Factors associated with misdiagnosis of hospitalised patients: A mixed method study in five general hospitals of Central Uganda

Abstract

Abstract Introduction: Inpatient misdiagnosis is a major public health problem in sub-Saharan Africa, the scope and causes of which are unknown. The purpose of this cross-sectional study, conducted in five hospitals in central Uganda, was to identify the factors associated with inpatient misdiagnosis in general hospitals in central Uganda. Methodology: An explanatory mixed methods cross-sectional study was used. A retrospective review of 2,431 patient records was performed using explicit review methods to determine the extent of patient misdiagnosis and other variables thought to be related to patient misdiagnosis. Any discrepancy between the admission diagnosis made in the emergency room or outpatient clinic and the patient's discharge diagnosis made upon discharge was defined as a misdiagnosis. The diagnoses were classified using the World Health Organization ICD-11. Six clinical staff and six medical staff were interviewed using in-depth interviews (IDIs) in a phenomenological approach to obtain their explanatory account of factors associated with misdiagnosis. A logistic regression and a deductive thematic analysis were carried out on quantitative and qualitative data analyses. The quantitative and qualitative findings of the study were mixed in interpretation. Results: Misdiagnosis was discovered in 223/2431 (9.2%) of the admitted patients' records. Misdiagnosis was associated with the following factors: a patient admitted to Nakaseke hospital [aOR = 1.95, 95% CI = 1.17–3.25, p = 0.01], admission at night [aOR = 3, 95% CI = 1.81–5.02, p0.01], male patient [aOR = 1.89, 95% CI = 1.35–2.64, p0.01], patient's age groups 10–19 [AOR = 2.3, 95% CI = 2.3-9. Misdiagnosis was also linked to multimorbidity (aOR = 4.71, 95% CI = 1.91–11.65, p0.01) and patients with rare diseases (aOR = 2.57, 95% CI = 1.28–5.18, p0.01). Patients with no underlying diseases [aOR = 0.63; 95% CI = 0.43–0.91, p = 0.015] and those who were not referred [aOR = 0.51; 95% CI = 0.31–0.86, p = 0.011] had a lower risk of misdiagnosis. The quantitative findings of significant (p 0.05) and non-significant patient, contextual, disease, and health system factors associated with misdiagnosis were validated by the qualitative findings. Conclusion: To improve diagnostic accuracy, hospitals should reorganize patient admission processes, provide targeted training, create policies or guidelines targeting risk factors for misdiagnosis, and implement a diagnostic error prevention culture that addresses factors related to misdiagnosis in the respective hospitals oriented.