Dataset Information

How accurate are medical record data in Afghanistan's maternal health facilities? An observational validity study.

ABSTRACT:

Objectives

Improvement activities, surveillance and research in maternal and neonatal health in Afghanistan rely heavily on medical record data. This study investigates accuracy in delivery care records from three hospitals across workshifts.

Design

Observational cross-sectional study.

Setting

The study was conducted in one maternity hospital, one general hospital maternity department and one provincial hospital maternity department. Researchers observed vaginal deliveries and recorded observations to later check against data recorded in patient medical records and facility registers.

Outcome measures

We determined the sensitivity, specificity, area under the receiver operator characteristics curves (AUROCs), proportions correctly classified and the tendency to make performance seem better than it actually was.

Results

600 observations across the three shifts and three hospitals showed high compliance with active management of the third stage of labour, measuring blood loss and uterine contraction at 30 min, cord care, drying and wrapping newborns and Apgar scores and low compliance with monitoring vital signs. Compliance with quality indicators was high and specificity was lower than sensitivity. For adverse outcomes in birth registries, specificity was higher than sensitivity. Overall AUROCs were between 0.5 and 0.6. Of 17 variables that showed biased errors, 12 made performance or outcomes seem better than they were, and five made them look worse (71% vs 29%, p=0.143). Compliance, sensitivity and specificity varied less among the three shifts than among hospitals.

Conclusions

Medical record accuracy was generally poor. Errors by clinicians did not appear to follow a pattern of self-enhancement of performance. Because successful improvement activities, surveillance and research in these settings are heavily reliant on collecting accurate data on processes and outcomes of care, substantial improvement is needed in medical record accuracy.

SUBMITTER: Broughton EI

PROVIDER: S-EPMC3641480 | biostudies-literature | 2013

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

How accurate are medical record data in Afghanistan's maternal health facilities? An observational validity study.

Broughton Edward I EI Ikram Abdul Naser AN Sahak Ihsanullah I

BMJ open 20130424 4

<h4>Objectives</h4>Improvement activities, surveillance and research in maternal and neonatal health in Afghanistan rely heavily on medical record data. This study investigates accuracy in delivery care records from three hospitals across workshifts.<h4>Design</h4>Observational cross-sectional study.<h4>Setting</h4>The study was conducted in one maternity hospital, one general hospital maternity department and one provincial hospital maternity department. Researchers observed vaginal deliveries ...[more]

PMID: 23619087

Similar Datasets

Project description:BackgroundImproving the quality of breastfeeding counselling delivered by primary care providers can improve breastfeeding outcomes and ultimately reduce mortality and morbidity of children and mothers. Accurate data on coverage and quality of primary care breastfeeding counselling is essential for monitoring progress; however, global and national indicators are limited. To help address this gap, this study validated indicators of receipt and quality of breastfeeding counselling during routine consultations for infant care at seven primary health facilities across Kosovo.MethodsMothers' reports of breastfeeding counselling received during routine consultations for their infants (0-12 months of age) were collected by exit interview in 2019 and 2021 (n = 609). Responses were compared against direct observation of their consultation using a structured checklist (reference standard) by a trained third-party observer at the primary care facility. We assessed 13 indicators; ten were related to the receipt and content of breastfeeding counselling, and three were specific to the provider's interpersonal skills. We calculated sensitivity, specificity, and area under the receiver operating curve (AUC) to determine individual-level reporting accuracy.ResultsTen indicators had an agreement rate above 70% and seven indicators had high overall individual-level validity (AUC ≥ 0.7). High prevalence indicators recorded high sensitivity and low specificity, and the inverse for low prevalence indicators. More subjective indicators were less reliable, e.g., mothers over-reported the prevalence of all three indicators related to providers' interpersonal skills.ConclusionsThis study offers evidence on breastfeeding counselling quality by validating maternal reports of whether a provider discussed breastfeeding, the clinical content of that counselling, and how it was delivered. It is also situated in a primary care setting within a fragile state of which there is limited evidence. We observed that mothers reported accurately when asked directly to recall breastfeeding counselling services received. However, there is a need to further validate subjective questions about interpersonal skills and other measures for the 'experience of care' quality dimension.

Project description:ImportanceThe conditions required for health record data sources to accurately assess treatment effectiveness remain unclear. Emulation of randomized clinical trials (RCTs) with health record data and subsequent calibration of the results can help elucidate this.ObjectiveTo pilot an emulation of the KEYNOTE-189 RCT using a commercially available electronic health record (EHR) data source.Design, setting, and participantsThis retrospective cohort study used an EHR database spanning from April 2007 to February 2023. Follow-up began on treatment initiation and proceeded until an outcome event, loss to follow-up, end of data, or end of study period (640 days). The population-based cohort was ascertained from EHRs provided by 52 health systems across the US. Eligibility criteria were defined as closely as possible to the benchmark RCT. Patients with non-small cell lung cancer initiating first-line treatment for metastatic disease were included. Patients with evidence of squamous non-small cell lung cancer, primary nonlung malignant neoplasms, or identified EGFR/ALK variations were excluded. Data were analyzed from June to October 2023.ExposuresInitiation of first-line pembrolizumab and chemotherapy and chemotherapy alone. Chemotherapy in both groups was defined as a combination of pemetrexed and platinum-based (carboplatin or cisplatin) therapy.Main outcomes and measuresOutcomes of interest were 12-month survival probability and mortality hazard ratio (HR).ResultsA total of 1854 patients (mean [SD] age, 63.7 [9.6] years; 971 [52.4%] men) were eligible, including 589 patients who initiated pembrolizumab and chemotherapy and 1265 patients who initiated chemotherapy only. The cohort included 364 Black patients (19.6%) and 1445 White patients (77.9%). The 12-month survival probabilities were 0.60 (95% CI, 0.54-0.65) in the pembrolizumab group and 0.58 (95% CI, 0.55-0.62) in the chemotherapy-only group, compared with 0.69 (95% CI, 0.64-0.74) in the KEYNOTE-189 pembrolizumab group and 0.49 (95% CI, 0.42-0.56) in the KEYNOTE-189 chemotherapy-only group. The mortality HR was 0.95 (95% CI, 0.78-1.16), compared with 0.49 (95% CI, 0.38-0.64) in the KEYNOTE-189 RCT.Conclusions and relevanceIn this cohort study piloting an RCT emulation, results were incongruous with the benchmark trial. Differences in patient treatment and data capture between the RCT and EHR populations, confounding by indication, treatment crossover, and accuracy of captured diagnoses may explain these findings. Future feasibility assessments will require data sources to have important oncology-specific measures curated.

Project description:BackgroundHealth information exchange and multiplatform health record viewers support more informed medical decisions, improve quality of care, and reduce the risk of adverse outcomes due to fragmentation and discontinuity in care during transition of care. An example of a multiplatform health record viewer is the VA/DoD Joint Longitudinal Viewer (JLV), which supports the Department of Veterans Affairs (VA) and Department of Defense (DoD) health care providers with read-only access to patient medical records integrated from multiple sources. JLV is intended to support more informed medical decisions such as reducing duplicate medical imaging when previous image study results may meet current clinical needs.ObjectiveWe estimated the impact of provider usage of JLV on duplicate imaging for service members transitioning from the DoD to the VA health care system.MethodsWe conducted a retrospective cross-sectional study in fiscal year 2018 to examine the relationship between providers' use of JLV and the likelihood of ordering duplicate images. Our sample included recently separated service members who had a VA primary care visit in fiscal year 2018 within 90 days of a DoD imaging study. Patients who received at least one imaging study at VA within 90 days of a DoD imaging study of the same imaging mode and on the same body part are considered to have received potentially duplicate imaging studies. We use a logistic regression model with "JLV provider" (providers with 1 or more JLV audits in the prior 6 months) as the independent variable to estimate the relationship between JLV use and ordering of duplicate images. Control variables included provider image ordering rates in the prior 6 months, provider type, patient demographics (age, race, gender), and clinical characteristics (Elixhauser comorbidity score).ResultsProviders known to utilize JLV in the prior 6 months order fewer duplicate images relative to providers not utilizing JLV for similar visits over time (odds ratio 0.44, 95% CI 0.24-0.78; P=.005). This effect is robust across multiple specifications of linear and logistic regression models. The provider's practice pattern of ordering image studies and the patient's health status are powerful confounders.ConclusionsThis study provides evidence that adoption of a longitudinal viewer of health records from multiple electronic health record systems is associated with a reduced likelihood of ordering duplicate images. Investments in health information exchange systems may be effective ways to improve the quality of care and reduce adverse outcomes for patients experiencing fragmentation and discontinuity of care.

Project description:BackgroundMultimorbidity is common in women across the life course. Preterm birth is the single biggest cause of neonatal mortality and morbidity. We aim to estimate the prevalence of multimorbidity in pregnant women and to examine the association between maternal multimorbidity and PTB.MethodsThis is a retrospective cohort study using electronic health records from the Scottish Morbidity Records. All pregnancies among women aged 15 to 49 with a conception date between 1 January 2014 and 31 December 2018 were included. Multimorbidity was defined as the presence of two or more pre-existing long-term physical or mental health conditions, and complex multimorbidity as the presence of four or more. It was calculated at the time of conception using a predefined list of 79 conditions published by the MuM-PreDiCT consortium. PTB was defined as babies born alive between 24 and less than 37 completed weeks of gestation. We used Generalised Estimating Equations adjusted for maternal age, socioeconomic status, number of previous pregnancies, BMI, and smoking history to estimate the effect of maternal pre-existing multimorbidity. Absolut rates are reported in the results and tables, whilst Odds Ratios (ORs) are adjusted (aOR).ResultsThirty thousand five hundred fifty-seven singleton births from 27,711 pregnant women were included in the analysis. The prevalence of pre-existing multimorbidity and complex multimorbidity was 16.8% (95% CI: 16.4-17.2) and 3.6% (95% CI: 3.3-3.8), respectively. The prevalence of multimorbidity in the youngest age group was 10.2%(95% CI: 8.8-11.6), while in those 40 to 44, it was 21.4% (95% CI: 18.4-24.4), and in the 45 to 49 age group, it was 20% (95% CI: 8.9-31.1). In women without multimorbidity, the prevalence of PTB was 6.7%; it was 11.6% in women with multimorbidity and 15.6% in women with complex multimorbidity. After adjusting for maternal age, socioeconomic status, number of previous pregnancies, Body Mass Index (BMI), and smoking, multimorbidity was associated with higher odds of PTB (aOR = 1.64, 95% CI: 1.48-1.82).ConclusionsMultimorbidity at the time of conception was present in one in six women and was associated with an increased risk of preterm birth. Multimorbidity presents a significant health burden to women and their offspring. Routine and comprehensive evaluation of women with multimorbidity before and during pregnancy is urgently needed.

Project description:ImportanceCardiovascular disease is the leading cause of death in the United States. To improve cardiovascular outcomes, primary care must have valid methods of assessing performance on cardiovascular clinical quality measures, including aspirin use (aspirin measure), blood pressure control (BP measure), and smoking cessation counseling and intervention (smoking measure).ObjectiveTo compare observed performance scores measured using 2 imperfect reference standard data sources (medical record abstraction [MRA] and electronic health record [EHR]-generated reports) with misclassification-adjusted performance scores obtained using bayesian latent class analysis.Design, setting, and participantsThis cross-sectional study used a subset of the 2016 aspirin, BP, and smoking performance data from the Healthy Hearts for Oklahoma Project. Each clinical quality measure was calculated for a subset of a practice's patient population who can benefit from recommended care (ie, the eligible population). A random sample of 380 eligible patients were included for the aspirin measure; 126, for the BP measure; and 115, for the smoking measure. Data were collected from 21 primary care practices belonging to a single large health care system from January 1 to December 31, 2018, and analyzed from February 21 to April 17, 2019.Main outcomes and measuresThe main outcomes include performance scores for the aspirin, BP, and smoking measures using imperfect MRA and EHRs and estimated through bayesian latent class models.ResultsA total of 621 eligible patients were included in the analysis. Based on MRA and EHR data, observed aspirin performance scores were 76.0% (95% bayesian credible interval [BCI], 71.5%-80.1%) and 74.9% (95% BCI, 70.4%-79.1%), respectively; observed BP performance scores, 80.6% (95% BCI, 73.2%-86.9%) and 75.1% (95% BCI, 67.2%-82.1%), respectively; and observed smoking performance scores, 85.7% (95% BCI, 78.6%-91.2%) and 75.4% (95% BCI, 67.0%-82.6%), respectively. Misclassification-adjusted estimates were 74.9% (95% BCI, 70.5%-79.1%) for the aspirin performance score, 75.0% (95% BCI, 66.6%-82.5%) for the BP performance score, and 83.0% (95% BCI, 74.4%-89.8%) for the smoking performance score.Conclusions and relevanceEnsuring valid performance measurement is critical for value-based payment models and quality improvement activities in primary care. This study found that extracting information for the same individuals using different data sources generated different performance score estimates. Further research is required to identify the sources of these differences.

Dataset Information

How accurate are medical record data in Afghanistan's maternal health facilities? An observational validity study.

Objectives

Design

Setting

Outcome measures

Results

Conclusions

Publications

How accurate are medical record data in Afghanistan's maternal health facilities? An observational validity study.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets