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No-Show Clinical Data Analytics

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No-show rates range between 15% to 30% in an ambulatory setting and lead to wasted resources, increased financial burdens and inaccurate or missed diagnoses of patients (Goldman et al., 1982). Previous studies have shown that various patient factors can predict future no-show behavior. For example, the type of appointment scheduled for a patient can predict patient absenteeism (Zeber, Pearson, & Smith, 2009). Zeber et al. found that colonoscopy appointments are the most commonly missed appointments (Zeber et al., 2009). Furthermore, previous missed appointments is one of the most significant predictors of no-show appointments (Dove & Schneider, 1981). Studies have also shown that patients’ various psychosocial diagnoses are indicators of missed appointments (Goldman et al., 1982). Patients diagnosed with at least one psychological diagnosis, including mood disorders, such as depression and bipolar disease, anxiety disorders, such as panic attacks and posttraumatic stress disorder, and thought disorders, such as schizophrenia and personality disorders, were more likely to miss appointments compared to patients without psychological diagnoses (Savageau et al., 2004). Finally, Perron et al. showed that patients with substance abuse disorders are more likely to miss appointments (Perron et al., 2010).
In order to reduce no-show rates in a hospital gastrointestinal (GI) clinic this project analyzed potential indicators of missed appointments. Based on a conceptual model grouping various barriers that lead to missed appointments (Figure 1, Appendix A), patient level factors were the main focus. The patient-level factors analyzed are colonoscopy procedure, previous GI appointment absenteeism, mood disorder, personality disorder and other substance abuse disorder among patients at the GI clinic.
Variables were selected based on information presented in lecture by

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