6 |
CRAMER et al .
participant receptivity to the intervention was the percentage of hyperlink hits that occurred primarily during the first months after enrollment (Figure 1). Again, English‐only speaking participants were more likely to hit the hyperlinks. Finally, the CHW had fre‐ quent telephone calls ( n = 210) with the 41 participants, and the majority ( N = 203 calls) involved medical appointment reminders. The average number of calls was 5.83 per participant, with a range of 1–10 per participant. The CHW successfully resolved 97% of participant issues by phone and the focus was mainly on preparing participants for office visits. Enactment of intervention Three issues affected intervention enactment (1) loaning smart‐ phones to participants, (2) issues with clinical partners, and (3) a placebo effect. We learned during the study that most participants (86%) already owned a smartphone, had unlimited texting (86%), and at‐home Wi‐Fi (65%). Thus, participants said that it had been inconvenient to carry two phones (both theirs and the study phone). Participants sometimes forgot to carry the study phone and check intervention messages. Some of the provided phones transmitted errant spam messages from old phone numbers causing participants to turn off their phones for a week or more. The spam problem was resolved after several weeks. Issues with clinical partners included getting provider buy in and changes in clinical practice after initiation of the study. Although we had the support of the community advisory board, and many clinical providers not all providers were motivated to refer patients. The diaper incentive, which was unsuccessful at promoting enroll‐ ment of participants, did increase referrals, making us believe that further incentives for patients or even for clinicians may have in‐ creased motivation to refer patients to participate in the study. An additional issue was when clinic partners altered their “usual med‐ ical care” during the study by (1) hiring a CHW and/or (2) changing clinical practices (e.g., greater attention to missed appointments, increasing patient education). These changes may have skewed re‐ sults of the study design and impacted the control group which was recruited last and most likely to benefit from the deviation from usual medical care that had been established before the study. Finally, there may have been a placebo effect among the con‐ trol group based on control group participants who commented on the CSQ‐8 that they enjoyed the “program,” the “home visits,” and the “information” provided during the study. It is possible that these comments reflect that at least some in the control group may have believed the informational packets and two CHW home visits for data collection constituted the study “treatment.”
3.2.4 | Promise of intervention Since pilot studies are not designed to assess evidence of benefit for‐ mally and are, in general, underpowered to achieve statistical significance at the 5% level (Lancaster, Dodd, & Williamson, 2004; Lee, Whitehead, Jacques, & Julious, 2014; Thabane et al., 2010), as was the case in our study. We analyzed descriptive statistics to report on the appropriate‐ ness and promise of the intervention for improving outcomes (Table 1). In this study, the intervention group had more full‐term deliveries (97.5%) than the control group (94.6%). The intervention group also had slightly longer average weeks gestation ( M = 39.43, SD = 1.1) versus the control group ( M = 39.13, SD = 1.6). The intervention group had slightly more normal birth weight infants (97.5%) versus the control group (97.3%). We also measured whether the intervention would result in greater pre‐post PAM scores, and results showed that the intervention group had a greater increase in PAM scores than the control group. Individual analysis of the PAM showed that two items showed the biggest im‐ provement for the intervention group: Item 5: “I am confident that I can tell whether I need to go to the doctor or whether I can take care of a health problem myself”; and Item 12: “I am confident I can figure out solutions when new problems arise with my health.” 3.2.5 | Financial impact of intervention The financial impact analysis was to determine whether the PTP intervention was cost‐effective and could produce health care cost savings for the intervention group relative to the control group. To undertake this analysis, we compiled data on participants’ use of hospital services, including hospital setting (e.g., inpatient vs. emer‐ gency), dates of admission and discharge, age, the primary source of payment, payment amounts, total hospital charges, and primary clinical diagnosis and its description. Three hospital partners for this study provided data for study participants in both the intervention and control groups. The financial analyses were undertaken from the perspective of a health care provider. Program costs consisted of the following components: the PTP service fee, the CHW, and provision of a smartphone to participants for the duration of the study. The per member per month cost of the PTP for this study was $3.00 which included the ability to chat within the platform. The cost of the CHW was a function of the pro‐ portion of full‐time equivalence (FTE) allocated to the program and the average wage plus benefits of a CHW. The duties of the CHW include receiving 2 weeks training to utilize the PTP in addition to 0.3 FTE of CHW time allocated toward participant outreach after its implementation. The hourly cost of the CHW used in our study was
TABLE 2 Return on investment analysis by estimated inpatient cost savings per participant and option based on $520 cost savings per participant
Intervention cost per participant
Return on investment (%)
Option
Intervention description
A B
Mobile Technology service only Mobile Technology service, CHW training, and CHW program management
$27.00
1,859%
$251.25
90%
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