Multiple Sources Of Health Care Research Articles

Facilitators and Barriers to Health Seeking among People Who Use Drugs in the Sunyani Municipality of Ghana: An Exploratory Study.

Drug use is one of the global public health issues, and its accompanying disorders have consequences on people's mental, physical, and environmental health. Nevertheless, the majority of people who use drugs have never been treated for drug dependence and other health conditions whilst others discontinue their treatment for drug use disorder. Using the health belief model, the study aimed at exploring facilitators and barriers to health-seeking among people who use drugs in the Sunyani Municipality of Ghana. A descriptive study design was used, employing a qualitative approach. In-depth interviews were conducted with a total of 22 participants, including two key informants (male and female). The first group of participants was recruited from the ghetto (an area in the municipality where people who use drugs are usually located). The other group of participants was recruited using hospital-based records. The interview data were transcribed, coded, and analysed for the generation of themes with the aid of Nvivo version 12 pro. The results showed that people who use drugs face health challenges such as drug dependence, malaria, lungs and breathing complications, cardiovascular complications, and skin complications. People who use drugs experienced poor perceived quality of life and low health status. Health-seeking behaviours of interviewees were influenced by the perceived benefit, perceived severity, cues to action, among others. Multiple sources of healthcare were used by the people who use drugs. Whereas ease of communication, perceived severity, benefit, among others were facilitators to their health-seeking behaviours, cost, dwindling social support, lack of knowledge of the condition, and fear of arrest by law enforcement agencies also served as barriers to seeking healthcare at the orthodox health facilities. This paper suggests a holistic approach to help improve the health and health-seeking behaviours of people who use drugs. The researchers wish to indicate that an earlier version of this manuscript has been presented at the University of Ghana as a thesis.

Deep Learning based Optimal Multimodal Fusion Framework for Intrusion Detection Systems for Healthcare Data

Data fusion is a multidisciplinary research area that involves different domains. It is used to attain minimum detection error probability and maximum reliability with the help of data retrieved from multiple healthcare sources. The generation of huge quantity of data from medical devices resulted in the formation of big data during which data fusion techniques become essential. Securing medical data is a crucial issue of exponentially-pacing computing world and can be achieved by Intrusion Detection Systems (IDS). In this regard, since singular-modality is not adequate to attain high detection rate, there is a need exists to merge diverse techniques using decision-based multimodal fusion process. In this view, this research article presents a new multimodal fusion-based IDS to secure the healthcare data using Spark. The proposed model involves decision-based fusion model which has different processes such as initialization, pre-processing, Feature Selection (FS) and multimodal classification for effective detection of intrusions. In FS process, a chaotic Butterfly Optimization (BO) algorithm called CBOA is introduced. Though the classic BO algorithm offers effective exploration, it fails in achieving faster convergence. In order to overcome this, i.e., to improve the convergence rate, this research work modifies the required parameters of BO algorithm using chaos theory. Finally, to detect intrusions, multimodal classifier is applied by incorporating three Deep Learning (DL)-based classification models. Besides, the concepts like Hadoop MapReduce and Spark were also utilized in this study to achieve faster computation of big data in parallel computation platform. To validate the outcome of the presented model, a series of experimentations was performed using the benchmark NSLKDDCup99 Dataset repository. The proposed model demonstrated its effective results on the applied dataset by offering the maximum accuracy of 99.21%, precision of 98.93% and detection rate of 99.59%. The results assured the betterment of the proposed model.

Medical record-based ascertainment of behaviors suggestive of opioid misuse, diversion, abuse, and/or addiction among individuals showing evidence of doctor/pharmacy shopping.

ObjectivesDoctor/pharmacy shopping, the practice of seeking prescriptions from multiple healthcare sources without their coordination, may be a measure of prescription medicine abuse. This cross-sectional study examined the relationship between a claims-based doctor/pharmacy shopping definition and medical record documented behaviors suggestive of misuse, diversion, abuse and/or addiction.MethodsPatients with ≥2 opioid dispensings starting in 2012 in a US administrative claims database were grouped into doctor/pharmacy shopping categories by number of providers and pharmacies used over 18 months: no shopping, minimal shopping, moderate shopping and severe shopping. Medical charts of opioid prescribers were reviewed to identify behaviors suggestive of misuse, diversion, abuse and/or addiction.ResultsAmong 581,940 opioid users, 78% were classified as no shopping, 11% minimal shopping, 8% moderate shopping and 3% severe shopping. Almost 40% of severe shopping patients had no medical record documented behaviors (positive predictive value: 24.3%). Compared with no shopping, the odds ratio [OR] of ≥3 behaviors was 1.70 (95% confidence interval [CI] 0.50–5.78) for minimal shopping, 1.81 (95% CI 0.54–6.03) for moderate shopping, and 8.93 (95% CI 3.12–25.54) for severe shopping.ConclusionsClaims-identified severe doctor/pharmacy shopping was strongly associated with behaviors suggestive of misuse, diversion, abuse and/or addiction, but the proportion of medical records documenting these was low.

A comparison between physicians and computer algorithms for form CMS-2728 data reporting.

CMS-2728 form (Medical Evidence Report) assesses 23 comorbidities chosen to reflect poor outcomes and increased mortality risk. Previous studies questioned the validity of physician reporting on forms CMS-2728. We hypothesize that reporting of comorbidities by computer algorithms identifies more comorbidities than physician completion, and, therefore, is more reflective of underlying disease burden. We collected data from CMS-2728 forms for all 296 patients who had incident ESRD diagnosis and received chronic dialysis from 2005 through 2014 at Indiana University outpatient dialysis centers. We analyzed patients' data from electronic medical records systems that collated information from multiple health care sources. Previously utilized algorithms or natural language processing was used to extract data on 10 comorbidities for a period of up to 10 years prior to ESRD incidence. These algorithms incorporate billing codes, prescriptions, and other relevant elements. We compared the presence or unchecked status of these comorbidities on the forms to the presence or absence according to the algorithms. Computer algorithms had higher reporting of comorbidities compared to forms completion by physicians. This remained true when decreasing data span to one year and using only a single health center source. The algorithms determination was well accepted by a physician panel. Importantly, algorithms use significantly increased the expected deaths and lowered the standardized mortality ratios. Using computer algorithms showed superior identification of comorbidities for form CMS-2728 and altered standardized mortality ratios. Adapting similar algorithms in available EMR systems may offer more thorough evaluation of comorbidities and improve quality reporting.

Community Mobilization in Mumbai Slums to Improve Perinatal Care and Outcomes: A Cluster Randomized Controlled Trial

Improving maternal and newborn health in low-income settings requires both health service and community action. Previous community initiatives have been predominantly rural, but India is urbanizing. While working to improve health service quality, we tested an intervention in which urban slum-dweller women's groups worked to improve local perinatal health. A cluster randomized controlled trial in 24 intervention and 24 control settlements covered a population of 283,000. In each intervention cluster, a facilitator supported women's groups through an action learning cycle in which they discussed perinatal experiences, improved their knowledge, and took local action. We monitored births, stillbirths, and neonatal deaths, and interviewed mothers at 6 weeks postpartum. The primary outcomes described perinatal care, maternal morbidity, and extended perinatal mortality. The analysis included 18,197 births over 3 years from 2006 to 2009. We found no differences between trial arms in uptake of antenatal care, reported work, rest, and diet in later pregnancy, institutional delivery, early and exclusive breastfeeding, or care-seeking. The stillbirth rate was non-significantly lower in the intervention arm (odds ratio 0.86, 95% CI 0.60-1.22), and the neonatal mortality rate higher (1.48, 1.06-2.08). The extended perinatal mortality rate did not differ between arms (1.19, 0.90-1.57). We have no evidence that these differences could be explained by the intervention. Facilitating urban community groups was feasible, and there was evidence of behaviour change, but we did not see population-level effects on health care or mortality. In cities with multiple sources of health care, but inequitable access to services, community mobilization should be integrated with attempts to deliver services for the poorest and most vulnerable, and with initiatives to improve quality of care in both public and private sectors. Current Controlled Trials ISRCTN96256793

Does socio-economic status explain use of modern and traditional health care services?

Although socioeconomic status is acknowledged to be an important determinant of modern health care utilisation, most analyses to date have failed to include traditional systems as alternative, or joint, providers of care. In developing countries, where pluralistic care systems are common, individuals are likely to be using multiple sources of health care, and the order in which systems are chosen is likely to vary according to income. This paper uses self-collected data from households in Ghana and econometric techniques (biprobit modelling and ordered logit) to show that rising income is associated with modern care use whilst decreasing income is associated with traditional care use. When utilisation is analysed in order, results show rising income to have a positive effect on choice of modern care as a first provider, whilst choosing it second, third or never is associated with decreasing income. The effects of income on utilisation patterns of traditional care are stronger: as income rises, utilisation of traditional care as a first choice decreases. Policy should incorporate traditional care into the general utilisation framework and recognise that strategies which increase income may encourage wider utilisation of modern over traditional care, whilst high levels of poverty will see continued use of traditional care.

Drug-resistant tuberculosis in Mumbai, India: An agenda for operations research

Operations research (OR) is well established in India and is also a prominent feature of the global and local agendas for tuberculosis (TB) control. India accounts for a quarter of the global burden of TB and of new cases. Multidrug-resistant TB is a significant problem in Mumbai, India’s most populous city, and there have been recent reports of totally resistant TB. Much thought has been given to the role of OR in addressing programmatic challenges, by both international partnerships and India’s Revised National TB Control Programme. We attempt to summarize the major challenges to TB control in Mumbai, with an emphasis on drug resistance. Specific challenges include diagnosis of TB and defining cure, detecting drug resistant TB, multiple sources of health care in the private, public and informal sectors, co-infection with human immunodeficiency virus (HIV) and a concurrent epidemic of non-communicable diseases, suboptimal prescribing practices, and infection control. We propose a local agenda for OR: modeling the effects of newer technologies, active case detection, and changes in timing of activities, and mapping hotspots and contact networks; modeling the effects of drug control, changing the balance of ambulatory and inpatient care, and adverse drug reactions; modeling the effects of integration of TB and HIV diagnosis and management, and preventive drug therapy; and modeling the effects of initiatives to improve infection control.

Socioeconomic and Demographic Factors Associated With Health Care Choices in Taiwan

By using the data from the 2001 National Health Interview Survey and the National Heath Insurance database in Taiwan, this study aims at investigating the socioeconomic and demographic factors associated with different health care choices. This study incorporated hierarchical cluster analysis into multiple correspondent analysis to determine 5 attribute clusters of socioeconomic and demographic factors associated with different health care choices. This study found that older women with higher education levels were more likely to choose multiple sources of health care and that low- to middle-income people were more likely to use over-the-counter medications in pharmacies. In addition, people's self-reported health care choices were inconsistent with their observed health care seeking behavior. The health policy authority may need to provide more health promotion education programs, especially for older women with higher educational levels, and funding incentives for quality of care provided rather than relying solely on reimbursements for episodic care.

Dual Use of VA and Non-VA Services Among Primary Care Patients with Depression

Depression treatment requires close monitoring to achieve optimal, long-term control. Use of multiple sources of health care can affect coordination and continuity of treatment for depression. To assess levels of non-Veterans Health Administration (VA) use among depressed primary care patients by service type and examine patient factors associated with non-VA use. Cross-sectional comparison of dual and VA-only users among depressed primary care patients. Depression was defined as PHQ-9 >or=10. Five hundred fifty depressed patients from the baseline sample of a group-randomized trial of collaborative care for depression in ten VA primary care practices. VA and non-VA outpatient utilization for physical and emotional health problems in the prior 6 months, patient demographics, and co-morbid conditions. All measures were self-reported and obtained at the baseline interview. Overall, 46.8% of VA depressed primary care patients utilized non-VA care. Dual users were more likely to use acute care services (emergency room or inpatient), especially for physical health problems. Dual users of physical health services had more total visits, but fewer VA visits than VA-only users, while dual users of emotional health services had fewer total and VA visits. Factors associated with dual use were urban clinic location, having other insurance coverage, and dissatisfaction with physical health care in general. Almost half of depressed primary care patients used non-VA care, with most of their non-VA use for physical rather than emotional health problems. Care management strategies for depressed patients should include communication and coordination with non-VA providers.

MALARIA-RELATED HEALTH-SEEKING BEHAVIOUR AND CHALLENGES FOR CARE PROVIDERS IN RURAL ETHIOPIA: IMPLICATIONS FOR CONTROL

A range of activities are currently underway to improve access to malaria prevention and control interventions. As disease control strategies change over time, it is crucial to understand the health-seeking behaviour and the local socio-cultural context in which the changes in interventions operate. This paper reflects on how people in an area of seasonal malaria perceive the causes and transmission of the disease, and what prevention and treatment measures they practise to cope with the disease. It also highlights some of the challenges of malaria treatment for health care providers. The study was undertaken in 2003 in Adami Tulu District in south-central Ethiopia, where malaria is a major health problem. Pre-tested structured questionnaires and focus group discussions were conducted among men and women. Malaria, locally known as busa, was perceived as the most important cause of ill health in the area. Respondent's perception and knowledge about the cause and transmission of the disease were relatively high. The newly introduced insecticide-treated nets were not popular in the area, and only 6.4% of households possessed at least one. The results showed that patients use multiple sources of health care for malaria treatment. Public health facilities, private clinics and community health workers were the main providers of malaria treatment. Despite higher treatment costs, people preferred to use private health care providers for malaria treatment due to the higher perceived quality of care they offer. In conclusion, effort in the prevention and control of malaria should be intensified through addressing not only public facilities, but also the private sector and community-based control interventions. Appropriate and relevant information on malaria should be disseminated to the local community. The authors propose the provision of effective antimalarial drugs and malaria prevention tools such as subsidized or free insecticide-treated nets.

Multiple System Utilization and Mortality for Veterans With Stroke

Many Veteran Health Administration (VHA) enrollees receive health services outside the VHA system. However, limited information is available about poststroke utilization and mortality by veterans who used multiple sources of health care. This study assessed the likelihood of 12-month poststroke rehospitalization and mortality of veterans who used VHA only versus those who used multiple sources of care. Our retrospective observational study examined veterans living in Florida and diagnosed with acute stroke. We categorized users into 4 groups: VHA-only, VHA-Medicare, VHA-Medicaid, and VHA-Medicare-Medicaid based on their use of each health care program. Logistic regression models were fitted for 12-month poststroke general rehospitalization, recurrent stroke readmission, and mortality, adjusting for sociodemographic and clinical factors. The sample consisted of 29% VHA-only users, 61% VHA-Medicare users, 3% VHA-Medicaid users, and 7% VHA-Medicare-Medicaid triple users. Compared with the VHA-only users, multiple system users were significantly more likely to be rehospitalized for any cause and for recurrent stroke 12-months postindex. Mortality outcomes depended on when the outcome was measured; at the index admission date, we found no significant difference in mortality across the user groups; at the index discharge date, the VHA-only users was less likely to die within the first 12 months than the users of the 2 dual groups (VHA-Medicare and VHA-Medicaid). Multiple health care source use was common among VHA enrollees with acute stroke in Florida. Multiple system users were more likely to be rehospitalized and the mortality outcomes were dependent on when the outcome was measured.

Health care switching behaviour of malaria patients in a Kenyan rural community

Patients ordinarily use multiple sources of health care. This study reveals the transitions patients in a rural region of Gusii, Kenya are likely to make beyond the homestead in their search for alternatives to combat malaria. Malaria is a very common health problem in the region resulting in enormous human and economic losses. Data on health care seeking behaviour were collected over a 10-month period. The primary data for this paper is from malaria-focused ethnographic interviews with 35 adults (18 women and 17 men). Results show that patients are more likely to start with self-treatment at home as they wait for a time during which they observe their progress. This allows them to minimise expenditure incurred as a result of the sickness. They are more likely to choose treatments available outside the home during subsequent decisions. The decisions include visiting a private health care practitioner, a government health centre or going to a hospital when the situation gets desperate. Knowledge and duration of sickness, the anticipated cost of treatment, and a patient's judgement of the intensity of sickness determine their choice of treatment.