although our results do not indicate any evidence of harm, given the quality of evidence available, abstinence and advice of abstinence from alcohol may be the most prudent choice for patients and healthcare professionals respectively. Further studies of the effects of gestational alcohol use are required; particularly those which can reduce selection bias, reporting bias and confounding.

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Background: Developing complex interventions for testing in randomised controlled trials is of increasing importance in healthcare planning. There is a need for careful design of interventions for secondary prevention of coronary heart disease (CHD). It has been suggested that integrating qualitative research in the development of a complex intervention may contribute to optimising its design but there is limited evidence of this in practice. This study aims to examine the contribution of qualitative research in developing a complex intervention to improve the provision and uptake of secondary prevention of CHD within primary care in two different healthcare systems.

Methods: In four general practices, one rural and one urban, in Northern Ireland and the Republic of Ireland, patients with CHD were purposively selected. Four focus groups with patients (N = 23) and four with staff (N = 29) informed the development of the intervention by exploring how it could be tailored and integrated with current secondary prevention activities for CHD in the two healthcare settings. Following an exploratory trial the acceptability and feasibility of the intervention were discussed in four focus groups (17 patients) and 10 interviews (staff). The data were analysed using thematic analysis.

Results: Integrating qualitative research into the development of the intervention provided depth of information about the varying impact, between the two healthcare systems, of different funding and administrative arrangements, on their provision of secondary prevention and identified similar barriers of time constraints, training needs and poor patient motivation. The findings also highlighted the importance to patients of stress management, the need for which had been underestimated by the researchers. The qualitative evaluation provided depth of detail not found in evaluation questionnaires. It highlighted how the intervention needed to be more practical by minimising administration, integrating role plays into behaviour change training, providing more practical information about stress management and removing self-monitoring of lifestyle change.

Conclusion: Qualitative research is integral to developing the design detail of a complex intervention and tailoring its components to address individuals' needs in different healthcare systems. The findings highlight how qualitative research may be a valuable component of the preparation for complex interventions and their evaluation.

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Objectives: To explore children's views on microneedle use for this population, particularly as an alternative approach to blood sampling, in monitoring applications, and so, examine the acceptability of this approach to children.

Methods: Focus groups were conducted with children (aged 10-14 years) in a range of schools across Northern Ireland. Convenience sampling was employed, i.e. children involved in a university-directed community-outreach project (Pharmacists in Schools) were recruited.

Key findings: A total of 86 children participated in 13 focus groups across seven schools in Northern Ireland. A widespread disapproval for blood sampling was evident, with pain, blood and traditional needle visualisation particularly unpopular aspects. In general, microneedles had greater visual acceptability and caused less fear. A patch-based design enabled minimal patient awareness of the monitoring procedure, with personalised designs, e.g. cartoon themes, favoured. Children's concerns included possible allergy and potential inaccuracies with this novel approach; however, many had confidence in the judgement of healthcare professionals if deeming this technique appropriate. They considered paediatric patient education critical for acceptance of this new approach and called for an alternative name, without any reference to 'needles'.

Conclusions: The findings presented here support the development of blood-free, minimally invasive techniques and provide an initial indication of microneedle acceptability in children, particularly for monitoring purposes. A proactive response to these unique insights should enable microneedle array design to better meet the needs of this end-user group. Further work in this area is recommended to ascertain the perspectives of a purposive sample of children with chronic conditions who require regular monitoring. © 2013 Royal Pharmaceutical Society.

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OBJECTIVES: Microneedle (MN) arrays could offer a pain-free, minimally invasive approach to monitoring. This is envisaged to be particularly beneficial for younger patients, but parents' views to date are unknown. The aim of this study was to explore parental perceptions of MN-mediated ISF monitoring, as an alternative to the use of conventional blood sampling, and to understand the important factors for technique approval.

METHODS: Semi-structured interviews were conducted with parents with recent experience of a premature birth. Recruitment was through the Northern Ireland premature infant charity, Tinylife. Interviews progressed until data saturation was reached and thematic analysis employed.

KEY FINDINGS: The study included 16 parents. Parental support for MN-mediated monitoring was evident, alongside the unpopularity of traditional blood sampling in neonates. Factors facilitating MN approval included the opportunity for pain reduction, the simplicity of the procedure, the potential for increased parental involvement and the more favourable appearance, owing to the minute size of MNs and similarities with a sticking plaster. Confirmation of correct application, a pain-free patch removal and endorsement from trusted healthcare professionals were important.

CONCLUSION: These findings will inform researchers in the field of MN development and enlighten practitioners regarding parental distress resulting from conventional blood sampling. Further work is necessary to understand MN acceptability among practitioners. This work should assist in the development of an acceptable MN device and facilitate the reduction of parental distress.