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A hybrid Forecast Cost Benefit Classification of diabetes mellitus prevalence based on epidemiological study on Real-life patient's data.

ABSTRACT: The increasing ratio of diabetes is found risky across the planet. Therefore, the diagnosis is important in population with extreme risk of diabetes. In this study, a decision-making classifier (J48) is applied over a data-mining platform (Weka) to measure accuracy and linear regression on classification results to forecast cost/benefit ratio in diabetes mellitus patients along with prevalence. In total 108 invasive and non-invasive medical features are considered from 251 patients for assessment, and the real-time data are gathered from Pakistan over a time span of June 2017 to April 2018. The results indicate that J48 classifiers achieved the best accuracy of (99.28%), whereas, error rate (0.08%), Kappa stats, PRC, and MCC are (0.98%), precision, recall, and F-matrix are (0.99%). In addition, true positive rate is (0.99%) and false positive is (0.08%). The regression forecast decision indicates blood pressure and glucose level are key features for diabetes. The cost/benefit matrix indicates two predictions for positive test with accuracy (66.68%) and (30.60%), and key attributes with total Gain (118.13%). The study confirmed the proposed prediction is practical for screening of diabetes mellitus patients at the initial stage without invasive medical tests and found effectual in the early diagnosis of diabetes.

SUBMITTER: Sohail MN

PROVIDER: S-EPMC6626127 | biostudies-literature | 2019 Jul

REPOSITORIES: biostudies-literature

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A hybrid Forecast Cost Benefit Classification of diabetes mellitus prevalence based on epidemiological study on Real-life patient's data.

Sohail Muhammad Noman MN Jiadong Ren R Uba Musa Muhammad MM Irshad Muhammad M Iqbal Wasim W Iqbal Wasim W Arshad Jehangir J John Antony Verghese AV

Scientific reports 20190712 1

The increasing ratio of diabetes is found risky across the planet. Therefore, the diagnosis is important in population with extreme risk of diabetes. In this study, a decision-making classifier (J48) is applied over a data-mining platform (Weka) to measure accuracy and linear regression on classification results to forecast cost/benefit ratio in diabetes mellitus patients along with prevalence. In total 108 invasive and non-invasive medical features are considered from 251 patients for assessmen ...[more]

PMID: 31300715

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Project description:BackgroundThe economic burden of type 2 diabetes has not been adequately investigated in many low- and lower middle-income countries, including Bangladesh. The aim of this study was to estimate the cost-of-illness of type 2 diabetes and to find its determinants in Bangladesh.MethodsA cross-sectional study was conducted in 2017 to recruit 1253 participants with type 2 diabetes from six diabetes hospitals, providing primary to tertiary health care services, located in the northern and central regions of Bangladesh. A structured questionnaire was used for face-to-face interviewing to collect non-clinical data. Patients' medical records were reviewed for clinical data and hospital records were reviewed for hospitalisation data. Cost was calculated from the patient's perspective using a bottom-up methodology. The direct costs for each patient and indirect costs for each patient and their attendants were calculated. The micro-costing approach was used to calculate direct cost and the human capital approach was used to calculate indirect cost. Median regression analysis was performed to identify the determinants of average annual cost.ResultsAmong the participants, 54% were male. The mean (±SD) age was 55.1?±?12.5?years and duration of diabetes was 10.7?±?7.7?years. The average annual cost was US$864.7 per patient. Medicine cost accounted for 60.7% of the direct cost followed by a hospitalisation cost of 27.7%. The average annual cost for patients with hospitalisation was 4.2 times higher compared to those without hospitalisation. Being females, use of insulin, longer duration of diabetes, and presence of diabetes complications were significantly related to the average annual cost per patient.ConclusionsThe cost of diabetes care is considerably high in Bangladesh, and it is primarily driven by the medicine and hospitalisation costs. Optimisation of diabetes management by positive lifestyle changes is urgently required for prevention of comorbidities and complications, which in turn will reduce the cost.

Project description:ObjectivesComparison of real time teledermatology with outpatient dermatology in terms of clinical outcomes, cost-benefits, and patient reattendance.DesignRandomised controlled trial with a minimum follow up of three months.SettingFour health centres (two urban, two rural) and two regional hospitals.Subjects204 general practice patients requiring referral to dermatology services; 102 were randomised to teledermatology consultation and 102 to traditional outpatient consultation.Main outcome measuresReported clinical outcome of initial consultation, primary care and outpatient reattendance data, and cost-benefit analysis of both methods of delivering care.ResultsNo major differences were found in the reported clinical outcomes of teledermatology and conventional dermatology. Of patients randomised to teledermatology, 55 (54%) were managed within primary care and 47 (46%) required at least one hospital appointment. Of patients randomised to the conventional hospital outpatient consultation, 46 (45%) required at least one further hospital appointment, 15 (15%) required general practice review, and 40 (39%) no follow up visits. Clinical records showed that 42 (41%) patients seen by teledermatology attended subsequent hospital appointments compared with 41 (40%) patients seen conventionally. The net societal cost of the initial consultation was pound132.10 per patient for teledermatology and pound48.73 for conventional consultation. Sensitivity analysis revealed that if each health centre had allocated one morning session a week to teledermatology and the average round trip to hospital had been 78 km instead of 26 km, the costs of the two methods of care would have been equal.ConclusionsReal time teledermatology was clinically feasible but not cost effective compared with conventional dermatological outpatient care. However, if the equipment were purchased at current prices and the travelling distances greater, teledermatology would be a cost effective alternative to conventional care.

Project description:BackgroundPulmonary rehabilitation (PR) has demonstrated patients' physiological and psychosocial improvements, symptoms reduction and health-economic benefits whilst enhances the ability of the whole family to adjust to illness. However, PR remains highly inaccessible due to lack of awareness of its benefits, poor referral and availability mostly in hospitals. Novel models of PR delivery are needed to enhance its implementation while maintaining cost-efficiency. We aim to implement an innovative community-based PR programme and assess its cost-benefit.MethodsA 12-week community-based PR will be implemented in primary healthcare centres where programmes are not available. Healthcare professionals will be trained. 73 patients with CRD and their caregivers (dyads patient-caregivers) will compose the experimental group. The control group will include dyads age- and disease-matched willing to collaborate in data collection but not in PR. Patients/family-centred outcomes will be dyspnoea (modified Medical Research Council Questionnaire), fatigue (Checklist of individual strength and Functional assessment of chronic illness therapy - fatigue), cough and sputum (Leicester cough questionnaire and Cough and sputum assessment questionnaire), impact of the disease (COPD Assessment Test), emotional state (The Hospital Anxiety and Depression Scale), number of exacerbations, healthcare utilisation, health-related quality of life and family adaptability/cohesion (Family Adaptation and Cohesion Scale). Other clinical outcomes will be peripheral (biceps and quadriceps-hand held dynamometer, 1 or 10 repetition-maximum) and respiratory (maximal inspiratory and expiratory pressures) muscle strength, muscle thickness and cross sectional area (biceps brachialis, rectus femoris and diaphragm-ultrasound imaging), exercise capacity (six-minute walk test and one-minute sit to stand test), balance (brief-balance evaluation systems test) and physical activity (accelerometer). Data will be collected at baseline, at 12 weeks, at 3- and 6-months post-PR. Changes in the outcome measures will be compared between groups, after multivariate adjustment for possible confounders, and effect sizes will be calculated. A cost-benefit analysis will be conducted.DiscussionThis study will enhance patients access to PR, by training healthcare professionals in the local primary healthcare centres to conduct such programmes and actively involving caregivers. The cost-benefit analysis of this intervention will provide an evidence-based insight into the economic benefit of community-based PR in chronic respiratory diseases.Trial registrationThe trial was registered in the ClinicalTrials.gov U.S. National Library of Medicine, on 10th January, 2019 (registration number: NCT03799666 ).

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A hybrid Forecast Cost Benefit Classification of diabetes mellitus prevalence based on epidemiological study on Real-life patient's data.

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A hybrid Forecast Cost Benefit Classification of diabetes mellitus prevalence based on epidemiological study on Real-life patient's data.

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