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Challenges Facing Home-Based Caregivers in the Management of Health Care Risk Waste.

ABSTRACT: The quadruple burden of diseases, early discharge from hospital and hospital at home have resulted in home-based care services becoming a requirement in South Africa. These home-based care services generate a significant amount of health care risk waste that is mismanaged. More attention is given to the health care risk waste generated in hospitals and clinics than to health care risk waste generated by home-based caregivers. Therefore, this study investigates the health care risk waste management practices by home-based caregivers. The study adopted a mixed research approach, qualitative and quantitative methods, using a literature review, interviews, and questionnaires as means of data collection. Results show that there are different types of health care risk waste generated as a result of different activities performed by home-based caregivers, but that the waste was found to be managed in an unsafe manner. The majority of households receiving home-based care did not have basic sanitation facilities such as toilets, running water and waste removal services, aggravating the issue of health care risk waste mismanagement. The study recommends a new policy framework that will lead to safe management practices of generated health care risk waste to be adopted by home-based caregivers.

SUBMITTER: Zikhathile T

PROVIDER: S-EPMC6313601 | biostudies-literature | 2018 Nov

REPOSITORIES: biostudies-literature

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Challenges Facing Home-Based Caregivers in the Management of Health Care Risk Waste.

Zikhathile Thobile T Atagana Harrison H

International journal of environmental research and public health 20181130 12

The quadruple burden of diseases, early discharge from hospital and hospital at home have resulted in home-based care services becoming a requirement in South Africa. These home-based care services generate a significant amount of health care risk waste that is mismanaged. More attention is given to the health care risk waste generated in hospitals and clinics than to health care risk waste generated by home-based caregivers. Therefore, this study investigates the health care risk waste manageme ...[more]

PMID: 30513572

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Project description:ImportanceMore than 17 million people in the US provide uncompensated care for adults with physical or cognitive limitations. Such caregiving is associated with worse mental and physical health, yet little research has investigated how publicly funded home care might ameliorate these harms.ObjectiveTo investigate the association between Medicaid home care services and family caregivers' health.Design setting and participantsThis longitudinal cohort study used data from the 1996 to 2017 Medical Expenditures Panel Survey. Data on all household members were collected in 5 interviews over 2 years. Person-level difference-in-difference models were used to isolate within-person changes associated with new onset of Medicaid home care. The Medical Expenditures Panel Survey longitudinal data sets included 331 202 individuals (approximately 10% excluded owing to loss to follow-up). Adult (age ≥21 years) members of households that contained at least 1 person with limited activities of daily living were included in our study. The analysis itself was performed from March to August of 2020.ExposuresNew onset of regular (≥1 time per month) Medicaid home care in the household.Main outcomes and measuresSelf-rated mental and physical health (planned prior to beginning the study).ResultsThe study population was 14 013 adults; 7232 were "likely caregivers," or nondisabled adult coresidents of someone with activities of daily living limitations. Overall, 962 likely caregivers were ever exposed to Medicaid home care in the household; for 563, we observed the onset. Of likely caregivers exposed to Medicaid home care, 479 (50%) were women; 296 (31%) were White non-Hispanic, 309 (31%) were Hispanic or Latinx, and 279 (29%) were Black non-Hispanic individuals, respectively; 326 (34%) had less than a high school education; and 300 (31%) were in or near poverty. Median age of participants was 51 (interquartile range, 39-62) years. New-onset Medicaid home care was associated with a 0.08 standard deviation improvement in likely caregivers' self-rated mental health (95% CI, 0.01-0.14; P = .02) measured 1 to 6 months after onset, equivalent to a 3.39% improvement (95% CI, 0.05%-6.33%) over their average preonset mental health. No association with self-rated physical health was found (<0.001 standard deviations; 95% CI, -0.06 to 0.06; P = .99).Conclusions and relevanceIn this cohort study, Medicaid home care was associated with improvement in caregiver self-rated mental health, but not with any short-term change in self-rated physical health. When evaluating the social value of home care programs, policy makers should consider spillover benefits to caregivers.

Project description:Algorithmic scoring methods are widely used in the finance industry for several decades in order to prevent risk and to automate and optimize decisions. Regulatory requirements as given by the Basel Committee on Banking Supervision (BCBS) or the EU data protection regulations have led to an increasing interest and research activity on understanding black box machine learning models by means of explainable machine learning. Even though this is a step into a right direction, such methods are not able to guarantee for a fair scoring as machine learning models are not necessarily unbiased and may discriminate with respect to certain subpopulations such as a particular race, gender, or sexual orientation-even if the variable itself is not used for modeling. This is also true for white box methods like logistic regression. In this study, a framework is presented that allows analyzing and developing models with regard to fairness. The proposed methodology is based on techniques of causal inference and some of the methods can be linked to methods from explainable machine learning. A definition of counterfactual fairness is given together with an algorithm that results in a fair scoring model. The concepts are illustrated by means of a transparent simulation and a popular real-world example, the German Credit data using traditional scorecard models based on logistic regression and weight of evidence variable pre-transform. In contrast to previous studies in the field for our study, a corrected version of the data is presented and used. With the help of the simulation, the trade-off between fairness and predictive accuracy is analyzed. The results indicate that it is possible to remove unfairness without a strong performance decrease unless the correlation of the discriminative attributes on the other predictor variables in the model is not too strong. In addition, the challenge in explaining the resulting scoring model and the associated fairness implications to users is discussed.

Project description:Background: Medical education has been rapidly growing and transforming due to the enormous evolution of medicine. There have been many proficient ways to learn in medicine, but academic lectures, attending wards, and ambulatory care clinics (ACC) remain the three main ways of gaining clinical knowledge and experience for medical students. Over the past decade, there has been a dramatic shift in care by focusing on ambulatory care rather than inpatient settings, which provides a golden opportunity to reinforce medical education. Purpose: Most of the published studies that have focused on the teaching barriers in ACC were descriptive rather than analytic studies. Herein, we aim to detect and determine the barriers to teaching in ACC settings using qualitative analysis. Methods: This is a cross-sectional, observational study, involving medical students in their clerkship years (i.e., fourth and fifth) from two different medical colleges in Riyadh, Saudi Arabia. Faculty who are involved in undergraduate medical education in both colleges were also included. Main Results: A total of 387 medical students studying at the two universities were enrolled in the study. Most of the participants preferred attending outpatient clinics with consultants (44.2%) and the majority preferred attending internal medicine (IM) and IM subspecialties clinics (40.4%). Regarding the challenges, students believe the top three barriers are related to: faculty (39%), environment (34.8%), and patients (14.8%). Faculty on the other hand see that the top three barriers are related to environment (55.6%), patients (24.4%), and faculty (20%). Conclusion: Undergraduate medical education in outpatient settings has many challenges. In our study, the most significant challenges were COVID-19-related restrictions, patient refusal, and insufficient time for teaching. Future studies are needed to investigate these barriers and explore potential solutions that can decrease their burden on undergraduate medical education.

Dataset Information

Challenges Facing Home-Based Caregivers in the Management of Health Care Risk Waste.

Publications

Challenges Facing Home-Based Caregivers in the Management of Health Care Risk Waste.

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