- Cincinnati Children's Hospital Medical Center, Biomedical Informatics, Faculty Memberadd
- I am a biomedical informaticist and researcher focused on improving perinatal health outcomes in at-risk populations.... moreI am a biomedical informaticist and researcher focused on improving perinatal health outcomes in at-risk populations. For more than 10 years I have demonstrated motivation, leadership, and expertise while establishing a record of productive team science. I currently lead data management and integration supporting research and quality improvement within the Cincinnati Children's Hospital Medical Center (CCHMC) Perinatal Institute. Our systems utilize maternal and child health data originating from hospital electronic health records, vital records, geospatially-based measures from the American Communities Survey and other public data resources, and measures collected by community-based programs. My primary interests involve the linkage and integration of disparate data sets to facilitate the analysis of high-risk populations. My expertise in extraction, management, analysis, and modeling of complex electronic health data has positioned me as a key member of many interdisciplinary teams within the Perinatal Institute and as part of multi-institutional collaborations. I am also the director of data analysis and management for Cradle Cincinnati, a collective impact collaborative to reduce infant mortality in Hamilton County, Ohio. While my principal focus has been on preterm birth and infant mortality reduction, my interests extend to other high-risk maternal and child populations including those affected by withdrawal following in-utero exposure to narcotics.edit
OBJECTIVES: To develop generalizable methods for estimating the economic impact of preterm birth at the community level on initial hospital expenditures, educational attainment and lost earnings as well as to estimate potential savings... more
OBJECTIVES:
To develop generalizable methods for estimating the economic impact of preterm birth at the community level on initial hospital expenditures, educational attainment and lost earnings as well as to estimate potential savings associated with reductions in preterm birth.
STUDY DESIGN:
The retrospective, population-based analysis used vital statistics and population demographics from Hamilton County, Ohio, USA, in 2012.
METHODS:
We adjusted previously reported, mean initial hospital cost estimates (stratified by each week of gestation) to 2012 dollars using national cost-to-charge ratios. Next, we calculated excess costs attributable to prematurity and potential hospital cost savings, which could be realized by prolonging each preterm pregnancy by a single week of gestation. Using reported associations among preterm birth, educational attainment and adult earnings, we developed generalizable formulas to calculate lost academic degrees and lost income estimates attributable to preterm birth. The formulas generated estimates based on local population demographics.
RESULTS:
The annual initial hospital cost associated with 1444 preterm infants was estimated at $93 million. In addition, over 9000 fewer college degrees and over $300 million in lost annual earnings were attributed to local adults who were born preterm. Prolonging each preterm birth by 1 week could potentially reduce initial hospital expenditures by over $25 million. Additional potential savings could be realized as healthier infants attain higher levels of education and earnings as adults.
CONCLUSIONS:
The generalizable methods developed for estimating the economic impact of preterm birth at the community level can be used by any community in which vital statistics and population demographics are available. Cost estimates can serve to rally support for local stakeholder investment in developing strategies for preterm birth intervention leading to improved pregnancy outcomes.
To develop generalizable methods for estimating the economic impact of preterm birth at the community level on initial hospital expenditures, educational attainment and lost earnings as well as to estimate potential savings associated with reductions in preterm birth.
STUDY DESIGN:
The retrospective, population-based analysis used vital statistics and population demographics from Hamilton County, Ohio, USA, in 2012.
METHODS:
We adjusted previously reported, mean initial hospital cost estimates (stratified by each week of gestation) to 2012 dollars using national cost-to-charge ratios. Next, we calculated excess costs attributable to prematurity and potential hospital cost savings, which could be realized by prolonging each preterm pregnancy by a single week of gestation. Using reported associations among preterm birth, educational attainment and adult earnings, we developed generalizable formulas to calculate lost academic degrees and lost income estimates attributable to preterm birth. The formulas generated estimates based on local population demographics.
RESULTS:
The annual initial hospital cost associated with 1444 preterm infants was estimated at $93 million. In addition, over 9000 fewer college degrees and over $300 million in lost annual earnings were attributed to local adults who were born preterm. Prolonging each preterm birth by 1 week could potentially reduce initial hospital expenditures by over $25 million. Additional potential savings could be realized as healthier infants attain higher levels of education and earnings as adults.
CONCLUSIONS:
The generalizable methods developed for estimating the economic impact of preterm birth at the community level can be used by any community in which vital statistics and population demographics are available. Cost estimates can serve to rally support for local stakeholder investment in developing strategies for preterm birth intervention leading to improved pregnancy outcomes.
Research Interests:
OBJECTIVE: To better address barriers arising from missing and unreliable identifiers in neonatal medical records, we evaluated agreement and discordance among traditional and non-traditional linkage fields within a linked neonatal data... more
OBJECTIVE:
To better address barriers arising from missing and unreliable identifiers in neonatal medical records, we evaluated agreement and discordance among traditional and non-traditional linkage fields within a linked neonatal data set.
STUDY DESIGN:
The retrospective, descriptive analysis represents infants born from 2013 to 2015. We linked children's hospital neonatal physician billing records to newborn medical records originating from an academic delivery hospital and evaluated rates of agreement, discordance and missingness for a set of 12 identifier field pairs used in the linkage algorithm.
RESULTS:
We linked 7293 of 7404 physician billing records (98.5%), all of which were deemed valid upon manual review. Linked records contained a mean of 9.1 matching and 1.6 non-matching identifier pairs. Only 4.8% had complete agreement among all 12 identifier pairs.
CONCLUSION:
Our approach to selection of linkage variables and data formatting preparatory to linkage have generalizability, which may inform future neonatal and perinatal record linkage efforts.
To better address barriers arising from missing and unreliable identifiers in neonatal medical records, we evaluated agreement and discordance among traditional and non-traditional linkage fields within a linked neonatal data set.
STUDY DESIGN:
The retrospective, descriptive analysis represents infants born from 2013 to 2015. We linked children's hospital neonatal physician billing records to newborn medical records originating from an academic delivery hospital and evaluated rates of agreement, discordance and missingness for a set of 12 identifier field pairs used in the linkage algorithm.
RESULTS:
We linked 7293 of 7404 physician billing records (98.5%), all of which were deemed valid upon manual review. Linked records contained a mean of 9.1 matching and 1.6 non-matching identifier pairs. Only 4.8% had complete agreement among all 12 identifier pairs.
CONCLUSION:
Our approach to selection of linkage variables and data formatting preparatory to linkage have generalizability, which may inform future neonatal and perinatal record linkage efforts.
Research Interests:
STUDY OBJECTIVE: We evaluated the influence of home visiting on the risk for medically attended unintentional injury during home visiting (0 to 3 years) and subsequent to home visiting (3 to 5 years). METHODS: A retrospective,... more
STUDY OBJECTIVE:
We evaluated the influence of home visiting on the risk for medically attended unintentional injury during home visiting (0 to 3 years) and subsequent to home visiting (3 to 5 years).
METHODS:
A retrospective, quasi-experimental study was conducted in a cohort of mother-child pairs in Hamilton County, OH. The birth cohort (2006 to 2012) was linked to administrative home visiting records and data from a population-based injury surveillance system containing records of emergency department (ED) visits and hospitalizations. Cox proportional-hazard regression was used to compare medically attended unintentional injury risk (0 to 2, 0 to 3, and 3 to 5 years) in a home-visited group versus a propensity score-matched comparison group. The study population was composed of 2,729 mother-child pairs who received home visiting and 2,729 matched mother-child pairs in a comparison group.
RESULTS:
From birth to 2 years, 17.2% of the study population had at least one medically attended unintentional injury. The risk for medically attended unintentional injury from aged 0 to 2 and 0 to 3 years was significantly higher in the home-visited group relative to the comparison group (hazard ratio 1.17, 95% confidence interval 1.01 to 1.35; hazard ratio 1.15, 95% confidence interval 1.00 to 1.31, respectively). Additional injuries in the home-visited group were superficial, and the increased risk for medically attended unintentional injury was observed for ED visits and not hospitalizations.
CONCLUSION:
Home-visited children were more likely to have a medically attended unintentional injury from birth to aged 3 years. This finding may be partially attributed to home visitor surveillance of injuries or greater health care-seeking behavior. Implications and alternative explanations are discussed.
We evaluated the influence of home visiting on the risk for medically attended unintentional injury during home visiting (0 to 3 years) and subsequent to home visiting (3 to 5 years).
METHODS:
A retrospective, quasi-experimental study was conducted in a cohort of mother-child pairs in Hamilton County, OH. The birth cohort (2006 to 2012) was linked to administrative home visiting records and data from a population-based injury surveillance system containing records of emergency department (ED) visits and hospitalizations. Cox proportional-hazard regression was used to compare medically attended unintentional injury risk (0 to 2, 0 to 3, and 3 to 5 years) in a home-visited group versus a propensity score-matched comparison group. The study population was composed of 2,729 mother-child pairs who received home visiting and 2,729 matched mother-child pairs in a comparison group.
RESULTS:
From birth to 2 years, 17.2% of the study population had at least one medically attended unintentional injury. The risk for medically attended unintentional injury from aged 0 to 2 and 0 to 3 years was significantly higher in the home-visited group relative to the comparison group (hazard ratio 1.17, 95% confidence interval 1.01 to 1.35; hazard ratio 1.15, 95% confidence interval 1.00 to 1.31, respectively). Additional injuries in the home-visited group were superficial, and the increased risk for medically attended unintentional injury was observed for ED visits and not hospitalizations.
CONCLUSION:
Home-visited children were more likely to have a medically attended unintentional injury from birth to aged 3 years. This finding may be partially attributed to home visitor surveillance of injuries or greater health care-seeking behavior. Implications and alternative explanations are discussed.
Research Interests:
Objective Gastroschisis is a congenital defect in which the abdominal viscera herniate through the abdominal wall. In this population, antibiotics are often initiated immediately following delivery; however, this may be unnecessary as... more
Objective Gastroschisis is a congenital defect in which the abdominal viscera herniate through the abdominal wall. In this population, antibiotics are often initiated immediately following delivery; however, this may be unnecessary as infections typically develop as a consequence of chronic issues in gastroschisis. The objective of this study was to evaluate the incidence of culture positive early onset sepsis, the reliability of the immature to mature neutrophil count (I:T) ratio as an infectious biomarker, and antibiotic use in infants with gastroschisis.
Study Design This retrospective chart review analyzed clinical data from 103 infants with gastroschisis and 103 weight-matched controls that were evaluated for early onset infection.
Results Compared with the control group, there was a significantly increased percentage of infants with an I:T ratio > 0.2 in the gastroschisis group (43% vs. 12%, p < 0.001) and an increased percentage of infants exposed to greater than 5 days of antibiotics regardless of their I:T ratio (75% vs. 6%, p < 0.001). There were no episodes of culture positive early onset sepsis in either group.
Conclusion Our results indicate that I:T ratio is not a reliable marker of infection in gastroschisis, and suggest that empiric septic evaluation and antibiotic use, immediately following delivery in gastroschisis infants, may be unnecessary.
Study Design This retrospective chart review analyzed clinical data from 103 infants with gastroschisis and 103 weight-matched controls that were evaluated for early onset infection.
Results Compared with the control group, there was a significantly increased percentage of infants with an I:T ratio > 0.2 in the gastroschisis group (43% vs. 12%, p < 0.001) and an increased percentage of infants exposed to greater than 5 days of antibiotics regardless of their I:T ratio (75% vs. 6%, p < 0.001). There were no episodes of culture positive early onset sepsis in either group.
Conclusion Our results indicate that I:T ratio is not a reliable marker of infection in gastroschisis, and suggest that empiric septic evaluation and antibiotic use, immediately following delivery in gastroschisis infants, may be unnecessary.
Research Interests:
OBJECTIVE: The objective of this study was to evaluate the prevalence of late pregnancy nicotine exposures, including secondhand smoke exposures, and to evaluate the associated risk of exposure to drugs of abuse. STUDY DESIGN: The study... more
OBJECTIVE: The objective of this study was to evaluate the prevalence of late pregnancy nicotine exposures, including secondhand smoke exposures, and to evaluate the associated risk of exposure to drugs of abuse.
STUDY DESIGN: The study was a retrospective single-center cohort analysis of more than 18 months. We compared self-reported smoking status from vital birth records with mass spectrometry laboratory results of maternal urine using a chi-square test. Logistic regression estimated adjusted odds for detection of drugs of abuse based on nicotine detection.
RESULTS: Compared with 8.6% self-reporting cigarette use, mass spectrometry detected high-level nicotine exposures for 16.5% of 708 women (P<0.001) and an additional 7.5% with low-level exposures. We identified an increased likelihood of exposure to drugs of abuse, presented as adjusted odds ratios, (95% confidence interval (CI), for both low-level (5.69, CI: 2.09 to 15.46) and high-level (13.93, CI: 7.06 to 27.49) nicotine exposures.
CONCLUSION: Improved measurement tactics are critically needed to capture late pregnancy primary and passive nicotine exposures from all potential sources.
STUDY DESIGN: The study was a retrospective single-center cohort analysis of more than 18 months. We compared self-reported smoking status from vital birth records with mass spectrometry laboratory results of maternal urine using a chi-square test. Logistic regression estimated adjusted odds for detection of drugs of abuse based on nicotine detection.
RESULTS: Compared with 8.6% self-reporting cigarette use, mass spectrometry detected high-level nicotine exposures for 16.5% of 708 women (P<0.001) and an additional 7.5% with low-level exposures. We identified an increased likelihood of exposure to drugs of abuse, presented as adjusted odds ratios, (95% confidence interval (CI), for both low-level (5.69, CI: 2.09 to 15.46) and high-level (13.93, CI: 7.06 to 27.49) nicotine exposures.
CONCLUSION: Improved measurement tactics are critically needed to capture late pregnancy primary and passive nicotine exposures from all potential sources.
Research Interests:
Background Test the hypothesis that exposure to fine particulate matter in the air (PM2.5) is associated with increased risk of preterm birth (PTB). Methods Geo-spatial population-based cohort study using live birth records from Ohio... more
Background
Test the hypothesis that exposure to fine particulate matter in the air (PM2.5) is associated with increased risk of preterm birth (PTB).
Methods
Geo-spatial population-based cohort study using live birth records from Ohio (2007–2010) linked to average daily measures of PM2.5, recorded by 57 EPA network monitoring stations across the state. Geographic coordinates of the home residence for births were linked to the nearest monitoring station using ArcGIS. Association between PTB and high PM2.5 levels (above the EPA annual standard of 15 μg/m3) was estimated using GEE, with adjustment for age, race, education, parity, insurance, tobacco, birth season and year, and infant gender. An exchangeable correlation matrix for the monitor stations was used in the models. Analyses were limited to non-anomalous singleton births at 20-42weeks with no known chromosome abnormality occurring within 10 km of a monitor station.
Results
The frequency of PTB was 8.5 % in the study cohort of 224,921 singleton live births. High PM2.5 exposure (>EPA recommended maximum) occurred frequently during the study period, with 24,662 women (11 %) having high exposure in all three trimesters. Pregnancies with high PM2.5 exposure through pregnancy had increased PTB risk even after adjustment for coexisting risk factors, adjOR 1.19 (95 % CI 1.09–1.30). Assessed per trimester, high 3rd trimester PM2.5 exposure resulted in the highest PTB risk, adjOR 1.28 (95 % CI 1.20–1.37).
Conclusions
Exposure to high levels of particulate air pollution, PM2.5, in pregnancy is associated with a 19 % increased risk of PTB; with greatest risk with high 3rd trimester exposure. Although the risk increase associated with high PM2.5 levels is modest, the potential impact on overall PTB rates is robust as all pregnant women are potentially at risk. This exposure may in part contribute to the higher preterm birth rates in Ohio compared to other states in the US, especially in urban areas.
Test the hypothesis that exposure to fine particulate matter in the air (PM2.5) is associated with increased risk of preterm birth (PTB).
Methods
Geo-spatial population-based cohort study using live birth records from Ohio (2007–2010) linked to average daily measures of PM2.5, recorded by 57 EPA network monitoring stations across the state. Geographic coordinates of the home residence for births were linked to the nearest monitoring station using ArcGIS. Association between PTB and high PM2.5 levels (above the EPA annual standard of 15 μg/m3) was estimated using GEE, with adjustment for age, race, education, parity, insurance, tobacco, birth season and year, and infant gender. An exchangeable correlation matrix for the monitor stations was used in the models. Analyses were limited to non-anomalous singleton births at 20-42weeks with no known chromosome abnormality occurring within 10 km of a monitor station.
Results
The frequency of PTB was 8.5 % in the study cohort of 224,921 singleton live births. High PM2.5 exposure (>EPA recommended maximum) occurred frequently during the study period, with 24,662 women (11 %) having high exposure in all three trimesters. Pregnancies with high PM2.5 exposure through pregnancy had increased PTB risk even after adjustment for coexisting risk factors, adjOR 1.19 (95 % CI 1.09–1.30). Assessed per trimester, high 3rd trimester PM2.5 exposure resulted in the highest PTB risk, adjOR 1.28 (95 % CI 1.20–1.37).
Conclusions
Exposure to high levels of particulate air pollution, PM2.5, in pregnancy is associated with a 19 % increased risk of PTB; with greatest risk with high 3rd trimester exposure. Although the risk increase associated with high PM2.5 levels is modest, the potential impact on overall PTB rates is robust as all pregnant women are potentially at risk. This exposure may in part contribute to the higher preterm birth rates in Ohio compared to other states in the US, especially in urban areas.
Research Interests:
To describe use of the emergency department (ED) among late preterm versus term infants enrolled in a home visiting program and to determine whether home visiting frequency was associated with outcome differences. Retrospective, cohort... more
To describe use of the emergency department (ED) among late preterm versus term infants enrolled in a home visiting program and to determine whether home visiting frequency was associated with outcome differences. Retrospective, cohort study. Regional home visiting program in southwest Ohio from 2007–2010. Late preterm and term infants born to mothers enrolled in home visiting. Program eligibility requires ≥ one of four characteristics: unmarried, low income, < 18 years, or suboptimal prenatal care. Data were derived from vital statistics, hospital discharges, and home visiting records. Negative binomial regression was used to determine association of ED visits in the first year with late preterm birth and home visit frequency, adjusting for maternal and infant characteristics. Of 1,804 infants, 9.2% were born during the late preterm period. Thirty-eight percent of all infants had at least one ED visit, 15.6% had three or more. No significant difference was found between the numb...
Research Interests:
Efforts to study relationships between maternal airborne pollutant exposures and poor pregnancy outcomes have been frustrated by data limitations. Our objective was to report the proportion of Ohio women in 2006-2010 experiencing... more
Efforts to study relationships between maternal airborne pollutant exposures and poor pregnancy outcomes have been frustrated by data limitations. Our objective was to report the proportion of Ohio women in 2006-2010 experiencing stillbirth whose pregnancy exposure to six criteria airborne pollutants could be approximated by applying a geospatial approach to vital records and Environmental Protection Agency air monitoring data. In addition, we characterized clinical and socio-demographic differences among women who lived within 10 km of monitoring stations compared to women who did not live within proximity of monitoring stations. For women who experienced stillbirth, 10.8% listed a residence within 10 km of each type of monitoring station. Maternal race, education, and marital status were significantly different (p<0.0001) comparing those within proximity to monitoring stations to those outside of monitoring range. No significant differences were identified in maternal age, ethnicity, smoking status, hypertension, or diabetes between groups.
Research Interests:
Background Although electronic health records (EHRs) have the potential to provide a foundation for quality and safety algorithms, few studies have measured their impact on automated adverse event (AE) and medical error (ME) detection... more
Background Although electronic health records (EHRs)
have the potential to provide a foundation for quality
and safety algorithms, few studies have measured their
impact on automated adverse event (AE) and medical
error (ME) detection within the neonatal intensive care
unit (NICU) environment.
Objective This paper presents two phenotyping AE
and ME detection algorithms (ie, IV infiltrations, narcotic
medication oversedation and dosing errors) and
describes manual annotation of airway management and
medication/fluid AEs from NICU EHRs.
Methods From 753 NICU patient EHRs from 2011,
we developed two automatic AE/ME detection
algorithms, and manually annotated 11 classes of AEs in
3263 clinical notes. Performance of the automatic AE/
ME detection algorithms was compared to trigger tool
and voluntary incident reporting results. AEs in clinical
notes were double annotated and consensus achieved
under neonatologist supervision. Sensitivity, positive
predictive value (PPV), and specificity are reported.
Results Twelve severe IV infiltrates were detected. The
algorithm identified one more infiltrate than the trigger
tool and eight more than incident reporting. One
narcotic oversedation was detected demonstrating 100%
agreement with the trigger tool. Additionally, 17
narcotic medication MEs were detected, an increase of
16 cases over voluntary incident reporting.
Conclusions Automated AE/ME detection algorithms
provide higher sensitivity and PPV than currently used
trigger tools or voluntary incident-reporting systems,
including identification of potential dosing and frequency
errors that current methods are unequipped to detect.
have the potential to provide a foundation for quality
and safety algorithms, few studies have measured their
impact on automated adverse event (AE) and medical
error (ME) detection within the neonatal intensive care
unit (NICU) environment.
Objective This paper presents two phenotyping AE
and ME detection algorithms (ie, IV infiltrations, narcotic
medication oversedation and dosing errors) and
describes manual annotation of airway management and
medication/fluid AEs from NICU EHRs.
Methods From 753 NICU patient EHRs from 2011,
we developed two automatic AE/ME detection
algorithms, and manually annotated 11 classes of AEs in
3263 clinical notes. Performance of the automatic AE/
ME detection algorithms was compared to trigger tool
and voluntary incident reporting results. AEs in clinical
notes were double annotated and consensus achieved
under neonatologist supervision. Sensitivity, positive
predictive value (PPV), and specificity are reported.
Results Twelve severe IV infiltrates were detected. The
algorithm identified one more infiltrate than the trigger
tool and eight more than incident reporting. One
narcotic oversedation was detected demonstrating 100%
agreement with the trigger tool. Additionally, 17
narcotic medication MEs were detected, an increase of
16 cases over voluntary incident reporting.
Conclusions Automated AE/ME detection algorithms
provide higher sensitivity and PPV than currently used
trigger tools or voluntary incident-reporting systems,
including identification of potential dosing and frequency
errors that current methods are unequipped to detect.
Research Interests:
In recent years, the U.S. has experienced a significant increase in the prevalence of pregnant opioid-dependent women and of neonatal abstinence syndrome (NAS), which is caused by withdrawal from in-utero drug exposure. While... more
In recent years, the U.S. has experienced a significant increase in the prevalence of pregnant opioid-dependent women and of neonatal abstinence syndrome (NAS), which is caused by withdrawal from in-utero drug exposure. While methadone-maintenance currently is the standard of care for opioid dependence during pregnancy, research suggests that buprenorphine-maintenance may be associated with shorter infant hospital lengths of stay (LOS) relative to methadone-maintenance. There is no "gold standard" treatment for NAS but there is evidence that buprenorphine, relative to morphine or methadone, treatment may reduce LOS and length of treatment. Point-of-care clinical trial (POCCT) designs, maximizing external validity while reducing cost and complexity associated with classic randomized clinical trials, were selected for two planned trials to compare methadone to buprenorphine treatment for opioid dependence during pregnancy and for NAS. This paper describes design consideratio...
Research Interests:
Research Interests:
To demonstrate a generalizable approach for developing maternal-child health data resources using state administrative records and community-based program data. We used a probabilistic and deterministic linking strategy to join vital... more
To demonstrate a generalizable approach for developing maternal-child health data resources using state administrative records and community-based program data. We used a probabilistic and deterministic linking strategy to join vital records, hospital discharge records, and home visiting data for a population-based cohort of at-risk, first time mothers enrolled in a regional home visiting program in Southwestern Ohio and Northern Kentucky from 2007 to 2010. Because data sources shared no universal identifier, common identifying elements were selected and evaluated for discriminating power. Vital records then served as a hub to which other records were linked. Variables were recoded into clinically significant categories and a cross-set of composite analytic variables was constructed. Finally, individual-level data were linked to corresponding area-level measures by census tract using the American Communities Survey. The final data set represented 2,330 maternal-infant pairs with both home visiting and vital records data. Of these, 56 pairs (2.4 %) did not link to either maternal or infant hospital discharge records. In a 10 % validation subset (n = 233), 100 % of the reviewed matches between home visiting data and vital records were true matches. Combining multiple data sources provided more comprehensive details of perinatal health service utilization and demographic, clinical, psychosocial, and behavioral characteristics than available from a single data source. Our approach offers a template for leveraging disparate sources of data to support a platform of research that evaluates the timeliness and reach of home visiting as well as its association with key maternal-child health outcomes.
Research Interests:
BACKGROUND AND OBJECTIVE: Home visiting programs seek to improve care management for women at high risk for preterm birth (<37 weeks). Our objective was to evaluate the effect of home visiting dosage on preterm birth and small for... more
BACKGROUND AND OBJECTIVE:
Home visiting programs seek to improve care management for women at high risk for preterm birth (<37 weeks). Our objective was to evaluate the effect of home visiting dosage on preterm birth and small for gestational age (SGA) infants.
METHODS:
Retrospective cohort study of women in southwest Ohio with a singleton pregnancy enrolled in home visiting before 26 weeks’ gestation. Vital statistics and hospital discharge data were linked with home visiting data from 2007 to 2010 to ascertain birth outcomes. Eligibility for home visiting required ≥1 of 4 risk factors: unmarried, low income, <18 years of age, or suboptimal prenatal care. Logistic regression tested the association of gestational age at enrollment and number of home visits before 26 weeks with preterm birth. Proportional hazards analysis tested the association of total number of home visits with SGA status.
RESULTS:
Among 441 participants enrolled by 26 weeks, 10.9% delivered preterm; 17.9% of infants were born SGA. Mean gestational age at enrollment was 18.9 weeks; mean number of prenatal home visits was 8.2. In multivariable regression, ≥8 completed visits by 26 weeks compared with ≤3 visits was associated with an odds ratio 0.38 for preterm birth (95% confidence interval: 0.16–0.87), while having ≥12 total home visits compared with ≤3 visits was significantly associated with a hazards ratio 0.32 for SGA (95% confidence interval: 0.15–0.68).
CONCLUSIONS:
Among at-risk, first time mothers enrolled prenatally in home visiting, higher dosage of intervention is associated with reduced likelihood of adverse pregnancy outcomes.
Home visiting programs seek to improve care management for women at high risk for preterm birth (<37 weeks). Our objective was to evaluate the effect of home visiting dosage on preterm birth and small for gestational age (SGA) infants.
METHODS:
Retrospective cohort study of women in southwest Ohio with a singleton pregnancy enrolled in home visiting before 26 weeks’ gestation. Vital statistics and hospital discharge data were linked with home visiting data from 2007 to 2010 to ascertain birth outcomes. Eligibility for home visiting required ≥1 of 4 risk factors: unmarried, low income, <18 years of age, or suboptimal prenatal care. Logistic regression tested the association of gestational age at enrollment and number of home visits before 26 weeks with preterm birth. Proportional hazards analysis tested the association of total number of home visits with SGA status.
RESULTS:
Among 441 participants enrolled by 26 weeks, 10.9% delivered preterm; 17.9% of infants were born SGA. Mean gestational age at enrollment was 18.9 weeks; mean number of prenatal home visits was 8.2. In multivariable regression, ≥8 completed visits by 26 weeks compared with ≤3 visits was associated with an odds ratio 0.38 for preterm birth (95% confidence interval: 0.16–0.87), while having ≥12 total home visits compared with ≤3 visits was significantly associated with a hazards ratio 0.32 for SGA (95% confidence interval: 0.15–0.68).
CONCLUSIONS:
Among at-risk, first time mothers enrolled prenatally in home visiting, higher dosage of intervention is associated with reduced likelihood of adverse pregnancy outcomes.
Research Interests:
Using vital records and census data representing 165,136 singleton births from 2003-2006, geospatial filtering and density estimates enabled the calculation of preterm birth rates at each geographical point within three urban Ohio... more
Using vital records and census data representing 165,136 singleton births from 2003-2006, geospatial filtering and density estimates enabled the calculation of preterm birth rates at each geographical point within three urban Ohio counties. Adjusted attributable risk calculations were used to identify risk factors associated with regions of high and low rates of preterm birth. Among the three counties, affected populations varied in size as well as in demographic composition. Variation in the risk factors from one region to another suggests that a single one size fits all intervention strategy would be unlikely to efficiently or effectively impact the complex preterm birth problem. Although more useful in areas with a heterogeneous distribution of preterm birth, application of the presented approach supports the development of efficient community-level health intervention strategies by identifying communities with the highest potential impact and allowing for the prioritization of efforts on specific risk factors within those communities.
Research Interests:
This paper presents methods for identifying and analyzing associations among nursing care processes, patient attributes, and patient outcomes using unit-level and patient-level representations of care derived from computerized nurse... more
This paper presents methods for identifying and analyzing associations among nursing care processes, patient attributes, and patient outcomes using unit-level and patient-level representations of care derived from computerized nurse documentation. The retrospective, descriptive analysis included documented nursing events for 900 Labor and Delivery patients at three hospitals over the 2-month period of January and February 2006. Two models were used to produce quantified measurements of nursing care received by each patient. The first model considered only the hourly census of nurses and patients. The second model considered the size of nurses' patient loads as represented by computerized nurse-entered documentation. Significant relationships were identified between durations of labor and nursing care scores generated by the second model. In addition to the clinical associations identified, the study demonstrated an approach with global application for representing the amount of nursing care received at the individual patient level in analyses of patient outcomes.
Research Interests:
Our study objectives included the development and evaluation of models for representing the distribution of shared unit-wide nursing care resources among individual Labor and Delivery patients using quantified measurements of nursing... more
Our study objectives included the development and evaluation of models for representing the distribution of shared unit-wide nursing care resources among individual Labor and Delivery patients using quantified measurements of nursing care, referred to as Nursing Effort. The models were intended to enable discrimination between the amounts of care delivered to patient subsets defined by attributes such as patient acuity. For each of five proposed models, scores were generated using an analysis set of 686,402 computerized nurse-documented events associated with 1,093 patients at three hospitals during January and February 2006. Significant differences were detected in Nursing Effort scores according to patient acuity, care facility, and in scores generated during shift-change versus non shift-change hours. The development of nursing care quantification strategies proposed in this study supports outcomes analysis by establishing a foundation for measuring the effect of patient-level nursing care on individual patient outcomes.
Research Interests:
This paper presents methods for generating nurse profiles using computerized documentation. NuProGen (Nurse Profile Generator), a custom-built knowledge discovery tool, enabled profile generation by calculating the numbers of various... more
This paper presents methods for generating nurse profiles using computerized documentation. NuProGen (Nurse Profile Generator), a custom-built knowledge discovery tool, enabled profile generation by calculating the numbers of various complicated patient cases (including high body mass index, bleeding, and multiple gestation) managed by each of 91 Labor and Delivery nurses at a single Intermountain Healthcare facility during the 3-month study period of January through March 2007. The tool identified patterns of documentation recorded by each nurse, as well as nursing care patterns associated with each of the three patient conditions examined in the study. Individual nurse profiles supported identification of expert and novice nurses corresponding to the management of specific conditions. A discussion of the benefits provided by available nurse profile data is also presented.