The largest source of health insurance coverage in the United States is through an employer or union. Despite the size and importance of this market, prices are opaque. In this study, we use 2016 to 2018 data from all but one state in the United States, covering $33.8 billion in hospital spending from three sources-self-insured employers, state-based all-payer claims databases, and health plans-to document variation in facility and professional prices for the commercially insured population. We also examine trends and potential reasons that may explain the observed variation in prices. In this study, prices reflect the negotiated allowed amount paid per service, including amounts from both the health plan and the patient, with adjustments for the intensity of services provided. We report differences in standardized negotiated prices and prices relative to Medicare reimbursement rates for the same procedures and facilities.This report is designed to provide price transparency to a large and important market. Price transparency has not been traditionally available in a manner that allows for an easy comparison of prices between hospitals and other providers. The price information in this report can help employers and other purchasers of health care assess the prices that they pay for health care services. This report can also help contribute to policy discussions on price transparency and how to lower health care prices for privately insured Americans.The findings of this study are reported at a high level in this report, and a supplemental Microsoft Excel spreadsheet and an interactive map both provide additional detail (www.rand.org/t/RR4394). This report follows two previous studies on hospital prices (White 2017; White and Whaley, 2019). The current report extends these prior studies by examining additional data sources and documenting prices for additional providers and for specific service categories. Unlike many other examinations of hospital prices, our studies identify hospitals and groups of hospitals under joint ownership ("hospital systems") by name.This research was funded by the Robert Wood Johnson Foundation and participating selfinsured employers and was carried out within the Payment, Cost, and Coverage Program in RAND Health Care in collaboration with the Employers' Forum of Indiana.RAND Health Care, a division of the RAND Corporation, promotes healthier societies by improving health care systems in the United States and other countries. We do this by providing health care decisionmakers, practitioners, and consumers with actionable, rigorous, objective evidence to support their most complex decisions. For more information, see www.rand.org/health-care, or contact

No abstract

The present study evaluates the personal values reported by a sample of New York Hispanic residents using an open evaluation format in which the participants identified and prioritized their personal values. Four hundred and forty-five participants were assigned to one of three groups: Young (n= 159), Adult (n= 168) and Senior (n= 118). The values reported were categorized into post-materialist, materialist or non-classifiable. The Percentage Difference Index between post-materialist and materialist values was calculated in order to determine the value profile for each age group. The results showed that reports of personal values and values attributed to the participants' own generation were similar in Adult and Senior groups, but were very different in the Young Group, with a differential report of post-materialist values. Furthermore, exposure to American culture did not appear to have a significant effect on the reported values of NYC Hispanics. To confirm these findings, we need to conduct additional studies with larger samples of culturally diverse populations.

Age at diagnosisIncome Occupation a b s t r a c t Background/objectives: We have found that chronic myelocytic leukemia (CML) is diagnosed at an earlier age in poorer populations than in more affluent populations. We had used data from the Glivec ® Patient Assistance Program (GIPAP) involving 33,985 patients from 94 participating countries and documented the geographic variation in CML age of onset, with low income identified as a major risk factor for early age of onset. As India is the largest cohort within GIPAP, we studied several demographic factors in this population to investigate other possible contributors to early age at onset. Methods:We analyzed data collected 2002-2008 from 14,167 Indian patients to investigate demographic factors related to age at diagnosis focusing on income and occupation as risk factors.Results: As in the first study, patients with an earlier age at diagnosis of CML were more likely to be in families with lower annual income. In addition, we found age at diagnosis varied across different occupations; patients who were self-employed and worked in agriculture/ fishing were more likely to be diagnosed at a younger age than patients working in the government. Geographic variation in age at CML diagnosis was also observed, possibly reflecting the influence of environmental and socioeconomic factors on the pathogenesis of CML.Conclusions: Environmental factors apparently play a major role in determining age of diagnosis of CML. Analytic studies are needed to determine the relative importance of various exposures such as to herbicides/pesticides, dietary habits and other factors related to income to identify specific contributory factors in the pathogenesis of CML.

Approximately 160 million Americans receive health insurance coverage through an employer or a union. Self-funded employers typically rely on insurance carriers and third-party administrators to negotiate prices and manage benefits but often have little insight into the prices negotiated on their behalf. However, price transparency has not been traditionally available in a manner that allows employers and health care purchasers to easily compare prices between hospitals and other providers.In this study, we use 2018 to 2020 medical claims data from all U.S. states covering hospital and other provider spending to document variation in negotiated prices for the commercially insured population. We found wide variation in hospital prices across states. Case mix-adjusted hospital prices were below 175 percent of Medicare in Arkansas, Hawaii, and Washington, and were above 310 percent of Medicare in Florida, West Virginia, and South Carolina. The price information in this report can help employers and other purchasers of health care assess the prices that they pay for health care services. This report can also help contribute to policy discussions on hospital prices and health care prices for privately insured Americans.This report contains a high-level summary of findings. A supplemental spreadsheet provides additional detail. This report follows three previous RAND Corporation studies on hospital prices and extends these studies by examining additional data sources and more recent periods and by documenting prices for additional providers. Unlike many other studies that have examined health care price variation, this study reports prices and identifies hospitals and groups of hospitals under joint ownership (hospital systems) by name.This study was funded by the Robert Wood Johnson Foundation and participating employers and was carried out within the Payment, Cost, and Coverage Program in RAND Health Care and in collaboration with the Employers' Forum of Indiana.RAND Health Care, a division of the RAND Corporation, promotes healthier societies by improving health care systems in the United States and other countries. We do this by providing health care decisionmakers, practitioners, and consumers with actionable, rigorous, objective evidence to support their most complex decisions.

No abstract

The growth in cancer immunotherapy agents requires an understanding of the immune contexture of the tumor microenvironment (TME). Understanding immune contexture requires multiplex staining, imaging, and analysis to obtain multi-marker phenotypes of specific cells and analyze their biodistribution in the TME. Imaging Mass Cytometry™ (IMC) is the method of choice for single-step staining and highplex imaging of FFPE tissues. FFPE tissue is autofluorescent, which limits the utility of immunofluorescence methods. Lung and colorectal tissue (and bone, skin, etc) are highly autofluorescent, and therefore good targets for IMC. However, developments in analysis software for highplex imagery have not kept pace with imaging advances. We present a comprehensive workflow designed specifically for highplex image analysis, covering tissue segmentation, cell segmentation based on IMC DNA images, cellular phenotyping, and spatial analyses. Lung and colorectal tissue sections with a 30-marker IMC panel of structural, tumor, stroma, immune cell, and immune activation markers were imaged (Hyperion+™, Standard BioTools). Highplex image analysis (Phenoplex™, Visiopharm) was performed as a multi-step workflow in a single software package that includes: conversion of IMC images to pyramidal format; easy visualization methods for displaying different marker subsets; a paint-to-train algorithm for tissue segmentation (into tumor, stroma, blood vessels, etc.); deep-learning-based nuclear segmentation pre-trained on IMC DNA channels; cellular phenotyping based on thresholds based on visual assessment of positivity; spatial biodistribution metrics for cell populations; and a flexible set of outputs for downstream analysis. Tissue segmentation was used to divide the tissue into tumor, stromal, and tumor margin regions, and these regions were used to compare the immune contexture through a series of t-SNE images partitioned by spatial region. We demonstrate that a simple analysis workflow can be used for highplex images of different tissue types by users with no programming knowledge. Visualization templates for the marker subsets and the pre-trained IMC nuclear segmentation are reusable. A new tissue segmentation algorithm for each tissue type is required, as are new thresholds for biomarker positivity. Spatial biodistribution metrics, heatmaps and partitioned t-SNE plots were generated for each tissue type with a minimum of work. Highplex IMC imaging of lung and colorectal tumor samples is a simple and effective means of obtaining high-parameter images without interfering autofluorescence. Having a comprehensive workflow for the analysis of this complex data makes obtaining useful results from highplex images more accessible to biologists and immunologists by circumventing the requirement for expert programming for each specific application. Citation Format: Brenna O'Neill, Smriti Kala, Sam Lim, Clinton Hupple, Nina Lane, Rasmus Norre Sorensen, Rasmus A. Lyngby, Alessandro Massaro, Andreas Hussing, Jeppe Thagaard, Johan Dore-Hansen, James Robert Mansfield. A comprehensive guided workflow for highplex imaging, tissue segmentation, and multiplex cellular phenotyping for tumor microenvironment analysis. [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 4625.

No abstract