Application of Natural Language Processing to Determine User Satisfaction in Public Services

Research on customer satisfaction has increased substantially in recent years. However, the relative importance and relationships between different determinants of satisfaction remains uncertain. Moreover, quantitative studies to date tend to test for significance of pre-determined factors thought to have an influence with no scalable means to identify other causes of user satisfaction. The gaps in knowledge make it difficult to use available knowledge on user preference for public service improvement. Meanwhile, digital technology development has enabled new methods to collect user feedback, for example through online forums where users can comment freely on their experience. New tools are needed to analyze large volumes of such feedback. Use of topic models is proposed as a feasible solution to aggregate open-ended user opinions that can be easily deployed in the public sector. Generated insights can contribute to a more inclusive decision-making process in public service provision. This novel methodological approach is applied to a case of service reviews of publicly-funded primary care practices in England. Findings from the analysis of 145,000 reviews covering almost 7,700 primary care centers indicate that the quality of interactions with staff and bureaucratic exigencies are the key issues driving user satisfaction across England

Choosing optimal rapid manufacturing process for thin-walled products using expert algorithm

Choosing right Rapid Prototyping technology is not easy, especially for companies inexperienced with that group of manufacturing techniques. Paper summarizes research focused on creating an algorithm for expert system, helping to choose optimal process and determine its parameters for thin-walled products rapid manufacturing. Research was based upon trial manufacturing of different thin-walled items using various RP technologies. Products were categorized, each category was defined by a set of requirements. Basing on research outcome, main algorithm has been created. Next step was developing detailed algorithms for optimizing particular methods. Implementation of these algorithms brings huge benefit for recipients, including cost reduction, supply time decrease and improvements in information flow.Peer Reviewe

The prognostic value of different glucose abnormalities in patients with acute myocardial infarction treated invasively

BACKGROUND: Diabetes (DM) deteriorates the prognosis in patients with coronary heart disease. However, the prognostic value of different glucose abnormalities (GA) other than DM in subjects with acute myocardial infarction (AMI) treated invasively remains unclear. AIMS: To assess the incidence and impact of GA on clinical outcomes in AMI patients treated with percutaneous coronary intervention (PCI). METHODS: A single-center, prospective registry encompassed 2733 consecutive AMI subjects treated with PCI. In all in-hospital survivors (n = 2527, 92.5%) without the history of DM diagnosed before or during index hospitalization standard oral glucose tolerance test (OGTT) was performed during stable condition before hospital discharge and interpreted according to WHO criteria. The mean follow-up period was 37.5 months. RESULTS: The incidence of GA was as follows: impaired fasting glycaemia - IFG (n = 376, 15%); impaired glucose tolerance - IGT (n = 560, 22%); DM (n = 425, 17%); new onset DM (n = 384, 15%); and normal glucose tolerance – NGT (n = 782, 31%). During the long-term follow-up, death rate events for previously known DM, new onset DM and IGT were significantly more frequent than those for IFG and NGT (12.3; 9.6 and 9.4 vs. 5.6 and 6.4%, respectively, P < 0.05). The strongest and common independent predictors of death in GA patients were glomerular filtration rate < 60 ml/min/1,73 m^2 (HR 2.0 and 2.8) and left ventricle ejection fraction < 35% (HR 2.5 and 1.8, all P < 0.05) respectively. CONCLUSIONS: Glucose abnormalities are very common in AMI patients. DM, new onset DM and IGT increase remote mortality. Impaired glucose tolerance bears similar long-term prognosis as diabetes

NHS Choices reviews from beginning up to 17 Dec 2017

The GP reviews datase

Improving Public Services by Mining Citizen Feedback: An Application of Natural Language Processing

Research on user satisfaction has increased substantially in recent years. To date, most studies have tested the significance of pre‐defined factors thought to influence user satisfaction, with no scalable means of verifying the validity of their assumptions. Digital technology has created new methods of collecting user feedback where service users post comments. As topic models can analyze large volumes of feedback, they have been proposed as a feasible approach to aggregating user opinions. This novel approach has been applied to process reviews of primary‐care practices in England. Findings from an analysis of more than 200,000 reviews show that the quality of interactions with staff and bureaucratic exigencies are the key drivers of user satisfaction. In addition, patient satisfaction is strongly influenced by factors that are not measured by state‐of‐the‐art patient surveys. These results highlight the potential benefits of text mining and machine learning for public administration

Choosing optimal rapid manufacturing process for thin-walled products using expert algorithm

Choosing right Rapid Prototyping technology is not easy, especially for companies inexperienced with that group of manufacturing techniques. Paper summarizes research focused on creating an algorithm for expert system, helping to choose optimal process and determine its parameters for thin-walled products rapid manufacturing. Research was based upon trial manufacturing of different thin-walled items using various RP technologies. Products were categorized, each category was defined by a set of requirements. Basing on research outcome, main algorithm has been created. Next step was developing detailed algorithms for optimizing particular methods. Implementation of these algorithms brings huge benefit for recipients, including cost reduction, supply time decrease and improvements in information flow.Peer Reviewe