Association of initial opioid prescription duration and an opioid refill by pain diagnosis: Evidence from outpatient settings in ten US health systems.

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.

Prescription Opioid Dose Reductions and Potential Adverse Events: a Multi-site Observational Cohort Study in Diverse US Health Systems.

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.

Utility of fertility procedures and prenatal tests to estimate gestational age for live-births and stillbirths in electronic health plan databases.

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.

Prevalence of prescription opioid use during pregnancy in eight US health plans during 2001-2014.

PURPOSE: To estimate prevalence of prescription opioid use during pregnancy in eight US health plans during 2001-2014. METHODS: We conducted a cohort study of singleton live birth deliveries. Maternal characteristics were ascertained from health plan and/or birth certificate data and opioids dispensed during pregnancy from health plan pharmacy records. Prevalence of prescription opioid use during pregnancy was calculated for any use, cumulative days of use, and number of dispensings. RESULTS: We examined prevalence of prescription opioid use during pregnancy in each health plan. Tennessee Medicaid had appreciably greater prevalence of use compared to the seven other health plans. Thus, results for the two groups were reported separately. In the seven health plans (n = 587 093 deliveries), prevalence of use during pregnancy was relatively stable at 9%-11% throughout 2001-2014. In Tennessee Medicaid (n = 256 724 deliveries), prevalence increased from 29% in 2001 to a peak of 36%-37% in 2004-2010, and then declined to 28% in 2014. Use for ≥30 days during pregnancy was stable at 1% in the seven health plans and increased from 2% to 7% in Tennessee Medicaid during 2001-2014. Receipt of ≥5 opioid dispensings during pregnancy increased in the seven health plans (0.3%-0.6%) and Tennessee Medicaid (3%-5%) during 2001-2014. CONCLUSION: During 2001-2014, prescription opioid use during pregnancy was more common in Tennessee Medicaid (peak prevalence in late 2000s) compared to the seven health plans (relatively stable prevalence). Although a small percentage of women had opioid use during pregnancy for ≥30 days or ≥ 5 dispensings, they represent thousands of women during 2001-2014.

Validation of an ICD-10-based algorithm to identify stillbirth in the Sentinel System.

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.

Validation of an electronic algorithm for Hodgkin and non-Hodgkin lymphoma in ICD-10-CM.

PURPOSE: Lymphoma is a health outcome of interest for drug safety studies. Studies using administrative claims data require the accurate identification of lymphoma cases. We developed and validated an International Classification of Diseases, Tenth Revision, Clinical Modification (ICD-10-CM)-based algorithm to identify lymphoma in healthcare claims data. METHODS: We developed a three-component algorithm to identify patients aged ≥15 years who were newly diagnosed with Hodgkin (HL) or non-Hodgkin (NHL) lymphoma from January 2016 through July 2018 among members of four Data Partners within the FDA's Sentinel System. The algorithm identified potential cases as patients with ≥2 ICD-10-CM lymphoma diagnosis codes on different dates within 183 days; ≥1 procedure code for a diagnostic procedure (e.g., biopsy, flow cytometry) and ≥1 procedure code for a relevant imaging study within 90 days of the first lymphoma diagnosis code. Cases identified by the algorithm were adjudicated via chart review and a positive predictive value (PPV) was calculated. RESULTS: We identified 8723 potential lymphoma cases via the algorithm and randomly sampled 213 for validation. We retrieved 138 charts (65%) and adjudicated 134 (63%). The overall PPV was 77% (95% confidence interval: 69%-84%). Most cases also had subtype information available, with 88% of cases identified as NHL and 11% as HL. CONCLUSIONS: Seventy-seven percent of lymphoma cases identified by an algorithm based on ICD-10-CM diagnosis and procedure codes and applied to claims data were true cases. This novel algorithm represents an efficient, cost-effective way to target an important health outcome of interest for large-scale drug safety and public health surveillance studies.

Validity of diagnosis and procedure codes for identifying neural tube defects in infants.

PURPOSE: The use of validated criteria to identify birth defects in electronic healthcare databases can avoid the cost and time-intensive efforts required to conduct chart reviews to confirm outcomes. This study evaluated the validity of various case-finding methodologies to identify neural tube defects (NTDs) in infants using an electronic healthcare database. METHODS: This analysis used data generated from a study whose primary aim was to evaluate the association between first-trimester maternal prescription opioid use and NTDs. The study was conducted within the Medication Exposure in Pregnancy Risk Evaluation Program. A broad approach was used to identify potential NTDs including diagnosis and procedure codes from inpatient and outpatient settings, death certificates and birth defect flags in birth certificates. Potential NTD cases were chart abstracted and confirmed by clinical experts. Positive predictive values (PPVs) and 95% confidence intervals (95% CI) are reported. RESULTS: The cohort included 113 168 singleton live-born infants: 55 960 infants with opioid exposure in pregnancy and 57 208 infants unexposed in pregnancy. Seventy-three potential NTD cases were available for the validation analysis. The overall PPV was 41% using all diagnosis and procedure codes plus birth certificates. Restricting approaches to codes recorded in the infants' medical record or to birth certificate flags increased the PPVs (72% and 80%, respectively) but missed a substantial proportion of confirmed NTDs. CONCLUSIONS: Codes in electronic healthcare data did not accurately identify confirmed NTDs. These results indicate that chart review with adjudication of outcomes is important when conducting observational studies of NTDs using electronic healthcare data.

Misclassification in Assessment of First Trimester In-utero Exposure to Drugs Used Proximally to Conception: the Example of Letrozole Utilization for Infertility Treatment.

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.

Use of Antidiabetic drugs during pregnancy among U.S. women with Livebirth deliveries in the Mini-Sentinel system.

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.

Utilization of drugs with pregnancy exposure registries during pregnancy.

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.

Antiemetic use among pregnant women in the United States: the escalating use of ondansetron.

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.

Trimethoprim-sulfonamide use during the first trimester of pregnancy and the risk of congenital anomalies.

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.

Use of selective serotonin reuptake inhibitors (SSRIs) in women delivering liveborn infants and other women of child-bearing age within the U.S. Food and Drug Administration's Mini-Sentinel program.

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.

Surveillance of Medication Use During Pregnancy in the Mini-Sentinel Program.

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.

Beginning and duration of pregnancy in automated health care databases: review of estimation methods and validation results.

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.

The prevalence and trends of antiviral medication use during pregnancy in the US: a population-based study of 664,297 deliveries in 2001-2007.

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.

Use of the Sentinel System to Examine Medical Product Use and Outcomes During Pregnancy.

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.

A critical review of methods to evaluate the impact of FDA regulatory actions.

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.

Validation of anaphylaxis in the Food and Drug Administration's Mini-Sentinel.

PURPOSE: We aim to develop and validate the positive predictive value (PPV) of an algorithm to identify anaphylaxis using health plan administrative and claims data. Previously published PPVs for anaphylaxis using International Classification of Diseases, ninth revision, Clinical Modification (ICD-9-CM) codes range from 52% to 57%. METHODS: We conducted a retrospective study using administrative and claims data from eight health plans. Using diagnosis and procedure codes, we developed an algorithm to identify potential cases of anaphylaxis from the Mini-Sentinel Distributed Database between January 2009 and December 2010. A random sample of medical charts (n = 150) was identified for chart abstraction. Two physician adjudicators reviewed each potential case. Using physician adjudicator judgments on whether the case met diagnostic criteria for anaphylaxis, we calculated a PPV for the algorithm. RESULTS: Of the 122 patients for whom complete charts were received, 77 were judged by physician adjudicators to have anaphylaxis. The PPV for the algorithm was 63.1% (95%CI: 53.9-71.7%), using the clinical criteria by Sampson as the gold standard. The PPV was highest for inpatient encounters with ICD-9-CM codes of 995.0 or 999.4. By combining only the top performing ICD-9-CM codes, we identified an algorithm with a PPV of 75.0%, but only 66% of cases of anaphylaxis were identified using this modified algorithm. CONCLUSIONS: The PPV for the ICD-9-CM-based algorithm for anaphylaxis was slightly higher than PPV estimates reported in prior studies, but remained low. We were able to identify an algorithm that optimized the PPV but demonstrated lower sensitivity for anaphylactic events.

Drug safety data mining with a tree-based scan statistic.

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.