What matters when exploring fidelity when using health IT to reduce disparities?

BACKGROUND: Implementation of evidence-based interventions often involves strategies to engage diverse populations while also attempting to maintain external validity. When using health IT tools to deliver patient-centered health messages, systems-level requirements are often at odds with 'on-the ground' tailoring approaches for patient-centered care or ensuring equity among linguistically diverse populations. METHODS: We conducted a fidelity and acceptability-focused evaluation of the STAR MAMA Program, a 5-month bilingual (English and Spanish) intervention for reducing diabetes risk factors among 181 post-partum women with recent gestational diabetes. The study's purpose was to explore fidelity to pre-determined 'core' (e.g. systems integration) and 'modifiable' equity components (e.g. health coaching responsiveness, and variation by language) using an adapted implementation fidelity framework. Participant-level surveys, systems-level databases of message delivery, call completion, and coaching notes were included. RESULTS: 96.6% of participants are Latina and 80.9% were born outside the US. Among those receiving the STAR MAMA intervention; 55 received the calls in Spanish (61%) and 35 English (39%). 90% (n = 81) completed ≥ one week. Initially, systems errors were common, and increased triggers for health coach call-backs. Although Spanish speakers had more triggers over the intervention period, the difference was not statistically significant. Of the calls triggering a health coach follow-up, attempts were made for 85.4% (n = 152) of the English call triggers and for 80.0% (n = 279) of the Spanish call triggers (NS). Of attempted calls, health coaching calls were complete for 55.6% (n = 85) of English-language call triggers and for 56.6% of Spanish-language call triggers (NS). Some differences in acceptability were noted by language, with Spanish-speakers reporting higher satisfaction with prevention content (p = < 0.01) and English-speakers reporting health coaches were less considerate of their time (p = 0.03). CONCLUSIONS: By exploring fidelity by language-specific factors, we identified important differences in some but not all equity indicators, with early systems errors quicky remedied and high overall engagement and acceptability. Practice implications include: (1) establishing criteria for languge-equity in interventions, (2) planning for systems level errors so as to reduce their impact between language groups and over time; and (3) examining the impact of engagement with language-concordant interventions on outcomes, including acceptability. Trial Registration National Clinical Trials registration number: CT02240420 Registered September 15, 2014. ClinicalTrials.gov.

Uncertainty and operational considerations in mass prophylaxis workforce planning.

BACKGROUND: The public health response to an influenza pandemic or other large-scale health emergency may include mass prophylaxis using multiple points of dispensing (PODs) to deliver countermeasures rapidly to affected populations. Computer models created to date to determine "optimal" staffing levels at PODs typically assume stable patient demand for service. The authors investigated POD function under dynamic and uncertain operational environments. METHODS: The authors constructed a Monte Carlo simulation model of mass prophylaxis (the Dynamic POD Simulator, or D-PODS) to assess the consequences of nonstationary patient arrival patterns on POD function under a variety of POD layouts and staffing plans. Compared are the performance of a standard POD layout under steady-state and variable patient arrival rates that may mimic real-life variation in patient demand. RESULTS: To achieve similar performance, PODs functioning under nonstationary patient arrival rates require higher staffing levels than would be predicted using the assumption of stationary arrival rates. Furthermore, PODs may develop severe bottlenecks unless staffing levels vary over time to meet changing patient arrival patterns. Efficient POD networks therefore require command and control systems capable of dynamically adjusting intra- and inter-POD staff levels to meet demand. In addition, under real-world operating conditions of heightened uncertainty, fewer large PODs will require a smaller total staff than many small PODs to achieve comparable performance. CONCLUSIONS: Modeling environments that capture the effects of fundamental uncertainties in public health disasters are essential for the realistic evaluation of response mechanisms and policies. D-PODS quantifies POD operational efficiency under more realistic conditions than have been modeled previously. The authors' experiments demonstrate that effective POD staffing plans must be responsive to variation and uncertainty in POD arrival patterns. These experiments highlight the need for command and control systems to be created to manage emergency response successfully.