Unravelling patient pathways in the context of antibacterial resistance in East Africa

Abstract

Background: A key factor driving the development and maintenance of antibacterial resistance (ABR) is individuals' use of antibiotics (ABs) to treat illness. To better understand motivations and context for antibiotic use we use the concept of a patient treatment-seeking pathway: a treatment journey encompassing where patients go when they are unwell, what motivates their choices, and how they obtain antibiotics. This paper investigates patterns and determinants of patient treatment-seeking pathways, and how they intersect with AB use in East Africa, a region where ABR-attributable deaths are exceptionally high.

Methods: The Holistic Approach to Unravelling Antibacterial Resistance (HATUA) Consortium collected quantitative data from 6,827 adult outpatients presenting with urinary tract infection (UTI) symptoms in Kenya, Tanzania, and Uganda between February 2019- September 2020, and conducted qualitative in-depth patient interviews with a subset (n = 116). We described patterns of treatment-seeking visually using Sankey plots and explored explanations and motivations using mixed-methods. Using Bayesian hierarchical regression modelling, we investigated the associations between socio-demographic, economic, healthcare, and attitudinal factors and three factors related to ABR: self-treatment as a first step, having a multi-step treatment pathway, and consuming ABs.

Results: Although most patients (86%) sought help from medical facilities in the first instance, many (56%) described multi-step, repetitive treatment-seeking pathways, which further increased the likelihood of consuming ABs. Higher socio-economic status patients were more likely to consume ABs and have multi-step pathways. Reasons for choosing providers (e.g., cost, location, time) were conditioned by wider structural factors such as hybrid healthcare systems and AB availability.

Conclusion: There is likely to be a reinforcing cycle between complex, repetitive treatment pathways, AB consumption and ABR. A focus on individual antibiotic use as the key intervention point in this cycle ignores the contextual challenges patients face when treatment seeking, which include inadequate access to diagnostics, perceived inefficient public healthcare and ease of purchasing antibiotics without prescription. Pluralistic healthcare landscapes may promote more complex treatment seeking and therefore inappropriate AB use. We recommend further attention to healthcare system factors, focussing on medical facilities (e.g., accessible diagnostics, patient-doctor interactions, information flows), and community AB access points (e.g., drug sellers).

Keywords: Africa; Antibacterial Resistance; Antibiotics; Healthcare system; Mixed methods; Patient pathways; Treatment seeking; Urinary tract Infection.

Fig. 1

Flow of questions used to collect quantitative data on the patient treatment-seeking pathway for UTI-like symptoms

Fig. 2

Sankey plot describing patient treatment seeking pathways for UTI-like symptoms for pooled analysis (N = 6,378). Figure notes: n = 230 were excluded from the analysis sample due to missing data on the relevant variables. Percentages might not add up to 100% due to rounding

Fig. 3

Descriptive statistics on reasons for patient’s first choice of treatment (n = 3,546). Notes: Includes patients who tried to treat their UTI symptoms before going to the recruitment clinic (n = 3,546); patients could choose multiple reasons

Fig. 4

Odds ratios and 95% HPDI from adjusted logistic regression models for outcomes of self-treating in step 1, having 2 + steps in the pathway and taking ABs in the pathway (N = 6,608). Notes: Antibiotic consumption at step 1 or 2 outcome (n = 3,546) excludes patients going to the recruitment clinic as their 1^st step. Reference categories: Feeling symptoms stigma (‘No’) Meeting healthcare costs (‘Easy’); Had previous UTI episode (‘No’); Age (< 25 years); Education: No quals/ primary; Marital status (‘married’); Wealth quintile (1.^st- poorest); Working (‘formal employment’); Household size (1–2 people); Hospital level (2–3)

Fig. 5

Number of pathway steps as percent of the total within each country (N = 6,608)