Action research methodology in clinical pharmacy: how to involve and change

Introduction The focus in clinical pharmacy practice is and has for the last 30–35 years been on changing the role of pharmacy staff into service orientation and patient counselling. One way of doing this is by involving staff in change process and as a researcher to take part in the change process by establishing partnerships with staff. On the background of the authors’ widespread action research (AR)-based experiences, recommendations and comments for how to conduct an AR-study is described, and one of their AR-based studies illustrate the methodology and the research methods used. Methodology AR is defined as an approach to research which is based on a problem-solving relationship between researchers and clients, which aims at both solving a problem and at collaboratively generating new knowledge. Research questions relevant in AR-studies are: what was the working process in this change oriented study? What learning and/or changes took place? What challenges/pitfalls had to be overcome? What were the influence/consequences for the involved parts? When to use If you want to implement new services and want to involve staff and others in the process, an AR methodology is very suitable. The basic advantages of doing AR-based studies are grounded in their participatory and democratic basis and their starting point in problems experienced in practice. Limitations Some of the limitations in AR-studies are that neither of the participants in a project steering group are the only ones to decide. Furthermore, the collective process makes the decision-making procedures relatively complex.

     

Genotoxicity of synthetic amorphous silica nanoparticles in rats following short‐term exposure. Part 1: Oral route

Synthetic amorphous silica (SAS) in its nanosized form is now used in food applications although the potential risks for human health have not been evaluated. In this study, genotoxicity and oxidative DNA damage of two pyrogenic (NM‐202 and 203) and two precipitated (NM‐200 and ‐201) nanosized SAS were investigated in vivo in rats following oral exposure. Male Sprague Dawley rats were exposed to 5, 10, or 20 mg/kg b.w./day for three days by gavage. DNA strand breaks and oxidative DNA damage were investigated in seven tissues (blood, bone marrow from femur, liver, spleen, kidney, duodenum, and colon) with the alkaline and the (Fpg)‐modified comet assays, respectively. Concomitantly, chromosomal damage was investigated in bone marrow and in colon with the micronucleus assay. Additionally, malondialdehyde (MDA), a lipid peroxidation marker, was measured in plasma. When required, a histopathological examination was also conducted. The results showed neither obvious DNA strand breaks nor oxidative damage with the comet assay, irrespective of the dose and the organ investigated. Similarly, no increases in chromosome damage in bone marrow or lipid peroxidation in plasma were detected. However, although the response was not dose‐dependent, a weak increase in the percentage of micronucleated cells was observed in the colon of rats treated with the two pyrogenic SAS at the lowest dose (5 mg/kg b.w./day). Additional data are required to confirm this result, considering in particular, the role of agglomeration/aggregation of SAS NMs in their uptake by intestinal cells. Environ. Mol. Mutagen. 56:218–227, 2015. © 2014 Wiley Periodicals, Inc.     

Absence of FGFR3–TACC3 rearrangement in hematological malignancies with numerical chromosomal alteration

FGFR–TACC, found in different tumor types, is characterized by the fusion of a member of fibroblast grown factor receptor (FGFR) tyrosine kinase (TK) family to a member of the transforming acidic coiled-coil (TACC) proteins. Because chromosome numerical alterations, hallmarks of FGFR–TACC fusions are present in many hematological disorders and there are no data on the prevalence, we studied a series of patients with acute myeloid leukemia and myelodysplastic syndrome who presented numerical alterations using cytogenetic traditional analysis. None of the analyzed samples showed FGFR3–TACC3 gene fusion, so screening for this mutation at diagnosis is not recommended.     

Prevalence and Predictors of Quality of Recovery at Home After Day Surgery

Traditionally, major complications and unanticipated admission/readmission rates were used to assess outcome after day surgery. However, in view of the relative absence of major complications the quality of recovery (QOR) should be considered one of the principal endpoints after day surgery. In our study, the level of QOR is defined by a combination of the Global Surgical Recovery (GSR) Index and the Quality of Life (QOL).The aim of this study was to analyze prevalence and predictors of QOR after day surgery on the fourth postoperative day.Elective patients scheduled for day surgery from November 2008 to April 2010 were enrolled in a prospective cohort study. Outcome parameters were measured by using questionnaire packages at 2 time points: 1 week preoperatively and 4 days postoperatively. Primary outcome parameter is the QOR and is defined as good if the GSR index >80% as well as the postoperative QOL is unchanged or improved as compared with baseline. QOR is defined as poor if both the GSR index ≤80% and if the postoperative QOL is decreased as compared with baseline. QOR is defined as intermediate in all other cases. Three logistic regression analyses were performed to determine predictors for poor QOR after day surgery.A total of 1118 patients were included. A good QOR was noted in 17.3% of patients, an intermediate QOR in 34.8%, and a poor QOR in 47.8% 4 days after day surgery. The best predictor for poor QOR after day surgery was type of surgery. Other predictors were younger age, work status, and longer duration of surgery. A history of previous surgery, expected pain (by the patient) and high long-term surgical fear were significant predictors of poor QOR in only 1 of 3 prediction models.The QOR at home 4 days after day surgery was poor in the majority of patients and showed a significant procedure-specific variation. Patients at risk for poor QOR can be identified during the preoperative period based on type of surgery, age, work status, and the duration of the surgery.