Evaluation of Telehealth Use in Prenatal Care for Patient and Provider Satisfaction: A Step Toward Reducing Barriers to Care

Telehealth Use by Pregnancy Stage Among Commercially Insured Patients in the United States, 2016-2019

Introduction: Relatively little is known about the proportion of maternal health services utilized through telehealth and whether rural-urban disparities in telehealth use exist throughout antenatal, delivery, and postpartum phases of maternal services. In this study, we describe patterns of care, including telehealth utilization, by rurality and racial/ethnic composition of the health service area during the antenatal, labor/delivery, and postpartum stages of pregnancy among commercially insured patients between 2016 and 2019. Methods: We present univariate and comparative descriptive statistics of patient and facility characteristics and site of care by the degree of rurality and racial/ethnic composition of the health service area (defined as geozips). The individual-level utilization data for 238,695 patients were aggregated to the geo-zip level (n = 404). Results: Between 2016 and 2019, 3.5% of pregnancy, delivery, and postpartum-related visits among commercially insured patients were delivered through telehealth. Telehealth use was higher in the antenatal (3.5% of claim lines) and postpartum (4.1% of claim lines) periods, compared with labor and delivery (0.7% of claim lines). We also found that the proportion of telehealth services (of total services billed) increased with the share of Black and Latinx residents at the geozip level. Discussion: Our findings highlight disparities in telehealth use, consistent with findings from studies using different data sources and time periods. Future research is needed to examine whether the relative differences in proportion of telehealth services, even if small, are associated with telehealth capacity in the hospital or community and why the proportion of telehealth services differs across community-level characteristics, specifically rurality and proportion of Black and Latinx residents.

Patient engagement practice within perinatal eHealth: A scoping review

BACKGROUND

There is a gap in knowledge about how perinatal eHealth programs function to support autonomy for new and expectant parents from pursuing wellness goals.

OBJECTIVES

To examine patient engagement (access, personalization, commitment and therapeutic alliance) within the practice of perinatal eHealth.

DESIGN

Scoping review.

METHODS

Five databases were searched in January 2020 and updated in April 2022. Reports were vetted by three researchers and included if they documented maternity/neonatal programs and utilized World Health Organization (WHO) person-centred digital health intervention (DHI) categories. Data were charted using a deductive matrix containing WHO DHI categories and patient engagement attributes. A narrative synthesis was conducted utilizing qualitative content analysis. Preferred Reporting Items for Systematic Reviews and Meta-Analyses 'extension for scoping reviews' guidelines were followed for reporting.

RESULTS

Twelve eHealth modalities were found across 80 included articles. The analysis yielded two conceptual insights: (1) The nature of perinatal eHealth programs: (1) emergence of a complex structure of practice and (2) practising patient engagement within perinatal eHealth.

CONCLUSION

Results will be used to operationalize a model of patient engagement within perinatal eHealth.

Effect of Remote Peer-Counsellor- delivered Behavioral Activation and Peer-support for Antenatal Depression on Gestational Age at Delivery: a single-blind, randomized control trial

BACKGROUND

Antenatal depression (AD) is the most common complication of pregnancy in developed countries and increases the risk of preterm birth (PTB). Many pregnant individuals with AD do not obtain treatment due in part to risks associated with antidepressant medications, the expense and wait times for psychological services, and perceived stigma. Accessible and timely treatment of antenatal depression is crucial to minimize foetal impacts and associated long-term child health outcomes. Previous studies show that behavioural activation and peer support are promising avenues of treatment for perinatal depression. Additionally, remote and paraprofessional counselling interventions show promise as more accessible, sustainable, and cost-effective treatment avenues than traditional psychological services. The primary aim of this trial is to test the effectiveness of a remote, behavioural activation and peer support intervention, administered by trained peer para-professionals, for increasing gestational age at delivery among those with antenatal depression. The secondary aims are to evaluate the effectiveness for treating AD prior to delivery, with persistence into the postpartum; improving anxiety symptoms; and improving parenting self-efficacy compared to controls.

METHODS

A two-arm, single-blinded, parallel groups randomized controlled trial (RCT) with repeated measures will be conducted. Participants scoring >10 on the Edinburgh Postnatal Depression Scale will be recruited from the larger P3 cohort and invited to enroll. Assessments will be conducted prior to 27 weeks' gestation at trial intake (T1), post-intervention, prior to delivery (T2), 5-6 months postpartum (T3), and 11-12 months postpartum (T4) and will include self-report questionnaires and linked medical records.

DISCUSSION

Our remote, peer paraprofessional-delivered behavioural activation plus peer support intervention has the potential to successfully reduce symptoms of AD, which may in turn decrease the risk of PTB and subsequent health impacts. The current trial builds on previous findings and uses a patient-oriented approach to address priorities for patient care and to provide a cost-effective, accessible, and evidence-based treatment to pregnant individuals with AD.

TRIAL REGISTRATION

International Standard Randomised Controlled Trial Number (ISRCTN) registry (ISRCTN51098220) ISRCTN51098220. Registered on April 7, 2022.

Gestational age assessed by optical skin reflection in low-birth-weight newborns: Applications in classification at birth

Introduction

A new medical device was previously developed to estimate gestational age (GA) at birth by processing a machine learning algorithm on the light scatter signal acquired on the newborn's skin. The study aims to validate GA calculated by the new device (test), comparing the result with the best available GA in newborns with low birth weight (LBW).

Methods

We conducted a multicenter, non-randomized, and single-blinded clinical trial in three urban referral centers for perinatal care in Brazil and Mozambique. LBW newborns with a GA over 24 weeks and weighing between 500 and 2,500 g were recruited in the first 24 h of life. All pregnancies had a GA calculated by obstetric ultrasound before 24 weeks or by reliable last menstrual period (LMP). The primary endpoint was the agreement between the GA calculated by the new device (test) and the best available clinical GA, with 95% confidence limits. In addition, we assessed the accuracy of using the test in the classification of preterm and SGA. Prematurity was childbirth before 37 gestational weeks. The growth standard curve was Intergrowth-21st, with the 10th percentile being the limit for classifying SGA.

Results

Among 305 evaluated newborns, 234 (76.7%) were premature, and 139 (45.6%) were SGA. The intraclass correlation coefficient between GA by the test and reference GA was 0.829 (95% CI: 0.785-0.863). However, the new device (test) underestimated the reference GA by an average of 2.8 days (95% limits of agreement: -40.6 to 31.2 days). Its use in classifying preterm or term newborns revealed an accuracy of 78.4% (95% CI: 73.3-81.6), with high sensitivity (96.2%; 95% CI: 92.8-98.2). The accuracy of classifying SGA newborns using GA calculated by the test was 62.3% (95% CI: 56.6-67.8).

Discussion

The new device (test) was able to assess GA at birth in LBW newborns, with a high agreement with the best available GA as a reference. The GA estimated by the device (test), when used to classify newborns on the first day of life, was useful in identifying premature infants but not when applied to identify SGA infants, considering current algohrithm. Nonetheless, the new device (test) has the potential to provide important information in places where the GA is unknown or inaccurate.

Newborn Skin Maturity Medical Device Validation for Gestational Age Prediction: Clinical Trial

Background

Early access to antenatal care and high-cost technologies for pregnancy dating challenge early neonatal risk assessment at birth in resource-constrained settings. To overcome the absence or inaccuracy of postnatal gestational age (GA), we developed a new medical device to assess GA based on the photobiological properties of newborns’ skin and predictive models.

Objective

This study aims to validate a device that uses the photobiological model of skin maturity adjusted to the clinical data to detect GA and establish its accuracy in discriminating preterm newborns.

Methods

A multicenter, single-blinded, and single-arm intention-to-diagnosis clinical trial evaluated the accuracy of a novel device for the detection of GA and preterm newborns. The first-trimester ultrasound, a second comparator ultrasound, and data regarding the last menstrual period (LMP) from antenatal reports were used as references for GA at birth. The new test for validation was performed using a portable multiband reflectance photometer device that assessed the skin maturity of newborns and used machine learning models to predict GA, adjusted for birth weight and antenatal corticosteroid therapy exposure.

Results

The study group comprised 702 pregnant women who gave birth to 781 newborns, of which 366 (46.9%) were preterm newborns. As the primary outcome, the GA as predicted by the new test was in line with the reference GA that was calculated by using the intraclass correlation coefficient (0.969, 95% CI 0.964-0.973). The paired difference between predicted and reference GAs was −1.34 days, with Bland-Altman limits of −21.2 to 18.4 days. As a secondary outcome, the new test achieved 66.6% (95% CI 62.9%-70.1%) agreement with the reference GA within an error of 1 week. This agreement was similar to that of comparator-LMP-GAs (64.1%, 95% CI 60.7%-67.5%). The discrimination between preterm and term newborns via the device had a similar area under the receiver operating characteristic curve (0.970, 95% CI 0.959-0.981) compared with that for comparator-LMP-GAs (0.957, 95% CI 0.941-0.974). In newborns with absent or unreliable LMPs (n=451), the intent-to-discriminate analysis showed correct preterm versus term classifications with the new test, which achieved an accuracy of 89.6% (95% CI 86.4%-92.2%), while the accuracy for comparator-LMP-GA was 69.6% (95% CI 65.3%-73.7%).

Conclusions

The assessment of newborn’s skin maturity (adjusted by learning models) promises accurate pregnancy dating at birth, even without the antenatal ultrasound reference. Thus, the novel device could add value to the set of clinical parameters that direct the delivery of neonatal care in birth scenarios where GA is unknown or unreliable.

International Registered Report Identifier (IRRID)

RR2-10.1136/bmjopen-2018-027442

Telehealth to Improve Perinatal Care Access

ABSTRACT

The United States has the worst maternal mortality rate of peer countries. Since 1935, the maternal mortality risk among Black women has remained three to four times higher than that of White women. Perinatal health care is not available in all areas, which limits the access for certain groups. Many women in the United States live in maternity care deserts with no access to obstetric providers, whereas others live in areas with very limited access. One way to bridge the gap between effective perinatal care and access to care is use of telehealth. Telehealth allows health care providers to communicate directly with patients that cannot physically be seen in a clinic or hospital. Telehealth is endorsed by the American College of Obstetricians and Gynecologists as an alternate mode to deliver prenatal and postpartum services. The potential for telehealth services as part of perinatal care to reduce maternal and neonatal morbidity and mortality by improving access to care is presented.