A conceptual approach to enhance the well-being of elderly people

The number of elderly people living alone is increasing. Consequently, a lot of research works have been addressing this issue in order to propose solutions that can enhance the quality of life of elderly people. Most of them have been concerned in dealing with objective issues such as forgetfulness or detecting falls. In this paper, we propose a conceptual approach of a system that intends to enhance the daily sense of user’s well-being. For that, our proposal consists in a system that works as a social network and a smartwatch application that works unobtrusively and collects the user’s physiological data. In addition, we debate how important features such as to detect user’s affective states and to potentiate user’s memory could be implemented. Our study shows that there are still some important limitations which affect the success of applications built in the context of elderly care and which are mostly related with accuracy and usability of this kind of system. However, we believe that with our approach we will be able to address some of those limitations and define a system that can enhance the well-being of elderly people and improve their cognitive capabilities.The work presented in this paper has been developed under the EUREKA - ITEA3 Project PHE (PHE-16040), and by National Funds through FCT (Fundação para a Ciência e a Tecnologia) under the projects UID/EEA/00760/2019 and UID/CEC/00319/2019 and by NORTE-01-0247-FEDER-033275 (AIRDOC - “Aplicação móvel Inteligente para suporte individualizado e monitorização da função e sons Respiratórios de Doentes Obstrutivos Crónicos ”) by NORTE 2020 (Programa Operacional Regional do Norte)

Performance Scores in General Practice: A Comparison between the Clinical versus Medication-Based Approach to Identify Target Populations

CONTEXT: From one country to another, the pay-for-performance mechanisms differ on one significant point: the identification of target populations, that is, populations which serve as a basis for calculating the indicators. The aim of this study was to compare clinical versus medication-based identification of populations of patients with diabetes and hypertension over the age of 50 (for men) or 60 (for women), and any consequences this may have on the calculation of P4P indicators. METHODS: A comparative, retrospective, observational study was carried out with clinical and prescription data from a panel of general practitioners (GPs), the Observatory of General Medicine (OMG) for the year 2007. Two indicators regarding the prescription for statins and aspirin in these populations were calculated. RESULTS: We analyzed data from 21.690 patients collected by 61 GPs via electronic medical files. Following the clinical-based approach, 2.278 patients were diabetic, 8,271 had hypertension and 1.539 had both against respectively 1.730, 8.511 and 1.304 following the medication-based approach (% agreement = 96%, kappa = 0.69). The main reasons for these differences were: forgetting to code the morbidities in the clinical approach, not taking into account the population of patients who were given life style and diet rules only or taking into account patients for whom morbidities other than hypertension could justify the use of antihypertensive drugs in the medication-based approach. The mean (confidence interval) per doctor was 33.7% (31.5-35.9) for statin indicator and 38.4% (35.4-41.4) for aspirin indicator when the target populations were identified on the basis of clinical criteria whereas they were 37.9% (36.3-39.4) and 43.8% (41.4-46.3) on the basis of treatment criteria. CONCLUSION: The two approaches yield very "similar" scores but these scores cover different realities and offer food for thought on the possible usage of these indicators in the framework of P4P programmes

Bias associated with delayed verification in test accuracy studies: accuracy of tests for endometrial hyperplasia may be much higher than we think!

BACKGROUND: To empirically evaluate bias in estimation of accuracy associated with delay in verification of diagnosis among studies evaluating tests for predicting endometrial hyperplasia. METHODS: Systematic reviews of all published research on accuracy of miniature endometrial biopsy and endometr ial ultrasonography for diagnosing endometrial hyperplasia identified 27 test accuracy studies (2,982 subjects). Of these, 16 had immediate histological verification of diagnosis while 11 had verification delayed > 24 hrs after testing. The effect of delay in verification of diagnosis on estimates of accuracy was evaluated using meta-regression with diagnostic odds ratio (dOR) as the accuracy measure. This analysis was adjusted for study quality and type of test (miniature endometrial biopsy or endometrial ultrasound). RESULTS: Compared to studies with immediate verification of diagnosis (dOR 67.2, 95% CI 21.7–208.8), those with delayed verification (dOR 16.2, 95% CI 8.6–30.5) underestimated the diagnostic accuracy by 74% (95% CI 7%–99%; P value = 0.048). CONCLUSION: Among studies of miniature endometrial biopsy and endometrial ultrasound, diagnostic accuracy is considerably underestimated if there is a delay in histological verification of diagnosis

Methods to identify the target population: implications for prescribing quality indicators

Background: Information on prescribing quality is increasingly used by policy makers, insurance companies and health care providers. For reliable assessment of prescribing quality it is important to correctly identify the patients eligible for recommended treatment. Often either diagnostic codes or clinical measurements are used to identify such patients. We compared these two approaches regarding the outcome of the prescribing quality assessment and their ability to identify treated and undertreated patients. Methods: The approaches were compared using electronic health records for 3214 diabetes patients from 70 general practitioners. We selected three existing prescribing quality indicators (PQI) assessing different aspects of treatment in patients with hypertension or who were overweight. We compared population level prescribing quality scores and proportions of identified patients using definitions of hypertension or being overweight based on diagnostic codes, clinical measurements or both. Results: The prescribing quality score for prescribing any antihypertensive treatment was 93% (95% confidence interval 90-95%) using the diagnostic code-based approach, and 81% (78-83%) using the measurement-based approach. Patients receiving antihypertensive treatment had a better registration of their diagnosis compared to hypertensive patients in whom such treatment was not initiated. Scores on the other two PQI were similar for the different approaches, ranging from 64 to 66%. For all PQI, the clinical measurement -based approach identified higher proportions of both well treated and undertreated patients compared to the diagnostic code -based approach. Conclusions: The use of clinical measurements is recommended when PQI are used to identify undertreated patients. Using diagnostic codes or clinical measurement values has little impact on the outcomes of proportion-based PQI when both numerator and denominator are equally affected. In situations when a diagnosis is better registered for treated than untreated patients, as we observed for hypertension, the diagnostic code-based approach results in overestimation of provided treatment

Using text messages to support recovering substance misusers

YesBackground: The use of digital technology in health and social care is developing rapidly. It is promoted in UK policy and research which suggests varied results surrounding its implementation and outcomes. Introduction: This article aimed to test the implementation and outcomes of a short messaging service sent to a dedicated phone. The target cohort were drug treatment clients in two sites in Northern England. Materials and methods: Through staff focus groups and interviews with a small cohort of clients, the implementation and perceptions of the system were examined. Results: Nineteen participants were recruited to site 1 (15 male, 4 female, average age=37.7 years) and 12 participants were recruited to site 2 (9 male, 3 female, average age=40.3 years). One outcome that was of interest was well-being in treatment which, in this study, was described as an overall sense of feeling better rather than just focusing on the rehabilitation aspect of the programme. Other outcomes included: the successful completion of treatment and any relapse or associated reported drug use. Discussion: The system shows some evidence of its ‘social actor’ role; however, its implementation was hindered by staff citing that it called for increased resources. For future implementation the use of client’s own phones may be considered which may help to embed the system more fully in recovery planning and targeting clients at a different treatment stage. Conclusions: Despite some indications of positive results for clients and a perception that the system may have value as an addition to existing clinical interventions, more evaluation is required to determine whether this system can be implemented in a drug treatment setting

Mathematical modelling for the study of respiratory mechanics

The target of this study was the development of mathematical models that best describe the behaviour of respiratory parameters. First of all, we studied lung volume in relation to time both for normal and maximal inspiration/ expiration by developing mathematical models. For the construction of these equations the exponential model was used Then we tried to study the flowvolume of a typical spirometer curve by dividing it into two parts: the first part reaches the Peak Expiratory Flow (PEF) point and the second follows until the volume reaches Vital Capacity (VC). For the first part we built an exponential equation; for the second part a number of existing prediction equations for the flow in various points of VC were used For the volume pressure diagram, we built exponential equations that describe the volume pressure relation below Vo (Vo: lung volume where pressure is zero). The equations were coupled for expiration and inspiration. The modeling of respiratory mechanics led us to the conclusion that the developed models could offer new potentials in the description of other respiratory parameters as well

Neural networks for the prediction of spirometric reference values

Normal lung function values are conventionally calculated according to prediction equations. The primary objective of this study is the development of a different method for the prediction of FVC and FEV1 parameters, in order to achieve better correlation of the predicted values to the real ones. Using a sample from the Greek elderly population that was separated into two groups (a training and a testing one), a number of artificial neural networks were trained. Considering that men and women were studied separately and that two parameters (FVC, FEV1) were the target of the study, four cases came up. In each case two neural networks were trained using different transfer functions, number of neurons and number of layers. When passing the inputs of the testing data set to the trained networks it was found that the outputs were well correlated with the corresponding measures of the sample. Furthermore, the match with the sample, for a number of neural networks developed, was better compared to the matches of Baltopoulos et al. study that used the same sample for developing prediction equations. This high match allows the potential use of neural networks for predicting not only FVC and FEV1 but also other spirometric parameters