Focusing On Public Health Is Required for Societal Resilience

We need to make strong decisions about increasing funding and providing quality research for real-world evidence/data that supports public health.

Public health funding has existed for decades. This neglect has had a major impact since the COVID-19 pandemic took hold and alerted policymakers and thought leaders to the need for more investment.

Consider the numbers: The United States spends about $3.6 billion a year on health, but less than 3% of that money is on public health and prevention. A 2020 Forbes report points out that "from the late 1960s to 2010, federal government spending on public health fell from 45% to 15%. This lack of interest in public health is partly responsible for the response." A recent McKinsey & Company study concluded: "Government leaders are focused on managing the current crisis, but smart investments now can improve the COVID response." -19 continues and strengthens the public health system. to reduce the risk of future epidemics. Investments in public health and other public goods are substantial; investment in prevention, the success of which is not visible, even more.

Other "public goods" that require more investment include health management and research. Although experts continue to argue about the difference between public health and public health, many do not need to. For our purposes, population health refers to the status of a group of people, whether they live in a country, state or country. Public health often casts a wider net, worrying about the state of society. Managing the health of these minorities requires an analytical approach that can take into account a long list of variables, including health determinants (SDoH), the content of their health records, and more. SoH data from Changing Health Care, for example, has shown that the Economic Stability Index (ESI) is a good predictor of health care use. The ESI is a clustering model that uses market behavior and financial behavior to group individuals into 30 categories, with group 1 representing those who may be economically stable and 30 categories minimum. This statistic, which combines race, ESI and health care in Kentucky, suggests that Black/African Americans are less likely to be economically stable (model 1). The same study found that Black/African Americans were almost twice as likely to use the ER as Whites (30.5% vs. 18.1%). An increasing number of medical institutions are beginning to see the benefits of these health systems and are incorporating these statistics into their decisions. Useful data sources that can inform public health include patient surveys, clinical records and EHRs. Many traditional analytical tools are available to extract actionable insights from these data sources, including logistic regression. Over the past decades, several basic studies have improved the risk scoring system to improve public health. The Framingham Heart Health Risk Score has been used for many years to determine the risk of developing heart disease within 10 years. Since the score can help predict the onset of heart disease, it can also be a useful tool for developing programs. prevention of people depends on people to reduce this risk. The tool asks patients to provide their age, gender, smoking status, total cholesterol, HDL cholesterol, systolic blood pressure, and whether they are taking blood pressure medication. The American Diabetes Association has developed its own risk score system to determine the risk of type 2 diabetes in people. The tool takes into account age, sex, history of gestational diabetes, level of physical activity, family history of diabetes, blood pressure, height and weight. The LACE Index is another useful evaluation method for human health. Acronym stands for Duration, Admission Severity, Charlson Comorbidity Index (CCI), and Number of ER Visits in the Past 6 Months. Recently, many AI-based diagnostic tools are now being used to improve people's health. A review of research methods related to ML revealed that algorithms based on neural networks are the most used (41%) in this context, compared to 25.5% for support vector machines and 21% for random forest simulation. .

There is no way to know how the world would have coped with COVID-19 if policy makers had invested enough in public health programs and research. But there is no doubt that we will all fare better in the next health crisis if we invest more time, energy and resources in these strategies.

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