Objective: Bone is the most common site of metastasis in breast cancer. Prognostic factors for predicting bone metastases in breast cancer are controversial yet. In this study, we investigated clinical factors associated with secondary bone metastasis of breast cancer. Methods: In total, 1690 patients with breast cancer recorded between 2002 and 2012 in Motamed Cancer Institute, Tehran, Iran entered in the retrospective study. We studied age, menopausal status, histologic type, tumor size, number of cancerous axillary lymph nodes, serum concentrations of alkaline phosphatase (ALP), carcinogenicity antigen (CEA), cancer antigen (CA)-153, and hemoglobin (HB) in 2 groups with bone metastases (n = 123) and without it, respectively. We applied logistic regression to identify bone metastasis prognostic factors in breast cancer patients and calculated the cut-off value, sensitivity, and characteristics of independent prognostic factors using receiver operating characteristic (ROC) curve analysis. Results: Menopause, larger tumor size, and the greater number of cancerous axillary lymph nodes increased the chance of bone metastases significantly ( P < .05). There was no significant difference between mean groups with and without bone metastases regarding serum concentration of CEA, CA-153, HB, and histopathologic type ( P > .05). Logistic regression showed that age (odds ratio (OR) = 1.021), menopausal status (OR = 1.854), number of cancerous axillary lymph nodes (OR = 1.065), a tumor size between 2 and 5 cm diameter (OR = 2.002) and more than 5 cm diameter (OR = 4.009), and ALP (OR = 1.005) are independent prognostic factors associated with bone metastases. The ROC curve showed that the abovementioned factors have comparable predictive accuracy for bone metastases. Conclusions: Age, menopausal status, number of axillary lymph node metastases, tumor size, and ALP were identified as prognostic factors for bone metastasis in patients with breast cancer. So patients with these characteristics should be monitored more precisely with regular follow-ups.

ObjectiveThe present study aimed to assess the quality of electronic medical records (EMR) retrieved from hospital information systems (HIS) of three educational hospitals in Mashhad, Iran.MethodsIn this multi-center, cross-sectional study, inpatient electronic records collected from three academic hospitals were categorized into five data groups, namely demographics (D); care handler (CH), indicating the doers of the medical actions; diagnosis and treatment (DT); administrative and financial (AF); and laboratory and Para clinic (LP). Next, we asked 25 physicians from the three academic hospitals to determine data elements of medical research and education value (called research and educational data) in every group. Flowingly, the quality of the five data groups (completeness * accuracy) was reported for entire sampled data and those specified as research and educational data, based on the exact concordance between electronic medical records and corresponding paper records. HISRA, standing for HIS recording ability, was also assessed compared to data elements of standard paper forms.ResultsFor entire data, HISRA was 58.5%. In all hospitals, the highest data quality (more than 90%) belongs to D and AF data groups, and the lowest quality goes to CH and DT groups (less than 50%, and 60%, respectively). For research and educational data, HISRA was 47%, and the quality of D and AF data groups were the highest (nearly 100%), while CH and DT stood around 50% and 60% in order. The quality of the LP data group was almost 85% in all hospitals but hospital C (well over 30%). Total data quality for the hospitals was almost less than 70%.ConclusionsThe low quality of electronic medical records was mostly a result of incompleteness, while the accuracy was relatively good. Results showed that the HIS application development mainly focused on administrative and financial aspects rather than academic and clinical goals.

Introduction:The validity of medical research based on electronic databases strongly relies on the quality of recorded data. Although the use of hospital information systems in Iran goes back to 1990s, few studies have assessed the quality of electronic medical records. The aim of this study was to assess the quality of electronic medical records, in the MUMS (Mashhad University of Medical Sciences) hospital information system (HIS), especially valuable ones for education and research. Methods: Samples of inpatient electronic records were selected in three academic hospitals: one general hospital (A) and two tertiary hospitals (B and C). We categorized all data elements of electronic medical records into five groups, including demographic, identification, diagnosis and treatment, administrative and financial; and laboratory and paraclinic. We asked 25 physicians from three academic hospitals to specify data elements with values of medical research and education (called research and educational data) in every group. Next we calculated recordability, completeness, and accuracy of five data groups according to the concordance between electronic records and corresponding paper records. Quality was calculated as a multiple of completeness and accuracy. Results: For all data elements, recordability of the software was 58.5%. Quality of demographic, identification, diagnosis and treatment, laboratory and paraclinic, and administrative and financial data groups was 97%, 32%, 42%, 82%, 89%, respectively, in hospital A. Quality of mentioned data groups was 99%, 44%, 60.5%, 91%, and 95.5% in hospital B, and 98%, 41%, 61%, 30%, and 97% in hospital C, respectively. For data elements, which were selected as valuable for research and education, recordability of the software was 47%. Also, quality of these data categorized in demographic, identification, diagnosis and treatment, laboratory and paraclinic, and administrative and financial was 100%, 67%, 48%, 89%, and 76%, respectively, in hospital A; 100%, 59%, 69%, 95%, and 90% in hospital B; and 100%, 34%, 65%, 32%, and 100% in hospital C, respectively. Conclusion: The low quality of electronic medical records was a result of incompleteness, while accuracy was relatively good. Results showed that the development and use of hospital information system focused on administrative and financial applications more than academic and clinical applications.