Intensity Of Asthmatic Exacerbations aggravates under the influence of environmental tobacco smoke and allergic sensitization pathways (Anderson et al. 2017). Accordingly, physicians require customizing asthma medication in accordance with the level of blood eosinophils and mechanisms of allergic sensitization that dominate the individuals of various age groups in different geographical regions. Evidence-based analysis by (Huckvale et al. 2012) reveals the incapacity of the existing asthma management applications in the effective enhancement of self-management approaches warranted for controlling the clinical manifestations of the asthmatic patients. Mobile based calculators fail to provide comprehensive and reliable asthma information in the context of utilizing appropriate tools and techniques for the systematic management of asthmatic manifestations (Huckvale et al. 2012). Generic information tools and applications utilized for asthma management fail to comply with the accepted standards of medical practice and therefore do not generate the desirable clinical benefits to the asthma patients (Huckvale et al. 2015). The necessitates the requirement of developing coordinated quality assurance systems in accordance with the changing healthcare needs of the patients affected with asthmatic manifestations. Analysis by (Burbank et al. 2015) indicates the significance of mobile applications in terms of enhancing the satisfaction rate of the asthmatic patients. Mobile applications prove to enhance the perception of asthmatic symptoms among the affected patients that resultantly facilitates the administration of self-management interventions warranted for reducing the risk of adverse asthmatic manifestations (Burbank et al. 2015).
Identification of asthma triggers through various mobile applications assist the assist the timely administration of controller medications for the systematic and timely acquisition of the treatment outcomes (Burbank et al. 2015). Technology assisted self-reported asthma questionnaire helps the asthma patients in recording their adverse manifestations attributing to shortness of breath, nocturnal dyspnoea and personal care challenges. Accordingly, asthma patients utilize appropriate rescue medication for instantly suppressing the adverse symptomatology during medical emergency (Burbank et al. 2015). Asthma self-care interventions require the systematic integration of various technology-assisted systems and processes for elevating the quality of life and wellness outcomes of the asthmatic patients across the community environment. Technology assisted asthma management applications prove advantageous for the illiterate patients or for patients with low literacy level. These applications effectively integrate the behaviour change norms and low-literacy design protocols for the systematic enhancement of asthma control practices and associated outcomes. Adherence to asthma management protocols with the systematic utilization of technology assisted applications (in the treated patients) reciprocally reduces the frequency of their asthma attacks and the resultant administration of rescue medications (Grossman et al. 2017). The enhancement of asthma management application systems requires the incorporation of various usability interventions through the assistance of healthcare agencies (Sage et al. 2017). Usability tests assist in the systematic validation of the user-centred asthma management design to facilitate the pattern of asthmatic self-regulation among the asthma patients. Asthma management applications assist the users in terms of undertaking calculated judgements facilitated by enhancement of their attitudes, beliefs, knowledge and reactions regarding adverse asthma manifestations (Sage et al. 2017).
The precise self-judgement of asthma symptoms by the asthmatic patients reduces their risk of experiencing life threatening complications during the adverse episodes of acute asthma exacerbations. The personalized asthma management applications provide significant information related to asthma complications and effectively integrate the asthma self-management features with the user-centred design to facilitate the medication adherence of the asthma patients in the context of improving the pattern of their asthma control (Sage et al. 2017). Evidence-based research literature advocates the requirement of implementing asthma control guidelines with the systematic utilization of computer generated applications by the treated patients (Dexheimer et al. 2014). A patient-centred asthma management application system requires incorporating the clinical history of the asthmatic patient while including the list of allergens that might aggravate the pattern of acute asthma exacerbation and associated debilitating manifestations (NIH 2007). This will assist in the systematic identification of asthma triggers by the treated patient in the context of administering remedial interventions for controlling the asthmatic adverse outcomes. The asthma management system requires incorporating detailed guidelines for directing the patients in terms of undertaking in-vitro evaluation or skin testing interventions with the objective of evaluating their sensitivity to inhalant allergens across the community environment (NIH 2007). This technology assisted system also warrants the systematic inclusion of information regarding patient’s sensitivity to seasonal allergens as well as past test results in the context of undertaking preventive and prophylactic treatment measures for reducing the risk of experiencing adverse asthmatic manifestations across the community environment (NIH 2007). Interactive asthma management system focuses on the development of technology assisted application for facilitating periodic interactions between caregivers, asthma patients as well as their family members (Dabbs et al. 2009). This systematically assists in the instant communication of medical emergencies to the treating physician as well as patient’s family members for their earliest mitigation. The incorporation of user-centred design in the asthma management applications assists in the development of self-care behaviours in the treated patients (Dabbs et al. 2009). Indeed, with the acquisition of self-care attitudes the asthmatic patients attain awareness regarding a variety of health indicators requiring utilization for the enhancement of their quality of life and associated wellness-outcomes.
Childhood asthma management is based on the healthcare goals that focus on the normalization of the lives of the asthmatic children across the community environment. The asthma management applications take into consideration the pulmonary functionality of children in various age groups while designing assistive methodology in the context of reducing their risk of experiencing exacerbation episodes. The thorough understanding of the genetic profile of the asthmatic children provides an insight to the healthcare professionals in the context of developing protective measures for reducing the frequency of occurrence of clinical complications under the influence of asthma attack (Potter 2009). The guidelines for the systematic implementation of these protective measures require incorporation in various asthma management applications with the objective of reducing the exposure of asthmatic patients to allergens, food additives, tobacco smoke, viral invasions and emotional and behavioural attributes (Potter 2009). Asthma management applications require systematic customization while considering the environmental factors of the asthmatic patients in the context of reducing their predisposition towards experiencing asthma exacerbation and associated adversities. The physicians and healthcare professionals require emphasizing the requirement of including evidence-based asthma management steps in various asthma management application systems in the healthcare settings (Geryk et al. 2016). These evidence-based steps include the medication pop-up messages, refill reminders and guidelines regarding the appropriate utilization of inhalers. The asthma management applications should prove to be compatible and user-friendly on various interfaces (including androids and iPhones) in the context of their easy utilization by asthma patients of various age groups (Geryk et al. 2016). The integrated asthma management applications in the medical facilities require incorporating the personalised asthma action plan in accordance with the healthcare requirements of the asthma patients of various age groups and geographical diversities (Pinnock 2015). The utilization of automated disease detection mechanisms remains limited among the asthma patients (Dexheimer et al. 2013). This indicates the elevated requirement of developing asthma management applications for inducing appropriate patient responses during medical emergencies in the context of substantially reducing the asthma related fatalities across the community environment.
The asthma management applications should consider the inclusion of the side effects of asthmatic medications for reducing the probability of occurrence of adverse events after their administration to the asthmatic patients (Dexheimer et al. 2013). The asthma management system must also guide the asthmatic patients in terms of utilizing evidence-based conventions for self-medicating their asthma exacerbation episodes in the absence of external clinical assistance. The asthma management guidelines advocate the requirement of maintaining pulmonary functionality of the asthmatic patients in the context of reducing their predisposition towards experiencing the pattern of pulmonary function deterioration in the longer term. These guidelines also emphasize the need of daily asthma control by enhancing the quality of life of the treated patients. The asthma management applications require the systematic inclusion of these conventions for reducing the pattern of health risks of the asthmatic patients across the community environment. The systematic asthma management system requires incorporating GINA (Global Initiative for Asthma) treatment model for antagonizing the pattern of asthma exacerbations and associated adverse clinical manifestations among the affected patients. The technology-assisted asthma management systems require embedding multiple steps of GINA approaches for controlling the intensity and pattern of adverse asthmatic manifestations in the asthmatic patients. The initial step directs the administration of β2-agonists in accordance with their requirement in medical emergencies (O’Byrne 2010). These rapid-acting drugs require inhalation by the asthmatic patients for the instant management of acute asthma exacerbation. The second step directs the administration of high-dose inhaled corticosteroids with β2-agonists as well as oral corticosteroids in accordance with the intensity and frequency of adverse asthma manifestations (O’Byrne 2010). The third step advocates the requirement of reducing the dosage of asthma treatment medications in accordance with the reduction in asthma symptoms following the acquisition of its sustained control among treated patients (O’Byrne 2010). The systematic asthma management system requires incorporating a range of indicators in accordance with the patient age groups and environmental influences. These indicators include the pattern of wheezing, cough, recurrent difficulty in breathing and chest tightness (Wechsler 2009). The indicators also include the clinical scenarios when the asthmatic symptoms worsen under the direct influence of exercise intervention, viral infection, animal hairs, dust mites, mold, smoke, pollen, weather alterations, emotional expression, airborne dust/chemical and menstrual dysregulation (Wechsler 2009). The symptoms might worsen at night time thereby indicating the requirement of administering therapeutic regimen for their effective control. The systematic asthma control applications must consider the pattern of these indicators as well as asthma symptomatology for effectively controlling asthma related adversities among the treated patients (Wechsler 2009).
An effective computerized asthma management application system will systematically integrate the following subsystems in the hospital setting.
An effective information support system will provide user-friendly interface to the asthma patients for systematically handling their clinical complications. This system will incorporate the details of the adverse effects of asthma associated chemicals for reducing the frequency of irritants exposure to the predisposed patients (Gabb & Blake 2016).The informatics infrastructure will disseminate useful information related to the asthma control measures to the asthmatic patients with the utilization of mobile devices, digital diaries, laptops, computer systems and other web-based platforms. This will eventually improve the knowledge (of asthma management conventions) of the treated patients. Resultantly, the pattern of self-reported asthma complications will facilitate the timely administration of treatment interventions by the medical practitioners for reducing the frequency of asthma exacerbations in the patient population. For example, patients will understand the influence of hormonal contraceptive administration on the self-reported cases of physician diagnosed asthma with the systematic utilization of informatics infrastructure (Nwaru & Sheikh 2015). Similarly, obese women will understand the influence of hormonal contraceptives administration on the frequency of their asthma exacerbations as well as the risk of developing associated clinical co-morbidities. A systematic and well-integrated informatics base will also integrate the information related to the epidemiology of asthma in various geographical regions. Accordingly, the physicians will be able to identify the overall burden of asthma and associated adverse manifestations in the community environment. These outcomes will provide a thorough insight to the clinicians and healthcare professionals in the context of configuring systematic primary care interventions for reducing the predisposition of asthmatic patients in terms of experiencing intensified exacerbations and associated morbidities. The informatics infrastructure will facilitate physician’s access to the information regarding the annual prevalence of patient-reported respiratory symptoms in the context of systematically differentiating the recorded manifestations from non-asthmatic complications (Mukherjee et al. 2016). Physicians will resultantly gain thorough insight for configuring community-based prescriptions for the systematic treatment of asthma complications and associated co-morbid states attributing to chronic obstructive pulmonary disease, pleural effusion, respiratory infection, upper airway dysfunction, allergic conditions and hyperventilation. The systematic configuration of respiratory prescriptions will also reduce the unnecessary cost incurred in prescribing inappropriate antibiotics and anti-allergy medications under the influence of incomplete information regarding asthma complications of the treated patients (Mukherjee et al. 2016). Evidence-based clinical literature advocates the requirement of developing informatics-assisted guideline delivery approaches for improving the pattern of homogeneity in the healthcare of the asthma patients. The currently prevalent paediatric asthma convention in the emergency room settings provides a thorough insight regarding the emergency management of the pattern of respiratory exacerbations in the paediatric patients. For example, the oxygen saturation level of more than 94% would suffice the requirement of administering three consecutive dosages of short acting beta agonists to the affected patients. Similarly, the emergency disposition of the treated asthma patients would require the systematic administration of patient education interventions in the context of improving the level of their compliance to the treatment follow-up requirements, asthma action plan, environmental control measures and medication inhalation mechanism. The integration of these evidence-based approaches through a well-developed informatics infrastructure will enhance the vision, knowledge, beliefs, perspectives, understanding, perception and thoughtfulness of the healthcare teams as well as asthma patients in the context of undertaking effective asthma management interventions in the clinical and residential settings (Dexheimer et al. 2013). The presently incorporated informatics infrastructure in the clinical settings assists in facilitating the implementation of an accurate diagnostic detection and therapeutic management system through the systematic integration of electronic health record, computerized respiratory intervention documentation approaches and whiteboard application as well as respiratory therapy strategies (Dexheimer et al. 2009).
The presently available electronic medical record systems in the asthma settings prove to be the primary repository of the significant patient information attributing to the test reports, caregiver communication, scanned consultation documents, procedure notes, clinical notes as well as respiratory problem list (Dexheimer et al. 2009).The recommended asthma management system advocates the requirement of linking the electronic medical records of the asthmatic patients with their mobile sets or digital diaries. Asthma patients would gain their individualized medical records with the utilization of a secured username and password. This will effectively safeguard their protected health information and improve their knowledge of asthma manifestations and recommended treatment regimen. Accordingly, after each physician visit the asthma patients will be able to access the updated medical records and follow the prescribed treatment regimen without any misunderstanding or inadequacy. The treating physicians will also gain access to the patient records and update the clinical findings in EMR after each follow-up visit. Direct remote accessibility of physicians and patients to the electronic medical records will reciprocally increase the patient compliance to the evidence-based asthma management guidelines and interventions. This type of asthma management system will also reduce the frequency of unnecessary OPD visits (of the treated patients) and enhance the quality and safety of healthcare interventions in a cost-effective manner. The incorporation of an electronic disease registry in the electronic medical record will facilitate the systematic incorporation of patient’s chronic conditions (Xi et al. 2015). Eventually, the inclusion of patient’s established co-morbid states in the electronic database will assist in the objective analysis of the extent of their influence on patient’s existing asthmatic manifestations by the treating physician. This will substantially facilitate the systematic configuration of evidence-based therapeutic strategies warranted for the establishment of an effective asthma control mechanism across the community environment. The electronic medical record system in the recommended asthma management application requires incorporating a well-developed asthma templatewarranting periodic enhancement by the treating physician in concordance with the IT team. This step will evidentially facilitate the systematic recording of asthma intensity and severity with the objective of recommending an appropriate therapeutic regimen for asthma patients (Davis et al. 2010). The development of an efficient electronic medical record system will evidentially improve the quality of asthma treatment modalities in the clinical settings. This will substantially reduce the length of stay of asthma patients in the medical facilities as well as the frequency of their respiratory exacerbation episodes during the post-discharge follow-up period. Electronic medical record system considerably assists in evaluating the potential risk factors of patient’s asthma exacerbation episodes (Laforest et al. 2015). Accordingly, the physicians acquire the insight of prescribing oral antibiotics, corticosteroids and other prophylactic medication for preventing the onset and establishment of asthma manifestations across the community environment. The systematic incorporation of EMR in patient’s asthma management system will assist the physicians, nurses as well as care takers in terms of evaluating the clinical condition of asthma patients in a timely manner (Manca 2015). Furthermore, EMR incorporation will facilitate the daily recording of patient’s blood pressure, cholesterol level, respiratory rate and weight and body mass index. EMR utilization will identify new screening targets and assist the physicians in undertaking quality measures for reducing the progression and establishment of asthma episodes across the community environment (Manca 2015).
The recommended asthma management application system will effectively include the emergency severity index with the objective of developing an enhanced triage scoring system for the systematic segregation of asthma patients in the clinical setting. The ESI (emergency severity index) will require direct incorporation in patient’s medical record. The physicians will gain accessibility to the ESI in emergency care settings for instantly identifying the suspected cases of asthma exacerbation and associated co-morbid states. The ESI intervention will identify the severity of patient’s asthmatic condition in accordance with the pattern of vital sign, clinical history and presenting complaints (Elias et al. 2015). The incorporation of CTA tool in the asthma management system will facilitate the appropriate utilization of clinical decision support strategies in the clinical settings. The CTA system will calculate the severity score for the asthmatic patients and accordingly the physicians could evaluate the requirement of administering lifesaving therapy during episodes of acute respiratory exacerbation (Elias et al. 2015). The severity scores would require direct access by the treating physicians through their mobile applications, digital diaries or computer systems. The severity score – 1 will suffice the requirement of administering potentially life saving drugs for effectively controlling the unstable state of the asthmatic patient (Elias et al. 2015). However, the severity score – 2 will indicate the state of disorientation, lethargy, confusion, distress and pain experienced by the asthma patient in the clinical setting. The score – 3 will reveal the state of patient’s clinical complexity warranting the urgent administration of medical interventions (Elias et al. 2015). Furthermore, the scores4 and 5 will indicate the decreased clinical complications of the asthmatic patient that would not require the urgent administration of medical interventions for the immediate acquisition of the treatment outcomes (Elias et al. 2015). The systematic utilization of this scoring system through CTA will assist the physicians and nurses in terms of cost-effectively administering focussed and goal oriented medical interventions for reducing the burden of asthma epidemic across the community environment. The presently deployed rapid triage system is based on lean approaches utilized in the hospital settings for reducing the patient’s wait times and left without being seen cases (Murrell, Offerman & Kauffman 2011). These lean approaches emphasize the systematic identification of extensive triage and non-value added steps for their effective elimination from the rapid triage methodology. However, the presently recommended CTA approach would integrate the findings of patient’s systemic evaluation, physical assessment and history of present illness with the utilization of standardized triage conventions for enhancing the treatment outcomes. The incorporation of value-stream mapping and direct visualization approaches in the CTA system will eventually customize the asthma management interventions in accordance with the individualized patient care requirements and treatment challenges encountered in the clinical and residential settings.
The respiratory manifestations of patients require computerized recording in the context of acquiring a precise and definitive diagnosis indicative of asthma or other respiratory conditions. Accordingly, physicians require recording the severity, intensity and pattern of patient’s airway obstruction as well as variation in the obstruction intensity for confirming the existence of asthma in the affected patient (Brigham & West 2015). The parameters of asthma detection require systematic incorporation in the recommended technology assisted asthma management system for the timely detection of respiratory manifestations of asthmatic patients in the clinical setting. The diagnosis detection mechanism would evaluate the clinical context of the patients and correlate the same with their asthma diagnosis for the timely administration of appropriate treatment interventions. Secured connectedness of clinical database with patients’ personalized computer-based applications would provide them a thorough insight regarding their asthma manifestations as well as the recommended prophylactic interventions warranted for reducing their risk of experiencing intense respiratory exacerbation, cough and chest congestion and associated health adversities. The systematic asthma management application should incorporate various parameters warranted for the objective measurement of patient’s bronchial hyperresponsiveness as well as pulmonary function (Kaplan et al. 2009). The application must possess the capacity of tracking the majority of asthma symptoms like expectoration, cough, wheezing and episodic breathlessness in terms of level II evidence (Kaplan et al. 2009). diagnosis detection functionality should evidentially record the spirometry finding with the objective of recording pulmonary function of the asthmatic patient. The pulmonary function measurement would require the systematic assessment of the variability, reversibility and severity of pulmonary airflow limitation as well as peak expiratory flow evaluation in accordance with the asthma assessment conventions. The diagnosis detection application would also record the allergic status of asthma patient in terms of level III evidence for selecting the appropriate rapid action inhalers in the context of their prospective utilization during medical emergencies (Kaplan et al. 2009). The computer-based diagnosis detection system would require incorporating the findings of the diagnostic interventions including inflammation measurement, serial peak-flow monitoring and bronchial challenge tests (in terms of level II evidence) for the systematic enhancement of appropriate asthma management approaches (Kaplan et al. 2009). The technology assisted diagnosis detection approaches require evaluating the airway responsiveness findings of asthma patients in the context of their normal/abnormal pulmonary function pattern. The diagnosis detection application should also recommend various diagnostic modalities warranting administration in accordance with the cases of occupational asthma, atypical respiratory manifestations or typical pulmonary symptoms with normal respiratory findings (Kaplan et al. 2009). A well-structured technology assisted asthma management system warrants the utilization of evidence-based parameters with the objective of recommending appropriate medications in accordance with the type and intensity of respiratory manifestations of the asthmatic patient (Kaplan et al. 2009). The appropriate utilization of a well-developed diagnosis detection mechanism in the asthma management application will facilitate the selection of desirable treatment drugs in accordance with the recorded respiratory manifestations. The recording of patient’s pulmonary function prior to and after the administration of β2-agonist will direct the selection of appropriate drugs for effective stabilization of pulmonary system of the asthmatic patient (Kaplan et al. 2009).
The recommended asthma management application system would require integrating an interactive learning interface for the end users (i.e. asthma patients) with the objective of increasing their self-management skills in the context of controlling the adverse respiratory manifestations. The interactive feedback interface would prove to be user-friendly platform warranted for enhancing the knowledge base of asthma patients in relation to their clinical complications and their mitigating interventions. This feedback application system will prove to be an exciting and motivating tool for children and adolescents affected with asthma complications (Morrison et al. 2014). This digital intervention will prove advantageous in terms of reducing the risk of asthma patients towards acquiring life threatening complications under the influence of acute asthma exacerbation episodes. The incorporation of asthma prevention learning tool in the hospital settings would enhance clinical decision support systems warranting utilization for administering therapeutic interventions to the asthma patients during the initial phase of disease development. Asthma prevention learning tools in the recommended asthma management application would require direct access by the treated patients through their mobile phones, iPhones or other similar digital devices. Evidence-based research literature rationally reveals the direct influence of the pattern of knowledge, beliefs, attitudes, perceptions and insight of the asthma patients of various age groups on the intensity, severity and duration of their adverse respiratory manifestations (Fiks 2011). The recommended asthma prevention interface will prove to be an interactive platform for the children, adolescents as well as their caretakers and physicians for sharing knowledge regarding asthma complications. This sharing of significant patient information will facilitate the process of shared medical decision-making warranted for the systematic enhancement of the patient care outcomes. The asthma prophylaxis learning tool will also prove advantageous in terms of administering person-centred and holistic remedial interventions while understanding the literacy and maturity level as well as emotional and behavioural requirements of the asthmatic patients. This evidence-based tool will provide informed options to the treated patients for opting the treatment of choice in accordance with their psychosocial, somatic, behavioural and cultural requirements in the context of acquiring desirable healthcare outcomes (Fiks 2011).
The incorporation of the asthma prescription instructions in the recommended asthma management application warrants the requirement of developing computerized clinical decision support system in the medical facilities (Stultz & Nahata 2012). These clinical decision-support systems would facilitate the incorporation of physician order entries in a centralized database with the objective of reducing the scope of medication errors in emergency situations. This centralized data base embedded with the asthma prescription protocols will provide protected and selective access to the treated patients in the context of accessing their asthma management pharmacotherapeutic recommendations on a regular basis. The patients will click on a usage checkbox before administering a recommended medication intervention. Accordingly, they could receive alerts regarding the dosage or frequency of therapeutic regimen. This will substantially reduce the pattern of medication mismanagement and decrease the risk of occurrence of adverse events under the influence of missed or over-dosages of the treatment medication. Utilization of medication management calculators in the recommended asthma application will allow the asthma patients to type their recommended medication and receive the sequential alerts regarding the expected pattern of allergy, drug-drug interaction, weight-drug discrepancy and inadequate fluid errors (Stultz & Nahata 2012). Accordingly, asthma patients could systematically customize their medications while evaluating their risk of experiencing adverse events and other treatment challenges. The computerized asthma prescription management system will provide an insight regarding the duration of inhalation drugs administration that reciprocates in concordance with the severity of respiratory manifestations of the treated patients. The electronic prescription management system will also generate periodic alerts related to therapeutic duplication that might occur during the configuration of outpatient/inpatient or hospital discharge prescriptions. Asthma prescription management system will recommend the alternative and integrative medication interventions warranted for treating the pattern of co-morbid states attributing to urticaria, croup, pharyngitis, constipation, sinusitis and allergic rhinitis (Stultz & Nahata 2012). Asthma prescription management system must also recommend the desirable environmental changes and nutritional interventions warranting administration for enhancing the effectiveness of asthma medications in relation to the timely acquisition of therapeutic outcomes (Stultz & Nahata 2012). The recommended asthma management system will recommend the non-prescription drugs and inhalation interventions (after the selection of the respiratory symptoms by the end-users) in the context of their evidence-based utilization during medical emergencies and in the absence of immediate medical assistance (Stultz & Nahata 2012).
Asthma patients require learning the appropriate skills required for the systematic utilization of devices like nebulizers and drug inhaler kit in the context of administering medications in medical emergencies (Akinbami et al. 2012). The administration of rescue medication requires thorough knowledge of the desirable dosage in accordance with the intensity and severity of the respiratory manifestations. The recommended asthma management system will categorically incorporate the drugs like systemic corticosteroids, anti-IgE medicines, LT-modifying drugs, short/long acting β-agonists as well as inhaled corticosteroids.The recommended asthma management application will systematically direct the administration of these drugs during the episodes of acute asthma exacerbations. Resultantly, the patients will not wait for the external medical aid and take calculated decisions in relation to the appropriate administration of asthma medication during medical emergencies. The asthma management application will recommend the dosages of the emergency medications in accordance with the intensity of respiratory impairment caused by the acute exacerbation episode. The customized application will also consider the repeatability pattern of the asthma management drugs and the resultant responsiveness of asthmatic patients to the administered medication under the influence of environmental conditions as well as their genetic constitution. The asthma management application will also prompt the users for checking the date of expiry of each inhaler intervention prior to its administration in accordance with the physician’s recommendation. The recommended device utilization application will contain educational matter regarding the utilization of MDI-spacer intervention for controlling the pattern of acute exacerbation of persistent asthma. Inappropriate utilization of MDI-spacer technique leads to inadequate delivery of the required drug to the distal respiratory passages thereby leading to adverse asthma outcomes (Reznik, Silver & Cao 2014). Therefore, the direct access of asthma patients to the device utilization training material (through their mobile application) will lead to the appropriate self-handling of MDI spacer device and enhancement of asthma treatment outcomes. The recommended asthma management system will utilize automated asthma monitoring device with the objective of detecting asthma manifestations during their initial phase (Rhee et al. 2015). The sensitivity and specificity of this automated device in tracking asthma symptoms will promote the process of asthma self-management by the affected patients. Timely evaluation of the worsening respiratory manifestations will reduce the frequency of prospective clinical conditions and associated fatalities. The tracking of asthma onset and progression during its initial stage through automated asthma monitoring device will also reduce the cost of treating adverse asthma consequences and associated economic implications (Rhee et al. 2015).
The recommended asthma application management system will extend the provision of centralized physician order entry system with the systematic utilization of a computerized interface. Systematic entries of physician prescriptions in complex clinical scenarios will assist the physicians as well as the asthma patients in avoiding the scope of medical errors. Automated asthma medication system will enhance the patient satisfaction rate and reduce the frequency of follow-up visits by the patients in the context of their prescription refill/management. Healthcare professionals will also acquire thorough knowledge of therapeutic management of the treated patients for their referring to the more specialized medical care in case of unexpected medical emergencies. The systematization of medication order through asthma management application will facilitate the process of medical decision-making by the healthcare practitioners. This will also reduce the redundant effort of recording the medication history during each patient visit. Indeed, by utilizing CMOES the treating physicians will attain a thorough insight regarding the allergy-profile of the asthmatic patients. Accordingly, they will prescribe an appropriate therapeutic regimen while considering the allergy history of the asthma patients. A thorough documentation of the medical management of the asthmatic patients will assist the physicians of multiple specialties in taking strategic decisions regarding the treatment of co-morbidities like pulmonary infection, respiratory failure and pneumonia. The incorporation of CMOES in the asthma management application will reduce the frequency and duration of evaluation and management visits of the asthma patients in the clinical settings. This will eventually reduce the unnecessary investment of time, efforts and cost for performing the clinical evaluation of asthmatic patients in the medical facilities. Evidence-based clinical literature reveals the increased utilization of computerized clinical decision support system in primary care settings (Lomotan et al. 2012). However, utilization of CMOES application in both primary, secondary and tertiary care settings and securely linking the same with patient interface will substantially improve the pattern of asthma self-management as well as medical intervention in the healthcare settings.
The recommended asthma management application will systematically incorporate digital whiteboard in web-based platform with the objective of improving the quality of healthcare coordination of the asthmatic patients. The digital whiteboard will allow the asthma patients in terms of escalating their queries and clarifications regarding medical management to the treating physicians. This personalized approach will facilitate the physician responses to the escalated queries in a timely manner to the patient population. Accordingly, asthma patients will effectively self-manage their clinical condition without the requirement of undertaking a face-to-face interactive session with the treating physicians. Traditionally, the hospital setting widely utilize the dry-erase whiteboards for recoding the patient conditions on a da-to-day basis (Gjære & Lillebo 2014). However, the concept of digital whiteboards is not prevalently utilized in the medical facilities. The integration of digital whiteboard information with the personalized patient devices will facilitate the direct access of the asthma patients to the significant information regarding their asthma status, medical decision-making as well as medication management.
Web-based asthma management system would require the digital incorporation of allergy testing indicators with the objective of treating adverse medical conditions attributing to asthma exacerbation and anaphylaxis. Allergy testing indicators will objectively incorporate the information regarding the utilization of injectables like adrenaline and epinephrine or other similar medications in asthma patients. Accordingly, patients will gain insight regarding the mechanism of administration of auto-injectors during medical emergencies. Allergy testing indicators will also incorporate the customized information regarding environmental factors, chemicals, drugs and other organic or inorganic substances that could potentially induce the episode of asthma exacerbation. Resultantly, the patient will gain knowledge regarding the requirement of removing asthma/anaphylaxis triggers from their immediate surroundings. The recommended computerized allergy indicator system will incorporate NICE (National Institute of Health and Clinical Excellence) guidelines for identifying the pattern of asthma triggers from the external/internal environment (Dhami et al. 2017). Patients will access this customized allergy evaluation system from their individualized cell-phones or personal computers for controlling episodes of their asthma exacerbations and associated adverse manifestations.
The recommended asthma management application will categorically record the primary and secondary asthma outcomes in the context of undertaking evidence-based measures for reducing the pattern of their intensity and frequency in the affected patients. The asthma symptom tracker will allow the patients for entering their respiratory symptoms and other clinical manifestations that they might experience during the medical management of their asthmatic manifestations. Physicians will accordingly customise medical interventions in accordance with the combination of respiratory manifestations recorded in the web-based asthma symptoms tracker. The ADSS (asthma decision support system) is prevalently utilized in the clinical settings with the objective of improving the knowledge of asthma patients as well as treating physicians in relation to the asthma symptomatology for its systematic remediation (Ahmed, Tamblyn & Winslade 2014). The ADSS application remains integrated with electronic prescribing drug management application that contains information regarding the medication intervention as well as treatment challenges experienced by the asthma patient (Ahmed, Tamblyn & Winslade 2014). This effectively customizes the patient-focussed and goal oriented medication management of the asthma patients while systematically reducing the scope of treatment inadequacies. However, the recommended asthma symptoms tracking mechanism will effectively integrate the symptoms tracker with the personalized patients devises as well as physician order entry system in a manner that any self-reported change (i.e. addition) in the respiratory manifestations would escalate the requirement of modifying the medication order by the treating physician. Symptoms tracking application will also recommend the type of medication intervention (requiring administration) while analysing the patient symptoms as well as the embedded prescription algorithms. This rationally reveals the elevated potential of the recommended asthma management system in terms of improving the quality of asthma treatment intervention for the systematic enhancement of the patient outcomes.
The risk of asthma patients in terms of experiencing serious and life-threatening conditions and associated fatalities is substantiated by several factors attributing to the adverse asthma control and severity, inappropriate utilization of treatment drugs, adverse psychosocial conditions of the asthma patients as well as physician-related attributes (Hodder et al. 2010). The recommended asthma management system will incorporate the significant signs and symptoms indicating the potentially fatal exacerbation of acute asthma in the affected patients. The patients would require checking the respiratory manifestations (from the list of the embedded signs and symptoms) that they might experience at any point in time at their locations. The selection of these adverse manifestations in the emergency medication advisor application would generate the name and dosages of the appropriate drugs requiring administration for effectively controlling the intensity of a fatal asthma attack. Therefore, the patients will eventually self-medicate themselves during medical emergencies without seeking an immediate medical assistance. This application will effectively customize the patient-specific emergency treatment interventions in accordance with his/her risk of developing specific respiratory conditions that could potentially aggravate the intensity of asthma exacerbation. Evidence-based clinical literature reveals the signs and symptoms including accessary muscle utilization, increased heart rate, dyspnoea, fatigue, altered consciousness, diaphoresis, cyanosis, air hunger, anxiety, progressive agitation and impending doom as the significant indicators of a fatal asthma episode (Hodder et al. 2010). The recommended web-based medication advisor will include these potential symptoms in the context of recommending an appropriate therapeutic regimen for its systematic utilization during fatal asthma exacerbation.
The recommended web-based asthma management system will prompt the physicians for entering the vital signs and other clinical measurements of the asthma patients in relation to the dose-specific customization of their treatment regimen. For example, the physician or patient could enter the information regarding temperature, pulse rate, weight, blood pressure as well as respiratory rate for acquiring a list of appropriate medications (with dosage recommendations) in the context of their safe administration to the selected patient. Evidence-based clinical literature also affirms the significance of weight-based dosage calculation system in terms of undertaking the safe and effective medical management of acute asthma exacerbation (Kokotajlo et al. 2014). The recommended asthma management application will evidentially acquire the same approach with the objective of increasing the patient care outcomes after the systematic administration of therapeutic interventions.
Evidence-based clinical literature reveals the elevated utilization of health information technology in terms of a mainstream tool in facilitating the process of medical decision-making and self-monitoring of asthma patients (Himes & Weitzman 2016). The recommended technological innovation will integrate multiple health informatics interventions for providing a user-friendly platform to asthma patients and concerned physicians in the context of promoting the process of asthma self-management for the reciprocal enhancement of patient outcomes.
The recommended asthma management application will utilize a blend of the following design attributes for the systematic enhancement of diagnostic assessment/treatment outcomes of the asthma patients (Thuemmler & Bai 2017).
The interoperability of various modules of the recommended asthma management system will facilitate the consistent transfer of contextual information between various levels of the application. This user-friendly application will deploy biosensors for enhancing the regular exchange of significant information between asthma patients and the treating physicians. The application will allow the systematic integration of various operational interventions with the objective of decoding the information obtained through data readings in the context of transforming the meaningful clinical information.
The recommended asthma management application will adapt to the recommended module in a manner to allow their prospective expansion in accordance with the changing treatment requirements. Recombinant modular functionality will also allow the generation of new features and functions while systematically reorienting already embedded modules in accordance with the clinical requirements of the asthma patients and their treating physician. Modular functioning of the recommended application will enhance its speed of execution and decrease the scope of occurrence of fatal errors.
The recommended asthma management application will deploy patient-centred approaches with the objective of customizing healthcare interventions in accordance with the individualized treatment requirements of the asthma patients. This will substantially improve the quality of treatment approaches and reduce the intensity and frequency of fatal asthma attacks among the predisposed patients. The application will ascertain the safety and protection of the protected health information in accordance with the stipulations formulated under HIPAA (Health Insurance Portability and Accountability Act) Omnibus Convention (Goldstein & Pewen 2013).
The recommended asthma management application will attempt to undertake the real-time amalgamation of diagnostics and therapy (i.e. theragnostics) in accordance with the conventions of personalized medicine (Thuemmler & Bai 2017). Eventually, the outcomes will prove beneficial for the patients as well as the physician community in relation to the considerable reduction in treatment cost and enhancement in the quality of healthcare interventions.
The recommended asthma management application will objectively incorporate decentralized approaches in the context of accomplishing the patient-centred and holistic healthcare requirements (Thuemmler & Bai 2017). The administration of technology assisted, patient-focused and goal oriented healthcare approaches will substantially enhance the patient care outcomes and reduce the burden of asthma and its associated health adversities across the community environment.
The systematic virtualization of healthcare approaches with the utilization of asthma management application will reduce the requirement of periodic interactive sessions between the asthma patients and the treating physicians (Thuemmler & Bai 2017). This will eventually reduce the frequency of follow-up sessions and enhance the pattern of self-efficacy and self-monitoring among the asthma patients. The virtual application will therefore improve the pattern of patient awareness regarding asthma manifestations and reduce the cost incurred in undertaking medical management and consultation interventions (in the hospital settings) following the occurrence of fatal asthma exacerbations.
Conclusion
Clinical management of asthmatic manifestations is a complex process requiring the utilization of evidence-based interventions for the substantial enhancement of patient care outcomes. The recommended asthma management system will integrate various evidence-based attributes with the objective of enhancing the quality of asthma care interventions for reducing the burden of the debilitating asthma manifestations across the community environment. The proposed asthma management application will integrate informatics infrastructure, EMR, CTA, DTM, APPLS, API, DUTL, CMOES, CWMS, ATI, ASTS, EMA, ADDAM and ATP modalities with the systematic utilization of design attributes including interoperability, modularity, service orientation, real-time capacity, decentralization and virtualization for the systematic acquisition of patient care outcomes.
References
Ahmed, S, Tamblyn, R & Winslade, N 2014, ‘Using decision support for population tracking of adherence to recommended asthma guidelines’, BMJ Open, vol 4, no. 3, <https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3948455/>.
Akinbami, LJ, Sullivan, SD, Campbell, JD, Grundmeier, RW, Hartert, TV, Lee, TA & Smith, RA 2012, ‘Asthma Outcomes: Healthcare Utilization and Costs’, Journal of Allergy and Clinical Immunology, vol 129, no. 30, pp. S49-S64, <https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4277846/>.
Anderson , WC, Apter, AJ, Dutmer , CM, Searing , DA & Szefler , SJ 2017, ‘Advances in asthma in 2016: Designing individualized approaches to management’, The Journal of Allergy and Clinical Immunology, vol 140, no. 3, pp. 671-680, <https://www.ncbi.nlm.nih.gov/pubmed/28709967>.
Brigham, EP & West, NE 2015, ‘Diagnosis of asthma: diagnostic testing’, International Forum of Allergy and Rhinology, vol 5, no. 1, pp. S27-S30, https://www.ncbi.nlm.nih.gov/pubmed/26335833.
Burbank, AJ, Lewis, SD, Hewes, M, Schellhase, DE, Rettiganti, M, Hall-Barrow, J, Bylander, LA, Brown , RH & Perry, TT 2015, ‘Mobile-based asthma action plans for adolescents’, Journal of Asthma, vol 52, no. 6, pp. 583-586, <https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5292936/>.
Burbank, AJ, Lewis, SD, Hewes, M, Schellhase, DE, Rettiganti, M, Hall-Barrow, J, Bylander, LA, Brown, RH & Perry, TT 2015, ‘Mobile-based asthma action plans for adolescents’, Journal of Asthma, vol 52, no. 6, pp. 583-586, <https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5292936/>.
Dabbs, ADV, Myers, BA, Curry, KRM, Dunbar-Jacob, J, Hawkins, RP, Begey, A & Dew, MA 2009, ‘User-Centered Design and Interactive Health Technologies for Patients’, Computers, Informatics, Nursing, vol 27, no. 3, p. 175, <https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2818536/>.
Davis , AM, Cannon , M, Ables , AZ & Bendyk , H 2010, ‘Using the electronic medical record to improve asthma severity documentation and treatment among family medicine residents’, Family Medicine, vol 42, no. 5, pp. 334-337, <https://www.ncbi.nlm.nih.gov/pubmed/20455109>.
Dexheimer , JW, Abramo , TJ, Arnold , DH, Johnson , KB, Shyr , Y, Ye , F, Fan , KH, Patel , N & Aronsky , D 2013, ‘An asthma management system in a pediatric emergency department’, International Journal of Medical Informatics, vol 82, no. 4, pp. 230-238, <https://www.ncbi.nlm.nih.gov/pubmed/23218449>.
Dexheimer, JW, Abramo, TJ, Arnold, DH, Johnson, KB, Shyr, Y, Ye, F, Fan, KH, Patel, N & Aronsky, D 2013, ‘An asthma management system in a pediatric emergency department’, International Journal of Medical Informatics, vol 82, no. 4, pp. 230-238, <https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3646328/>.
Dexheimer, JW, Arnold, DH, Abramo, TJ & Aronsky, D 2009, ‘Development of an Asthma Management System in a Pediatric Emergency Department’, AMIMA Annual Symposium Proceedings Archive, pp. 142-146, <https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2815470/>.
Dexheimer, JW, Borycki, EM, Chiu, KW, Johnson, KB & Aronsky, D 2014, ‘A systematic review of the implementation and impact of asthma protocols’, BMC Medical Informatics and Decision Making, <https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4174371/>.
Dhami, S, Sheikh, A, Muraro, A, Roberts, G, Halken, S, Rivas, MF, Worm, M & Sheikh, A 2017, ‘Quality indicators for the acute and long-term management of anaphylaxis: a systematic review’, Clinical and Translational Allergy, <https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5442671/>.
Elias, P, Damle, A, Casale, M, Branson, K, Churi, C, Komatireddy, R & Feramisco, J 2015, ‘A Web-Based Tool for Patient Triage in Emergency Department Settings: Validation Using the Emergency Severity Index’, JMIR Medical Informatics, vol 3, no. 2, https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4526930/.
Elias, P, Damle, A, Casale, M, Branson, K, Churi, C, Komatireddy, R & Feramisco, J 2015, ‘A Web-Based Tool for Patient Triage in Emergency Department Settings: Validation Using the Emergency Severity Index’, JMIR Medical Informatics, vol 3, no. 2, https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4526930/.
Fiks, AG 2011, ‘Designing Computerized Decision Support That Works for Clinicians and Families’, Current Problems in Pediatric and Adolescent Health Care, vol 41, no. 3, pp. 60-88, <https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3373310/>.
Gabb, HA & Blake, C 2016, ‘An Informatics Approach to Evaluating Combined Chemical Exposures from Consumer Products: A Case Study of Asthma-Associated Chemicals and Potential Endocrine Disruptors’, Environmental Health Perspectives, vol 124, no. 8, pp. 1155-1165, <https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4977060/>.
Geryk, LL, Roberts, CA, Sage, AJ, Coyne-Beasley, T, Sleath, BL & Carpenter, DM 2016, ‘Parent and Clinician Preferences for an Asthma App to Promote Adolescent Self-Management: A Formative Study’, JIMR Research Protocols, vol 5, no. 4, p. e229, <https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5174724/>.
Gjære, EA & Lillebo, B 2014, ‘Designing privacy-friendly digital whiteboards for mediation of clinical progress’, BMC Medical Informatics and Decision Making, <https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4021250/>.
Goldstein, MM & Pewen, WF 2013, ‘The HIPAA Omnibus Rule: Implications for Public Health Policy and Practice’, Public Health Reports, vol 128, no. 6, pp. 554-558, <https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3804103/>.
Grossman , B, Conner , S, Mosnaim , G, Albers , J, Leigh , J, Jones , S & Kenyon, R 2017, ‘Application of Human Augmentics: A Persuasive Asthma Inhaler’, Journal of Biomed Informatics, pp. 51-58, <https://www.ncbi.nlm.nih.gov/pubmed/28193465>.
Himes, BE & Weitzman, ER 2016, ‘Innovations in health information technologies for chronic pulmonary diseases’, Respiratory Research, <https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4822326/>.
Hodder, R, Lougheed, MD, Rowe, BH, FitzGerald, JM, Kaplan, AG & McIvor, RA 2010, ‘Management of acute asthma in adults in the emergency department: nonventilatory management’, CMAJ, vol 182, no. 2, pp. E55–E67, <https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2817338/>.
Hodder, R, Lougheed, MD, Rowe, BH, FitzGerald, JM, Kaplan, AG & McIvor, RA 2010, ‘Management of acute asthma in adults in the emergency department: nonventilatory management’, CMAJ, vol 182, no. 2, pp. E55-E67, <https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2817338/>.
Huckvale, K, Car, M, Morrison, C & Car, J 2012, ‘Apps for asthma self-management: a systematic assessment of content and tools’, BMC Medicine, <https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3523082/>.
Huckvale, K, Morrison, C, Ouyang, J, Ghaghda, A & Car, J 2015, ‘The evolution of mobile apps for asthma: an updated systematic assessment of content and tools’, BMC Medicine, <https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4391129/>.
Kaplan, AG, Balter, MS, Bell, AD, Kim, H & McIvor, RA 2009, ‘Diagnosis of asthma in adults’, CMAJ, vol 181, no. 10, pp. E210–E220, https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2774375/.
Kokotajlo, S, Degnan, L, Meyers, R, Siu, A & Robinson, C 2014, ‘Use of Intravenous Magnesium Sulfate for the Treatment of an Acute Asthma Exacerbation in Pediatric Patients’, The Journal of pediatric Pharmacology and Theraopeutics, vol 19, no. 2, pp. 91-97, <https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4093670/>.
Laforest, L, Licaj, I, Devouassoux, G, Eriksson, I, Caillet, P, Chatte, G, Belhassen, M & Ganse, E 2015, ‘Prescribed therapy for asthma: therapeutic ratios and outcomes’, BMC Family Practice, https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4408560/.
Lomotan, EA, Hoeksema, LJ, Edmonds, DE, Ramírez-Garnica, G, Shiffman, RN & Horwitz, LI 2012, ‘Evaluating the use of a computerized clinical decision support system for asthma by pediatric pulmonologists’, International Journal of Medical Informatics, vol 81, no. 3, pp. 157-165, <https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3279612/>.
Manca, DP 2015, ‘Do electronic medical records improve quality of care? Yes’, Can Fam Physician, vol 61, no. 10, pp. 846-847, https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4607324/.
Morrison, D, Wyke, S, Agur, K, Cameron, EJ, Docking, RI, MacKenzie, AM, McConnachie, A, Raghuvir, V, Thomson, NC & Mair, FS 2014, ‘Digital Asthma Self-Management Interventions: A Systematic Review’, Journal of Medical Internet Research, vol 16, no. 2, <https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3958674/>.
Mukherjee, M, Stoddart, A, Gupta, RP, Nwaru, BI, Farr, A, Heaven, M, Fitzsimmons, D, Bandyopadhyay, A, Aftab, C, Simpson, CR, Lyons, RA, Fischbacher, C, Dibben, C, Shields, MD, Phillips, CJ, Strachan, DP, Davies, GA, McKinstry, B & Sheikh, A 2016, ‘The epidemiology, healthcare and societal burden and costs of asthma in the UK and its member nations: analyses of standalone and linked national databases’, BMC Medicine, vol 14, no. 1, <https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5002970/>.
Murrell, KL, Offerman, SR & Kauffman, MB 2011, ‘Applying Lean: Implementation of a Rapid Triage and Treatment System’, West JEM, vol 12, no. 2, pp. 184-191, https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3099605/.
NIH 2007, ‘Control of Environmental Factors and Comorbid Conditions That Affect Asthma’, NIH.
Nwaru, BI & Sheikh, A 2015, ‘Hormonal contraceptives and asthma in women of reproductive age: analysis of data from serial national Scottish Health Surveys’, Journal of the Royal Society of Medicine, vol 108, no. 9, pp. 358-371, <https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4582260/>.
O’Byrne , PM 2010, ‘Global guidelines for asthma management: summary of the current status and future challenges’, Polskie Archiwum Medycyny Wewnetrznej, vol 120, no. 12, pp. 511-517, <https://www.ncbi.nlm.nih.gov/pubmed/21178908>.
Pinnock, H 2015, ‘Supported self-management for asthma’, Breathe (Sheff), vol 11, no. 2, pp. 98-109, <https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4487370/>.
Potter, PC 2009, ‘Current guidelines for the management of asthma in young children’, Allergy, Asthma & Immunology Research, vol 2, no. 1, pp. 1-13, <https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2831604/>.
Reznik, M, Silver, EJ & Cao, Y 2014, ‘Evaluation of MDI-spacer utilization and technique in caregivers of urban minority children with persistent asthma’, The Journal of Asthma, vol 51, no. 2, pp. 149-154, https://www.ncbi.nlm.nih.gov/pubmed/24131031.
Rhee, H, Belyea, MJ, Sterling, M & Bocko, MF 2015, ‘Evaluating the Validity of an Automated Device for Asthma Monitoring for Adolescents: Correlational Design’, Journal of Medical Internet Research, vol 17, no. 10, p. e234, https://www.ncbi.nlm.nih.gov/pubmed/26475634.
Sage, A, Roberts, C, Geryk, L, Sleath, B, Tate, D & Carpenter, D 2017, ‘A Self-Regulation Theory–Based Asthma Management Mobile App for Adolescents: A Usability Assessment’, JMIR Human Factors, vol 4, no. 1, <https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5311420/>.
Stultz, JS & Nahata, MC 2012, ‘Computerized clinical decision support for medication prescribing and utilization in pediatrics’, JAMIA, vol 19, no. 6, pp. 942-953, <https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3534459/>.
Wechsler, ME 2009, ‘Managing Asthma in Primary Care: Putting New Guideline Recommendations Into Context’, Mayo Clinic Proceedings, vol 84, no. 8, pp. 707-717, <https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2719524/>.
Xi, N, Wallace, R, Agarwal, G, Chan, D, Gershon, A & Gupta, S 2015, ‘Identifying patients with asthma in primary care electronic medical record systems’, Can Fam Physician, vol 61, no. 10, pp. e474–e483, <https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4607352/>.
Essay Writing Service Features
Our Experience
No matter how complex your assignment is, we can find the right professional for your specific task. Contact Essay is an essay writing company that hires only the smartest minds to help you with your projects. Our expertise allows us to provide students with high-quality academic writing, editing & proofreading services.
Free Features
Free revision policy
$10Free bibliography & reference
$8Free title page
$8Free formatting
$8How Our Essay Writing Service Works
First, you will need to complete an order form. It's not difficult but, in case there is anything you find not to be clear, you may always call us so that we can guide you through it. On the order form, you will need to include some basic information concerning your order: subject, topic, number of pages, etc. We also encourage our clients to upload any relevant information or sources that will help.
Complete the order form
Once we have all the information and instructions that we need, we select the most suitable writer for your assignment. While everything seems to be clear, the writer, who has complete knowledge of the subject, may need clarification from you. It is at that point that you would receive a call or email from us.
Writer’s assignment
As soon as the writer has finished, it will be delivered both to the website and to your email address so that you will not miss it. If your deadline is close at hand, we will place a call to you to make sure that you receive the paper on time.
Completing the order and download