Implications of response shift for micro-, meso-, and macro-level healthcare decision-making using results of patient-reported outcome measures

Abstract

Purpose Results of patient-reported outcome measures (PROMs) are increasingly used to inform healthcare decision-making. Research has shown that response shift can impact PROM results. As part of an international collaboration, our goal is to provide a framework regarding the implications of response shift at the level of patient care (micro), healthcare institute (meso), and healthcare policy (macro). Methods Empirical evidence of response shift that can influence patients’ self-reported health and preferences provided the foundation for development of the framework. Measurement validity theory, hermeneutic philosophy, and micro-, meso-, and macro-level healthcare decision-making informed our theoretical analysis. Results At the micro-level, patients’ self-reported health needs to be interpreted via dialogue with the clinician to avoid misinterpretation of PROM data due to response shift. It is also important to consider the potential impact of response shift on study results, when these are used to support decisions. At the meso-level, individual-level data should be examined for response shift before aggregating PROM data for decision-making related to quality improvement, performance monitoring, and accreditation. At the macro-level, critical reflection on the conceptualization of health is required to know whether response shift needs to be controlled for when PROM data are used to inform healthcare coverage. Conclusion Given empirical evidence of response shift, there is a critical need for guidelines and knowledge translation to avoid potential misinterpretations of PROM results and consequential biases in decision-making. Our framework with guiding questions provides a structure for developing strategies to address potential impacts of response shift at micro-, meso-, and macro-levels.

Response shift in patient-reported outcomes: definition, theory, and a revised model

“…These studies have helped to better understand occasional discrepancies between researchers' or healthcare professionals' expected assessments of patients' health and patients' self-reported health, by highlighting processes such as psychological adaptation to illness or the appraisal of PROM items. Thus, these insights have enriched the interpretation of PROM results [8,15]. Meanwhile, fundamental debates continued, evolving around the definition of response shift [16][17][18][19][20][21][22][23][24][25][26][27][28][29], the act of measuring subjective constructs [30], and the relationships between response shift and related concepts [31][32][33][34].…”

“…In 2019, an international, interdisciplinary working group of 26 researchers, consisting of response shift experts, new investigators, and independent external experts was formed to achieve this synthesis [14]. They were divided in four teams [12,14,15], with the current team focusing on definition and theory.…”

Emerging Marketing Research on Healthcare and Medical Decision Making: Toward a Consumer-Centric and Pluralistic Methodological Perspective

“…We also suggest four categories of independent variables as focal determinants of downstream healthcare outcomes. These include contextual influences (i.e., characteristics of local decision environments, e.g., information type, presentation format and textual structure), structural determinants (i.e., macro-level factors at the healthcare system level such as health coverage, market structure and the socioeconomic environment -Mhasawade, Zhao and Chunara 2021, Sawatzky et al 2021); antecedent individual differences (e.g., in knowledge, attitudes, skills, goals and values), and consumer segments or clusters (i.e., meaningfully differentiated consumer groups that share similar health needs, beliefs, attitudes, preferences and socio-cultural norms).…”

What should progress in response-shift research look like?

“…Clearly, there is a growing consensus among researchers that response-shift phenomena are central to any understanding of quality of life (QOL). However, as this series of papers clearly states, much of the uncertainty about how to align and reconcile different definitions and methods remains unclear [1][2][3][4]. Twenty-five years after the initial work on response shift [5], it feels less than satisfactory to leave these as unresolved.…”

“…Both the Vanier et al and Sawatzky et al papers promote a perspective that response shift is a form of bias in measurement [2,3]. This position is difficult to reconcile with an understanding of response shift as meaningful change.…”