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French, Joel; Weathersby, Robert
2010 International Journal of Innovation Science
Only 55% of patients receive recommended care, with little difference found between care recommended for prevention, to address acute episodes, or to treat chronic conditions (McGlynn et al, 2003). The lag time between the discovery of more effective forms of medical treatment and their incorporation into routine patient care averages seventeen (17) years (IOM). Computerized provider order entry (CPOE) has been widely documented as a necessary tool to reduce preventable medication and other related errors but only 7.4% of acute care hospitals in the United States utilize CPOE with appropriate rules and evidence (HIMSS Analytics). The most fundamental building block for CPOE is the evidence based order set, but complexities associated with creating, managing and updating order sets have introduced major obstacles to CPOE implementation efforts. Chronic conditions such as heart disease, diabetes or arthritis affect more than 130 million Americans directly, and account for 7 in 10 deaths. Further, these chronic conditions consume 75% of all healthcare spending, and account for nearly two-thirds of the growth in health spending over the past 20 years -costing the U. S. economy $1 trillion annually (Almanac of Chronic Conditions, 2008 Edition). Estimates suggest the average patient upon hospitalization has 2.75 diagnoses - meaning "appropriate care" must span and synthesize multiple morbidity-specific best practices to effectively administer care to that "average" patient. The traditional approach to treating patients with evidence based protocols requires a physician to perform an ad hoc exercise of "mental merging" - reconciling duplicate candidate orders across multiple order sets to treat a patient with co-morbidities (today's norm). A more clinically effective, productive, and patient safety-centric alternative is to employ a proprietary software merging algorithm. These advanced algorithms remove duplicate orders, resolve conflicts, completes validation of the appropriate medical evidence and organizes the resulting merged order set so the physician can succinctly address the patients' often complicated treatment by focusing on the unique combination of labs, medications, etc. appropriate for the specific presenting conditions. This article describes a patent-pending propriety method of algorithmically merging multiple independent order sets for patients with co-morbid and chronic conditions into a single, maintenance free and evidence-based order set that can be immediately implemented into physician workflow to satisfy "Meaningful Use" guidelines for incremental provider reimbursement based on the American Recovery and Reinvestment Act (ARRA) legislation.
2010 International Journal of Innovation Science
At the center of its core, Health Care is the application of a general body of knowledge to the needs of a specific patient. For centuries, this knowledge was generally regarded as the property of the healing professions and the individual clinician, not necessarily of the health care delivery organization. Managerial practice also had a tendency to treat this knowledge as an attribute of the provider, thus focusing on the resources clinicians used as they provided care and on the hotel-type functions associated with inpatient institutions. That is, there was a deliberate differentiation between management practice, focused on business processes, and clinical practice, focused on the activities and decisions of diagnosis and treatment. Though often described as bureaucratic and incrementally changing, health care is also a very dynamic and innovative field. Around the globe, research scientists, private industries, academics, and governmental and nongovernmental agencies continue to work in innovating new ways to provide better care, find cures, and improve health. At the same time, health care delivery has been undergoing a gradual but important change. Patient care, once the domain of the individual practitioner, is becoming the domain of the care delivery organization. Additionally, the mission of these organizations is shifting. As science, technology, care processes, and care teams have become more complex and diverse, the way in which the activities of care are organized and the institutional context in which they occur have become an increasingly important determinant of the effectiveness and efficiency of that care. As a result, the object of management has changed. In response to these changes, health care managers have started focusing on the management of the care as well as the management of the institutions in which the care takes place, thereby creating a set of ‘Best Practices’ which are briefly described in this paper along with how the process of innovation is developing in the health care system.
2010 International Journal of Innovation Science
Several challenges exist for implementing electronic health records (EHRs). Tantamount to these challenges are issues surrounding the most effective ways to model medical information and subsequently deliver that information to necessary stakeholders. Therefore, it is important to design and implement EHR systems that are robust in terms of their content and intuitive in terms of their use value. Ontologies can provide robust and intuitive EHR capabilities, since ontological approaches more closely mirror the ordinary ways in which people interact (and problem solve) with the world. In a like manner, cognitive systems engineering - particularly the area of cognitive work analysis (CWA) — offers empirically-based methodologies for better understanding the ways in which people interact with data. By combining ontologies and CWA methodologies in healthcare settings, it is possible to build systems that both model information in correct ways and present it to those that need to utilize it in their day-to-day work environments.
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