**3. Focus on data quality and high-fidelity event reporting**

Among the most crucial issues in patient and staff safety today is the necessity for accurate and non-judgmental reporting (and subsequent discussion) of patient and staff safety events and incidents [6]. While many systems exist for reporting safety incidents, medical errors often go unreported or underreported [16]. A major challenge to accurate reporting of safety miscues is the vulnerability of the so-called

#### *Introductory Chapter: Patient Safety Remains an Elusive, Fast-Moving Target DOI: http://dx.doi.org/10.5772/intechopen.109511*

"cognitive reality" toward bias and error [17]. Poor or incomplete understating of patient safety issues results in more inaccurate and less relevant epidemiological information available to medical group practices and healthcare organizations, thus hindering key efforts to reduce potential and actual harm to patients [16]. There are multiple barriers to reporting safety incidents, at individual, team, and systemic levels. More specifically, among opportunities to improve safety incident reporting, clinicians note that insufficient feedback to the reporter and anxiety related to reporting occur quite commonly and correspond with low participation rates and less reliable safety data. Notably, physicians are less likely than nurses to document safety incidents [16].

*Ex se intellegitur*, the accuracy of any reported data will depend heavily on a variety of factors, including the reporting environment and the way any such reporting is handled at the organizational level. The ability to effectively demonstrate and reassure that non-punitive, constructive approaches to addressing patient safety events are hardwired into the organizational fabric is of critical importance. Indeed, this philosophy of dealing with patient adverse event reporting and root cause analysis is known to result in the best overall outcomes and system-wide improvements [15]. Highly structured approaches that incorporate constructive and synergistic learning are required, with recognition of the fact that a vast majority of medical errors have multiple "contributory inputs" and very rarely can be attributed to a single individual and/or action [18]. It is also critical to acknowledge that rigidly hierarchical systems (e.g., top-down command and control environments) will inherently have more potential failure modes than more horizontal systems (e.g., matrix-like partnerships with equally weighted stakeholder inputs) [19].
