Strategies for identifying pregnancies in the automated medical records of the General Practice Research Database
ABSTRACT To develop a method for identifying the beginning and ending records of pregnancies in the automated medical records of the General Practice Research Database (GPRD).
Women's records from 1991 to 1999 were searched for codes from 17 pregnancy marker and 7 pregnancy outcome categories. Using the retrieved records, all possible pregnancy marker-outcome combinations were formed per woman. For each combination, the difference in days between record event dates was calculated. Restrictions were applied to select the combination with the earliest pregnancy marker mapped to the first outcome for each pregnancy. Iterations of the algorithm identified multiple pregnancies per woman when present. The algorithm was evaluated by analyzing time between marker and outcome event dates of mapped pregnancies and by analyzing unmapped pregnancy markers and outcomes.
A total of 297,082 pregnancies were identified: 80% by general practitioner (GP) visit codes as the earliest pregnancy marker and 14% by laboratory or procedure codes. Limiting pregnancies to one per woman aged 15-44 years yielded 209,266 pregnancies. Pregnancy mapping success was greater than 80%. Plotting the pregnancies by weeks from earliest pregnancy marker to outcome and by pregnancy marker category showed two peaks in the distribution: 2-3 weeks and 33 weeks.
Arranging codes and time into algorithms provides a useful tool for pregnancy identification in databases whose size prohibits the audit of printed records. Evaluation of our algorithm confirmed a high degree of mapping success and a sensible time distribution from pregnancy marker to outcome.
- SourceAvailable from: Cormac J Sammon
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- "The study population consisted of all women with a pregnancy ending after the start of the vaccination campaign on 21 October 2009 and starting before 1 January 2010, for whom at least 6 months of data was available before their LMP date (Figure 1). Pregnancies were identified using an algorithm similar to those described elsewhere , . In summary this algorithm identifies individual pregnancies based on records of pregnancy outcomes and estimates each pregnancy's start and end date using all pregnancy related events in a woman's record. "
ABSTRACT: To evaluate the risk of foetal loss associated with pandemic influenza vaccination in pregnancy. Retrospective cohort study. UK General Practice Research Database Pregnancies ending in delivery or spontaneous foetal death after 21 October 2009 and starting before 01 January 2010. Hazard ratios of foetal death for vaccinated compared to unvaccinated pregnancies were estimated for gestational weeks 9 to 12, 13 to 24 and 25 to 43 using discrete-time survival analysis. Separate models were specified to evaluate whether the potential effect of vaccination on foetal loss might be transient (for ∼4 weeks post vaccination only) or more permanent (for the duration of the pregnancy). 39,863 pregnancies meeting our inclusion criteria contributed a total of 969,322 gestational weeks during the study period. 9,445 of the women were vaccinated before or during pregnancy. When the potential effect of vaccination was assumed to be transient, the hazard of foetal death during gestational weeks 9 through 12 (HR(unadj) 0.56; CI(95) 0.43 to 0.73) and 13 through 24 (HR(unadj) 0.45; CI(95) 0.28 to 0.73) was lower in the 4 weeks after vaccination than in other weeks. Where the more permanent exposure definition was specified, vaccinated pregnancies also had a lower hazard of foetal loss than unvaccinated pregnancies in gestational weeks 9 through 12 (HR(unadj) 0.74; CI(95) 0.62 to 0.88) and 13 through 24 (HR(unadj) 0.59; CI(95) 0.45 to 0.77). There was no difference in the hazard of foetal loss during weeks 25 to 43 in either model. Sensitivity analyses suggest the strong protective associations observed may be due in part to unmeasured confounding. Influenza vaccination during pregnancy does not appear to increase the risk of foetal death. This study therefore supports the continued recommendation of influenza vaccination of pregnant women.PLoS ONE 12/2012; 7(12):e51734. DOI:10.1371/journal.pone.0051734 · 3.23 Impact Factor
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ABSTRACT: The General Practice Research Database (GPRD) is widely used to study incidence rates. This study examines whether incidence rates are overestimated during the first year after registration, how long one needs to wait to obtain accurate incidence rates, and whether the time period of overestimation differs among disease types. We measured incidence rates of nine acute, eight chronic, and eight neoplastic outcomes in 3-month intervals through month 36 after enrollment in GPRD. The incidence rates in months 13-36 were used to estimate baseline incidence rates for each diagnosis. For patients registering with practices that were already UTS, incidence rates were highest in the first 3 months after registration. In eight of nine acute diagnoses, the incidence rate was within 20% of baseline by months 4-6; and in seven of eight cancers, the incidence rate was within 20% of baseline by months 7-9. For chronic conditions, the incidence rate in months 10-12 differed from baseline by more than 20% for five of the eight outcomes, respectively. For patients registering prior to UTS, incidence rates during the first quarter were within 20% of baseline for all acute and cancer diagnoses and six of eight chronic diagnoses. Reported incidence rates are highest in the first 3 months after registration with an UTS practice and decline to baseline over the first year, more quickly for acute conditions than chronic conditions. For patients who registered prior to UTS, incidence rates are near the baseline level at the start of follow-up.Pharmacoepidemiology and Drug Safety 07/2005; 14(7):443-51. DOI:10.1002/pds.1115 · 3.17 Impact Factor
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ABSTRACT: To demonstrate a linkage methodology for mother and baby automated medical records, and describe frequency, type, and pregnancy risk level of medications prescribed during pregnancy in a GPRD cohort, 1991-1999. We linked records using a two-stage algorithm and selected pairs with > or = 7 months prenatal records and > or = 2 records in baby's first year of life. Periods of interest were: 90 days prior to a woman's earliest identified pregnancy record (Period I), and this record plus 70 days (Period II, approximate early pregnancy). Medications were classified using the British National Formulary and US Food and Drug Administration Pregnancy Risk Categories. We achieved over 80% record linkage and defined a cohort of 81,975. Sixty-five per cent of mothers had > or = 1 prescription during both periods combined. Most frequent medications in Period I were anti-bacterial, contraceptive, topical steroid, and bronchodilator. In Period II, they were folic acid, anti-bacterial, antacid, and gynecological anti-infective. In Period I, 4% were FDA category A (considered safest), 34% B, and 49% C and D combined. By Period II, prescription of category A medications increased (folic acid, iron) while other categories declined. Category X medications, with potential teratogenic risk that outweighs maternal benefit, were prescribed to 5714 (7%) women in Period I, and 501 (0.6%) women in Period II (46% progesterone). One in every 164 women received a category X prescription in early pregnancy. The visit when pregnancy is first medically recognized represents an opportunity to review prescribed medications in light of contraindication and/or fetal risk.Pharmacoepidemiology and Drug Safety 08/2006; 15(8):555-64. DOI:10.1002/pds.1269 · 3.17 Impact Factor