The research team, led by scientists at the International Centre for Recurrent Head and Neck Cancer based at the Royal Marsden Hospital and the London School of Hygiene & Tropical Medicine, assembled an extraordinary data infrastructure to answer a deceptively simple question: how long do head and neck cancer patients actually wait from first referral to the start of treatment, and which factors push some patients into dangerously long delays? To do this, they linked the national Cancer Registry with the Cancer Waiting Times dataset, Hospital Episodes Statistics, and national Radiotherapy and Chemotherapy datasets, creating a real-world picture of the entire diagnostic and treatment pathway that no single dataset could provide on its own.

The headline numbers are stark. Of the 30,506 patients analysed, 43 percent experienced what the study defines as treatment delay, meaning more than 62 days elapsed between referral and the start of first treatment, whether that was surgery or chemoradiation. The picture becomes even more concerning when the researchers examined the most extreme waits. Among patients whose primary treatment was surgery, 11 percent waited more than 90 days. For those treated primarily with radiotherapy or chemoradiation, the figure rose to 20 percent, one in five patients waiting more than three months from referral to the beginning of a treatment course on which their survival may depend.

Why does timing matter so much in this particular cancer? Head and neck tumours, which arise in the mouth, throat, voice box, nose and salivary glands, are among the most time-sensitive malignancies in oncology. Unlike some slow-growing cancers where a few extra weeks make little biological difference, head and neck tumours can progress rapidly, and a substantial body of evidence links even short treatment delays to worse outcomes. A landmark systematic review and meta-analysis published in the BMJ in 2020 estimated that delays in cancer treatment translate directly into excess mortality, with the risk of death rising measurably for every additional week of waiting. Studies of head and neck cancer specifically, including analyses of the United States National Cancer Database and systematic reviews published in JAMA Otolaryngology, have consistently shown that increasing time to treatment initiation is associated with poorer survival, larger tumours at treatment, and in some cases pathological upstaging, where the tumour is found to have advanced further than initial assessments suggested.

Against this biological backdrop, the new study’s identification of the strongest predictor of delay carries real weight. Patients who entered the cancer pathway through a non-urgent referral route, rather than the urgent suspected cancer referral pathway designed to fast-track people with red-flag symptoms, faced dramatically higher odds of long delay. After adjusting for other factors in multivariable logistic regression models, non-urgent referral was associated with an adjusted odds ratio of 4.07 for long delay, with a confidence interval of 3.54 to 4.68. In practical terms, patients referred through routine channels were roughly four times more likely to experience a treatment delay exceeding 62 days than those referred urgently. Notably, non-urgent referrals accounted for 30 percent of all patients in the cohort, meaning nearly a third of people who ultimately turned out to have head and neck cancer were not flagged as urgent when they first entered the system.

This finding points to a fundamental diagnostic challenge. The early symptoms of head and neck cancer, including persistent sore throat, hoarseness, mouth ulcers that fail to heal, difficulty swallowing, and unexplained lumps in the neck, overlap heavily with far more common and benign conditions. Distinguishing a cancer that will kill from a viral infection that will resolve within days is one of the hardest triage tasks in primary care, and the study’s authors argue that improving this recognition is where interventions should focus. Public and primary care awareness of head and neck cancer symptoms, they suggest, is a critical lever for shifting more patients onto the urgent referral pathway where rapid investigation follows.

But referral route was not the only determinant of delay. The researchers found that patients whose initial assessment took place at non-specialist hospitals, referred to in the study as spoke hospitals rather than the specialist hub centres where head and neck cancer expertise is concentrated, faced higher odds of delay. This reflects a broader tension in modern NHS organisation: the centralisation of complex cancer surgery into fewer, higher-volume specialist centres improves outcomes and quality, but it can add steps, transfers and logistical friction to the patient journey, particularly for those who first present at a district general hospital and must then be referred onward for specialist assessment. The study also found that patients with cancers arising outside the oropharynx, the part of the throat that includes the tonsils and base of the tongue, experienced longer waits, likely reflecting the more indistinct symptom profiles of tumours in sites such as the voice box, nasal cavity and salivary glands. Higher socio-economic deprivation emerged as a further risk factor, adding to a long record of evidence that cancer waits in England are systematically worse for patients from poorer communities, who may present later, navigate the system with less support, and face additional barriers at every stage of the pathway.

One of the study’s most technically interesting contributions is its demonstration that the drivers of delay differ fundamentally between the two main treatment modalities. Patients destined for primary surgery and patients destined for primary chemoradiation follow different pathways, and the factors that slow each group down are not identical. Surgical patients typically require pre-operative assessment, anaesthetic review and theatre capacity, while radiotherapy patients depend on planning processes, mould fabrication, and linear accelerator capacity, and those receiving concurrent chemotherapy face additional pharmaceutical and supportive care requirements. The finding that long delays were twice as common in the chemoradiation group, 20 percent versus 11 percent, suggests that the non-surgical pathway carries a distinct and heavier burden of system-level bottlenecks. The authors argue that any strategy to reduce waiting times must acknowledge and address these modality-specific drivers rather than treating the cancer pathway as a single undifferentiated queue.

The study’s methodology deserves attention because it exemplifies a growing trend in oncology research: the use of real-world data at national scale to answer questions that clinical trials, with their selected populations and controlled conditions, cannot address. By linking five national datasets covering registration, waiting times, hospital admissions, radiotherapy and chemotherapy, the researchers captured the full continuum of care for essentially an entire national population of head and neck cancer patients over the study period. The analyses were conducted in RStudio, and the work was funded by the International Centre for Recurrent Head and Neck Cancer, with ethics approval from the London School of Hygiene and Tropical Medicine Ethics Committee. The data were provided under licence by NHS Digital’s National Disease Registration Service, and the underlying data cannot be shared publicly, reflecting the governance constraints that accompany such sensitive linked health records.

The implications reach well beyond the borders of England. Health systems worldwide are grappling with post-pandemic backlogs, rising cancer incidence and constrained diagnostic capacity, and head and neck cancer services have been repeatedly identified as among those with the longest treatment waits. The study’s conclusions offer a roadmap: optimise referral pathways so that more patients with suspicious symptoms enter the urgent route, invest in symptom awareness among both the public and general practitioners, design diagnostic pathways that minimise transfers between spoke and hub hospitals, and build separate solutions for the surgical and radiotherapy arms of the service. The authors also point to emerging research programmes, such as the NIHR-funded EVEREST-HN initiative, which is developing a patient-reported symptom-based risk stratification system to redesign the suspected head and neck cancer referral pathway, as the kind of innovation the findings demand. For the one in five patients whose radiotherapy begins more than three months after their first referral, and for the 43 percent overall who wait beyond the 62-day standard, the message of this study is unambiguous: the delay is measurable, its causes are identifiable, and its consequences for survival are too well documented to ignore.

Subject of Research: Waiting times and determinants of treatment delay for head and neck cancer patients in England

Article Title: Waiting times and determinants of delay for head and neck cancer in England—a population cohort study using real world data

Article References: Jashek-Ahmed, F., Almilaji, O., Cowling, T. E., Hamilton, D. W., Walker, K., & Paleri, V. (2026). Waiting times and determinants of delay for head and neck cancer in England—a population cohort study using real world data. British Journal of Cancer. https://doi.org/10.1038/s41416-026-03630-8

Image Credits: AI Generated

DOI: 10.1038/s41416-026-03630-8

Keywords: head and neck cancer, treatment delay, waiting times, NHS England, cancer referral, real-world data, radiotherapy, cancer surgery, health inequalities, cancer epidemiology, diagnostic pathway, British Journal of Cancer

Researchers from Makerere University School of Public Health, working alongside the United Nations Population Fund, analyzed data from a 2023 cross-sectional survey that visited 614 health facilities providing family planning services across Uganda and interviewed 2,378 clients as they exited those service delivery points. Rather than simply measuring whether people use contraception—a metric that has dominated family planning research for decades—the team focused on process indicators drawn from the Availability, Accessibility, Acceptability and Quality framework, which capture the remediable, day-to-day realities that shape whether services actually reach the people who need them.

The headline availability figure is genuinely encouraging. On average, 89.7 percent of all surveyed service delivery points consistently provided a minimum of three modern contraceptive methods as part of their regular services. That threshold matters because offering a choice of at least three methods is widely regarded as a baseline for genuine contraceptive autonomy, allowing clients to select options that fit their bodies, relationships, and life circumstances rather than accepting whatever happens to be in stock.

But dig into the stratified results and a more complicated picture emerges. The facilities performing best were not the small rural outposts that serve the majority of Uganda’s population. Health Centre IV facilities—the highest tier of health centre in the country’s tiered system—reported the highest proportion of regular provision of at least three modern methods at 98.3 percent. Government-run facilities reached 93.1 percent, and rural facilities 91.3 percent, figures that outperformed their counterparts at lower levels and in other ownership categories. The pattern suggests that while the public sector has built impressive commodity availability at higher-level facilities, the lower-tier posts and clinics that rural women and adolescents are most likely to visit first may still be the weakest links in the supply chain.

Waiting time data tell an equally revealing story about who bears the cost of system strain. Clients aged 15 to 19—the very adolescents that family planning programs most struggle to reach—spent an average of 72 minutes waiting for services, the longest of any age group surveyed. Those aged 20 to 29 waited an average of 66 minutes, while clients aged 30 to 39 waited 69 minutes. The numbers indicate that the youngest clients, who often face the greatest social barriers to seeking contraception in the first place, are also asked to endure the longest physical waits once they arrive, a combination that discourages return visits and fuels discontinuation.

Gender and education both carved additional fault lines through the data. Female clients waited an average of 66 minutes for family planning services, while male clients waited just 43 minutes—a 23-minute gap that likely reflects both the greater complexity of services women receive and differences in how facilities triage and schedule clients. Education gradients were equally stark: clients with no education waited an average of 68.4 minutes and those with primary education 69.5 minutes, while clients with post-primary education waited just 55.8 minutes. In a health system where time is money and long absences from work or family responsibilities carry real costs, these waiting time disparities function as a regressive tax on the least privileged users.

Quality perceptions added a further dimension of concern. Only 53.3 percent of the 1,267 clients who were asked believed that service providers adhered to all best practices in family planning service delivery across all levels of service delivery points. In other words, nearly half of the clients leaving Ugandan family planning clinics had reservations about whether the care they received met accepted standards. Since acceptability and perceived quality are known drivers of contraceptive continuation, this finding suggests that even where commodities are physically present, the interpersonal and technical dimensions of care may be undermining trust and uptake.

The study’s methodology deserves attention because it illustrates how process indicators can illuminate problems that utilization statistics obscure. Data were collected between September 13 and October 3, 2023, through face-to-face interviews with facility managers and exit interviews with clients, and the analysis was performed using STATA version 15. Descriptive statistics—frequencies, percentages, and means—were generated across service delivery point and client characteristics to identify differences in outcomes across facility levels and population sub-groups. By disaggregating results by facility tier, ownership, location, age, sex, and education, the researchers transformed what could have been a single national average into a diagnostic map of exactly where the system is failing whom.

The authors argue that the path forward requires strengthening community-based distribution through outreach programs, community health workers, drug shops, and pharmacies, particularly to reach underprivileged groups such as adolescents and rural women who face the longest waits and the thinnest method choice. At the same time, they call for empowering and equipping lower-level service delivery points by skilling personnel, ensuring commodities and supplies are available, and improving service delivery processes so that even the smallest facilities can competently provide a full range of modern contraceptive methods. These are not glamorous interventions, but the evidence suggests they target precisely the bottlenecks the survey identified.

The broader significance of the work extends well beyond Uganda’s borders. As international funders and governments pour resources into expanding contraceptive access, the study demonstrates that availability metrics alone can mask profound inequities in how services are actually experienced. A country can report high method availability while adolescents wait more than an hour for care and half of all clients doubt the quality of what they receive. Measuring availability, accessibility, acceptability, and quality together—and disaggregating by the characteristics that determine who is left behind—offers a template for other low-resource settings seeking to convert nominal coverage into genuine, equitable access to reproductive health care for everyone in need.

Subject of Research: Equity assessment of family planning service delivery points in Uganda using UNFPA 2023 survey data

Article Title: Equity of family planning at service delivery points in Uganda

Article References: Nabukeera, S., Kasule, T., Makumbi, F., Etajak, S., Kabwijamu, L., Senkubuge, S., Tusubira, A. K., & Nalwadda, C. (2026). Equity of family planning at service delivery points in Uganda. International Journal for Equity in Health. https://doi.org/10.1186/s12939-026-03072-x

Image Credits: AI Generated

DOI: 10.1186/s12939-026-03072-x

Keywords: family planning, Uganda, health equity, contraception, service delivery, waiting times, adolescent health, UNFPA, reproductive health, health facilities, rural health, access to care

The study team, led by Chukwuma J. Okafor of the State University of Zanzibar together with colleagues Islam H. Mwita, Rodolfo Isidro Bosch Bayard, and Aziza Japhary, designed their investigation as a cross-sectional survey, a snapshot approach that captures patient attitudes at a single point in time. They adapted the Patient Satisfaction Questionnaire, a widely used instrument in health services research, into a structured 28-item tool spanning nine distinct domains: the physical environment, courtesy and interpersonal manner, communication, accessibility, time spent with the doctor, convenience, technical quality, expenses, and general satisfaction. This multidimensional framing matters because patient satisfaction is not a single feeling but a composite judgment, assembled from everything from the cleanliness of the waiting area to whether a clinician explained a diagnosis in words the patient could understand.

The granularity of the questionnaire allowed the researchers to see precisely where the service was succeeding and where it was collapsing. Administrative interactions fared comparatively well: 83.2 percent of respondents expressed satisfaction with registration staff, suggesting that the clerical backbone of the outpatient department functions acceptably. But the picture deteriorated sharply when the researchers turned to the human and environmental dimensions of care. Communication and patient-centred care items registered very low satisfaction, and a striking 92.9 percent of respondents reported dissatisfaction with cleanliness. Long waiting times emerged as another prominent source of frustration, compounding the sense that patients were spending hours in an unhygienic environment only to receive hurried, impersonal consultations.

Methodologically, the study makes several choices that reflect a growing sophistication in how health services researchers handle common outcomes and imperfect data. Because dissatisfaction affected well over 10 percent of the sample, the authors used modified Poisson regression with robust variance rather than ordinary logistic regression. The technical rationale is important: when an outcome is common, odds ratios derived from logistic models systematically overstate the underlying prevalence ratios, inflating the apparent strength of associations. Poisson regression with robust standard errors directly estimates prevalence ratios, giving a more honest picture of how much more likely one group is to be dissatisfied than another. Reporting adjusted prevalence ratios with 95 percent confidence intervals, the team identified lower satisfaction linked to perceived affordability, accessibility, and perceived socioeconomic barriers.

Equally notable is what the authors chose to disclose about the limits of their own statistics. Two adjusted prevalence ratios — one for perceived socioeconomic influence and one for female sex — came out with magnitudes exceeding 20, values so extreme that no prevalence ratio can plausibly represent them as true effects. Rather than presenting these numbers as headline findings, the researchers flagged them as almost certainly reflecting instability in the underlying data, reporting them for completeness but explicitly declining to interpret them as precise or generalisable effect sizes. They also reported that a logistic-regression specification of the same model failed to converge, a phenomenon known as quasi-complete separation, and chose to state this openly rather than dress up unstable odds-ratio estimates as reliable results. In a field where inflated effect estimates are too often laundered into policy claims, this kind of transparency is rare and welcome.

The reliability of the survey instrument itself received similarly candid treatment. The overall 28-item scale achieved a Cronbach’s alpha of 0.685, a figure the authors describe as acceptable-to-borderline, sitting just below the conventional 0.70 threshold that many researchers treat as the floor for internal consistency. Domain-level reliability varied widely, ranging from 0.42 to 0.82 for domains containing three or more items, and several domains did not reach conventional reliability thresholds at all. Instead of burying this variation behind a single summary statistic, the team reported it domain by domain, acknowledging that some subscales of the adapted questionnaire measured their intended constructs less consistently than others. For readers, this means the domain-level satisfaction percentages should be read as descriptive indicators of where problems lie rather than as precision instruments.

The authors are equally careful about the study’s sampling design. The 309 participants were recruited through a non-probability approach that combined purposive selection of the study hospital with convenience sampling of outpatients during the data-collection period. Convenience sampling, while practical in a busy clinical setting, cannot guarantee that the surveyed patients represent the full population of outpatients, and the researchers accordingly frame their multivariable associations as hypothesis-generating for this particular facility rather than as confirmed, generalisable predictors of patient satisfaction. This is a methodologically honest posture, and it does not diminish the study’s practical value; it simply locates its conclusions at the level of Jitimai District Hospital, where they are most actionable.

Ethical oversight for the research was provided by the Zanzibar Health Research Ethics Committee, which granted approval under number ZAHRE/02/ST/FEB/2025/51, with additional administrative permission from the State University of Zanzibar and the hospital administration. The study was conducted in accordance with the Declaration of Helsinki, and every participant provided written informed consent after being told the study’s purpose, their right to decline or withdraw at any stage without any effect on their care, and the confidentiality protections in place. Only adults aged 18 and above were eligible, so no parental or guardian consent procedures were required. The authors received no external funding for the work and declare no competing interests, and the article is published open access under a Creative Commons licence.

What elevates the study beyond a single hospital’s report card is its identification of modifiable targets. The domains that performed worst — communication, interpersonal care, cleanliness, and waiting time — are precisely the ones that facility-level quality improvement programmes can address without waiting for new buildings, new equipment, or new budgets of the magnitude required for tertiary care upgrades. Training clinicians in patient-centred communication, reforming provider attitudes, tightening cleaning protocols, and reorganising patient flow to cut waiting times are all interventions with documented track records in low- and middle-income country settings. The authors conclude that interventions targeting patient-centred communication, provider attitudes, and financial and access barriers are essential to improve outpatient service quality, and their data give hospital managers a concrete priority list.

The broader significance lies in what the findings suggest about health systems across similar settings. Outpatient departments in low-resource contexts are the primary interface between patients and healthcare systems, and service quality at that interface critically shapes whether people seek care early, adhere to treatment, or trust public medicine at all. Evidence from Zanzibar has historically been limited, making this study a useful data point for regional health planners. If nearly 59 percent dissatisfaction can be documented at one district hospital with transparent methods and honest uncertainty, the question becomes how many neighbouring facilities would produce similar numbers under the same scrutiny — and whether the modest, well-defined fixes this study points toward, from cleaner corridors to kinder consultations, might be among the highest-yield investments available to health systems operating on thin margins.

Subject of Research: Patient satisfaction and its associated factors among outpatients at a district hospital in Zanzibar

Article Title: Patient satisfaction and associated factors among outpatients at a district hospital in Zanzibar: a facility-based cross-sectional study

Article References: Okafor, C. J., Mwita, I. H., Bosch Bayard, R. I., & Japhary, A. (2026). Patient satisfaction and associated factors among outpatients at a district hospital in Zanzibar: a facility-based cross-sectional study. BMC Health Services Research. https://doi.org/10.1186/s12913-026-15685-7

Image Credits: AI Generated

DOI: 10.1186/s12913-026-15685-7

Keywords: patient satisfaction, outpatient care, Zanzibar, district hospital, health services research, PSQ-18, modified Poisson regression, low- and middle-income countries, healthcare quality, communication, waiting times, cleanliness