User:"jansimjan2828"/sandbox/Social Determinants data to enter into EHRs

Social Determinants data to enter into EHRs Many times it is often perceived that premature deaths are due to not receiving clinical care quick enough or some genetic disorder but according to the Centers for Disease Control and Prevention (CDC), only 10 percent of factors causing premature death is related to  clinical care,  and the other 30 percent are  due to genetics factors. This means that the others 60 percent are social and environmental factors. Trying to combat premature deaths and poverty  since in the United States today, a person’s ability to live a healthy satisfying  and rewarding life is dramatically affected by  their zip code  has brought into the picture the Social Determinants concept  which was introduce  in 1960s by  President Lyndon B. Johnson’s. This concept contains several domains which is viewed as non-medical factors that can influence healthcare outcomes. These domains includes Income and Social Protection, Education, Working life Conditions, Housing, Early Childhood Development, Basic Amenities and the Environment, Unemployment and Job Insecurity, Social Inclusion and non-discrimination, Food Insecurity, Structural Conflict, and Access to affordable health services of decent quality. Highlighting the relevance of Social Determinants of health to healthcare, has brought into the picture the benefit of using electronic health records (EHRs) for managing the healthcare population, for patients individually, has attracted attention. Many health care systems have begun to explore ways to integrate data related to social determinants with patient’s clinical records. As the population health status becomes more and more important in healthcare, providers are coming to realized that any data outside the traditional clinical findings can give a broader view on the potential drivers of a patient’s health and can identify the best approaches they need to take in order to improve care effectively. For example,  to show what   data can be  integrated into the Emergency Health Records(EHRs), an analyses was conducted from the  SDOH beta data files that was  curated from existing Federal datasets and other  data source available publicly. The task was to Select 3 factors (percentage of households with only one occupant, percentage of households with any internet connection, percentage of households without a computer) from different Domains (social, economic and healthcare context) and correlate them to any “outcomes” (Premature deaths: age-adjusted deaths per 100,000 population aged 74 and under) and then preform a regression analysis in Microsoft excel. The results from the analysis  showed a positive values of  0.47   and 0.65 respectively for percentage of households with only one occupant and  percentage of households without a computer  when  correlated with Premature deaths ” outcome”. This positive value indicated that these factors will not be a contributing factor for premature death. The other task was to perform multiple regression analysis which provided me with a pvalue below 0.05 for percentage of households with any internet connection. A low pvalue means there is a probability that the data is correct and can be trusted. The results is documented in a video attached. This is the type of dataset that can be included in the EHRs to give providers an idea on how social determinants can affect environment and behaviors.

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