Predicting stillbirth in a low resource setting.

BACKGROUND: Stillbirth is a major contributor to perinatal mortality and it is particularly common in low- and middle-income countries, where annually about three million stillbirths occur in the third trimester. This study aims to develop a prediction model for early detection of pregnancies at high risk of stillbirth. METHODS: This retrospective cohort study examined 6,573 pregnant women who delivered at Federal Medical Centre Bida, a tertiary level of healthcare in Nigeria from January 2010 to December 2013. Descriptive statistics were performed and missing data imputed. Multivariable logistic regression was applied to examine the associations between selected candidate predictors and stillbirth. Discrimination and calibration were used to assess the model's performance. The prediction model was validated internally and over-optimism was corrected. RESULTS: We developed a prediction model for stillbirth that comprised maternal comorbidity, place of residence, maternal occupation, parity, bleeding in pregnancy, and fetal presentation. As a secondary analysis, we extended the model by including fetal growth rate as a predictor, to examine how beneficial ultrasound parameters would be for the predictive performance of the model. After internal validation, both calibration and discriminative performance of both the basic and extended model were excellent (i.e. C-statistic basic model = 0.80 (95 % CI 0.78-0.83) and extended model = 0.82 (95 % CI 0.80-0.83)). CONCLUSION: We developed a simple but informative prediction model for early detection of pregnancies with a high risk of stillbirth for early intervention in a low resource setting. Future research should focus on external validation of the performance of this promising model.

Deploying unqualified personnel in health records practice: Role substitution or quackery? Implications for health services delivery in Nigeria.

Healthcare professionals are obliged to work collaboratively regardless of their professional differences in order to provide the highest possible standard of care to patients. However, this type of collaboration can also lead to role substitution and, in effect, engagement of unqualified personnel in all health professions, including the health information management profession. This is a particular problem in developing nations such as Nigeria, where this trend has the potential to undermine the delivery of health services, the quality and the confidentiality of health information and trust between patients and healthcare professionals. To clarify and protect the professional identity of qualified health information management professionals in Nigeria and to prevent other experts who also work in health facilities (e.g. IT specialists, librarians) from claiming membership of the profession, the nomenclature for the health information management profession has been changed to health records and information management profession.

Data quality assessment in healthcare: a 365-day chart review of inpatients' health records at a Nigerian tertiary hospital.

BACKGROUND: Health records are essential for good health care. Their quality depends on accurate and prompt documentation of the care provided and regular analysis of content. This study assessed the quantitative properties of inpatient health records at the Federal Medical Centre, Bida, Nigeria. METHOD: A retrospective study was carried out to assess the documentation of 780 paper-based health records of inpatients discharged in 2009. RESULTS: 732 patient records were reviewed from the departments of obstetrics (45.90%), pediatrics (24.32%), and other specialties (29.78%). Documentation performance was very good (98.49%) for promptness recording care within the first 24 h of admission, fair (58.80%) for proper entry of patient unit number (unique identifier), and very poor (12.84%) for utilization of discharge summary forms. Overall, surgery records were nearly always (100%) prompt regarding care documentation, obstetrics records were consistent (80.65%) in entering patients' names in notes, and the principal diagnosis was properly documented in all (100%) completed discharge summary forms in medicine. 454 (62.02%) folders were chronologically arranged, 456 (62.29%) were properly held together with file tags, and most (80.60%) discharged folders reviewed, analyzed and appropriate code numbers were assigned. CONCLUSIONS: Inadequacies were found in clinical documentation, especially gross underutilization of discharge summary forms. However, some forms were properly documented, suggesting that hospital healthcare providers possess the necessary skills for quality clinical documentation but lack the will. There is a need to institute a clinical documentation improvement program and promote quality clinical documentation among staff.