Disease Management System Research Articles

Understanding support systems for Parkinson's disease management in community settings: A cross-national qualitative study.

Health and social care systems face difficulties in managing multimorbidity, disease burden and complex needs in long-term conditions such as Parkinson's disease. This study aimed to develop a European understanding of how health and social care professionals can collaborate with stakeholders from different organizations and sectors to enhance the management of Parkinson's disease in a community setting by identifying the existing gaps in this process and how people with Parkinson's disease and their family carers could benefit from these partnerships. A mixed-methods sequential study was conducted in Denmark, Norway, Spain and the United Kingdom. The findings from the qualitative phase are presented. Individual semistructured interviews were analysed using Braun's and Clarke's thematic analysis. A meta-ethnography approach was used to analyse and synthesize cross-national findings. A total of 41 healthcare professionals and 39 stakeholders from different disciplines and sectors were interviewed in the four countries. The participants acknowledged a lack of awareness of available resources and poor communication between the different support systems in the management of Parkinson's disease. To promote multiagency collaborations, the participants highlighted the need to organize services along the Parkinson's disease journey, patient involvement and strategic involvement of carers in organizing resources and Parkinson's disease care pathways. According to the participants, the benefits from multiagency partnerships could lead to an enhanced continuity of care and specialized knowledge, mobilization of resources in the community, personalized support and improved access to services. Policymakers are called upon to create formal structures that facilitate multisectoral collaborations to promote an integrated system of care for the management of Parkinson's disease in the community. To address this challenge, we propose five strategies showing how organizations can work together to optimize the use of resources and enhance the management of Parkinson's disease throughout the illness trajectory. Patient and Public Involvement groups made up of stakeholders, healthcare professionals, patients with Parkinson's disease and family carers participated in the design of the study, the development of the interview guides and the validation of the findings.

Importance of full-cycle management for diabetic retinopathy

Diabetic retinopathy (DR), one of the chronic complications of diabetes, is a serious and irreversible blinding disease. It is difficult to detect in the early stage, to control in the progressive stage, to operate in the advanced stage of DR. Recently, the "14th Five-year plan" for National Eye Health proposed to "improve the management mode of chronic eye disease, and build a chronic disease management system". The project team used artificial intelligence technology based on cloud platform, joint outpatient service, virtual ward to explore the comprehensive management of DR from the aspects of early screening, multidisciplinary collaborative diagnosis and treatment, and refined blood glucose management during perioperative period. In the future, it is urgent to integrate DR chronic disease management with other systemic chronic diseases to reduce the blindness caused by DR.

Neem: A Novel Biocide for Pest and Disease Control of Plants

Plant extracts have recently captivated scientists’ attention as a potential source of biocide for plant protection. This is due to the health and environmental risks associated with the widespread use of synthetic chemicals with adverse effects on humans, nontarget organisms, and the agroecosystem. As a result, more environmentally friendly and safe alternative approaches to synthetic compounds are desirable. Neem (Azadirachta indica) has been identified as a promising biocontrol agent with low toxicity and high efficacy among several plant products for potential chemotherapeutic elements in plant pest and disease management systems. The biocidal potency of neem is attributed to its azadirachtin active ingredient, which impacts some metabolic processes in insects such as protein synthesis, changes in biological fitness, impaired sexual communication, and chitin synthesis. This systematic review intends to gather all the available scientific data regarding the application of neem and its formulations in pest and disease control of plants. The PRISMA (preferred reporting items for systematic reviews and meta-analysis) framework was employed in collecting data for the study. Findings from this review study have demonstrated the use of neem as an effective biocontrol agent for plants’ pests and diseases and have provided a solid foundation for future studies on the plant.

Sentinel surveillance of SARS-CoV-2 rates and equity impacts using labor and delivery patients in Phoenix, Arizona

Proactive management of SARS-CoV-2 requires timely and complete population data to track the evolution of the virus and identify at risk populations. However, many cases are asymptomatic and are not easily discovered through traditional testing efforts. Sentinel surveillance can be used to estimate the prevalence of infections for geographical areas but requires identification of sentinels who are representative of the larger population. Our goal is to evaluate applicability of a population of labor and delivery patients for sentinel surveillance system for monitoring the prevalence of SARS-CoV-2 infection. We tested 5307 labor and delivery patients from two hospitals in Phoenix, Arizona, finding 195 SARS-CoV-2 positive. Most positive cases were associated with people who were asymptomatic (79.44%), similar to statewide rates. Our results add to the growing body of evidence that SARS-CoV-2 disproportionately impacts people of color, with Black people having the highest positive rates (5.92%). People with private medical insurance had the lowest positive rates (2.53%), while Medicaid patients had a positive rate of 5.54% and people without insurance had the highest positive rates (6.12%). With diverse people reporting for care and being tested regardless of symptoms, labor and delivery patients may serve as ideal sentinels for asymptomatic detection of SARS-CoV-2 and monitoring impacts across a wide range of social and economic classes. A more robust system for infectious disease management requires the expanded participation of additional hospitals so that the sentinels are more representative of the population at large, reflecting geographic and neighborhood level patterns of infection and risk.

만성폐쇄성폐질환 환자의 자가관리 경험에 대한 질적메타합성

This study aimed to comprehensively review the self-management experiences of patients with chronic obstructive pulmonary disease(COPD) through meta-synthesis of qualitative studies. The method of this study was applied to Meta-ethnography of Noblit and Hare. Five databases were used to search the literature: PubMed, CINAHL, RISS, DBpia, National Assembly Library and searching keyword were ‘COPD’, ‘self management’, ‘experiences’, and ‘qualitative research’. 371 references were identified and relating to six qualitative studies were included in the review. Three themes were synthesized: “Perceived severity of symptoms”, “Coping strategies” and “Support system of disease management”. Through this study, it was possible to improve the understanding of self management experiences of COPD patients. The results of this study made grounds of a coping strategies for developing self-management programs of COPD patients.

A case-control study of acute hepatitis A in South Korea, 2019.

We aimed to reconfirm the source of hepatitis A virus (HAV) infection through epidemiological and genotype investigations of individual cases in a 2019 outbreak in South Korea. We investigated food intake histories, associations with hepatitis A, and genotypes of HAV in 31 patients with hepatitis aged 20 to 49 years registered in the integrated disease and health management system during December 1-7, 2019 (case group) and in 35 sex- and agematched people without a history of HAV vaccination or infection among patients' families and colleagues (control group). The consumption of salted clams was a significant factor (odds ratio, 4.33; 95% confidence interval, 1.32-14.18) in the risk factor analysis of food intake history. HAV genotypes were analyzed in 24 of 31 patients. Type IA and type IIIA were found in 23 and 1 cases, respectively. Salted clams are considered to have been the source of HAV infection at 49 weeks of the HAV outbreak in 2019; this result was consistent with that of a previous epidemiological investigation conducted by the Korea Disease Control and Prevention Agency in September 2019. Therefore, monitoring of the production and distribution of salted clams needs to be continued.

The coronavirus disease 2019 pandemic and chronic diseases

Background: Chronic diseases contribute to 74% of annual global deaths. The coronavirus disease (COVID-19) pandemic further aggravated the burden of chronic diseases. The reasons for this adverse impact must be elucidated to develop an appropriate response.Current Concepts: COVID-19 increases the burden of chronic disease in three ways. First, chronic disease comorbidities are associated with a higher severity and fatality rate in patients with COVID-19. Second, the post COVID-19 condition results in chronic health problems. Lastly, a disruption in the system for chronic disease screening and care was observed during the COVID-19 pandemic.Discussion and Conclusion: Strong efforts are needed to mitigate the impact of the COVID-19 pandemic on chronic diseases, and to re-establish an effective system for chronic disease management.

Telehealth care system for chronic disease management of middle-aged and older adults in remote areas.

With the global spread of the coronavirus disease pandemic, governments have become more interested in applying telehealth technology in 2020. This study integrates the technology acceptance model and information system success model to explore the influence of satisfaction, attitudes, and continued use of telehealth systems among middle-aged and older people in remote areas. The study participants were patients over 40years (inclusive) who lived in remote townships in eastern Taiwan, were diagnosed with diabetes or hypertension, and used the telehealth care system. In total, 545 questionnaires were returned, resulting in a recovery rate of 99%. Accepting the hypothesized structural equation model, this study found that information, system, and service quality were influenced by the mediating effect of perceived ease of use and the perceived usefulness of the technology acceptance model. The use of telehealth care systems among chronic patients increased significantly.

IMPACT OF FERTILISER APPLICATION ON BASAL STEM ROT AND LOWER FROND DESICCATION IN OIL PALMS ESTABLISHED IN PEAT SOIL

For oil palms established in deep peat soils in the Labuhan Batu district, North Sumatra, Ganoderma basal stem rot (BSR) and lower frond desiccation (LFD) are the two main maladies that have a serious impact on their long-term sustainability. Past experiences have shown that solitary control measures are unlikely to be successful in managing these two maladies and a number of integrated control strategies would be a prerequisite for their management. As nutrition is an important factor influencing fungal disease infection in many crops, nutrient manipulation can be considered as a vital component of any integrated disease management (IDM) system. This paper summarises the impact of fertiliser application on the level of BSR and LFD infection in five fertiliser trials, established in the affected areas from 1996-2021. In both trials established on first and second generation oil palms, application of nitrogen (N) and phosphorus (P) elicited a significant and linear increase in BSR infection levels, the higher the dosage, the higher the BSR incidence. In contrast, potassium (K) inputs had the reverse effect and significantly reduced BSR infection in the first trial but not in the second. A significant negative additive interaction between N x P and P x K was also observed in both trials. Increasing the rates of N together with P or P with K, increased BSR infection, with the highest infection levels being recorded at the highest N2P2 and P2K2 rates evaluated. Unlike macronutrients, application of boron (B), copper (Cu) and zinc (Zn) micronutrient fertilisers did not have any significant impact on BSR incidence. A similar trend was recorded on LFD incidence in both immature and mature second generation oil palms. Application of N and P also elicited a significant and linear increase in LFD and a strong negative and additive interaction effect between N x P and P x K was also observed. As for BSR, impact of K fertiliser was inconsistent, producing no positive or negative effects in immature palms and only significantly reducing LFD levels in two out of the 6 years of evaluation in mature oil palms. Likewise, application of B, Cu and Zn micronutrient fertilisers also had no impact on LFD incidence. Although peat is reported to be low in silica, application of silica fertilisers, even up to a dosage of 6 kg per palm per year produced no positive benefits. The relationship between nutrients and BSR/LFD infection and the physiological and biochemical mechanisms involved, remains unclear. However, it is interesting to note, that in all three NPK trials, the lowest infection rates were consistently recorded in the zero fertiliser plots. A possible hypothesis is that long-term application and concentration of N and P fertilisers in the weeded palm circles (WPC) could have had a negative impact on beneficial soil microbes inhabiting the root rhizosphere and associated with oil palm root protection or inducing systemic resistance in the oil palm. However, more detailed studies are required to ascertain the complex relationship between nutrients, soil microbes and disease infection. Keywords: Basal stem rot, fertilisers, lower frond desiccation, oil palm, peat.

GeoDLS: A Deep Learning-Based Corn Disease Tracking and Location System Using RTK Geolocated UAS Imagery

Deep learning-based solutions for precision agriculture have recently achieved promising results. Deep learning has been used to identify crop diseases at the initial stages of disease development in an effort to create effective disease management systems. However, the use of deep learning and unmanned aerial system (UAS) imagery to track the spread of diseases, identify diseased regions within cornfields, and notify users with actionable information remains a research gap. Therefore, in this study, high-resolution, UAS-acquired, real-time kinematic (RTK) geotagged, RGB imagery at an altitude of 12 m above ground level (AGL) was used to develop the Geo Disease Location System (GeoDLS), a deep learning-based system for tracking diseased regions in corn fields. UAS images (resolution 8192 × 5460 pixels) were acquired in cornfields located at Purdue University’s Agronomy Center for Research and Education (ACRE), using a DJI Matrice 300 RTK UAS mounted with a 45-megapixel DJI Zenmuse P1 camera during corn stages V14 to R4. A dataset of 5076 images was created by splitting the UAS-acquired images using tile and simple linear iterative clustering (SLIC) segmentation. For tile segmentation, the images were split into tiles of sizes 250 × 250 pixels, 500 × 500 pixels, and 1000 × 1000 pixels, resulting in 1804, 1112, and 570 image tiles, respectively. For SLIC segmentation, 865 and 725 superpixel images were obtained using compactness (m) values of 5 and 10, respectively. Five deep neural network architectures, VGG16, ResNet50, InceptionV3, DenseNet169, and Xception, were trained to identify diseased, healthy, and background regions in corn fields. DenseNet169 identified diseased, healthy, and background regions with the highest testing accuracy of 100.00% when trained on images of tile size 1000 × 1000 pixels. Using a sliding window approach, the trained DenseNet169 model was then used to calculate the percentage of diseased regions present within each UAS image. Finally, the RTK geolocation information for each image was used to update users with the location of diseased regions with an accuracy of within 2 cm through a web application, a smartphone application, and email notifications. The GeoDLS could be a potential tool for an automated disease management system to track the spread of crop diseases, identify diseased regions, and provide actionable information to the users.

A two-stage deep-learning based segmentation model for crop disease quantification based on corn field imagery

It is important to develop accurate disease management systems to identify and segment corn disease lesions and estimate their severity under complex field conditions. Although deep learning techniques are becoming increasingly popular to identify singular diseases, access to robust models for identifying multiple diseases and segmenting lesion areas for severity estimation under field conditions remain unsolved. In this study, a custom dataset consisting of handheld images of corn leaves infected with Gray Leaf Spot (GLS), Northern Leaf Blight (NLB), and Northern Leaf Spot (NLS) diseases, acquired under field conditions, was used to develop a novel two-stage semantic segmentation approach for identifying corn diseases and estimate their severity. Three semantic segmentation models were trained for each stage using SegNet, UNet, and DeepLabV3+ network architectures. Stage one used semantic segmentation to extract leaves from complex field backgrounds. In stage two, semantic segmentation was used to locate, identify, and calculate area coverage for disease lesions. After the models were trained, the best performance for stage one was observed from the UNet model, which achieved up to 0.9422 mean weighted intersection over union (mwIoU) and 0.8063 mean boundary F1-score (mBFScore). The best performance for stage two was observed from the DeepLabV3+ model, which could identify the disease lesions with a mwIoU of 0.7379 and mBFScore of 0.5351. Finally, severity was estimated by calculating the percentage of leaf area covered by disease lesions. In the test set, an R2 value (coefficient of determination) of 0.96 was achieved, which denotes that the integrated (UNet-DeepLabV3+) model predicted the severity of three diseases very close to the actual observations. This study developed a novel two-stage deep learning-based approach to accurately identify three targeted corn diseases and estimate their severity to pave the way for developing a field-worthy disease management system.

VI-RADS score system - A primer for urologists.

ABSTRACTBladder cancer (BCa) is one of the most common cancers worldwide and is also considered to be one of the most relapsing and aggressive neoplasms. About 30% of patients will present with muscle invasive disease, which is associated with a higher risk for metastatic disease. The aim of this article is to review the state of art imaging in Radiology, while providing a complete guide to urologists, with case examples, for the rationale of the development of the Vesical Imaging Reporting and Data System (VI-RADS), a scoring system emphasizing a standardized approach to multiparametric Magnetic Resonance Imaging (mpMRI) acquisition, interpretation, and reporting for BCa. Also, we examine relevant external validation studies and the consolidated literature of mpMRI for bladder cancer. In addition, this article discusses some of the potential clinical implications of this scoring system for disease management and follow-up.

Efficiency and Effectivity of a Biological–Epidemiological Fungal Disease Management System in Wheat—A Study of 26 Years

Foliar diseases are a major threat to worldwide wheat production, especially during the vegetative period in maritime climates. Despite advancements in agronomic practices, infestations by foliar diseases are possible under favourable weather conditions, thus, fungicides are essential for maintaining control. Stage-oriented applications are therefore common in farm practices. The optimization of fungicide use according to biological–epidemiological thresholds reduces the total amount of fungicides used, which is of political interest, especially in the European Union. Therefore, the efficiency and effectivity of the fungicides used to control the six major foliar diseases (Septoria tritici blotch, glume blotch, tans spot, powdery mildew, stripe rust, and leaf rust) were analysed in a long-term study of 26 years in northern Germany under favourable maritime conditions. Of those diseases, Septoria tritici blotch was the most dominant recurring disease, with high severity noted in every year of the study. The threshold-based disease management system was compared to a fungicide untreated control and a healthy-standard fungicide treatment (according to growth stages). The usage of the threshold-based system reduced the disease severities significantly compared to the fungicide untreated control, without any loss of yield compared to the healthy-standard fungicide treatment. Thereby, the use of fungicides was reduced by two thirds compared to the stage-oriented healthy-standard treatment. Thus, the advantages of the threshold-based system were obvious, and this approach will be an important tool for future evaluations of current farm practices.

Towards intelligent and integrated pest management through an AIoT-based monitoring system.

Main bottleneck in facilitating integrated pest management (IPM) is the unavailability of reliable and immediate crop damage data. Without sufficient insect pest and plant disease information, farm managers are unable to make proper decisions to prevent crop damage. This work aims to present how an integrated system was able to drive farm managers towards sustainable and data-driven IPM. A system called Intelligent and Integrated Pest and Disease Management (I2 PDM) system was developed. Edge computing devices were developed to automatically detect and recognize major greenhouse insect pests such as thrips (Frankliniella intonsa, Thrips hawaiiensis, and Thrips tabaci), and whiteflies (Bemisia argentifolii and Trialeurodes vaporariorum), to name a few, and measure environmental conditions including temperature, humidity, and light intensity, and send data to a remote server. The system has been installed in greenhouses producing tomatoes and orchids for gathering long-term spatiotemporal insect pest count and environmental data, for as long as 1368 days. The findings demonstrated that the proposed system supported the farm managers in performing IPM-related tasks. Significant yearly reductions in insect pest count as high as 50.7% were observed on the farms. It was concluded that novel and efficient strategies can be achieved by using an intelligent IPM system, opening IPM to potential benefits that cannot be easily realized with a traditional IPM program. This is the first work that reports the development of an intelligent strategic model for IPM based on actual automatically collected long-term data. The work presented herein can help in encouraging farm managers, researchers, experts, and industries to work together in implementing sustainable and data-driven IPM. © 2022 Society of Chemical Industry.

Care and Disease Management: Why Managed Care Organizations (MCOs) Need to have an Inclusive Approach to Patient Care

The health sector increasingly uses the terms "managed care" and "disease management," but few people understand them. Managed care refers to any health care system that pays for and provides treatment. Pressure to keep prices low has helped it flourish in the United States, and improved resource management is lowering costs. US managed care plans vary, but they share several traits. These include restricted doctor providers, secondary care access, selective contracting, financial incentives, quality monitoring, and utilization management. The NHS has all of these aspects, making it a united managed care system. Disease management coordinates resources across the health care system to treat patients throughout their illness. Business organizations have noticed that the NHS lacks a well-established system for disease management. Concerns regarding commercial engagement include the separation of basic medical services, the possibility of becoming a for-profit corporation, and the use of patient-based data. New guidelines may allow NHS disease control to increase.

Current care practices for patients with Duchenne muscular dystrophy in China

BackgroundThe coronavirus disease (COVID-19) pandemic has presented challenges in the care of patients with chronic diseases. We identified the challenges faced by Chinese patients with Duchenne muscular dystrophy (DMD) during the pandemic. MethodsAn online cross-sectional survey was conducted between March 27 and June 30, 2021. ResultsOf the 2105 valid questionnaire responses, 2,056 patients were from non-lockdown areas. In these areas, 42.8% reduced outside daily activities, 49.4% reduced rehabilitation service use, 39.7% postponed regular follow-ups, and 40.8% reported accelerated motor function decline. These figures generally increased for patients from lockdown areas—67.3% reduced outside daily activities, 44.9% reduced rehabilitation service use, 79.6% postponed regular follow-ups, and 55.1% reported accelerated motor function decline. Ambulation loss was most commonly reported in September and March before 2020; however, this trend was absent in 2020. Regarding the informed prices of disease-modifying drugs in Europe and the United States, 86.7% could afford a maximum of one-twentieth of the prices, 8.0% could afford one-tenth of the prices, and only 0.6% of the patients could afford the full prices. ConclusionsImplementation of standardized care for DMD in China is consistent with global practices, and the COVID-19 pandemic has affected the care of patients with chronic diseases worldwide, particularly in lockdown areas. Telemedicine is an effective model for providing healthcare to such patients. Healthcare workers should assist patients and establish more robust chronic disease management systems. Collaboration between governmental and non-governmental entities could address the cost of disease-modifying drugs in China and other developing countries.

People, process and technology: A model for digital transformation of healthcare

COVID-19 has brought forward unprecedented challenges for healthcare systems worldwide. As healthcare moves into a state of COVID-19 recovery, we must reflect on lessons learned from the COVID-19 pandemic to create a more resilient future. One of the most critical outcomes this pandemic has highlighted, is the role of digital technology and digital health in transforming health care services. We suggest that by focusing on people, processes and technologies, healthcare systems can not only recover from the impact of COVID-19, but also transform healthcare from the traditional disease management system of today into the post pandemic health system of tomorrow, one that is modernised to align with the needs of the populations that health systems serve. Currently, health care systems are predominantly transactional, delivering care focused on disease management to restore health and/or manage acute health conditions. A digital health ecosystem offers a strategy to realise the full health potential of every human everywhere, from the smallest village to the most complex health care environments in health systems. Digital health ecosystems identify and track progress towards health goals, tracking outcomes and health risks at the individual and population level, which informs care approaches that are personalised to people and populations and are focused on mitigating risks in order to support and sustain health and wellness. The sustainability of healthcare systems and the health of global populations will be influenced by the rate of adoption and scalability of digital health. This paper will examine digital health transformation as a strategy to overcome the challenges health systems are facing and to advance the sustainability of health systems globally.

Impact Analysis of De-Identification in Clinical Notes Classification.

Clinical notes provide valuable data in telemonitoring systems for disease management. Such data must be converted into structured information to be effective in automated analysis. One way to achieve this is by classification (e.g. into categories). However, to conform with privacy regulations and concerns, text is usually de-identified. This study investigated the effects of de-identification on classification. Two pseudonymisation and two classification algorithms were applied to clinical messages from a telehealth system. Divergence in classification compared to clear text classification was measured. Overall, de-identification notably altered classification. The delicate classification algorithm was severely impacted, especially losses of sensitivity were noticeable. However, the simpler classification method was more robust and in combination with a more yielding pseudonymisation technique, had only a negligible impact on classification. The results indicate that de-identification can impact text classification and suggest, that considering de-identification during development of the classification methods could be beneficial.

The role and tasks of patient groups as an innovator of health and medical system : Focused on the activities of Korean Society Type 1 Diabetes

The health and medical service paradigm is changing from provider-centered treatment to consumer-centered prevention and management. As medical expenses increase due to an increase in the number of chronically ill patients, national policy support is in progress to increase their healthy lifespan. The perception of the patient is also changing from a passive object to a subject. Accordingly, discussions on how to re-establish the role of the patient and organize and grow as an innovation agent are also in full swing. In this study, the case of ‘Korean Society Type 1 Diabetes’, which is leading user-driven innovation activities in the living lab method. The Korean Society Type 1 Diabetes has been building a new patient-led disease management system by not only developing patient-led devices, but also taking the lead in medical policies and improving social awareness. In particular, since it was an ‘undone science’ field that specialized institutions and related organizations were not interested in, patients and their families as the parties and the final user are making related technologies, laws, and institutions. By operating a field-based, patient-led living lab, it is becoming a major player of building a patient-centered research platform while developing capabilities and creating alternatives to problem-solving. Through technological experiments, network expansion, and related institutional innovation activities related to type 1 diabetes, patient group is conducting a leading experiment in achieving a transition from a hospital and treatment-oriented health care system to a patient-centered, prevention and care-centered health care system.

The Impact of Diabetes on Vascular Disease: Progress from the Perspective of Epidemics and Treatments

At present, the global incidence of diabetes has increased in countries with large populations, and the changes in developing regions are particularly worthy of attention. In the past 40 years or so, the income situation in China, India, and other countries has exploded, leading to changes in the way of life and work as well as an increase in the prevalence of diabetes. Metabolic disorders caused by diabetes can lead to secondary vascular complications, which have long-term malignant effects on the heart, kidneys, brain, and other vital organs of patients. Adequate primary prevention measures are needed to reduce the incidence of diabetic vascular complications, and more attention should be given to treatment after the disease. To this end, it is necessary to determine a standardized drug and physical therapy system and to build a more efficient and low-cost chronic disease management system.