Health Impact Assessment Guidance (2009)

This document describes Health Impact Assessment (HIA) and the steps involved in HIA.  It gives advice based on the experience of HIA practitioners and provides tools to help carry out these steps and adapt HIA to local circumstances. This guidance manual explains what Health Impact Assessment (HIA) is and the stages involved in conducting it. It has been revised and updated based on the experience of HIA practitioners and includes new tools which have been developed to assist each step of the HIA process. It aims to provide a user friendly and practical framework to guide policy-makers and practitioners in undertaking HIA. All HIA tools contained in this guidance and further information on HIA may be found at http://www.publichealth.ie/hia

Nonclassical measurement error with applications to labor and development issues

Zero correlation between measurement error and model error has been assumed in existing panel data models dealing specifically with measurement error. We extend this literature and propose a simple model where one regressor is mismeasured, allowing the measurement error to correlate with model error. Zero correlation between measurement error and model error is a special case in our model where correlated measurement error equals zero. We ask two research questions. First, we wonder if the correlated measurement error can be identified in the context of panel data. Second, we wonder if classical instrumental variables in panel data need to be adjusted when correlation between measurement error and model error cannot be ignored. Under some regularity conditions the answer is yes to both questions. We then propose a two-step estimation corresponding to the two questions. The first step estimates correlated measurement error from a reverse regression; and the second step estimates usual coefficients of interest using adjusted instruments.

Improving the Patient and Client Experience (PDF 3.92 MB)

New set of standards aimed at improving patient care

Ambulatory measurement of ankle kinetics for clinical applications.

This study aimed to design and validate the measurement of ankle kinetics (force, moment, and power) during consecutive gait cycles and in the field using an ambulatory system. An ambulatory system consisting of plantar pressure insole and inertial sensors (3D gyroscopes and 3D accelerometers) on foot and shank was used. To test this system, 12 patients and 10 healthy elderly subjects wore shoes embedding this system and walked many times across a gait lab including a force-plate surrounded by seven cameras considered as the reference system. Then, the participants walked two 50-meter trials where only the ambulatory system was used. Ankle force components and sagittal moment of ankle measured by ambulatory system showed correlation coefficient (R) and normalized RMS error (NRMSE) of more than 0.94 and less than 13% in comparison with the references system for both patients and healthy subjects. Transverse moment of ankle and ankle power showed R>0.85 and NRMSE<23%. These parameters also showed high repeatability (CMC>0.7). In contrast, the ankle coronal moment of ankle demonstrated high error and lower repeatability. Except for ankle coronal moment, the kinetic features obtained by the ambulatory system could distinguish the patients with ankle osteoarthritis from healthy subjects when measured in 50-meter trials. The proposed ambulatory system can be easily accessible in most clinics and could assess main ankle kinetics quantities with acceptable error and repeatability for clinical evaluations. This system is therefore suggested for field measurement in clinical applications.

Nursing Needs Assessment Tool User Guide 2006 (PDF 207 KB)

The user guide describes how to undertake an assessment using the nursing needs assessment tool.

Evaluation of different POCT devices for glucose measurement in a clinical neonatal setting.

Hypoglycaemia is a major cause of neonatal morbidity and may induce long-term developmental sequelae. Clinical signs of hypoglycaemia in neonatal infants are unspecific or even absent, and therefore, precise and accurate methods for the assessment of glycaemia are needed. Glycaemia measurement in newborns has some particularities like a very low limit of normal glucose concentration compared to adults and a large range of normal haematocrit values. Many bedside point-of-care testing (POCT) systems are available, but literature about their accuracy in newborn infants is scarce and not very convincing. In this retrospective study, we identified over a 1-year study period 1,324 paired glycaemia results, one obtained at bedside with one of three different POCT systems (Elite? XL, Ascensia? Contour? and ABL 735) and the other in the central laboratory of the hospital with the hexokinase reference method. All three POCT systems tended to overestimate glycaemia values, and none of them fulfilled the ISO 15197 accuracy criteria. The Elite XL appeared to be more appropriate than Contour to detect hypoglycaemia, however with a low specificity. Contour additionally showed an important inaccuracy with increasing haematocrit. The bench analyzer ABL 735 was the most accurate of the three tested POCT systems. Both of the tested handheld glucometers have important drawbacks in their use as screening tools for hypoglycaemia in newborn infants. ABL 735 could be a valuable alternative, but the blood volume needed is more than 15 times higher than for handheld glucometers. Before daily use in the newborn population, careful clinical evaluation of each new POCT system for glucose measurement is of utmost importance.