Editorial

Bridging the evidence–practice divide in developing health systems

Quinette A. Louw, Conran Joseph

Copyright: © 2025. The Author(s). Licensee: AOSIS.
This work is licensed under the Creative Commons Attribution 4.0 International (CC BY 4.0) license (https://creativecommons.org/licenses/by/4.0/).

The gap between research evidence and its translation into everyday patient care remains one of the most persistent and profound challenges in global health. Over decades, systematic reviews and clinical trials have built a robust foundation of evidence on ‘what works’. Yet, at the bedside or in the rehabilitation centre, clinicians often confront a far more complex reality – one shaped not only by a specific condition, impairment, disability and treatment protocols, but also by the deep structures of health systems, political forces, cultural and social determinants, and the personal psychosocial contexts of individual patients.

This persistent gap reflects more than a technical implementation failure. It is a systemic problem rooted in the inability to bridge evidence and practice in contexts where structural and social determinants profoundly shape who receives care, the kind of care they receive, acceptable and compliance to care and ultimately, their health outcomes.

Rethinking evidence-based practice

Evidence-based practice (EBP), which evolved from its origins in evidence-based medicine, was developed to equip clinicians with the skills to interpret and apply scientific research to improve care quality and patient outcomes (Dawes et al. 2005). However, a persistent misconception continues to pervade health practice: that evidence derived from randomised controlled trials (RCTs) represents a universal gold standard.

This interpretation overlooks the foundational principle of EBP: that evidence must be integrated with clinician expertise and patient values, and situated within the unique clinical and social context in which care is delivered. Randomised controlled trials, while powerful for establishing internal validity, are typically conducted under highly controlled conditions, often far removed from the realities of everyday clinical settings.

Translating these findings into practice requires careful adaptation, even in high-income settings where health systems are relatively well-resourced and organised (Reed et al. 2018). Achieving consistent implementation in such contexts is already challenging. These difficulties are amplified in low- and middle-income countries (LMICs), where health systems are still developing, are frequently fragmented, under-resourced and characterised by entrenched inequities. In these contexts, clinicians must navigate the double burden of interpreting evidence produced in tightly controlled settings and adapting evidence generated in high-income contexts to their own vastly different environments (Novak et al. 2021).

Inequity as a determinant of evidence translation

Equity is not a peripheral consideration in healthcare delivery; it is central to whether individuals have an equal chance of receiving evidence-based care and achieving comparable health outcomes. Health inequities are shaped by multiple intersecting factors, including socioeconomic status, geography, race, gender, education and access to services. In LMIC health systems, these inequities are not background conditions; they are structural forces that shape the entire care pathway and determine health trajectories.

In countries such as South Africa, where inequality remains among the highest globally, these forces are particularly visible. A dual health system – one private and well-resourced, the other public and overstretched – exacerbates disparities. People dependent on the public sector often face limited access to specialist services, rehabilitation and assistive technologies. In such settings, the promise of evidence-based care is constrained not by a lack of knowledge or health literacy, but by the social and structural conditions in which care is delivered.

Translating evidence generated in high-income countries into such contexts demands far more than technical adaptation. It requires systemic rethinking, acknowledging inequity as a core determinant of whether evidence can be meaningfully implemented and designing context-sensitive frameworks that bridge global evidence with local realities.

The PROGRESS-Plus (P: place of residence, R: race and/or ethnicity, O: occupation, G: gender, R: religion, E: socioeconomic status, S: social capital) framework offers a useful lens for ensuring that equity considerations – such as place of residence, socioeconomic status, gender and other structural determinants – are systematically addressed in research, reporting and implementation. Yet in practice, these factors are often poorly documented or insufficiently integrated into implementation models, leaving a gap between evidence and real-world patient experiences.

The PATIENT-FIT framework: Bridging the gap

In response to these challenges, the Stellenbosch University Undergraduate Research Team has developed the PATIENT-FIT (P: PROGRESS-Plus, A: access, Ti: TIDieR [Template for Intervention Description and Replication] elements of the intervention, E: empowerment of end-user, N: networks, T: timeliness, F: funding, I: information and communications technology, T: threats) framework – a pragmatic, person-centred model designed to help clinicians navigate the complexities of applying evidence in diverse and unequal contexts. The PATIENT-FIT framework (Figure 1) emphasises contextual fit: aligning intervention choices not only with clinical evidence but also with the patient’s personal goals, functional needs, social environment and the structural realities of the health system in which care is delivered.

FIGURE 1: PATIENT-FIT framework.

This framework complements existing models such as PROGRESS-Plus by bringing the equity lens closer to the point of care. Rather than assuming uniformity, it starts from the heterogeneity of patient experiences. It acknowledges that effective care is not merely about applying the ‘right’ intervention, but about ensuring that the intervention is feasible, acceptable and impactful in a patient’s real-world setting.

Bridging the evidence–practice gap requires an equity-centred mindset. In countries such as South Africa and across many LMICs, this means recognising how deeply unequal systems shape health outcomes, and designing implementation strategies that respond to, rather than ignore, these realities.

The PATIENT-FIT framework offers one step towards this goal: helping clinicians and students move from evidence to action in ways that are locally relevant, socially aware and person-centred. If we are serious about improving rehabilitation and health outcomes globally, equity must build into how we generate, translate and apply evidence.

At its core, the PATIENT-FIT framework is a tool to guide clinicians, students and researchers in mapping the unique characteristics of a patient case against the intervention evidence found in the literature. It goes beyond symptom checklists or generic implementation strategies by embedding equity, context and person-centredness into the heart of clinical decision-making.

The framework’s strength lies in its comprehensive structure, organised under the acronym PATIENT-FIT, which encompasses key factors essential to understanding how and whether an intervention is likely to work for a specific patient.

Breaking down the components

P – PROGRESS-Plus

This component integrates social determinants such as place of residence, ethnicity, socioeconomic position, disability and other equity factors (O’Neill et al. 2014). It prompts clinicians to recognise how a patient’s broader context can enhance or inhibit the effectiveness of care.

A – Access

Access focusses on a patient’s ability to seek, reach and benefit from healthcare services, taking into account logistical, social and cultural barriers. The inclusion of this aspect challenges providers to assess whether the care they recommend is truly accessible in practice. It should further assess whether the treatment is accessible over the entire course of care, which is often longer in duration and more frequent in rehabilitation than, for example, primary physician appointments.

Ti – TIDieR elements of the intervention

Adapted from the TIDieR checklist, this section breaks down the who, what, when, where, why and how of the intervention, encouraging scrutiny of whether the intervention’s design aligns with the patient’s context and possible to provide within the healthcare system on an equal basis, ranging from who should ideally implement the intervention, what material resources are required and whether suitable replacements are possible without influencing the fidelity of the intervention, and whether the intended dose (amount and frequency) can be delivered in line with the evidence, among other important elements.

E – Empowerment of end-user

This aspect acknowledges that optimal health outcomes depend on patients’ health literacy and ability to self-manage their conditions. It calls for clarity on the type of information and support needed by patients and carers. It further calls for employing a range of behaviour change techniques, such as mutual goal setting, self-monitoring, motivational interviewing to establish readiness for change and others, to be used by the healthcare professional and end-user to ensure a high level of self-efficacy, confidence and resilience in the change process.

N – Networks

The components evaluate the presence and quality of care networks, including formal health systems and informal community or indigenous support systems that are often overlooked in mainstream clinical models.

T – Timeliness

Delays in access to diagnostics, treatment or referrals can significantly impact outcomes. This indicator ensures that considerations of time and procedural efficiency are incorporated into the care plan.

F – Funding

Affordability is a cornerstone of care delivery. This part of the framework pushes clinicians to think through both direct and indirect costs – such as sick-leave absence, travel, medication and caregiving – faced by the patient.

I – Information and communications technology

With the rise of telehealth and digital care models, this component examines a patient’s digital literacy and access, ensuring that technology-based solutions are not imposed inappropriately. This indicator should further consider preferences for accessing healthcare services and the extent to which information and communications technology (ICT) can be used for specific goals such as self-monitoring, feedback and hotline.

T – Threats

The framework calls for an honest appraisal of any additional risks or barriers, for example psychological, social or systemic, that might prevent the patient from achieving a successful outcome.

What distinguishes the PATIENT-FIT framework is its capacity to humanise the clinical reasoning process. It shifts the narrative from ‘Does this intervention work?’ to ‘Will this intervention work for this patient, here and now?’ This reframing is critical for translating evidence into equitable and meaningful care, especially in resource-constrained or culturally diverse settings.

Moreover, the framework serves as an educational tool. It encourages students and early-career clinicians to think critically and contextually when attempting to translate evidence into practice at the coalface. It provides practical guidance for integrating clinical findings, scientific evidence and patient-specific details into a coherent, patient-centred strategy.

The way forward

The PATIENT-FIT framework offers a practical, person-centred strategy to one of health care’s biggest challenges: translating evidence into real-world context. It can be adapted across disciplines, from rehabilitation and primary care to mental health and community health, making care more responsive and equitable. For researchers, it brings patient-level insight into evidence generation. For policymakers, it exposes the layered realities of care delivery and the need for flexible, context-aware health systems, highlighting the need for trans-sectoral strategies to improve health. It gives healthcare students and clinicians a clear, ethically grounded way to ensure no patient is left behind. The PATIENT-FIT framework offers a structured approach to bridge the gap between research evidence and real-world healthcare.

References