Theoretical frameworks to support research of health service innovation

Health service managers and policy makers are increasingly concerned about the sustainability of innovations implemented in health care settings. The increasing demand on health services requires that innovations are both effective and sustainable however research in this field is limited with multiple disciplines, approaches and paradigms influencing the field. These variations prevent a cohesive approach and therefore the accumulation of research findings in development of a body of knowledge. A theoretical framework serves to guide research, determine variables, influence data analysis and is central to the quest for ongoing knowledge development. If left unaddressed, health services research will continue in an ad hoc manner preventing full utilisation of outcomes, recommendations and knowledge for effective provision of health services. The purpose of this paper is to provide an integrative review of the literature and introduce a theoretical framework for health services innovation sustainability research based on integration and synthesis of the literature. Finally recommendations for operationalising and testing this theory will be presented.

The glycosphingolipid P1 is an ovarian cancer-associated carbohydrate antigen involved in migration

Background The level of plasma-derived naturally circulating anti-glycan antibodies (AGA) to P1 trisaccharide has previously been shown to significantly discriminate between ovarian cancer patients and healthy women. Here we aim to identify the Ig class that causes this discrimination, to identify on cancer cells the corresponding P1 antigen recognised by circulating anti-P1 antibodies and to shed light into the possible function of this glycosphingolipid. Method An independent Australian cohort was assessed for the presence of anti-P1 IgG and IgM class antibodies using suspension array. Monoclonal and human derived anti-glycan antibodies were verified using three independent glycan-based immunoassays and flow cytometry-based inhibition assay. The P1 antigen was detected by LC-MS/MS and flow cytometry. FACS-sorted cell lines were studied on the cellular migration by colorimetric assay and real-time measurement using xCELLigence system. Results Here we show in a second independent cohort (n=155) that the discrimination of cancer patients is mediated by the IgM class of anti-P1 antibodies (P=0.0002). The presence of corresponding antigen P1 and structurally related epitopes in fresh tissue specimens and cultured cancer cells is demonstrated. We further link the antibody and antigen (P1) by showing that human naturally circulating and affinity-purified anti-P1 IgM isolated from patients ascites can bind to naturally expressed P1 on the cell surface of ovarian cancer cells. Cell-sorted IGROV1 was used to obtain two study subpopulations (P1-high, 66.1%; and P1-low, 33.3%) and observed that cells expressing high P1-levels migrate significantly faster than those with low P1-levels. Conclusions This is the first report showing that P1 antigen, known to be expressed on erythrocytes only, is also present on ovarian cancer cells. This suggests that P1 is a novel tumour-associated carbohydrate antigen recognised by the immune system in patients and may have a role in cell migration. The clinical value of our data may be both diagnostic and prognostic; patients with low anti-P1 IgM antibodies present with a more aggressive phenotype and earlier relapse.

Challenges in improving chronic disease survivorship outcomes using tele-health and self-managed online solutions

The advances in modern information and communication (ICT) technology continue to address the challenges and improve` health outcomes for the survivors of chronic disease such as prostate cancer. The management of survivorship is increasingly becoming an important need for the survivors to manage their chronic conditions. The technology interventions such as tele-health as well as self-managed technology applications have shown a potential to improve survivorship outcomes. However, the application of these tools should be supported by strong health economics evidence. This work discusses the challenges of technology led survivorship care models and presents an integrated approach to address these challenges.