Hopkins acg version 11 download

And currently I won't add more languages hard to maintain. This app is just a lite player, I do not write decoder, it uses system sdk component and free FFmpeg unmodifiable, under LGPL to decode data automatically. It should support most common formats, but it will not support all formats, just try, if not supported, I can do nothing to it. I may not see all the reviews. Thank you very much!!!

Some features depend on the system version. ACG Player. See system requirements. Surface Hub. Clin Interv Aging. Effect of dysphasia and dysphagia on inpatient mortality and hospital length of stay: a database study.

J Am Geriatr Soc. Consequence of dysphagia in the hospitalized patient: impact on prognosis and hospital resources. Arch Otolaryngol Head Neck Surg. Meta-analysis of dysphagia and aspiration pneumonia in frail elders. J Dent Res. Economic and survival burden of dysphagia among inpatients in the United States. Dis Esophagus. Diagnosis and management of oropharyngeal dysphagia among older persons, state of the art.

J Am Med Dir Assoc. Clave P, Shaker R. Dysphagia: current reality and scope of the problem. Nat Rev Gastroenterol Hepatol. Prevalence of and risk factors for dysphagia in the community dwelling elderly: a systematic review. J Nutr Health Aging. Maeda K, Akagi J. Sarcopenia is an independent risk factor of dysphagia in hospitalized older people. Geriatr Gerontol Int. Decreased skeletal muscle mass and risk factors of sarcopenic dysphagia: a prospective observational cohort study.

Oropharyngeal Dysphagia in a community-based elderly cohort: the Korean longitudinal study on health and aging. J Korean Med Sci.

The identification of frailty: a systematic literature review. Speech-language pathology care and short- and long-term outcomes of laryngeal cancer treatment in the elderly. Nutr Hosp. Dysphagia, short-term outcomes, and cost of care after anterior cervical disc surgery. Oropharyngeal dysphagia is a prevalent risk factor for malnutrition in a cohort of older patients admitted with an acute disease to a general hospital.

Clin Nutr. Brodsky R. Nutrition issues in Dysphagia: identification, management, and the role of the dietician. Nutr Clin Pract. Google Scholar. Predictors of aspiration pneumonia: how important is dysphagia? Payne M, Morley JE. Editorial: dysphagia, dementia, and frailty. Evaluation of the natural history of patients who aspirate. Prevalence of frailty in middle-aged and older community dwelling Europeans living in 10 countries. Frailty and pre-frailty in middle-aged and older adults and its association with multimorbidity and mortality: a prospective anlaysis of Lancet Public Health.

Accessed August 6, The system continues to evolve, providing ever-more refined tools used in the US and across the globe for over 30 years, from commercial health plans and governments to health systems and large employers. The beauty of the ACG System is its ability to combine data from an array of sources to reveal powerful insights that go beyond just medical records. By identifying risk and tracking patients over time, the ACG System can help you plan ahead and reduce health care costs—especially valuable to risk-bearing health systems and provider organizations.

Health budget —21 - vulekamali. Accessed March 22, Sullivan GM, Feinn R. Using effect size—or why the P value is not enough.

J Graduate Med Educ. Too big to fail: large samples and the p-value problem. Inf Syst Res. Gibbons MC. In: Bos L et al. Amsterdam: IOS Press; The association between neighborhood socioeconomic and housing characteristics with hospitalization: results of a National Study of veterans. J Am Board Fam Med. South African National Department of Health. World Health Organization.

About social determinants of health: WHO; Geographic bias related to geocoding in epidemiologic studies. Int J Health Geographics. Statistics South Africa. Accessed April 26, The impact of unemployment on health: a review of the evidence. J Public Health Policy. Frieden TR. A framework for public health action : the health impact pyramid.

Download references. You can also search for this author in PubMed Google Scholar. CM acquired the underlying data; executed the data exploration and final analysis; generated the results, diagrams and interpretation of results; and drafted the manuscript. HK mentored CM in the design of the study; assisted with the interpretation of the results; provided suggestions about the necessary revisions; and collaborated in writing the manuscript.

Both authors read and approved the final manuscript. Correspondence to Cristina Mannie. Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Characteristics of the Study Population. Figures that describe characteristics of the study population. List of districts per province with key indicators. Table that illustrates the districts per province and key study indicators.

District boundaries, South Africa. Map that illustrates the district boundaries in South Africa and district codes per province. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material.

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Reprints and Permissions. Mannie, C. Assessing the geographical distribution of comorbidity among commercially insured individuals in South Africa. BMC Public Health 20, Download citation. Received : 05 May Accepted : 26 October Published : 16 November Anyone you share the following link with will be able to read this content:. Sorry, a shareable link is not currently available for this article. Provided by the Springer Nature SharedIt content-sharing initiative.

Skip to main content. Search all BMC articles Search. Download PDF. Abstract Background Comorbidities are strong predictors of current and future healthcare needs and costs; however, comorbidities are not evenly distributed geographically. Methods This study assessed the geographical distribution of comorbidity and its associated financial implications among commercially insured individuals in South Africa SA.

Conclusions Our results show underlying disparities in CMI at national, provincial, and district levels. Background Timely information on leading causes of mortality, disease prevalence, and health-related risk factors in various regions of a country are fundamental to setting targeted health policies.

Methods Study objectives The primary objectives of this study were: 1 presenting a district-level geographical distribution of the average disease burden and healthcare utilization of commercially insured individuals; 2 assessing disease burden using a measure that describes the overall disease burden of an individual instead of isolated single diseases ; and, 3 showcasing the value of health status measurement towards understanding the full picture of disease burden in SA using data that is routinely collected for healthcare delivery.

Data sources Administrative claims data were obtained from one of the largest health risk management services providers and administrator of health plans in SA. Study population The initial study population assessed for inclusion included 3. Selection process of the study population. Full size image. Results Characteristics of the study population The 2. Discussion Comorbidities are essential predictors of cost and utilization in healthcare [ 8 ].