Overregulation of Health Care: Musings on Disruptive Innovation Theory

Disruptive innovation theory provides one lens through which to describe how regulations may stifle innovation and increase costs. Basing their discussion on this theory, Curtis and Schulman consider some of the effects that regulatory controls may have on innovation in the health sector

Unit Costs of Health and Social Care 2016

This is the latest updated volume in a well-established series bringing together information from a variety of sources to estimate national unit costs for a wide range of health and social care services. This report consists of tables for approaching 100 types of service which, as well as providing the most detailed and comprehensive information possible, also quotes sources and assumptions so users can adapt the information for their own purposes. This year we have included a guest editorial: Agency staff in the NHS; and two articles: Costs of the Well London programme and PUCC: The Preventonomics Unit Cost Calculator. There is also a new schema providing the costs of the Geriatric Care Management Model (GRACE) and new information has been added to the Adoption and GP schemas. Changes have also been made to further improve the costs of NHS overheads and environmental costs have been extended to appear in the mental health hospital services schema

Unit Costs of Health & Social Care 2020

A volume of unit costs relating to a variety of health and social care services and staf

A survey of Local Authorities and Home Improvement Agencies: identifying the hidden costs of providing a home adaptations service

Introduction: The Royal College of Occupational Therapists has launched a campaign to demonstrate that occupational therapists improve lives and save money for health and social care services. Occupational therapists play a major part in supporting older and disabled people to remain in their own homes through the provision of home adaptations. Among other benefits, studies have shown that home adaptations can reduce falls in the home and could therefore help reduce hospital admissions. To evidence savings however, information on the full costs of supplying and fitting home adaptations are needed. Method: Local authorities and Home Improvement Agencies were surveyed in 2013/14 to obtain the information required to estimate these costs. Time inputs for staff involved in their provision have been collected and staff costs and total costs calculated for 18 commonly fitted adaptations. The process of obtaining publicly funded home adaptations is also discussed. Findings: For major adaptations, the total mean cost was £16,647, ranging from £2474 to £36,681. Staffing costs absorbed up to 24% of the total mean cost. The total mean cost for minor adaptations was £451 with average staffing costs forming 76%. Conclusion: Staff costs are an important consideration when estimating the costs of providing home adaptations

Long‐Term Outcomes Among Elderly Survivors of Out‐of‐Hospital Cardiac Arrest

Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/139093/1/jah31396_am.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/139093/2/jah31396.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/139093/3/jah31396-sup-0001-SupInfo.pd

Integrative analyses identify modulators of response to neoadjuvant aromatase inhibitors in patients with early breast cancer

Introduction Aromatase inhibitors (AIs) are a vital component of estrogen receptor positive (ER+) breast cancer treatment. De novo and acquired resistance, however, is common. The aims of this study were to relate patterns of copy number aberrations to molecular and proliferative response to AIs, to study differences in the patterns of copy number aberrations between breast cancer samples pre- and post-AI neoadjuvant therapy, and to identify putative biomarkers for resistance to neoadjuvant AI therapy using an integrative analysis approach. Methods Samples from 84 patients derived from two neoadjuvant AI therapy trials were subjected to copy number profiling by microarray-based comparative genomic hybridisation (aCGH, n = 84), gene expression profiling (n = 47), matched pre- and post-AI aCGH (n = 19 pairs) and Ki67-based AI-response analysis (n = 39). Results Integrative analysis of these datasets identified a set of nine genes that, when amplified, were associated with a poor response to AIs, and were significantly overexpressed when amplified, including CHKA, LRP5 and SAPS3. Functional validation in vitro, using cell lines with and without amplification of these genes (SUM44, MDA-MB134-VI, T47D and MCF7) and a model of acquired AI-resistance (MCF7-LTED) identified CHKA as a gene that when amplified modulates estrogen receptor (ER)-driven proliferation, ER/estrogen response element (ERE) transactivation, expression of ER-regulated genes and phosphorylation of V-AKT murine thymoma viral oncogene homolog 1 (AKT1). Conclusions These data provide a rationale for investigation of the role of CHKA in further models of de novo and acquired resistance to AIs, and provide proof of concept that integrative genomic analyses can identify biologically relevant modulators of AI response