Patient Generated Health Data: Framework for Decision Making

Patient information is a major part of healthcare decision making. Although currently scattered due to multiple sources and diverse formats, decision making can be improved if the patient information is readily available in a unified manner. Mobile technologies can improve decision making by integrating patient information from multiple sources. This study explores how patient generated health data (PGHD) from multiple sources can lead to improved healthcare decision making. A semi-systematic review is conducted to analyze research articles for transparency, clarity, and complete reporting. We conceptualize the data generated by healthcare professional as primarily from EHR/EMR and the data generated by patient as primarily from mobile apps and wearables. Eight themes led to the development of Convergence Model for Patient Data (CMPD). A framework was developed to illustrate several scenarios, to identify quality and timeliness requirements in mobile healthcare environment, and to provide necessary decision support

Dialable Cryptography for Wireless Networks

The objective of this research is to develop an adaptive cryptographic protocol, which allows users to select an optimal cryptographic strength and algorithm based upon the hardware and bandwidth available and allows users to reason about the level of security versus the system throughput. In this constantly technically-improving society, the ability to communicate via wireless technology provides an avenue for delivering information at anytime nearly anywhere. Sensitive or classified information can be transferred wirelessly across unsecured channels by using cryptographic algorithms. The research presented will focus on dynamically selecting optimal cryptographic algorithms and cryptographic strengths based upon the hardware and bandwidth available. The research will explore the performance of transferring information using various cryptographic algorithms and strengths using different CPU and bandwidths on various sized packets or files. This research will provide a foundation for dynamically selecting cryptographic algorithms and key sizes. The conclusion of the research provides a selection process for users to determine the best cryptographic algorithms and strengths to send desired information without waiting for information security personnel to determine the required method for transferring. This capability will be an important stepping stone towards the military’s vision of future Net-Centric Warfare capabilities

Measuring the Utility of a Cyber Incident Mission Impact Assessment (CIMIA) Process for Mission Assurance

Information is a critical asset on which virtually all modern organizations depend upon to meet their operational mission objectives. Military organizations, in particular, have embedded Information and Communications Technologies (ICT) into their core mission processes as a means to increase their operational efficiency, exploit automation, improve decision quality, and shorten the kill chain. However, the extreme dependence upon ICT results in an environment where a cyber incident can result in severe mission degradation, or possibly failure, with catastrophic consequences to life, limb, and property. These consequences can be minimized by maintaining real-time situational awareness of mission critical resources so appropriate contingency actions can be taken in a timely manner following an incident in order to assure mission success. In this thesis, the design and analysis of an experiment is presented for the purpose of measuring the utility of a Cyber Incident Mission Impact Assessment (CIMIA) notification process, whose goal is to improve the timeliness and relevance of incident notification. In the experiment, subjects are placed into a model environment where they conduct operational tasks in the presence and absence of enhanced CIMIA notifications. The results of the experiment reveal that implementing a CIMIA notification process significantly reduced the response time required for subjects to recognize and take proper contingency actions to assure their organizational mission. The research confirms that timely and relevant notification following a cyber incident is an essential element of mission assurance

Continuous monitoring of enterprise risks: A delphi feasibility study

A constantly evolving regulatory environment, increasing market pressure to improve operations, and rapidly changing business conditions are creating the need for ongoing assurance that organizational risks are continually and adequately mitigated. Enterprises are perpetually exposed to fraud, poor decision making and/or other inefficiencies that can lead to significant financial loss and/or increased levels of operating risk. Increasingly, Information Systems are being harnessed to reinvent the risk management process. One promising technology is Continuous Auditing, which seeks to transform the audit process from periodic reviews of a few transactions to a continuous review of all transactions. However, the highly integrated, rapidly changing and hypercompetitive business environment of many corporations spawns numerous Enterprise Risks that have been excluded from standard risk management processes. An extension of Continuous Auditing is Continuous Monitoring, which is used by management to continually review business processes for unexpected deviations. Using a Delphi, the feasibility and desirability of applying Continuous Monitoring to different Enterprise Risks is studied. This study uncovers a significant relationship between the perceived business value of Continuous Monitoring and years of experience in Risk Management and Auditing, determines that all key architectural components for a Continuous Monitoring system are known, and indicates that Continuous Monitoring may be better suited for monitoring computer crime than monitoring strategic risks such as the loss of a competitive position

Bridging the Data Divide: Understanding State Agency and University Research Partnerships within SLDS

This report examines this question through an analysis of state agency-university researcher partnerships that exist in State Longitudinal Data Systems (SLDS). Building state agency-university researcher partnerships is an important value of SLDS. To examine state agency-university researcher partnerships within SLDS, our analysis is guided by the following set of questions based on 71 interviews conducted with individuals most directly involved with SLDS efforts in Virginia, Maryland, Texas and Washington. The findings from this analysis suggest that each state’s SLDS organization and governance structure includes university partners in differing ways. In general, stronger partnership efforts are driven by legislative action or executive-level leadership. Regardless of structure, the operation of these partnerships is shaped by the agency’s previous experience and cultural norms surrounding the value and inclusion of university researchers

Bridging the Data Divide: Understanding State Agency and University Research Partnerships within SLDS

This report examines this question through an analysis of state agency-university researcher partnerships that exist in State Longitudinal Data Systems (SLDS). Building state agency-university researcher partnerships is an important value of SLDS. To examine state agency-university researcher partnerships within SLDS, our analysis is guided by the following set of questions based on 71 interviews conducted with individuals most directly involved with SLDS efforts in Virginia, Maryland, Texas and Washington. The findings from this analysis suggest that each state’s SLDS organization and governance structure includes university partners in differing ways. In general, stronger partnership efforts are driven by legislative action or executive-level leadership. Regardless of structure, the operation of these partnerships is shaped by the agency’s previous experience and cultural norms surrounding the value and inclusion of university researchers

The Importance of Data Quality for SAP Implementation in Medium-sized Organizations

Data quality issues are critical for any type ofinformation systems. The purpose of this study is toexplore the importance of data quality for SAPimplementation. This study involved a case study of amedium-sized organization that had implementedSAP R3 as their ERP system. Knowledge gained fromthis study has the potential in assisting medium-sizedorganizations to enhance the quality of the data usedin their ERP systems

Tradespace and Affordability – Phase 1

One of the key elements of the SERC’s research strategy is transforming the practice of systems engineering – “SE Transformation.” The Grand Challenge goal for SE Transformation is to transform the DoD community’s current systems engineering and management methods, processes, and tools (MPTs) and practices away from sequential, single stovepipe system, hardware-first, outside-in, document-driven, point-solution, acquisition-oriented approaches; and toward concurrent, portfolio and enterprise-oriented, hardware-software-human engineered, balanced outside-in and inside-out, model-driven, set-based, full life cycle approaches.This material is based upon work supported, in whole or in part, by the U.S. Department of Defense through the Office of the Assistant Secretary of Defense for Research and Engineering (ASD(R&E)) under Contract H98230-08- D-0171 (Task Order 0031, RT 046).This material is based upon work supported, in whole or in part, by the U.S. Department of Defense through the Office of the Assistant Secretary of Defense for Research and Engineering (ASD(R&E)) under Contract H98230-08- D-0171 (Task Order 0031, RT 046)

PICT-DPA: A Quality-Compliance Data Processing Architecture to Improve the Performance of Integrated Emergency Care Clinical Decision Support System

Emergency Care System (ECS) is a critical component of health care systems by providing acute resuscitation and life-saving care. As a time-sensitive care operation system, any delay and mistake in the decision-making of these EC functions can create additional risks of adverse events and clinical incidents. The Emergency Care Clinical Decision Support System (EC-CDSS) has proven to improve the quality of the aforementioned EC functions. However, the literature is scarce on how to implement and evaluate the EC-CDSS with regard to the improvement of PHOs, which is the ultimate goal of ECS. The reasons are twofold: 1) lack of clear connections between the implementation of EC-CDSS and PHOs because of unknown quality attributes; and 2) lack of clear identification of stakeholders and their decision processes. Both lead to the lack of a data processing architecture for an integrated EC-CDSS that can fulfill all quality attributes while satisfying all stakeholders’ information needs with the goal of improving PHOs. This dissertation identified quality attributes (PICT: Performance of the decision support, Interoperability, Cost, and Timeliness) and stakeholders through a systematic literature review and designed a new data processing architecture of EC-CDSS, called PICT-DPA, through design science research. The PICT-DPA was evaluated by a prototype of integrated PICT-DPA EC-CDSS, called PICTEDS, and a semi-structured user interview. The evaluation results demonstrated that the PICT-DPA is able to improve the quality attributes of EC-CDSS while satisfying stakeholders’ information needs. This dissertation made theoretical contributions to the identification of quality attributes (with related metrics) and stakeholders of EC-CDSS and the PICT Quality Attribute model that explains how EC-CDSSs may improve PHOs through the relationships between each quality attribute and PHOs. This dissertation also made practical contributions on how quality attributes with metrics and variable stakeholders could be able to guide the design, implementation, and evaluation of any EC-CDSS and how the data processing architecture is general enough to guide the design of other decision support systems with requirements of the similar quality attributes