The Trump administration, as portrayed in an recent Axios piece by Sam Baker is more than quietly revolutionizing Medicaid, it is reducing membership in the safety net payor through administrative gates, work requirements, and enforcing premiums as low as $1. Readers note: Medicaid has historically not charged premiums and this action reduces membership by adding additional barries. Additionally, most billings activities are more expense than the revenue gained. These efforts have one goal - reduce the number of individuals on Medicaid.
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Food Access is loosely defined as “people’s ability to find and afford food”. However, there are a number of related concepts and terms depending on the mode of study being employed. A recent Tufts University study, categorized ten variations on the term including the colorful geographic nomenclature “food desert”, “food swamp”, and “food hinterland”. Food access is a difficult issue to categorize because of tremendous variation in prices, cultural preferences, and skill sets.
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What's the price?

Today the Health Care Cost Institute (HCCI) posted their annual report of United States health care spending. With an enviable data set of claims from commercial under 65-yr populations from. Aetna, Humana, Kaiser and UnitedHealthcare, HCCI concluded that health spending grew by 4.6% in 2016. In a vacuum that number may be seen as a success given historical year over year growth. Diving into the details we can view multiple trends that create opportunities in better managing care and ultimately supporting a reduction of costs in the future.
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this post is part of a series of in depth posts about specific modules in our Social Determinant Platform In many cases, patients put off or delay seeking care when they are not sure how they can pay for it. According to Commonwealth Fund surveys, 20% of patients did not see a doctor because of cost, and 18% did not get a recommended test. Other studies have reiterated these results.
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“Neighborhood stress” or neighborhood socioeconomic context, has long been a focus of public health research. The following summarizes the unique opportunities neighborhoods provide when researching health effects: …the “meso” level of neighborhoods is of interest for three important reasons. First, many of these broader social determinants are manifested, and directly affect individuals, through neighborhood social and physical environments. Thus the study of neighborhoods provides an opportunity to understand the processes linking these broader social and economic factors … in very concrete ways.
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Non-clinical factors including social determinants of health (SDOH) are responsible for, depending on the source, 20%, 60%, 70%, 80% of a persons overall health. (for more on the weighting debate see Different Perspectives on Assigning Weights to Determinants of Health) Whether a person is made directly sick through environmental exposure or lacks the means to engage in a complex treatment plan, these factors all combine to seriously determine outcomes. As health organizations adopt value-based payment schemes social determimnants impact the bottom line and deserve greater attention from value-seeking organizations.
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Medicaid, the federally financed but state-run insurance program for the poor, now covers 1 in 5 Americans nationwide. In seven states, the number is higher ranging from 24% to 29%. The increasing size and scope is starting to draw attention from government budget directors and policy wonks, but has not drawn the attention of new technology or innovation investment given the tremendous size and market potential. The California Health Care Foundation (CHCF), a nonprofit grantmaking philanthropy based in Oakland, is trying to change that.
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Innovation in Medicaid

Innovation in Medicaid Medicaid continues to be an area for tremendous growth and disruption in the health care market. Served by traditional Medicaid programs, Medicaid Managed Care Organizations, and increasingly through Medicaid Accountable Care Organizations under state-based 115 waivers, the innovation and opportunities for new solutions is growing rapidly. The majority of our work focuses on bringing new solutions to Medicaid and other underserved populations. One key element that drives our work is the need for greater emphasis on non-clinical factors – specifically social determinants of health (SDOH).
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How do you find a patient? It seems all too common that a provider or health analyst would say “How many patients are taking a statin?” or “How many patients didn’t have their physical?”. These are the fundamental questions of population health. The advent of electronic health data was supposed to make answering these questions easy and compared to a system on paper it does. So, when we want to know
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Health Care Reform With an on-again, off-again alphabet soup of legislative mandates and variants moving forward – ACHA, BCRA, GCHF – health care organizations are doing their best to plan for an uncertain future. What this means for the solution providers – ourselves included – is that we need to invest in flexible, scalable frameworks to deploy new outputs in support of this rapidly changing landscape. Going Forward Without a crystal ball to know the future, I am certain of one thing – the questions that organizations ask in the future are unknown today.
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10 Heatmaps 10 Libraries I recently watched Jake VanderPlas’ amazing PyCon2017 talk on the landscape of Python Data Visualization. That presentation inspired this post. In programming, we often see the same ‘Hello World’ or Fibonacci style program implemented in multiple programming languages as a comparison. In Jake’s presentation, he shows the same scatter plot in several of the libraries he featured. Below, I am following the same formula. I am recreating a heatmap about airline flights, in ten different python visualization libraries.
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Social Determinants and Neighborhoods Social determinants of health (SDOH) are “the structural determinants and conditions in which people are born, grow, live, work and age.”via KFF. They are receiving increased attention as healthcare organizations begin to increasingly emphasize population health and value-based payment models. For Algorex Health customers, social determinants are moving to the forefront as several value-based payment programs, especially in Medicaid, begin to use social determinants to directly effect payment through risk-adjustment.
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Is this the wearable revolution? Apple Watches to Aetna Many in the Heath IT (HIT) community are abuzz on a report from CNBC that Aetna and Apple are in discussions to roll out Apple Watches to all 23 Million Aetna customers. Last week, Apple and Aetna met to discuss bringing the Apple Watch to the insurer's 23M members. More: https://t.co/RJwyp811lf @chrissyfarr pic.twitter.com/kGr9ZMrrGQ — Rock Health (@Rock_Health) August 14, 2017
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Medication Days Over the past 150 years, some of the most influential medical breakthroughs have been medications that cure disease, relieve symptoms and ultimately extend life and wellness. Considering medication data is essential for measuring the health status of a patient or population, the standards we use to measure compliance with prescriptions should be widely available. Yet processing medication data into useful statistics presents a set of unique challenges.
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The CMS division of HHS produces a freely available algorithm for determining the diagnosis risk of cost for beneficiaries. The problem with this freely available algorithm is that it is written in a technology, SAS , that is not freely usable.1 We at Algorex Health have reimplemented the HCC algorithm in Python with two aims in mind. First, we want to promote truly free algorithms for value-based analytics, contributing to a community ethos of open-source population health libraries.
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Algorex Health Technologies

A blog for technology, policy, and grievances in the Open Health World

Opening the Healthcare Technology Doors

Boston, Massachusetts