Roy G.,Analytics Intelligence
Proceedings of the 2013 International Conference on Advances in Computing, Communications and Informatics, ICACCI 2013 | Year: 2013
To provide better and improved patient care, it's important to know the driver of critical clinical processes and focus areas of improvement. For example, readmission to hospital and death after discharge are adverse patient outcomes that are serious, common and costly. Similarly, prolonged 'Length of Stay' increases the possibility of nosocomial infections, introduces patient safety issues, increases the cost per discharge and consumes considerable hospital resources including beds and staff time. Being able to accurately predict the risk of such outcomes would allow health care professionals to focus on appropriate measures to reduce the risk. This paper demonstrates how, with the help of a predictive analytics tool, we can dynamically build models to predict any patient outcome of our choice. This prediction function calculates the probability of the outcome for a given set of patients and those probabilities are used to derive a risk score index for each patient. The result is finally presented in a dynamic business dashboard for further management actions. © 2013 IEEE. Source
Cleary P.D.,Yale University |
Meterko M.,and nter for Healthcare Organization and Implementation Research |
Meterko M.,Boston University |
Wright S.M.,Analytics Intelligence |
Zaslavsky A.M.,Harvard University
Medical Care | Year: 2014
BACKGROUND: Surveys are increasingly used to assess patient experiences with health care. Comparisons of hospital scores based on patient experience surveys should be adjusted for patient characteristics that might affect survey results. Such characteristics are commonly drawn from patient surveys that collect little, if any, clinical information. Consequently some hospitals, especially those treating particularly complex patients, have been concerned that standard adjustment methods do not adequately reflect the challenges of treating their patients. OBJECTIVES: To compare scores for different types of hospitals after making adjustments using only survey-reported patient characteristics and using more complete clinical and hospital information. RESEARCH DESIGN: We used clinical and survey data from a national sample of 1858 veterans hospitalized for an initial acute myocardial infarction (AMI) in a Department of Veterans Affairs (VA) medical center during fiscal years 2003 and 2004. We used VA administrative data to characterize hospitals. The survey asked patients about their experiences with hospital care. The clinical data included 14 measures abstracted from medical records that are predictive of survival after an AMI. RESULTS: Comparisons of scores across hospitals adjusted only for patient-reported health status and sociodemographic characteristics were similar to those that also adjusted for patient clinical characteristics; the Spearman rank-order correlations between the 2 sets of adjusted scores were >0.97 across 9 dimensions of inpatient experience. CONCLUSIONS: This study did not support concerns that measures of patient care experiences are unfair because commonly used models do not adjust adequately for potentially confounding patient clinical characteristics. Copyright © 2014 by Lippincott Williams & Wilkins. Source
Whitehead A.M.,Womens Health Services |
Czarnogorski M.,Womens Health Services |
Wright S.M.,Analytics Intelligence |
Hayes P.M.,Womens Health Services |
And 2 more authors.
American Journal of Public Health | Year: 2014
Increasing numbers of women veterans using Department of Veterans Affairs (VA) services has contributed to the need for equitable, high-quality care for women. The VA has evaluated performance measure data by gender since 2006. In 2008, the VA launched a 5-year women's health redesign, and, in 2011, gender disparity improvement was included on leadership performance plans. We examined data from VA Office of Analytics and Business Intelligence quarterly gender reports for trends in gender disparities in gender-neutral performance measures from 2008 to 2013. Through reporting of data by gender, leadership involvement, electronic reminders, and population management dashboards, VA has seen a decreasing trend in gender inequities on most Health Effectiveness Data and Information Set performance measures. Source
Analytics Intelligence | Date: 2011-04-11
A computer-implemented method, system and program for interactive data delivering are described. A method for the interactive data delivering provides an effective way for retrieving, analyzing, processing and presenting business analytics data to a user in a natural, conversational way. The method may comprise receiving a request from the user to provide the analytics data in the natural language format, converting the command in the natural language format into one or more Application Programming Interface (API) calls, retrieving generic data associated with the request of the user based on the API calls, generating a semantic model associated with the generic data and the user request, processing the retrieved generic data to generate analytics data, with the processing being based on the semantic model, communicating the analytics data to a chatbot, and converting, under control of the chatbot, the analytics data into a natural language format for delivering to the user.
Agency: Cordis | Branch: H2020 | Program: RIA | Phase: FCT-14-2014 | Award Amount: 5.00M | Year: 2015
The challenges of international police reform assistance are formidable. Conventional top-down institutional reform has proven neither effective nor sustainable. Community-based policing (COP) holds promise, however evaluations have pointed to a lack of in-depth understanding of police-community relations in police reform assistance. This project will conduct integrated social and technical research on COP in post-conflict countries in S.E. Europe, Asia, Africa and Central America. New knowledge, reflection on lessons learnt and best practices will support both national police and EU/International police reform assistance. The project will lead to a better understanding of police-community relations, and innovation in information and communication technology (ICT) for enhancing these relations in post-conflict countries undergoing serious security reform. Linking social and technological research, the project will study social, cultural, human security, legal and ethical dimensions of COP to understand how citizens and police can develop sustainable relations with the use of ICTs. We will explore how technological innovation can support COP in crime reporting and prevention. The project will explore ICT solutions to facilitate, strengthen and accelerate positive COP efforts and police-citizen interactions where trust levels are weak. Solutions will depend on the context and identified needs of end-users: communities, local police, national and international police (EU/UN), and policymakers, and may include citizen reporting, information monitoring, mobile value transfer, or improved organizational systems. The project includes a Policing Experts Network whose role is to support research planning, and dissemination and exploitation of findings, grounding the research in police practice. This will ensure findings are communicated by engaged police practitioners, and directly applied in COP education and training curricula in Europe and case countries.