Social Determinants of Health (SDOH) play a significant role in the health of individuals – and as a result have large-scale impact on the revenue operations of healthcare organizations and negative impacts on overall health outcomes in populations.
Individuals who are disproportionally affected by SDOH factors are more vulnerable to the spread of COVID-19 and to the economic shockwaves that result from pandemic response. Healthcare organizations in certain regions of the United States will experience long-term, negative effects in a similarly disproportionate manner, particularly in terms of growth in Medicaid populations and increased demand for social supports.
As health systems actively mobilize to prepare for the growing number of COVID-19 cases, many changes in day-to-day practices are occurring in order to ready the hospitals for this global pandemic. Some of the courses of action taken over the last few weeks include the cancellation of elective procedures, a swift scaling in the use of virtual care when appropriate, and pivots in specialties to bring more resources to departments where it is needed, just to name a few.
A new public health policy limiting the number of people allowed in the delivery room with a mother during labor to just one has introduced a new set of challenges in the era of COVID-19.
For many moms-to-be, this means — if they want a partner or family member to be there — their doula won’t be able to join them. While the immediate reaction to this scenario for many is likely to be disappointment, for others it could represent a serious risk factor to their outcome.
The COVID-19 Economy Across the United States communities are starting to implement necessary COVID-19 mitigation strategies focused on social distancing that necessitate the closing of schools, bars, restaurants and the cancellation of events. When looking at the risk of COVID-19, there are the clear medical risk factors; old age, cardiovascular disease, smoking, travel history. But the social distancing measures may also exacerbate worsening gaps in medical outcomes caused by social, economic, and environmental determinants of health, SDOH.
Helping First: As we work with groups across the country to deploy non-clinical programs to health plans, health systems, and community benefit organizations – there is one common theme that has emerged as the key factor between the status quo and greater-than-expected patient and member engagement. That common theme is, quite simply, an offer to help first. The dominant strategy in social needs deployment today starts with assessing patients or members using a standardized screening tool.
The New England Society for Health Strategy (NESHS) has been a great forum for innovation and the development of novel programs to support the engagement, care, and management of patients and health plan members. As such, we are proud and excited to sponsor the organization and be the Sponsor of the Month for July.
For more information about NESHS: https://www.neshs.org/
Layering Maps and Data: At Algorex Health, we make a lot of maps and get a lot of questions about the tools we use to make them. So, I thought I would briefly describe our process and the tools we use. I covered the basics of geographic charting in a past blog post and some of that terminology will be repeated here.
We use to two primary data visualization systems at Algorex Health both of which were chosen for their support withthin the Python/Jupyter stack, ease of use, and/or aesthetic flexibility:
When is Data Big? This week the health world turns to Orlando for the annual conference of the Health Information Management Systems Society annual conference. it is absolutely one of the biggest events in health IT and one of the top 25 trade shows in the entire country.
How many people attend HIMSS each year? We could search one of hundreds of press releases about the event from exhibitors. We could even visit the link above from Trade Show news.
This post is part of a larger series of posts that examines the use of declarative logic programming in implementing a healthcare-specific risk score called the HCC Risk Score. The scope of this series runs through such topics as
healthcare-intensive dissection of SAS code and translation into Python and PyDatalog a generic introduction to Logic Programming with Prolog and SQL (this post) discussions on the role of declarative programming in a technical organization the difference between forward-chaining and backward-chaining as an implementation strategy in logical/declarative technologies the choice of a forward-chaining embedded language called CHR for re-implementing our code from PyDatalog This post has the following characteristics: