An initial proposal for PDP of smes developing hospital furniture

A large percentage of the industrial SMEs has an organizational structure for product development too far from the adequate practices and models, elaborated by renowned authors with expertise in the theme of product development. On the other hand, the authors state that SMEs obtain considerable advantages by adopting a model of product development process (PDP) management. Healt is one of the most innovative sectors in the world, and countries like Brazil and Colombia are transitioning from a system that cares for contagious infecttions diseases where the drug product is the main form of treatment - to a system that cares for chronic degenerative conditions - where the equipment, including hospital furniture, has more relevance to the treatment. This change is offering better opportunities of specialized markets to hospital furniture SMEs that adopt an adquate PDF model. The present study proposes a first outline of a model of PDP management for industrial metal-mechanical SMEs that develop and manufacture hospital furniture, from a review of models proposed for great mechanical area.

Processo de desenvolvimento de produtos em PMEs industriais do setor de imóveis hospitalares.

Nas Pequenas e Médias Empresas (PMEs) industriais em que o seu produto é essencialmente metal mecânico e o desenvolvimento de produtos é estratégico, surgem questões sobre quais são as metodologias mais adequadas para as diferentes fases de projeto de produto e como implantá-las em um modelo de Processo de Desenvolvimento de Produto (PDP) adequado às necessidades dessas empresas, de modo a aumentar a probabilidade de sucesso do produto. O presente trabalho propõe um modelo de referência do PDP aplicado a PMEs industriais do setor metal mecânico que desenvolvem móveis hospitalares. O modelo é baseado em propostas de PDP da grande área mecânica, especificidades do produto, a saber, móveis hospitalares e dispositivos médicos e em fatores da realidade das PMEs. O trabalho divide-se nas seguintes fases principais: revisão bibliográfica sobre propostas de modelos de gestão do PDP da grande área mecânica e do setor específico de móveis e dispositivos médicos, revisão de normas e regulamentações que tenham influência no PDP, realização de estudos de casos múltiplos de PMEs industriais metal mecânicas que desenvolvem móveis hospitalares, no Brasil e na Colômbia e, por último, síntese de uma proposta final do modelo de referência de PDP, específico para as PMEs industriais do setor metal mecânico que desenvolvem móveis hospitalares, aplicado à realidade do Brasil e da Colômbia.

Bayesian hierarchical models in statistical quality control methods to improve healthcare in hospitals

Quality oriented management systems and methods have become the dominant business and governance paradigm. From this perspective, satisfying customers’ expectations by supplying reliable, good quality products and services is the key factor for an organization and even government. During recent decades, Statistical Quality Control (SQC) methods have been developed as the technical core of quality management and continuous improvement philosophy and now are being applied widely to improve the quality of products and services in industrial and business sectors. Recently SQC tools, in particular quality control charts, have been used in healthcare surveillance. In some cases, these tools have been modified and developed to better suit the health sector characteristics and needs. It seems that some of the work in the healthcare area has evolved independently of the development of industrial statistical process control methods. Therefore analysing and comparing paradigms and the characteristics of quality control charts and techniques across the different sectors presents some opportunities for transferring knowledge and future development in each sectors. Meanwhile considering capabilities of Bayesian approach particularly Bayesian hierarchical models and computational techniques in which all uncertainty are expressed as a structure of probability, facilitates decision making and cost-effectiveness analyses. Therefore, this research investigates the use of quality improvement cycle in a health vii setting using clinical data from a hospital. The need of clinical data for monitoring purposes is investigated in two aspects. A framework and appropriate tools from the industrial context are proposed and applied to evaluate and improve data quality in available datasets and data flow; then a data capturing algorithm using Bayesian decision making methods is developed to determine economical sample size for statistical analyses within the quality improvement cycle. Following ensuring clinical data quality, some characteristics of control charts in the health context including the necessity of monitoring attribute data and correlated quality characteristics are considered. To this end, multivariate control charts from an industrial context are adapted to monitor radiation delivered to patients undergoing diagnostic coronary angiogram and various risk-adjusted control charts are constructed and investigated in monitoring binary outcomes of clinical interventions as well as postintervention survival time. Meanwhile, adoption of a Bayesian approach is proposed as a new framework in estimation of change point following control chart’s signal. This estimate aims to facilitate root causes efforts in quality improvement cycle since it cuts the search for the potential causes of detected changes to a tighter time-frame prior to the signal. This approach enables us to obtain highly informative estimates for change point parameters since probability distribution based results are obtained. Using Bayesian hierarchical models and Markov chain Monte Carlo computational methods, Bayesian estimators of the time and the magnitude of various change scenarios including step change, linear trend and multiple change in a Poisson process are developed and investigated. The benefits of change point investigation is revisited and promoted in monitoring hospital outcomes where the developed Bayesian estimator reports the true time of the shifts, compared to priori known causes, detected by control charts in monitoring rate of excess usage of blood products and major adverse events during and after cardiac surgery in a local hospital. The development of the Bayesian change point estimators are then followed in a healthcare surveillances for processes in which pre-intervention characteristics of patients are viii affecting the outcomes. In this setting, at first, the Bayesian estimator is extended to capture the patient mix, covariates, through risk models underlying risk-adjusted control charts. Variations of the estimator are developed to estimate the true time of step changes and linear trends in odds ratio of intensive care unit outcomes in a local hospital. Secondly, the Bayesian estimator is extended to identify the time of a shift in mean survival time after a clinical intervention which is being monitored by riskadjusted survival time control charts. In this context, the survival time after a clinical intervention is also affected by patient mix and the survival function is constructed using survival prediction model. The simulation study undertaken in each research component and obtained results highly recommend the developed Bayesian estimators as a strong alternative in change point estimation within quality improvement cycle in healthcare surveillances as well as industrial and business contexts. The superiority of the proposed Bayesian framework and estimators are enhanced when probability quantification, flexibility and generalizability of the developed model are also considered. The empirical results and simulations indicate that the Bayesian estimators are a strong alternative in change point estimation within quality improvement cycle in healthcare surveillances. The superiority of the proposed Bayesian framework and estimators are enhanced when probability quantification, flexibility and generalizability of the developed model are also considered. The advantages of the Bayesian approach seen in general context of quality control may also be extended in the industrial and business domains where quality monitoring was initially developed.

Development and validation of 3-Minute Nutrition Screening (3-MinNS) tool for acute hospital patients in Singapore

It is important to detect and treat malnutrition in hospital patients so as to improve clinical outcome and reduce hospital stay. The aim of this study was to develop and validate a nutrition screening tool with a simple and quick scoring system for acute hospital patients in Singapore. In this study, 818 newly admitted patients aged above 18 years old were screened using five parameters that contribute to the risk of malnutrition. A dietitian blinded to the nutrition screening score assessed the same patients using the reference standard, Subjective Global Assessment (SGA) within 48 hours. The sensitivity and specificity were established using the Receiver Operator Characteristics (ROC) curve and the best cutoff scores determined. The nutrition parameter with the largest Area Under the ROC Curve (AUC) was chosen as the final screening tool, which was named 3-Minute Nutrition Screening (3-MinNS). The combination of the parameters weight loss, intake and muscle wastage (3-MinNS), gave the largest AUC when compared with SGA. Using 3-MinNS, the best cutoff point to identify malnourished patients is three (sensitivity 86%, specificity 83%). The cutoff score to identify subjects at risk of severe malnutrition is five (sensitivity 93%, specificity 86%). 3-Minute Nutrition Screening is a valid, simple and rapid tool to identify patients at risk of malnutrition in Singapore acute hospital patients. It is able to differentiate patients at risk of moderate malnutrition and severe malnutrition for prioritization and management purposes.

Development of hospital disaster resilience : conceptual framework and potential measurement

Objective Despite ‘hospital resilience’ gaining prominence in recent years, it remains poorly defined. This article aims to define hospital resilience, build a preliminary conceptual framework and highlight possible approaches to measurement. Methods Searches were conducted of the commonly used health databases to identify relevant literature and reports. Search terms included ‘resilience and framework or model’ or ‘evaluation or assess or measure and hospital and disaster or emergency or mass casualty and resilience or capacity or preparedness or response or safety’. Articles were retrieved that focussed on disaster resilience frameworks and the evaluation of various hospital capacities. Result A total of 1480 potentially eligible publications were retrieved initially but the final analysis was conducted on 47 articles, which appeared to contribute to the study objectives. Four disaster resilience frameworks and 11 evaluation instruments of hospital disaster capacity were included. Discussion and conclusion Hospital resilience is a comprehensive concept derived from existing disaster resilience frameworks. It has four key domains: hospital safety; disaster preparedness and resources; continuity of essential medical services; recovery and adaptation. These domains were categorised according to four criteria, namely, robustness, redundancy, resourcefulness and rapidity. A conceptual understanding of hospital resilience is essential for an intellectual basis for an integrated approach to system development. This article (1) defines hospital resilience; (2) constructs conceptual framework (including key domains); (3) proposes comprehensive measures for possible inclusion in an evaluation instrument, and; (4) develops a matrix of critical issues to enhance hospital resilience to cope with future disasters.

Development and evaluation of training in culturally specific screening and brief intervention for hospital patients with alcohol-related injuries

Objective To evaluate health practitioners’ confidence and knowledge of alcohol screening, brief intervention and referral after training in a culturally adapted intervention on alcohol misuse and well-being issues for trauma patients. Design Mixed methods, involving semi-structured interviews at baseline and a post-workshop questionnaire. Setting: Targeted acute care within a remote area major tertiary referral hospital. Participants Ten key informants and 69 questionnaire respondents from relevant community services and hospital-based health care professionals. Intervention Screening and brief intervention training workshops and resources for 59 hospital staff. Main outcome measures Self-reported staff knowledge of alcohol screening, brief intervention and referral, and satisfaction with workshop content and format. Results After training, 44% of participants reported being motivated to implement alcohol screening and intervention. Satisfaction with training was high, and most participants reported that their knowledge of screening and brief intervention was improved. Conclusion Targeted educational interventions can improve the knowledge and confidence of inpatient staff who manage patients at high risk of alcohol use disorder. Further research is needed to determine the duration of the effect and influence on practice behaviour. Ongoing integrated training, linked with systemic support and established quality improvement processes, is required to facilitate sustained change and widespread dissemination.

Development of a Chinese version WHO Self-Assessment Tool for Evaluating Health Promotion in Hospital

[Support Institutions:] Department of Administration of Health, University of Montreal, Canada Public Health School of Fudan University, Shanghai, China

Transformation of a Woodworking and Furniture Industrial District in Kampala, Uganda: Dichotomous Development of SME Cluster and Large Firm Sector

Clustering small manufacturers are believed to attain various types of collective efficiency. A woodworking and furniture SME district in Uganda has created a learning environment for artisans to start up their own workshops. In the district workers can access various managerial information including business skills and input materials easily than outside. Hence it attracted new entrants to follow and district growth continued. On contrary large firms are locating separately and dispersedly from SME district and have a negative image to SME. This dichotomy has been created partly through spatial division of two sectors and partly through policy favouritism toward large firms.

HUD guarantee of tax-exempt hospital financing : hearing before the Subcommittee on Housing and Community Development of the Committee on Banking, Finance, and Urban Affairs, House of Representatives, Ninety-sixth Congress, first session, May 17, 1979.

"Serial no. 96-21."