Notes

Medical methods and also endeavours concerning COVID19 within Pakistan: Telemedicine a method to expect.
This commentary explores the ways in which robust research focused on policy implementation will increase our ability to understand how to - and how not to - address social determinants of health. We make three key points in this commentary. First, policies that affect our lives and health are developed and implemented every single day, like it or not. Epigallocatechin clinical trial These include "small p" policies, such as those at our workplaces that influence whether we have affordable access to healthy food at work, as well as "large P" policies that, for example, determine at a larger level whether our children's schools are required to provide physical education. However, policies interact with context and are likely to have differential effects across different groups based on demographics, socioeconomic status, geography, and culture. We are unlikely to improve health equity if we do not begin to systematically evaluate the ways in which policies can incorporate evidence-based approaches to reducing inequities and to provide structon. Third, development of an explicit policy implementation science agenda focused on health equity is critical. This will include efforts to bridge scientific evidence and policy adoption and implementation, to evaluate policy impact on a range of health equity outcomes, and to examine differential effects of varied policy implementation processes across population groups. We cannot escape the reality that policy influences health and health equity. Policy implementation science can have an important bearing in understanding how policy impacts can be health-promoting and equitable.
To understand barriers and facilitators to the adaptation of programs reflecting changing scientific guidelines for breast/cervical cancer screening, including factors influencing the de-implementation of messaging, program components, or screening practices no longer recommended due to new scientific evidence.

National sample of NWP sites from across the United States.

We conducted a convergent mixed-methods design in partnership with The National Witness Project (NWP), a nationally implemented evidence-based lay health advisor (LHA) program for breast/cervical cancer screening among African American (AA) women. Surveys were conducted among 201 project directors (PDs) and LHAs representing 14 NWP sites; in-depth interviews were conducted among 14 PDs to provide context to findings. Survey data and qualitative interviews were collected concurrently from January 2019-January 2020.

Trust and mistrust were important themes that arose in quantitative and qualitative data. Common concerns about adapting tosidered in implementation science as they 1) have critical implications for shaping health inequities; and 2) help explain and contextualize why new screening guidelines may not be fully embraced in the AA community.
The high prevalence of trauma and its negative impact on health among people living with HIV underscore the need for adopting trauma-informed care (TIC), an evidence-based approach to address trauma and its physical and mental sequelae. However, virtually nothing is known about factors internal and external to the clinical environment that might influence adoption of TIC in HIV primary care clinics.

We conducted a pre-implementation assessment consisting of in-depth interviews with 23 providers, staff, and administrators at a large urban HIV care center serving an un-/under-insured population in the southern United States. We used the Consolidated Framework for Implementation Research (CFIR) to guide qualitative coding to ascertain factors related to TIC adoption.

Inner setting factors perceived as impacting TIC adoption within HIV primary care included relative priority, compatibility, available resources, access to knowledge and information (ie, training), and networks and communications. Relevant outementation strategies that could be employed to support successful TIC implementation.
Uncontrolled hypertension is a significant risk factor for cardiovascular morbidity and mortality. In the United States, many patients remain uncontrolled, in part, due to poor medication adherence. Efforts to improve hypertension control include not only attending to medical management of the disease but also the social determinants of health, which impact medication adherence, and ultimately blood pressure control.

To determine which social determinants - health care access or community and social stressors - explain medication adherence.

In this cross-sectional analysis, we used baseline data (N=1820, collected August 2017 to October 2019) from a pragmatic trial, which compares the effectiveness of a multi-level intervention including collaborative care and a stepped approach with enhanced standard of care for improving blood pressure. We used logistic regression analyses to examine the association between patient experiences of care and community and social stressors with medication adherence.

Theocus on addressing social stressors.
To identify ICD-10-CM diagnostic codes associated with the social determinants of health (SDOH), determine frequency of use of the code for homelessness across time, and examine the frequency of interrupted periods of Medicaid eligibility (ie, Medicaid churn) for beneficiaries with and without this code.

Retrospective data analyses of New York State (NYS) Medicaid claims data for years 2006-2017 to determine reliable indicators of SDOH hypothesized to affect Medicaid churn, and for years 2016-2017 to examine frequency of Medicaid churn among patients with and without an indicator for homelessness.

Any interruption in the eligibility for Medicaid insurance (Medicaid churn), assessed via client identification numbers (CIN) for continuity.

Analyses were conducted to assess the frequency of use and pattern of New York State Medicaid claims submission for SDOH codes. Analyses were conducted for Medicaid claims submitted for years 2016-2017 for Medicaid patients with and without a homeless code (ie, ICD-10-CM Z59.0) in 2017.

ICD-9-CM / ICD-10-CM codes for lack of housing / homelessness demonstrated linear reliability over time (ie, for years 2006-2017) with increased usage. In 2016-2017, 22.9% of New York Medicaid patients with a homelessness code in 2017 experienced at least one interruption of Medicaid eligibility, while 18.8% of Medicaid patients without a homelessness code experienced Medicaid churn.

Medicaid policies would do well to take into consideration the barriers to continued enrollment for the Medicaid population. Measures ought to be enacted to reduce Medicaid churn, especially for individuals experiencing homelessness.
Medicaid policies would do well to take into consideration the barriers to continued enrollment for the Medicaid population. Measures ought to be enacted to reduce Medicaid churn, especially for individuals experiencing homelessness.
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