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OBJECTIVE: The Centers for Disease Control and Prevention's 2022 Clinical Practice Guideline for Prescribing Opioids for Pain cautioned that inflexible opioid prescription duration limits may harm patients. Information about the relationship between initial opioid prescription duration and a subsequent refill could inform prescribing policies and practices to optimize patient outcomes. We assessed the association between initial opioid duration and an opioid refill prescription. METHODS: We conducted a retrospective cohort study of adults ≥19 years of age in 10 US health systems between 2013 and 2018 from outpatient care with a diagnosis for back pain without radiculopathy, back pain with radiculopathy, neck pain, joint pain, tendonitis/bursitis, mild musculoskeletal pain, severe musculoskeletal pain, urinary calculus, or headache. Generalized additive models were used to estimate the association between opioid days' supply and a refill prescription. RESULTS: Overall, 220,797 patients were prescribed opioid analgesics upon an outpatient visit for pain. Nearly a quarter (23.5%) of the cohort received an opioid refill prescription during follow-up. The likelihood of a refill generally increased with initial duration for most pain diagnoses. About 1 to 3 fewer patients would receive a refill within 3 months for every 100 patients initially prescribed 3 vs. 7 days of opioids for most pain diagnoses. The lowest likelihood of refill was for a 1-day supply for all pain diagnoses, except for severe musculoskeletal pain (9 days' supply) and headache (3-4 days' supply). CONCLUSIONS: Long-term prescription opioid use increased modestly with initial opioid prescription duration for most but not all pain diagnoses examined.
Subject(s)
Musculoskeletal Pain , Radiculopathy , Adult , Humans , Analgesics, Opioid/therapeutic use , Retrospective Studies , Outpatients , Musculoskeletal Pain/diagnosis , Musculoskeletal Pain/drug therapy , Prescriptions , Headache , Practice Patterns, Physicians' , Back PainABSTRACT
BACKGROUND: In response to the opioid crisis in the United States, population-level prescribing of opioids has been decreasing; there are concerns, however, that dose reductions are related to potential adverse events. OBJECTIVE: Examine associations between opioid dose reductions and risk of 1-month potential adverse events (emergency department (ED) visits, opioid overdose, benzodiazepine prescription fill, all-cause mortality). DESIGN: This observational cohort study used electronic health record and claims data from eight United States health systems in a prescription opioid registry (Clinical Trials Network-0084). All opioid fills (excluding buprenorphine) between 1/1/2012 and 12/31/2018 were used to identify baseline periods with mean morphine milligram equivalents daily dose of ≥ 50 during six consecutive months. PATIENTS: We identified 60,040 non-cancer patients with ≥ one 2-month dose reduction period (600,234 unique dose reduction periods). MAIN MEASURES: Analyses examined associations between dose reduction levels (1- < 15%, 15- < 30%, 30- < 100%, 100% over 2 months) and potential adverse events in the month following a dose reduction using logistic regression analysis, adjusting for patient characteristics. KEY RESULTS: Overall, dose reduction periods involved mean reductions of 18.7%. Compared to reductions of 1- < 15%, dose reductions of 30- < 100% were associated with higher odds of ED visits (OR 1.14, 95% CI 1.10, 1.17), opioid overdose (OR 1.41, 95% CI 1.09-1.81), and all-cause mortality (OR 1.39, 95% CI 1.16-1.67), but lower odds of a benzodiazepine fill (OR 0.83, 95% CI 0.81-0.85). Dose reductions of 15- < 30%, compared to 1- < 15%, were associated with higher odds of ED visits (OR 1.08, 95% CI 1.05-1.11) and lower odds of a benzodiazepine fill (OR 0.93, 95% CI 0.92-0.95), but were not associated with opioid overdose and all-cause mortality. CONCLUSIONS: Larger reductions for patients on opioid therapy may raise risk of potential adverse events in the month after reduction and should be carefully monitored.
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PURPOSE: Current algorithms to evaluate gestational age (GA) during pregnancy rely on hospital coding at delivery and are not applicable to non-live births. We developed an algorithm using fertility procedures and fertility tests, without relying on delivery coding, to develop a novel GA algorithm in live-births and stillbirths. METHODS: Three pregnancy cohorts were identified from 16 health-plans in the Sentinel System: 1) hospital admissions for live-birth, 2) hospital admissions for stillbirth, and 3) medical chart-confirmed stillbirths. Fertility procedures and prenatal tests, recommended within specific GA windows were evaluated for inclusion in our GA algorithm. Our GA algorithm was developed against a validated delivery-based GA algorithm in live-births, implemented within a sample of chart-confirmed stillbirths, and compared to national estimates of GA at stillbirth. RESULTS: Our algorithm, including fertility procedures and 11 prenatal tests, assigned a GA at delivery to 97.9% of live-births and 92.6% of stillbirths. For live-births (n = 4 701 207), it estimated GA within 2 weeks of a reference delivery-based GA algorithm in 82.5% of pregnancies, with a mean difference of 3.7 days. In chart-confirmed stillbirths (n = 49), it estimated GA within 2 weeks of the clinically recorded GA at delivery for 80% of pregnancies, with a mean difference of 11.1 days. Implementation of the algorithm in a cohort of stillbirths (n = 40 484) had an increased percentage of deliveries after 36 weeks compared to national estimates. CONCLUSIONS: In a population of primarily commercially-insured pregnant women, fertility procedures and prenatal tests can estimate GA with sufficient sensitivity and accuracy for utility in pregnancy studies.
Subject(s)
Live Birth , Stillbirth , Electronics , Female , Fertility , Gestational Age , Humans , Live Birth/epidemiology , Pregnancy , Stillbirth/epidemiologyABSTRACT
PURPOSE: To develop and validate an International Classification of Diseases, 10th Revision, Clinical Modification (ICD-10-CM)-based algorithm to identify cases of stillbirth using electronic healthcare data. METHODS: We conducted a retrospective study using claims data from three Data Partners (healthcare systems and insurers) in the Sentinel Distributed Database. Algorithms were developed using ICD-10-CM diagnosis codes to identify potential stillbirths among females aged 12-55 years between July 2016 and June 2018. A random sample of medical charts (N = 169) was identified for chart abstraction and adjudication. Two physician adjudicators reviewed potential cases to determine whether a stillbirth event was definite/probable, the date of the event, and the gestational age at delivery. Positive predictive values (PPVs) were calculated for the algorithms. Among confirmed cases, agreement between the claims data and medical charts was determined for the outcome date and gestational age at stillbirth. RESULTS: Of the 110 potential cases identified, adjudicators determined that 54 were stillbirth events. Criteria for the algorithm with the highest PPV (82.5%; 95% CI, 70.9%-91.0%) included the presence of a diagnosis code indicating gestational age ≥20 weeks and occurrence of either >1 stillbirth-related code or no other pregnancy outcome code (i.e., livebirth, spontaneous abortion, induced abortion) recorded on the index date. We found ≥90% agreement within 7 days between the claims data and medical charts for both the outcome date and gestational age at stillbirth. CONCLUSIONS: Our results suggest that electronic healthcare data may be useful for signal detection of medical product exposures potentially associated with stillbirth.
Subject(s)
International Classification of Diseases , Stillbirth , Algorithms , Databases, Factual , Female , Humans , Infant , Pregnancy , Retrospective Studies , Stillbirth/epidemiologyABSTRACT
Letrozole is an aromatase inhibitor that has an unapproved use for ovulation induction with infertility. Because of the proximity of this use to conception, we selected letrozole to study the effect of 3 different methods for identifying the pregnancy start date and their impact on exposure misclassification. Using electronic health data from the US Sentinel database (2001-2015), we identified live-birth pregnancies conceived through in-vitro fertilization or intrauterine insemination. The pregnancy start was calculated using 1) a validated algorithm to estimate the last menstrual period (LMP), 2) LMP + 14 days (i.e., conception estimate), and 3) the fertility-procedure date. We identified 47,628 live-births after intrauterine insemination (n = 24,962) and in-vitro fertilization (n = 22,666), in which 2,458 (5.3%) mothers received letrozole. The algorithm-based conception estimate occurred within 14 days of the fertility procedure for 78.3% of pregnancies. Defining pregnancy start as LMP (45.7/1,000 pregnancies) or LMP + 14 days (12.7/1,000 pregnancies) overestimated letrozole exposure during pregnancy by 8.4-fold and 2.3-fold, respectively, compared with defining it at the date of the fertility procedure (5.5/1,000 pregnancies). While most studies of drug utilization in pregnancy use LMP as the conventional pregnancy start, this introduced substantial exposure misclassification in the example of letrozole. LMP + 14 days was less biased. Researchers should carefully consider the impact of the method for identifying the pregnancy start date on the potential for exposure misclassification.
Subject(s)
Aromatase Inhibitors/administration & dosage , Fertilization/physiology , Letrozole/administration & dosage , Pregnancy Trimester, First/physiology , Prenatal Exposure Delayed Effects/epidemiology , Research Design/standards , Adolescent , Adult , Algorithms , Child , Female , Fertilization in Vitro/methods , Humans , Insemination, Artificial/methods , Middle Aged , Pregnancy , United States , Young AdultABSTRACT
BACKGROUND: As the prevalence of diabetes mellitus increases in the population, the exposure to antidiabetic drugs (ADDs) during pregnancies is expected to grow, as has been seen over the last decade. The objective of this study was to estimate the prevalence of ADD use during pregnancy among women in the Mini-Sentinel Distributed Database (MSDD) who delivered a liveborn infant. METHODS: We identified qualifying livebirth pregnancies among women aged 10 to 54 years in the MSDD from 2001 to 2013. ADD use was estimated using outpatient pharmacy dispensing claims and days-supplied among three cohorts: all livebirth pregnancies, pregnancies among women with pre-existing diabetes, and pregnancies among women without prior ADD use. RESULTS: Among the 1.9 million pregnancies in the MSDD that resulted in a livebirth from 2001 to 2013, 4.4% were exposed to an ADD. Of the 15,606 pregnancies (0.8%) with pre-existing diabetes, 92.8% were also exposed during the pregnancy period. The most commonly used product in these pregnancies was insulin (75.6% of pregnancies). In contrast, in pregnancies of women without prior ADD use, the most commonly used products were glyburide and insulin, and most of these users were diagnosed with gestational diabetes. CONCLUSIONS: Patterns of ADD use during pregnancy described here, along with changes in disease incidence and management, highlight the importance of continuing surveillance of ADD utilization patterns and examining the safety and effectiveness of these products in pregnancy.
Subject(s)
Diabetes Mellitus/drug therapy , Diabetes, Gestational/drug therapy , Hypoglycemic Agents/therapeutic use , Pregnancy in Diabetics/drug therapy , Administrative Claims, Healthcare/statistics & numerical data , Adolescent , Adult , Child , Databases, Factual , Drug Prescriptions/statistics & numerical data , Female , Glyburide/therapeutic use , Humans , Insulin/therapeutic use , Live Birth , Middle Aged , Pregnancy , United States , Young AdultABSTRACT
PURPOSE: To describe the utilization of drugs with pregnancy exposure registries by trimester during pregnancy, in comparison with matched nonpregnant episodes and a pre-pregnancy period. METHODS: We identified live-born deliveries from women aged 10 to 54 years and matched the pregnancies 1:1 with nonpregnant episodes from a comparator cohort not delivering live-born infants, using data from 2001 to 2013 in the Sentinel Distributed Database. We evaluated the utilization of 34 drugs with pregnancy exposure registries, comparing utilization during pregnancy to the matched nonpregnant episodes, and to the 90 days before pregnancy. RESULTS: We identified 1 895 597 pregnancies ending in live births in 1 598 697 women and 1 895 597 matched nonpregnant episodes in 1 582 581 women. We observed a lower prevalence of use for most drugs during pregnancy compared with the matched nonpregnant episodes, and the 90-day pre-pregnancy period. The median (interquartile range) prevalence ratio of use, at any time during pregnancy, for all products was 0.2 (0.1-0.3) comparing pregnant to nonpregnant episodes. Overall, there was a decrease in drug utilization by trimester; from 2.6% in the 90 days preceding pregnancy to 2.1% in the first trimester, 1.1% in the second trimester, and 0.9% in the third trimester. CONCLUSIONS: Among drugs with pregnancy exposure registries, use was less during pregnancy compared with before pregnancy and to the matched nonpregnant episodes. The lower utilization during pregnancy suggests that women may be avoiding these drugs to minimize potentially harmful exposure during pregnancy. This lower utilization may increase the challenges of further studying the safety of these drugs using pregnancy exposure registries.
Subject(s)
Drug Utilization Review , Drug Utilization/statistics & numerical data , Pregnancy Complications/drug therapy , Pregnancy Trimesters , Registries/statistics & numerical data , Adolescent , Adult , Child , Cohort Studies , Female , Humans , Live Birth , Middle Aged , Postpartum Period , Pregnancy , Young AdultABSTRACT
PURPOSE: To examine ondansetron use in pregnancy in the context of other antiemetic use among a large insured United States population of women delivering live births. METHODS: We assessed ondansetron and other antiemetic use among pregnant women delivering live births between 2001 and 2015 in 15 data partners contributing data to the Mini-Sentinel Distributed Database. We identified live birth pregnancies using a validated algorithm, and all forms of ondansetron and other available antiemetics were identified using National Drug Codes or procedure codes. We assessed the prevalence of antiemetic use by trimester, calendar year, and formulation. RESULTS: In over 2.3 million pregnancies, the prevalence of ondansetron, promethazine, metoclopramide, or doxylamine/pyridoxine use anytime in pregnancy was 15.2, 10.3, 4.0, and 0.4%, respectively. Ondansetron use increased from <1% of pregnancies in 2001 to 22.2% in 2014, with much of the increase attributable to oral ondansetron beginning in 2006. Promethazine and metoclopramide use increased modestly between 2001 (13.8%, 3.2%) and 2006 (16.0%, 6.0%) but decreased annually through 2014 (8.0%, 3.2%). Doxylamine/pyridoxine, approved for management of nausea and vomiting in pregnancy in 2013, was used in 1.8% of pregnancies in 2014. For all antiemetics, use was highest in the first trimester. CONCLUSIONS: We observed a marked increase in ondansetron use by study year, prescribed to nearly one-quarter of insured pregnant women in 2014, occurring in conjunction with decreased use of promethazine and metoclopramide. Given the widespread use of ondansetron in pregnancy, data establishing product efficacy and methodologically rigorous evaluation of post-marketing safety are needed. Published 2017. This article is a U.S. Government work and is in the public domain in the USA.
Subject(s)
Antiemetics/therapeutic use , Morning Sickness/drug therapy , Ondansetron/therapeutic use , Practice Patterns, Physicians'/trends , Adult , Algorithms , Female , Humans , Morning Sickness/epidemiology , Pilot Projects , Pregnancy , Pregnancy Trimesters , United States/epidemiologyABSTRACT
BACKGROUND: Sulfonamide antibacterials are widely used in pregnancy, but evidence about their safety is mixed. The objective of this study was to assess the association between first-trimester sulfonamide exposure and risk of specific congenital malformations. METHODS: Mother-infant pairs were selected from a cohort of 1.2 million live-born deliveries (2001-2008) at 11 US health plans comprising the Medication Exposure in Pregnancy Risk Evaluation Program. Mothers with first-trimester trimethoprim-sulfonamide (TMP-SUL) exposures were randomly matched 1:1 to (i) a primary comparison group (mothers exposed to penicillins and/or cephalosporins) and (ii) a secondary comparison group (mothers with no dispensing of an antibacterial, antiprotozoal, or antimalarial medication during the same time period). The outcomes were cardiovascular abnormalities, cleft palate/lip, clubfoot, and urinary tract abnormalities. RESULTS: We first identified 7615 infants in the TMP-SUL exposure group, of which 7595 (99%) were exposed to a combination of TMP-SUL and the remaining 1% to sulfonamides alone. After matching (1:1) to the comparator groups and only including those with complete data on covariates, there were 20 064 (n = 6688 per group) in the primary analyses. Overall, cardiovascular defects (1.52%) were the most common and cleft lip/palate (0.10%) the least common that were evaluated. Compared with penicillin/cephalosporin exposure, and no antibacterial exposure, TMP-SUL exposure was not associated with statistically significant elevated risks for cardiovascular, cleft lip/palate, clubfoot, or urinary system defects. CONCLUSIONS: First-trimester TMP-SUL exposure was not associated with a higher risk of the congenital anomalies studied, compared with exposure to penicillins and/or cephalosporins, or no exposure to antibacterials.
Subject(s)
Abnormalities, Drug-Induced/epidemiology , Pregnancy Trimester, First/drug effects , Prenatal Exposure Delayed Effects/chemically induced , Prenatal Exposure Delayed Effects/epidemiology , Sulfonamides/adverse effects , Trimethoprim/adverse effects , Abnormalities, Drug-Induced/diagnosis , Adult , Anti-Bacterial Agents/adverse effects , Cohort Studies , Female , Humans , Infant , Infant, Newborn , Male , Pregnancy , Prenatal Exposure Delayed Effects/diagnosis , Retrospective Studies , Risk Factors , Young AdultABSTRACT
This study was conducted in order to assess the prevalence of use of selective serotonin reuptake inhibitors (SSRIs) among pregnant women delivering a liveborn infant in the USA. A retrospective study was conducted using the automated databases of 15 health-care systems participating in the Mini-Sentinel program. Diagnosis and procedure codes were used to identify women ages 10 to 54 years delivering a liveborn infant between April 2001 and December 2013. A comparison group of age- and date-matched women without live births was identified. The frequency of use of SSRIs was identified from outpatient dispensing data. Among the 1,895,519 liveborn deliveries, 113,689 women (6.0 %) were exposed to an SSRI during pregnancy during the period 2001-2013; 5.4 % were exposed to an SSRI during 2013. During the corresponding time period, 10.5 % of the age- and date-matched cohort of women without live births was exposed to an SSRI, with 10.1 % exposed to an SSRI during 2013. The most common agents dispensed during pregnancy were sertraline (n = 48,678), fluoxetine (n = 28,983), and citalopram (n = 20,591). Among those women exposed to an SSRI during pregnancy, 53.8 % had a diagnosis of depression and 37.3 % had a diagnosis of an anxiety disorder during pregnancy or within 180 days prior to pregnancy. Our finding that 6 % of women with live births were prescribed SSRIs during pregnancy highlights the importance of understanding the differential effects of these medications and other therapeutic options on the developing fetus and on the pregnant women.
Subject(s)
Depressive Disorder , Pregnancy Complications , Selective Serotonin Reuptake Inhibitors/therapeutic use , Adult , Depressive Disorder/drug therapy , Depressive Disorder/epidemiology , Female , Humans , Live Birth/epidemiology , Live Birth/psychology , Pregnancy , Pregnancy Complications/drug therapy , Pregnancy Complications/epidemiology , Prevalence , Sentinel Surveillance , United States/epidemiology , United States Food and Drug Administration/statistics & numerical dataABSTRACT
OBJECTIVES: Mini-Sentinel is a pilot project sponsored by the U.S. Food and Drug Administration to create an active surveillance system to monitor the safety of FDA-regulated medical products. We assessed the capability of the Mini-Sentinel pilot to provide prevalence rates of medication use among pregnant women delivering a liveborn infant. METHODS: An algorithm was developed to identify pregnancies for a reusable analytic tool to be executed against the Mini-Sentinel Distributed Database. Diagnosis and procedure codes were used to identify women ages 10-54 years delivering a liveborn infant between April 2001 and December 2012. A comparison group of age- and date-matched nonpregnant women was identified. The analytic code was distributed to all 18 Mini-Sentinel data partners. The use of specific medications, selected because of concerns about their safe use during pregnancy, was identified from outpatient dispensing data. We determined the frequency of pregnancy episodes and nonpregnant episodes exposed to medications of interest, any time during the pregnant/matched nonpregnant period, and during each trimester. RESULTS: The analytic tool successfully identified 1,678,410 live birth deliveries meeting the eligibility criteria. The prevalence of use at any time during pregnancy was 0.38 % for angiotensin-converting enzyme inhibitors and 0.22 % for statins. For ≤0.05 % of pregnancy episodes, the woman was dispensed warfarin, methotrexate, ribavirin, or mycophenolate. CONCLUSIONS: The analytic tool developed for this study can be used to assess the use of medications during pregnancy as safety issues arise, and is adaptable to include different medications, observation periods, pre-existing conditions, and enrollment criteria.
Subject(s)
Databases, Factual , Drug Prescriptions/statistics & numerical data , Drug Utilization/statistics & numerical data , Prenatal Care/methods , Prescription Drugs/therapeutic use , Adult , Cohort Studies , Female , Humans , Infant, Newborn , Maternal Age , Middle Aged , Pregnancy , Pregnancy Trimesters , Prevalence , United States , Young AdultABSTRACT
PURPOSE: To describe methods reported in the literature to estimate the beginning or duration of pregnancy in automated health care data, and to present results of validation exercises where available. METHODS: Papers reporting methods for determining the beginning or duration of pregnancy were identified based on Pubmed searches, by consulting investigators with expertise in the field and by reviewing conference abstracts and reference lists of relevant papers. From each paper or abstract, we extracted information to characterize the study population, data sources, and estimation algorithm. We then grouped these studies into categories reflecting their general methodological approach. RESULTS: Methods were classified into 5 categories: (i) methods that assign a uniform duration for all pregnancies, (ii) methods that assign pregnancy duration based on preterm-delivery or health care related codes, or codes for other pregnancy outcomes, (iii) methods based on the timing of prenatal care, (iv) methods based on birth weight, and (v) methods that combine elements from 2 and 3. Validation studies evaluating these methods used varied approaches, with results generally reporting on the mistiming of the start of pregnancy, incorrect estimation of the duration of pregnancy, or misclassification of drug exposure during pregnancy or early pregnancy. CONCLUSIONS: In the absence of accurate information on the beginning or duration of pregnancy, several methods of varying complexity are available to estimate them. Validation studies have been performed for many of them and can serve as a guide for method selection for a particular study.
Subject(s)
Databases, Factual , Delivery of Health Care/methods , Electronic Data Processing/methods , Electronic Data Processing/standards , Pregnancy/statistics & numerical data , Female , Humans , Infant, Newborn , Pregnancy Outcome , Reproducibility of ResultsABSTRACT
To evaluate the prevalence, trends, timing and duration of exposure to antiviral medications during pregnancy within a US cohort of pregnant women and to evaluate the proportion of deliveries with a viral infection diagnosis among women given antiviral medication during pregnancy. Live-born deliveries between 2001 and 2007, to women aged 15-45 years, were included from the Medication Exposure in Pregnancy Risk Evaluation Program, a collaborative research program between the U.S. Food and Drug Administration and eleven health plans. They were evaluated for prevalence, timing, duration, and temporal trends of exposure to antiviral medications during pregnancy. We also calculated the proportion of deliveries with a viral infection diagnosis among those exposed to antiviral medications. Among 664,297 live births, the overall prevalence of antiviral exposure during pregnancy was 4 % (n = 25,155). Between 2001 and 2007, antiviral medication exposure during pregnancy doubled from 2.5 to 5 %. The most commonly used antiviral medication was acyclovir, with 3 % of the deliveries being exposed and most of the exposure occurring after the 1st trimester. Most deliveries exposed to antiviral medications were exposed for less than 30 days (2 % of all live births). Forty percent of the women delivering an infant exposed to antiviral medications had a herpes diagnosis. Our findings highlight the increased prevalence of women delivering an infant exposed to antiviral medications over time. These findings support the need for large, well-designed studies to assess the safety and effectiveness of these medications during pregnancy.
Subject(s)
Antiviral Agents/therapeutic use , Infectious Disease Transmission, Vertical/prevention & control , Pregnancy Complications, Infectious/drug therapy , Pregnancy Outcome/epidemiology , Adolescent , Adult , Antiviral Agents/adverse effects , Female , Humans , Maternal Age , Middle Aged , Multicenter Studies as Topic , Population Surveillance , Pregnancy , Pregnancy Complications, Infectious/epidemiology , Pregnancy Complications, Infectious/virology , Prevalence , Retrospective Studies , Risk Assessment , Time Factors , United States/epidemiology , Young AdultABSTRACT
While many pregnant individuals use prescription medications, evidence supporting product safety during pregnancy is often inadequate. Existing electronic healthcare data sources provide large, diverse samples of health plan members to allow for the study of medical product utilization during pregnancy, as well as pregnancy, maternal, and infant outcomes. The Sentinel System is a national medical product surveillance system that includes administrative claims and electronic health record databases from large national and regional health insurers. In addition to these data sources, Sentinel develops and maintains a sizeable selection of analytic tools to facilitate epidemiologic analyses in a way that protects patient privacy and health system autonomy. In this article, we provide an overview of Sentinel System infrastructure, including the Mother-Infant Linkage Table, parameterizable analytic tools, and algorithms to estimate gestational age and identify pregnancy outcomes. We also describe past and future Sentinel work that contributes to our understanding of the way medical products are used and the safety of these products during pregnancy.
ABSTRACT
PURPOSE: To conduct a synthesis of the literature on methods to evaluate the impacts of FDA regulatory actions and identify best practices for future evaluations. METHODS: We searched MEDLINE for manuscripts published between January 1948 and August 2011 that included terms related to FDA, regulatory actions, and empirical evaluation; the review additionally included FDA-identified literature. We used a modified Delphi method to identify preferred methodologies. We included studies with explicit methods to address threats to validity and identified designs and analytic methods with strong internal validity that have been applied to other policy evaluations. RESULTS: We included 18 studies out of 243 abstracts and papers screened. Overall, analytic rigor in prior evaluations of FDA regulatory actions varied considerably; less than a quarter of studies (22%) included control groups. Only 56% assessed changes in the use of substitute products/services, and 11% examined patient health outcomes. Among studies meeting minimal criteria of rigor, 50% found no impact or weak/modest impacts of FDA actions and 33% detected unintended consequences. Among those studies finding significant intended effects of FDA actions, all cited the importance of intensive communication efforts. There are preferred methods with strong internal validity that have yet to be applied to evaluations of FDA regulatory actions. CONCLUSIONS: Rigorous evaluations of the impact of FDA regulatory actions have been limited and infrequent. Several methods with strong internal validity are available to improve trustworthiness of future evaluations of FDA policies.
Subject(s)
Consumer Product Safety/legislation & jurisprudence , Drug Approval/legislation & jurisprudence , Drug Labeling/legislation & jurisprudence , Endpoint Determination/methods , Government Regulation , Research Design , Endpoint Determination/statistics & numerical data , Research Design/statistics & numerical data , United States , United States Food and Drug AdministrationABSTRACT
PURPOSE: To validate an algorithm that uses delivery date and diagnosis codes to define gestational age at birth in electronic health plan databases. METHODS: Using data from 225,384 live born deliveries to women aged 15-45 years in 2001-2007 within eight of the 11 health plans participating in the Medication Exposure in Pregnancy Risk Evaluation Program, we compared (1) the algorithm-derived gestational age versus the "gold-standard" gestational age obtained from the infant birth certificate file and (2) the prenatal exposure status of two antidepressants (fluoxetine and sertraline) and two antibiotics (amoxicillin and azithromycin) as determined by the algorithm-derived versus the gold-standard gestational age. RESULTS: The mean algorithm-derived gestational age at birth was lower than the mean obtained from the birth certificate file among singleton deliveries (267.9 vs 273.5 days) but not among multiple-gestation deliveries (253.9 vs 252.6 days). The algorithm-derived prenatal exposure to the antidepressants had a sensitivity and a positive predictive value of ≥95%, and a specificity and a negative predictive value of almost 100%. Sensitivity and positive predictive value were both ≥90%, and specificity and negative predictive value were both >99% for the antibiotics. CONCLUSIONS: A gestational age algorithm based upon electronic health plan data correctly classified medication exposure status in most live born deliveries, but trimester-specific misclassification may be higher for drugs typically used for short durations.
Subject(s)
Algorithms , Databases, Factual/statistics & numerical data , Delivery, Obstetric/statistics & numerical data , Gestational Age , Adolescent , Adult , Anti-Bacterial Agents/administration & dosage , Antidepressive Agents/administration & dosage , Birth Certificates , Female , Humans , Infant, Newborn , International Classification of Diseases , Middle Aged , Pharmacoepidemiology/methods , Predictive Value of Tests , Pregnancy , Pregnancy, Multiple , Sensitivity and Specificity , Young AdultABSTRACT
PURPOSE: In post-marketing drug safety surveillance, data mining can potentially detect rare but serious adverse events. Assessing an entire collection of drug-event pairs is traditionally performed on a predefined level of granularity. It is unknown a priori whether a drug causes a very specific or a set of related adverse events, such as mitral valve disorders, all valve disorders, or different types of heart disease. This methodological paper evaluates the tree-based scan statistic data mining method to enhance drug safety surveillance. METHODS: We use a three-million-member electronic health records database from the HMO Research Network. Using the tree-based scan statistic, we assess the safety of selected antifungal and diabetes drugs, simultaneously evaluating overlapping diagnosis groups at different granularity levels, adjusting for multiple testing. Expected and observed adverse event counts were adjusted for age, sex, and health plan, producing a log likelihood ratio test statistic. RESULTS: Out of 732 evaluated disease groupings, 24 were statistically significant, divided among 10 non-overlapping disease categories. Five of the 10 signals are known adverse effects, four are likely due to confounding by indication, while one may warrant further investigation. CONCLUSION: The tree-based scan statistic can be successfully applied as a data mining tool in drug safety surveillance using observational data. The total number of statistical signals was modest and does not imply a causal relationship. Rather, data mining results should be used to generate candidate drug-event pairs for rigorous epidemiological studies to evaluate the individual and comparative safety profiles of drugs.
Subject(s)
Adverse Drug Reaction Reporting Systems/statistics & numerical data , Antifungal Agents/adverse effects , Data Mining/methods , Hypoglycemic Agents/adverse effects , Adult , Aged , Databases, Factual/statistics & numerical data , Electronic Health Records/statistics & numerical data , Female , Health Maintenance Organizations , Humans , Likelihood Functions , Male , Middle Aged , Pharmacoepidemiology/methods , Pharmacovigilance , Product Surveillance, Postmarketing/methods , Young AdultABSTRACT
PURPOSE: Research on medication safety in pregnancy often utilizes health plan and birth certificate records. This study discusses methods used to link mothers with infants, a crucial step in such research. METHODS: We describe how eight sites participating in the Medication Exposure in Pregnancy Risk Evaluation Program created linkages between deliveries, infants and birth certificates for the 2001-2007 birth cohorts. We describe linkage rates across sites, and for two sites, we compare the characteristics of populations linked using different methods. RESULTS: Of 299,260 deliveries, 256,563 (86%; range by site, 74-99%) could be linked to infants using a deterministic algorithm. At two sites, using birth certificate data to augment mother-infant linkage increased the representation of mothers who were Hispanic or non-White, younger, Medicaid recipients, or had low educational level. A total of 236,460 (92%; range by site, 82-100%) deliveries could be linked to a birth certificate. CONCLUSIONS: Tailored approaches enabled linking most deliveries to infants and to birth certificates, even when data systems differed. The methods used may affect the composition of the population identified. Linkages established with such methods can support sound pharmacoepidemiology studies of maternal drug exposure outside the context of a formal registry.
Subject(s)
Databases, Factual , Medical Record Linkage , Medical Records Systems, Computerized , Perinatal Care , Pregnancy Outcome , Adolescent , Adult , Adverse Drug Reaction Reporting Systems , Algorithms , Birth Certificates , Chi-Square Distribution , Data Mining , Databases, Factual/statistics & numerical data , Drug Prescriptions , Drug Utilization Review , Ethnicity , Female , Health Services Research , Humans , Infant, Newborn , Medical Records Systems, Computerized/statistics & numerical data , Perinatal Care/economics , Perinatal Care/statistics & numerical data , Pregnancy , Pregnancy Outcome/economics , Pregnancy Outcome/ethnology , Racial Groups , Socioeconomic Factors , United States/epidemiology , Young AdultABSTRACT
PURPOSE: To evaluate the validity of health plan and birth certificate data for pregnancy research. METHODS: A retrospective study was conducted using administrative and claims data from 11 U.S. health plans and corresponding birth certificate data from state health departments. Diagnoses, drug dispensings, and procedure codes were used to identify infant outcomes (cardiac defects, anencephaly, preterm birth, and neonatal intensive care unit [NICU] admission) and maternal diagnoses (asthma and systemic lupus erythematosus [SLE]) recorded in the health plan data for live born deliveries between January 2001 and December 2007. A random sample of medical charts (n = 802) was abstracted for infants and mothers identified with the specified outcomes. Information on newborn, maternal, and paternal characteristics (gestational age at birth, birth weight, previous pregnancies and live births, race/ethnicity) was also abstracted and compared to birth certificate data. Positive predictive values (PPVs) were calculated with documentation in the medical chart serving as the gold standard. RESULTS: PPVs were 71% for cardiac defects, 37% for anencephaly, 87% for preterm birth, and 92% for NICU admission. PPVs for algorithms to identify maternal diagnoses of asthma and SLE were ≥ 93%. Our findings indicated considerable agreement (PPVs > 90%) between birth certificate and medical record data for measures related to birth weight, gestational age, prior obstetrical history, and race/ethnicity. CONCLUSIONS: Health plan and birth certificate data can be useful to accurately identify some infant outcomes, maternal diagnoses, and newborn, maternal, and paternal characteristics. Other outcomes and variables may require medical record review for validation.
Subject(s)
Biomedical Research/methods , Birth Certificates , Databases, Factual/statistics & numerical data , Insurance, Health/statistics & numerical data , Female , Humans , Infant , Infant, Newborn , Male , Medical Records/statistics & numerical data , Predictive Value of Tests , Pregnancy , Pregnancy Complications/epidemiology , Pregnancy Outcome , Retrospective Studies , United StatesABSTRACT
This study aims to estimate the prevalence of and temporal trends in prenatal antipsychotic medication use within a cohort of pregnant women in the U.S. We identified live born deliveries to women aged 15-45 years in 2001-2007 from 11 U.S. health plans participating in the Medication Exposure in Pregnancy Risk Evaluation Program. We ascertained prenatal exposure to antipsychotics from health plan pharmacy dispensing files, gestational age from linked infant birth certificate files, and ICD-9-CM diagnosis codes from health plan claims files. We calculated the prevalence of prenatal use of atypical and typical antipsychotics according to year of delivery, trimester of pregnancy, and mental health diagnosis. Among 585,615 qualifying deliveries, 4,223 (0.72%) were to women who received an atypical antipsychotic and 548 (0.09%) were to women receiving a typical antipsychotic any time from 60 days before pregnancy through delivery. There was a 2.5-fold increase in atypical antipsychotic use during the study period, from 0.33% (95% confidence interval: 0.29%, 0.37%) in 2001 to 0.82% (0.76%, 0.88%) in 2007, while the use of typical antipsychotics remained stable. Depression was the most common mental health diagnosis among deliveries to women with atypical antipsychotic use (63%), followed by bipolar disorder (43%) and schizophrenia (13%). The number and proportion of pregnancies exposed to atypical antipsychotics has increased dramatically in recent years. Studies are needed to examine the comparative safety and effectiveness of these medications relative to other therapeutic options in pregnancy.