Hospital Healthcare Service Risk Assessment and Management with Risk-O-Meter Software Metrics for a Field Application
Titel:
Hospital Healthcare Service Risk Assessment and Management with Risk-O-Meter Software Metrics for a Field Application
Auteur:
Sahinoglu, Mehmet Samelo, Erman Wool, Kenneth Morton, Scott
Verschenen in:
Journal of integrated design & process science
Paginering:
Jaargang 18 (2014) nr. 2 pagina's 45-76
Jaar:
2014-03-24
Inhoud:
This applied research paper implements a practical methodology about how to assess and improve patient-centred quality of care in the light of nationwide healthcare quality mandate to disseminate and utilize results for the "most bang for the buck". Patient-centred quality of care risk assessment and management are inseparable aspects of healthcare in a hospital, yet both are frequently overlooked. In the State of Alabama, a 2004 study by the Kaiser Family Foundation found substantial dissatisfaction with the quality of healthcare as well as other related national reports and managing insurance companies. The primary author's automated software, Risk-O-Meter (RoM), supported by a simulation analysis to verify the analytical outcomes, will provide a patient-centred metric of hospital health-care risk, and risk mitigation advice for vulnerabilities and threats associated with automated management of healthcare quality in a hospital or clinic. The RoM will be demonstrated to assess and enhance quality in the case of an ambulatory or non-ambulatory patient seeking healthcare at local hospitals. The Risk of Service (RoS) metric out of a 100% will be followed up by a remedial cost-optimized game-theoretic analysis about how to mitigate an undesirable risk to a tolerable level by determining what first priority precautions to be taken. The primary goal of this survey paper is to evaluate a random sample of 15 subjects' questionnaires from various corners of the State of Alabama so as to indicate the practical applicability of this software with tangible results. These questionnaires have been examined by the RoM automated software algorithm resulting with conclusive risk measures and what to do toward a cost-effective risk mitigation and remedial action.