Abstract
BackgroundTypical measures of maternity performance remain focused on the technical elements of birth, especially pathological elements, with insufficient measurement of nontechnical measures and those collected pre- and postpartum. New technologies allow for patient-reported outcome measures (PROMs) and patient-reported experience measures (PREMs) to be collected from large samples at multiple time points, which can be considered alongside existing administrative sources; however, such models are not widely implemented or evaluated. Since 2018, a longitudinal, personalized, and integrated user-reported data collection process for the maternal care pathway has been used in Tuscany, Italy. This model has been through two methodological iterations.ObjectiveThe aim of this study was to compare and contrast two sampling models of longitudinal user-reported data for the maternity care pathway, exploring factors influencing participation, cost, and suitability of the models for different stakeholders.MethodsData were collected by two modes: (1) “cohort” recruitment at the birth hospital of a predetermined sample size and (2) continuous, ongoing “census” recruitment of women at the first midwife appointment. Surveys were used to collect experiential and outcome data related to existing services. Women were included who passed 12 months after initial enrollment, meaning that they either received the surveys issued after that interval or dropped out in the intervening period. Data were collected from women in Tuscany, Italy, between September 2018 and July 2020. The total sample included 7784 individuals with 38,656 observations. The two models of longitudinal collection of user-reported data were analyzed using descriptive statistics, survival analysis, cost comparison, and a qualitative review.ResultsCohort sampling provided lower initial participation than census sampling, although very high subsequent response rates (87%) were obtained 1 year after enrollment. Census sampling had higher initial participation, but greater dropout (up to 45% at 1 year). Both models showed high response rates for online surveys. There were nonproportional dropout hazards over time. There were higher rates of dropout for women with foreign nationality (hazard ratio [HR] 1.88, P<.001), and lower rates of dropout for those who had a higher level of education (HR 0.77 and 0.61 for women completing high school and college, respectively; P<.001), were employed (HR 0.87, P=.01), in a relationship (HR 0.84, P=.04), and with previous pregnancies (HR 0.86, P=.002). The census model was initially more expensive, albeit with lower repeat costs and could become cheaper if repeated more than six times.ConclusionsThe digital collection of user-reported data enables high response rates to targeted surveys in the maternity care pathway. The point at which pregnant women or mothers are recruited is relevant for response rates and sample bias. The census model of continuous enrollment and real-time data availability offers a wider set of potential benefits, but at an initially higher cost and with the requirement for more substantial data translation and managerial capacity to make use of such data.
Highlights
Most health care performance data are derived from administrative sources, which can be used to measure the more technical aspects or process measures of maternity care provided to women
The point at which pregnant women or mothers are recruited is relevant for response rates and sample bias
Studies highlighting the importance of priority setting, use of management models, incentives, and other similar efforts have shown that data related to patient-centered measurement may prove to be more useful [4-6]. This includes assessments of patients’ preferences for care, experiences with services, and a range of disease-specific and general health and well-being–related markers. These latter two domains are typically collected through validated tools such as patient-reported experience measures (PREMs) and patient-reported outcome measures (PROMs), respectively [7,8], which can provide responsive and reliable measures of outcomes and experiences [9]
Summary
Most health care performance data are derived from administrative sources, which can be used to measure the more technical aspects or process measures of maternity care provided to women Such data can only capture some dimensions of the quality of care and do not address important features such as patient preferences or overall well-being. Studies highlighting the importance of priority setting, use of management models, incentives, and other similar efforts have shown that data related to patient-centered measurement may prove to be more useful [4-6] This includes assessments of patients’ preferences for care, experiences with services, and a range of disease-specific and general health and well-being–related markers.
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