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$18.75/hour including benefits, which resulted in $1,500 in train‐ ing or approximately $37.50 per intervention participant. Similarly, participant outreach by the CHW was estimated to cost $213.75 per intervention participant. Finally, the average cost of providing a smartphone to participants was estimated at $20 per month. Based on these data, we performed return on investment (ROI) analysis stratified by two scenarios, where the provision of a smart‐ phone was not included (due to the high participant ownership of smartphone). Option #1 assumed that the only intervention cost was the PTP, which was calculated to be $27 per participant. Option #2 incorporated the CHW training in addition to the PTP as well as the CHW cost of participant outreach totaling $251.25 per participant (Table 2). We calculated average differences in inpatient costs between intervention and control groups in addition to cost differences after adjusting for outliers (highest 5% of charges) and selected pa‐ tient characteristics (patient age in years, primary payer (Medicaid, Blue Cross/Blue Shield, other commercial insurance, self‐pay), and cesarean vs. vaginal delivery). Adjustments were based on multi‐ variable regression analysis. The average overall difference in costs totaled $1,079 savings for intervention participants compared to the controls. Excluding outlier patients, the average difference in costs was $1,547 savings between intervention and control groups. This decreased to a $529 savings for the intervention group after adjusting for age, primary payer, and cesarean section. Therefore, we estimated ROI by this range of cost savings, that is, $529, $1,079, and $1,547. This range provides information on the sensitivity of ROI to substantial differences in program health care cost savings. Utilizing the above data on inpatient cost in addition to the two op‐ tions described above concerning anticipated program costs per par‐ ticipant, returns are highest for option #1 (1859%) because of the low per member per month cost of providing the PTP with chat enabled. However, even after including all cost components (PTP, CHW train‐ ing, and CHW participant outreach), ROI is estimated at 90% showing either option presents a good ROI and increase in health care savings.
effectiveness. Intervention participants showed higher increases in their patient activation (PAM), and they were satisfied with interven‐ tion participation. Participants were actively engaged with the CHW and used the PTP as evidenced by the number of hyperlinks, chats, and phone calls. Participants valued the personalized aspects of the intervention, and all offered positive comments on the intervention. Further research is needed to determine the extent of the promise for the use of both smartphones and CHWs toward improving birth outcomes. Our study showed that the intervention had significant cost savings. The ROI analysis suggests that an intervention that utilizes the PTP with CHW reinforcement is likely to be cost‐effective and financially sustainable. Depending on the scenario, the ROI for the intervention ranged from 90% to over 1859%. While the reasons for these cost savings are not clear, possible reasons could include the improved patient activation scores associated with the inter‐ vention group. Research shows that patient activation is associated with reduced health care costs (Hibbard et al., 2016) and has been shown to accurately predict the use of costly services in patients up to 4 years (Hibbard, Green, Shi, Mittler, & Scanlon, 2015). Based on nonresponses to some PAM questions regarding “health problems,” and even though emerging research shows increased PAM scores may associate with improved pregnancy experience and increased vagi‐ nal delivery rate (Ledford et al., 2018), further research is needed on the PAM as a measurement tool in pregnant patients. Additionally, more research is required to establish the link between mobile tech‐ nology and CHW reinforcement on patient activation in a prenatal population. Our feasibility findings contribute to a better understanding of intervention delivery and sampling issues as well as the appro‐ priateness of impact measures in rural populations—all of which are essential for larger scale studies (Thabane et al., 2010; Conn, Algase, Rawl, Zerwic, & Wyman, 2011). Our study outcome results show promising trends for the intervention to improve patient communication and promote self‐care competence during preg‐ nancy. These findings are consistent with recent research show‐ ing mobile phones to be an emerging health technology that can positively modify health behaviors (Abroms et al., 2015; Muench & Baumel, 2017; Singh et al., 2016). Additional research is needed that includes more at‐risk participants who can benefit from the intervention and a larger sample to draw conclusions about inter‐ vention effectiveness and financial implications compared to usual prenatal care. 4.1 | Limitations The small sample size and the low‐risk population were signifi‐ cant limitations, although appropriate for a pilot feasibility study ((Lancaster et al., 2004; Lee et al., 2014; Thabane et al., 2010). An unexpected limitation was the study bias introduced when clinic staff changed clinical practices, and some clinics hiring CHWs unre‐ lated to our study. The limitations of our financial analysis are based on restricting the cost data to hospital billing charges.
4 | DISCUSSION
We conducted a pilot feasibility study using the PTP intervention that leveraged smartphone technology and CHW reinforcement to promote prenatal self‐care among rural women. Feasibility studies help research‐ ers determine whether a study is likely to be delivered successfully, while considering the practical aspects and challenges of the project. Despite numerous study difficulties with recruitment and enrollment and the change in clinical practices and potential placebo effect that may have impacted our control group, the PTP appeared to our research team to be a feasible and cost‐effective intervention. Considering some of the below recommendations, we believe that this study could be conducted on a larger, fully powered scale. The intervention showed promise for improving health out‐ comes in participants but needs a larger sample size to determine
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