An Informatics Blueprint for Healthcare Quality Information Systems. Abstract. There is a critical gap in our nation's ability to accurately measure and manage the quality of medical care. A robust healthcare quality information system (HQIS) has the potential to address this deficiency through the capture, codification, and analysis of information about patient treatments and related outcomes. Because non- technical issues often present the greatest challenges, this paper provides an overview of these socio- technical issues in building a successful HQIS, including the human, organizational, and knowledge management (KM) perspectives.
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Search the history of over 505 billion pages on the Internet. Volume 10, Number 20 (2015) Special Issues. Power Quality Compensation for an Induction Motor Drive with UPQC pp.15227-15231 Arjun R, Sindhu S. Package Weight* Description; buildoutpip 0.1dev: 9: Buildout extension to install from pip requirements files: celery-pipeline 0.15: 9: Runtime-configurable execution.
Through an extensive literature review and direct experience in building a practical HQIS (the National Comprehensive Cancer Network Outcomes Research Database system), we have formulated an “informatics blueprint” to guide the development of such systems. While the blueprint was developed to facilitate healthcare quality information collection, management, analysis, and reporting, the concepts and advice provided may be extensible to the development of other types of clinical research information systems.
- Jennifer Waller obtained a PhD in Biostatistics from the School of Public Health at the University of South Carolina in 1994. She is an Associate Professor and.
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Introduction. Physician practice patterns and corresponding treatment outcomes vary much more widely than previously realized, and such variations have been associated with both sub- optimal patient outcomes and increased treatment costs. Observed differences in treatment outcomes across populations suggest that major opportunities for improvement exist, and clinicians, patients, and the general public are demanding more information about healthcare quality. Healthcare consumers seek to become better informed about their choices, and expect to see provider- specific clinical outcomes data to confirm the promised benefits of medical treatments.
There is a critical gap in our nation's ability to accurately measure and manage the quality of medical care. A robust healthcare quality information. Big data analysis concepts and references 1. Big Data Analysis 1Author: Vikram Andem ISRM & IT GRC Conference Big Data Analysis Concepts.
Payors require clinical outcome data to evaluate quality of care and cost- effectiveness. It remains extremely difficult to accurately measure quality indicators in the general patient population, and to relate these measurements to outcomes. A healthcare quality information system (HQIS) is a data system that captures data on medical programs and practices, and provides monitoring and reports on care and outcomes for patients treated within the caregiver system. Thus a HQIS offers the opportunity to address current deficiencies in healthcare evaluation, and to ultimately improve the quality of care. Since 1. 99. 6 the Division of Information Sciences at City of Hope National Medical Center has been responsible for the development, implementation, and maintenance of a multi- centered Internet- based HQIS, the National Comprehensive Cancer Network (NCCN) Outcomes Research Database System.
The NCCN is a volunteer organization of 2. Cancer Centers around the country, formed to continually improve the quality of oncology care. The first objective of the NCCN was to establish a robust set of care guidelines based on clinical trials evidence and expert opinion; these guidelines now exist for over 9. The next goal of the NCCN was to measure guideline concordance across participating Cancer Centers, assess patterns of care over time, and benchmark that care against quality indicators and patient outcomes. The NCCN HQIS was developed to collect standardized coded data on all patients receiving primary care at a participating NCCN institution, and to facilitate analysis of these data to support delivery of the highest possible quality of cancer care. After initial treatment at the NCCN center and at specified follow- up intervals thereafter, coded data are abstracted by Clinical Research Associates, based on existing medical records and patient surveys obtained during the routine care process.
The NCCN HQIS was designed to: . However, recognizing the power and efficiencies that could be gained, our design specifications called for the implementation of a Web- enabled relational database that follows a client- server model. The Web interfaces were created using Microsoft Active Server Page (ASP) technology and Java.
Script, on Microsoft Internet Information Server (IIS) and SQL Server platforms. The NCCN HQIS was constructed over a robust security framework that includes role- based data access, data encryption, and digital certification. Authorized users can enter the data directly into the central repository via Web- based screens that invoke logic checks, skip patterns, and conditional drop- down menus. Alternatively, for centers that already have existing electronic data that matches or can be mapped to the NCCN data dictionary, an electronic data file may be transmitted to the DCC on a quarterly basis, for uploading into the pooled repository. Through the process of developing the NCCN outcomes research system, an appreciation of the many challenges and difficulties in creating a robust HQIS has been gained. While descriptions of information systems typically focus on the technology involved, a successful HQIS consists of much more than hardware and software. In fact the socio- technical considerations of the organizational culture, data structure, and knowledge management processes of the HQIS often prove to be far more challenging in building such systems.
To be well accepted, any new technical system has to be part of a working socio- technical system, engaging with the complex world of tasks, procedures and culture within an organization. Otherwise high failure rates and low utilization levels are certain consequences. Based on our past experience and ongoing efforts to fully optimize the NCCN outcomes research database system, we were motivated to identify and summarize the most important HQIS socio- technical characteristics as described in the informatics literature. In this paper we first document the critical need for information systems to capture practice patterns and outcomes, to facilitate benchmarking against established healthcare quality guidelines. We then present our review of the relevant literature, organized around several higher order themes that form the foundation of an “informatics blueprint” for HQIS efforts. While this review was motivated by our NCCN HQIS to support oncology outcomes research, the resulting blueprint serves as a guide to the construction and evaluation of information systems across many related domain areas. Background. The Demand for Outcomes Data.
Outcomes research is the science of accurately measuring treatment patterns in the general patient population, and relating those patterns to patient outcomes. With the growing human and financial burdens attributed to chronic illnesses, the demand for outcomes data and healthcare quality measurement is increasing on a national scale. Stake- holders include patients, healthcare providers, purchasers, accrediting organizations, professional societies, and government agencies. This “outcomes movement” has been fueled by research that describes substantial geographical differences in hospital admissions and medical procedures, differences that cannot be explained solely by severity of illness. Such practice variations are driven by many factors, including patient population differences, lack of professional consensus, non- uniform access to care, differences in local or regional capabilities, and the overall quality of care practices.
The great concern is that this practice variability may lead to suboptimal treatment for a substantial proportion of patients. To facilitate healthcare quality, there is a burgeoning interest in the relationship between healthcare processes and outcomes, leading to a growing demand for data to support such studies. Patients want to understand treatment risks and benefits, and to receive the best possible outcomes from their selected treatment regimens. Clinicians are increasingly interested in objective information regarding their own practice patterns, and the ability to benchmark their treatment practices against peers within the medical community.
The pursuit of answers to these questions requires empirical data to allow assessments of practice patterns and corresponding intervention outcomes. Healthcare quality measurement is an elusive goal, and current quality of care measurement practices are relatively primitive.
There is a paucity of data to assess the implementation of treatment guidelines and related treatment outcomes. In an effort to monitor and improve care, insurers and managed- care groups often apply utilization review, profiling, and other rudimentary methods.
Such approaches are largely based on administrative or billing data, and lack the clinical details to accurately evaluate treatment outcomes while adjusting for confounding factors such as co- morbidity. Limited diagnostic coding in administrative databases restricts the amount of clinical detail that can be captured, making it difficult to discern important temporal distinctions between existing co- morbidity and complications of the care itself. Through the implementation of a robust HQIS raw data can be transformed into useful codified information, leading to new knowledge that may improve patient care. These systems must support a particular form of knowledge management (KM), defined as “the process of creating, capturing, and using knowledge to enhance organizational performance.” 2. The development of large, sophisticated databases will be required to support complex analyses involved in effective outcomes monitoring and management. Requirements of a Successful HQISIn addition to the requisite hardware and software, HQIS developers must specify a complete “information framework,” 2. This framework must support the precise measurement of practice patterns, outcomes, and potential confounders such as severity of illness, precision of diagnosis, and socioeconomic characteristics.
The Total Solution Life Cycle. Contents. Module.
Objective. Lessons Covered in This. Course. Curriculum Overview.
Lesson 1: Introducing. Players and Their Roles. Lesson 2: Developing. Business Strategy and Plans. Lesson 3: Building a.
Solution: Overview of Frameworks and Methodologies. Lesson 4: Deploying and.
Operating a Solution. Module Objective. This module takes you through the total solution.
Thetotal solution life cycle includes the business strategy. SDLC), as well as the deployment and ongoing operations that follow. We examine. the tools used to create business strategies, develop and implement solutions, and. A solutions architect that understands the total. SDLC. Lessons Covered in This Course.
Curriculum Overview. We will be referring to these competencies throughout this curriculum. Effective architects must also invest the time needed to refine their. Microsoft Certified Architect Program Solutions Architect. Skills. The Microsoft Certified Architect program has.
Leadership. Candidates demonstrate that they can develop partnerships. The following are some ways to demonstrate these qualities. Candidates have the. The following are some ways. Candidates recognize the political landscape. The following are.
They understand the. In addition, candidates understand the economic dimension of. The. following are some ways to demonstrate these qualities.
For example, use the Zachman. Framework for Enterprise Architecture or The Open Group Architecture Framework. TOGAF) to map the business strategy of the organization to your solution.
For example, understand. Control Objectives for Information and related Technology (COBIT) or IT Infrastructure. Library (ITIL), impact your solution. They exhibit the ability to refine. The. following are some ways to demonstrate these qualities. Candidates. also demonstrate the ability to quickly assimilate information about new technologies.
This lesson addresses the individuals. Key Point. As a solutions architect invests the time to understand. To Learn More. We use the areas of solutions architect competencies. MCA program in Appendix A as skill goals throughout this lesson.
Topic 2: The Players and Their Roles. First we will examine the individual. Figure 1- 1 illustrates. It is. neither a framework nor a methodology (which can be iterative and are covered. Because Figure 1- 1 reflects the current state of. The solutions architect, along with every.
This diagram can be used to identify and communicate. The total solution life. Key Point. Individuals in a solution often perceive their. A solutions architect recognizes each of the. Exercises for Understanding. Draw a diagram that reflects the reality of the roles and timelines for.
How does it differ from Figure 1- 1? Topic 3: Interacting with the Players. This topic provides more detail about each of the. Business Stakeholders. In medium- to- large for- profit organizations, the. Chief Executive Officer.
CEO), Chief Financial Officer (CFO), Chief Operations Officer (COO), Chief Technology. Officer (CTO), and Chief Information Officer (CIO). There are others emerging in. Chief Security Officer (CSO). These roles may have different. Often, secondary business stakeholders will emerge. A sales and marketing.
Generally, there is a strong financial component. In addition, regulatory mandates drive many business.
Key Point. It is a business stakeholder. As a technologist, the solutions. Discuss solutions.
At what level were the business stakeholders. How did this affect the success of your solution? Business Analyst. A business analyst is generally a business domain. Business analysts may be experts. Six Sigma, Lean Manufacturing, the Capabilities Maturity Model Integration. CMMI), or other operational methodologies.
They are generally technology- aware. These. individuals may be internal or external to the organization. Key Point. A business analyst will assist and direct the business. What can you do to.
Enterprise Architect. Larger organizations may have an enterprise. The enterprise architect is aware of. Consider for Yourself. What if a solutions. Where there is alignment, there.
Where there are gaps, issues are bound to exist. The solutions architect must engage strategy skills with a keen understanding. Project Manager. The project manager is responsible for planning.
From a project management perspective, organizations. Solutions architects.
This means that staff (including the solutions. There are many different project management methodologies. Determining the solution. Work breakdown structures are a standard project. PMI methodology embraces. The solutions architect and project.
Figure 1- 2, for planning. Some tools let you create dependencies at the time that you. Work Breakdown Structure. But the PMI- recommended approach is to. Figure 1- 2. Work breakdown structure.
Other organizations have adopted less prescriptive. Agile. A solutions architect should understand. For example, in a. In. a more iterative project management methodology, designs may be continuously revised. Ideally, even in an agile project, the high- level. The design at the end of an agile project is often substantially. The. architecture may also change as greater insight is gained during the solution.
At times, the solutions architect will be asked to. This can put a project at. Also, most. architects do not have the same level of project management skills as full- time. When this occurs, effective architecture generally diminishes. Key Point. The project manager coordinates budgets, schedules. The project manager does not judge a solution.
Where do we need to modify the schedule? What resources are required. The solutions architect engages process and tactics skills when supplying the project manager with appropriately summarized. Ideally, the solutions architect and.
Developers. Developers are the conduit between the architecture. Solutions architects engage. A solutions architect benefits. Infrastructure Architect. The infrastructure architect has parallel and. Key Point. The infrastructure architect must understand the. The infrastructure and solutions architects share.
They must effectively apply these skills. Infrastructure architects are a valued. However, poor communication between. Too often, infrastructure. Consider for Yourself.
At what time was the infrastructure team involved? How would you. modify that today? Solutions Architect. The solutions architect succeeds through a mutual. Key Point. The goal of the solutions architect is to. As such, you must identify and. To Learn More. Check out the Project Management Institute Web.
There are Project Management Institute chapters in many larger. Lesson Wrap Up. The. Consider how to most effectively interact. Lesson 2: Developing Business. Strategy and Plans. Elements of the next three topics apply directly.
In a. similar way, the people in an organization charged with strategic planning have. Just as a business stakeholder who has invested the. UML diagram or an entity relationship diagram can engage.
Understanding strategic business tools can also. As organizations move from strategy to. Figure 2- 2. Figure 2- 2.
From strategy to execution. Business schools and business literature teach a. In this. lesson, we provide an overview of two tools that are both popular and. From a business value perspective, most.
The strategy map is a tool that. A solutions architect does not need to be an expert. In addition to understanding. These might include Lean Six Sigma, Total. Quality Management (TQM), and the Capability Maturity Model Integration (CMMI). If. so, have you read it?
Some organizations are unwilling to share strategic. Consider asking if the strategic. A solutions architect who understands. Strategy maps are a business tool that helps an organization.
After these objectives are identified. Therefore, an organization that uses a tool like a strategy. We will start by looking at an example of a strategy. Figure 2- 3, based on an example in Norton and Kaplan. The arrows show causality between strategic objectives. In turn, these will help us to both keep our. A strategy map for increased.
Before you create a strategy map, your organization. Patrick Lencioni defines a thematic. These strategic objectives should be grouped. Most organizations also have many operational and regulatory. Strategic planning tools, such as strategy maps.
IT solution ideas. The organization that created the strategy map in. Figure 2- 3 determined that its most important IT investment is a crew scheduling.
The solutions architect that helps build this crew scheduling system is. IT investments that will most benefit the organization. Consider for Yourself?
Do you think working. How might this affect your architectural decisions?? Might this lead to different. Exercises for Understanding. Can you. show how this strategic objective, in turn, ties back to a financial objective?
Overcoming the Five Dysfunctions. Team. San Francisco: Jossey- Bass, 2. September/October 2. The Balanced Scorecard: Translating. Strategy into Action. Boston: Harvard Business School Press.
The Strategy- Focused Organization. How Balanced Scorecard Companies Thrive in the New Business Environment. Strategy Maps: Converting Intangible. Assets into Tangible Outcomes. Boston: Harvard Business School. Press. Balanced Scorecard Step- by- Step. Maximizing Performance and Maintaining Results.
Hoboken: John Wiley. Sons. Balanced Scorecard Step- by- Step for. Government and Nonprofit Agencies. Hoboken: John Wiley. Sons. Balanced Scorecard Diagnostics: Maintaining. Maximum Performance. Hoboken: John Wiley & Sons.
A strategy. canvas is a tool that is part of the Blue Ocean Strategy analytical framework. Organizations that focus strictly on bottom- line. Kim and Mauborgne argue that this leads. Blue Ocean Strategy argues that the path to sales.
Their process for. For each factor of competition, then ask. Many technologists love to build things, and to add value by incorporating. Blue Ocean Strategy argues that if you eliminate new features that. Exercises for Understanding?
Whom do you see your organization competing.