Predictive Factors for Loss to Postpartum Follow-Up Among Low Income HIV-Infected Women in Texas

Self Cite

Optimal retention in HIV care postpartum is necessary to benefit the health and wellbeing of mothers and their infants. However, postpartum retention in HIV care among low-income women is suboptimal, particularly in the Southern United States. A mixed-methods study was conducted to identify factors associated with postpartum retention in care among HIV-infected women. Participants (n = 35) were recruited during pregnancy at two county clinics and completed self-report demographic and psychosocial surveys. Twenty-two women who returned for a postpartum appointment completed a semi-structured interview about lifestyle factors and retention in care. Of the participants enrolled at baseline, 71.4% completed a follow-up with an obstetrician (OB), while 57.1% completed a follow-up with a primary care physician (PCP). High CD4 count at delivery, low viral load at baseline, low levels of depression, high interpersonal social support, and fewer other children were significantly associated with completion of postpartum follow-up. Barriers and facilitators to retention identified during qualitative interviews included competing responsibilities for time, lack of social support outside of immediate family members, limited transportation access, experiences of institutionalized stigma, knowledge about the benefits of adherence, and strong relationships with healthcare providers. OB and PCP follow-up postpartum was suboptimal in this sample. Findings underscore the importance of addressing depressive symptoms, social support, viral suppression, competing responsibilities for time, institutionalized stigma, and transportation issues in order to reduce the barriers that inhibit women from seeking postpartum HIV care.

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confidence: 52%

Section: Postpartum Care Of Hiv Infection 129mentioning

confidence: 99%

A Mixed-Methods Approach to Understanding Barriers to Postpartum Retention in Care Among Low-Income, HIV-Infected Women

Buchberg

Fletcher

Vidrine

et al. 2015

Self Cite

“…10,14,16,33 The association between race and appointment attendance could be explained by potential unmeasured mediators such as socioeconomic status, lack of transportation, proximity to health care centers, challenges navigating the healthcare system, geographic mobility, point of HIV-infection identification, pregnancy, and aspects of the patient-provider relationship. 10,[34][35][36][37][38][39][40] Additionally, factors more unique to patients with HIV-infection, including stigma and HIV status disclosure, are known to affect appointment attendance. 41 These factors are not routinely measured as part of clinical care and would be difficult to operationalize.…”

Section: Discussionmentioning

confidence: 99%

Risk Prediction Tool for Medical Appointment Attendance Among HIV-Infected Persons with Unsuppressed Viremia

Woodward

Person²,

Rebeiro³

et al. 2015

Successful treatment of HIV infection requires regular clinical follow-up. A previously published risk-prediction tool (RPT) utilizing data from the electronic health record (EHR) including medication adherence, previous appointment attendance, substance abuse, recent CD4 + count, prior antiretroviral therapy (ART) exposure, prior treatment failure, and recent HIV-1 viral load (VL) has been shown to predict virologic failure at 1 year. If this same tool could be used to predict the more immediate event of appointment attendance, high-risk patients could be identified and interventions could be targeted to improve this outcome. We conducted an observational cohort study at the Vanderbilt Comprehensive Care Clinic from August 2013 through March 2014. Patients with routine medical appointments and most recent HIV-1 VL > 200 copies/mL were included. Risk scores for a modified RPT were calculated based on data from the EHR. Odds ratios (OR) for missing the next appointment were estimated using multivariable logistic regression. Among 510 persons included, median age was 39 years, 74% were male, 55% were black, median CD4 + count was 327 cells/mm 3 [Interquartile Range (IQR): 142-560], and median HIV-1 VL was 21,818 copies/mL (IQR: 2,030-69,597). Medium [OR 3.95, 95% confidence interval (CI) 2.08-7.50, p-value < 0.01] and high (OR 9.55,, p-value < 0.01) vs. low RPT risk scores were independently associated with missing the next appointment. RPT scores, constructed using readily available data, allow for risk-stratification of HIV medical appointment non-attendance and could support targeting limited resources to improve appointment adherence in groups most at-risk of poor HIV outcomes.

“…However, research suggests that pregnancy may represent the best time to educate HIV-infected women about health management 30 due to lack of adherence to antiretroviral medications 31 and loss to follow-up of primary care following childbirth. 30 Nevertheless, these findings underscore the importance of evaluating the impact of health status on stress burden and vice versa in high risk populations.…”

Section: Discussionmentioning

confidence: 99%

Improving Parental Stress Levels Among Mothers Living with HIV: A Randomized Control Group Intervention Study

Johnson

Davies

Aban

et al. 2015

Limited knowledge exists regarding parenting efficacy interventions for mothers living with HIV (MLH). This study evaluated the impact of a supportive group intervention on lowering parenting stress among MLH. Eighty MLH were randomized to a parenting (N=34) or health focused (control) (N=46) group intervention. Pre- and post-intervention stress levels were assessed using the Parental Stress Index-Short Form (PSI/SF). Differences in PSI/SF scores were examined using ANOVA, and predictors of PSI/SF scores were evaluated using multivariable linear regression. Findings indicate that both groups experienced significant decreases in parenting stress from baseline to post-intervention (p=0.0001), with no significant differences between interventions. At baseline, 41% of participants were identified as highly stressed and 30% as clinically stressed, with PSI/SF scores above the 85(th) and 90(th) percentile, respectively. Amongst the highly stressed subpopulation, significant improvements in PSI/SF scores for Parental Distress PSI/SF (p=0.039), Difficult Child PSI/SF (p=0.048), and total PSI/SF (p=0.036) were seen, with greater improvements in the parenting intervention. Among the clinically stressed subpopulation, significant improvements in total post-intervention PSI/SF scores were seen (p=0.049), with greater improvements in the parenting intervention. Results indicate that screening for high levels of stress should be considered in clinical practice to effectively implement stress-reducing interventions among MLH.