The circuits of healthcare: Understanding healthcare seeking behaviour—A qualitative study with tuberculosis patients in Lisbon, Portugal

Background Understanding health delivery service from a patient´s perspective, including factors influencing healthcare seeking behaviour, is crucial when treating diseases, particularly infectious ones, like tuberculosis. This study aims to trace and contextualise the trajectories patients pursued towards diagnosis and treatment, while discussing key factors associated with treatment delays. Tuberculosis patients’ pathways may serve as indicator of the difficulties the more vulnerable sections of society experience in obtaining adequate care. Methods We conducted 27 semi-structured interviews with tuberculosis patients attending a treatment centre in a suburban area of Lisbon. We invited nationals and migrant patients in active treatment to participate by sharing their illness experiences since the onset of symptoms until the present. The Health Belief Model was used as a reference framework to consolidate the qualitative findings. Results By inductive analysis of all interviews, we categorised participants’ healthcare seeking behaviour into 4 main types, related to the time participants took to actively search for healthcare (patient delay) and time the health system spent to diagnose and initiate treatment (health system delay). Each type of healthcare seeking behaviour identified (inhibited, timely, prolonged, and absent) expressed a mindset influencing the way participants sought healthcare. The emergency room was the main entry point where diagnostic care cascade was initiated. Primary Health Care was underused by participants. Conclusions The findings support that healthcare seeking behaviour is not homogeneous and influences diagnostic delays. If diagnostic delays are to be reduced, the identification of behavioural patterns should be considered when designing measures to improve health services’ delivery. Healthcare professionals should be sensitised and perform continuous capacity development training to deal with patients´ needs. Inhibited and prolonged healthcare seeking behaviour contributes significantly to diagnostic delays. These behaviours should be detected and reverted. Timely responses, from patients and the healthcare system, should be promoted.

Comparison of Delay in Tuberculosis Diagnosis Between Migrants and Local Residents in an Eastern County of China: An Analysis of the Electronic Data Between 2015 and 2019

Introduction: China continues to rank among one of the countries with the highest number of tuberculosis (TB) cases globally. Migrants are a particularly at-risk subgroup for TB and pose a challenge for case management in contemporary China. The early diagnosis and treatment of patients with TB are pivotal for effective TB control. This study investigates the delay in the TB diagnosis of migrants as compared with residents, to provide an evidence base for improved case detection and the better management of migrant patients with TB.Materials and Methods: The data was collected from the Tuberculosis Information Management System (TBIMS) (2015–2019) in an eastern county of China. The total diagnostic delay, consisting of patient delay and health system delay, is defined as the interval between the onset of TB symptoms and the confirmation of TB diagnosis in the designated TB hospital. The comparison of the delay in the TB diagnosis between migrants and residents was conducted using a Mann-Whitney U-test and chi-square test. The difference in the delay curves between these two groups was examined using a log-rank test.Results: Of 2,487 patients with TB, 539 (22%) were migrants. The migrants tended to be younger, presented with less severe conditions, received an initial diagnosis at prefectural and above-level hospitals. Compared with the local patients with TB, the migrant patients with TB had a longer median total diagnostic delay (30 vs. 9, P = 0.000) and a higher proportion of patients with this delay >28 days (52 vs. 13%, P = 0.000). Similarly, the migrant patients with TB also had a longer median patient delay (13 vs. 9, P = 0.000) and a higher proportion of patients with this delay >14 days (47 vs. 30%, P = 0.000), longer median health system delay (9 vs. 0, P = 0.000), and a higher proportion of patients with this delay >14 days (42 vs. 0.5%, P = 0.000) than the local patients with TB. The survival curves of delay showed that the longer the time interval was, the more likely the migrant patients with TB were to be diagnosed (P < 0.05).Conclusions: Diagnosis is significantly delayed among migrant patients with TB. Our study highlights the importance of early screening and diagnosis for TB especially among migrants, to improve access and ensure better management for all patients with TB.

Diagnostic Pathways and Delays in Initiation of Treatment among Newly Diagnosed Tuberculosis Patients in Ballabgarh, India

ABSTRACTA delay in diagnosis and initiation of treatment in patients with tuberculosis (TB) can affect the period of communicability and cost of treatment. We aimed to describe the diagnostic pathways and delays in initiation of treatment among drug-sensitive newly diagnosed TB patients in Ballabgarh, India. In May 2019, we interviewed 110 TB patients who were put on treatment in the past 2 months. It was a cross-sectional study where data collection was conducted by a physician. We used a structured questionnaire to collect the information on care-seeking practices, delays, and patient’s cost. Descriptive analysis was carried out for the pathways, delays, and patient cost. The mean number of health facility contacted before the diagnosis of TB was 2.8 (SD: 1.3); 76% of patients first sought care at a private health facility. The median total delay was 34.5 (IQR: 21–60) days; median patient delay seven (IQR: 2–21) days, median health system delay 16 (IQR: 8–45) days, median diagnostic delay 32.5 (IQR: 18–57) days, and median treatment delay two (IQR: 1–3) days. Health system delay was 2.2 times longer than patient delay; the health system delay was primarily due to delay in diagnosis. Patients contacting private health facility first had 1.7 times total delay, 2.4 times longer health system delay, and 3.4 times of direct cost compared with patients contacting a public health facility first. Accelerated efforts are needed to achieve India’s target to eliminate TB by 2025.

Individual and public health consequences associated with a missed diagnosis of pulmonary tuberculosis in the emergency department: A retrospective cohort study

Objectives To determine: i) the emergency department (ED) utilization history of pulmonary tuberculosis (PTB) patients, and ii) the potential individual and public health consequences of a missed diagnosis of PTB in this setting. Design Retrospective observational cohort study. Participants Patients with PTB aged >16 years diagnosed between April 1, 2010 and December 31, 2016 in the Province of Alberta, Canada. Methods We identified valid new cases of PTB from a provincial registry and linked them to ED attendees in administrative databases. Visits are considered ‘PTB’, pulmonary ‘other’, and non-pulmonary based on the most responsible discharge diagnosis. Individual consequences of a missed diagnosis included health system delay and PTB-related death; public health consequences included nosocomial ED exposure time and secondary cases. Results Of 711 PTB patients, 378 (53%) made 845 ED visits in the six months immediately preceding the date of diagnosis. The most responsible ED discharge diagnosis was PTB in 92 (10.9%), pulmonary ‘other’ in 273 (32%) and non-pulmonary in 480 (56.8%). ED attendees had a median (IQR) health system delay of 27 (7,180) days and, compared to non-ED attendees were more likely to die a TB-related death 5.9% vs 1.2%, p = 0.001. Emergency attendees generated 3812 hours of ED nosocomial exposure time, and 31 secondary cases (60.8% of all secondary cases reported). Mycobacterium tuberculosis isolates from ED-attendees were more likely than non-attendees to be clustered–i.e., have an identical DNA fingerprint with another isolate (27% vs. 21%, p = 0.037). Conclusions ED utilization by PTB patients, and related consequences, are substantial. EDs are a potential resource for earlier PTB diagnosis.

Delayed diagnosis of tuberculosis in patients with diabetes mellitus co-morbidity and its associated factors in Zhejiang Province, China

Background Tuberculosis (TB) remains a significant global public health problem. China has the second highest TB burden in the world. With a growing TB population with diabetes mellitus (DM), the TB control system faces mounting challenges. To date, evidence remains inconclusive regarding the association between TB-DM co-morbidity and delayed diagnosis of TB patients. This study aims to assess the diagnostic delay of TB patients with known DM and identify the factors associated with this delay. Methods Data was collected from China’s Tuberculosis information management system in two counties of Zhejiang province, China. Patient delay, health system delay and total diagnostic delay are defined as follows: 1) the interval between the onset of TB symptoms and first visit to any health facility; 2) from the first visit to the health facility to the confirmed TB diagnosis in the designated hospital; 3) the sum of patient and health system’s respective delays. Comparison of these delays was made between TB patients with and without DM using Mann-Whitney U test and Chi-square test. Univariate and multivariate regression analysis was used to identify factors influencing delays among TB patients with DM. Results Of 969 TB patients, 67 (7%) TB patients had DM co-morbidity. Compared with TB patients without DM, TB patients with DM experienced significantly shorter health system delays (p < 0.05), and there was a significantly lower proportion of patients whose health system delayed> 14 days (7.0% vs. 18%, p < 0.05). However, no significant difference was observed between both patient categories regarding patient delay and total diagnostic delay. The multivariate regression analysis suggested that TB patients with DM who were aged < 60 years (AOR = 3.424, 95%CI: 1.008–11.627, p < 0.05) and non-severe cases (AOR = 9.725, 95%CI: 2.582–36.626, p < 0.05) were more likely to have a total diagnostic delay of> 14 days. Conclusions Our study suggests that DM does not contribute to further diagnostic delay as expected. Instead, we observed significantly improved health system delay among TB patients with DM. The findings indicate the importance of early screening and diagnosis for TB among diabetic patients and of strengthening the integrated control and management of TB and diabetic programs.

Health system delay in the treatment of tuberculosis patients in Ethiopia: a systematic review and meta-analysis

Background: Delay in diagnosis and initiation of effective treatment associated with increase in morbidity, mortality and on-going person-to-person transmission in the community at large. In Ethiopia, several studies have been conducted regarding health system delay among tuberculosis patients. However, studies assessing the health system delay in treatment of tuberculosis patients in Ethiopia had inconsistent and inconclusive findings. Therefore, this systematic review and meta-analysis aimed to determine the pooled median time of the health system delay in the treatment of tuberculosis and its determinants in Ethiopia. Methods: We systematically searched from different databases: Google Scholar, Science Direct, PubMed, Embase, Scopus and Springer link databases for studies published from June 6, 1997 up to December 20, 2020. The quality of the studies was assessed using the Newcastle-Ottawa scale adapted for observational studies. Heterogeneity was evaluated using I squared statistic. We conducted a meta-analysis for the pooled median time of health system delay and its determinants using random-effects model in R version 4.0.3 software(for median estimation) and Stata version 14 (for metan). The pooled estimates with 95% confidence intervals (CI) were presented using forest plots. Results: A total of 14 studies which comprising 6161 patients satisfying a priori set criteria were included. Our meta-analysis showed that, the estimated pooled median time of the health system delay was 15.29(95%CI: 9.94–20.64) days. In the subgroup analysis, studies conducted from 1997 to 2015 the pooled median health system delay was 21.63(95% CI: 14.38-28.88) days, whereas studies conducted after 2015 the pooled median time of 9.33(95% CI: 3.95-14.70) days. Living in rural area (pooled OR: 2.42, 95%CI: 1.16-5.02) was significantly associated with health system delay. Conclusions: In Ethiopia, patients are delayed more-than two weeks in the treatment of tuberculosis. Being from rural residence was more likely to lead prolonged health system delay. Implementing efforts by targeting rural residence may help to shorten the health system delay and important implications for the success of tuberculosis control.

Patient and health care system characteristics are associated with delayed treatment of tuberculosis cases in Taiwan

Background The decline of the incidence rate of tuberculosis in Taiwan has been partly attributed to the launch of the directly observed therapy short course (DOTS) program in 2006, followed by the DOTS-Plus in 2007. However, with the phasing out of the specialized tuberculosis care system and the declining incidence, clinical workers in Taiwan might become less familiar with the presentation of tuberculosis. Complementing the patient-pathway analysis with health system delay estimates, the objective of this study is twofold: to estimate the alignment between patient care initiation and the availability of prompt diagnostic and treatment services, and to identify the risk factors of delayed tuberculosis treatment. Methods The study population included all Taiwanese patients with incident tuberculosis in 2013. We (1) identified 11,507 incident tuberculosis patients from the 2013 National TB Registry, and (2) linked 10,932 Taiwanese from the registry to the 2012–2013 National Health Insurance Research Database. We assessed patient’s care-seeking pathways and associated the determinants of health system delay in a Cox model. Results The overall health system delay was 46 days. We found that 20.5 and 3.5% of 10,932 tuberculosis patients were diagnosed and treated respectively at the initial visit to seek care for TB-related symptoms. Risk factors related to the prolonged health system delay included female gender (adjusted HR = 0.921, 95% CI: 0.884, 0.960), age > =65 years (adjusted HR = 0.720, 95% CI: 0.692, 0.750), non-severe (chest X-ray without cavities) (adjusted HR =0.721, 95% CI 0.683–0.760), chronic respiratory diseases (adjusted HR = 0.544, 95% CI: 0.522, 0.566), living in long-term care facilities (adjusted HR = 0.580, 95% CI: 0.525,0.640), an initial visit at a primary care clinic (adjusted HR = 0.588, 95% CI: 0.565, 0.612), and living in southern Taiwan (adjusted HR = 0.887, 95% CI: 0.798, 0.987). Conclusions The low access to TB diagnostic and treatment services at the initial visit and the prolonged health system delay indicate inefficiency in the health care system. Strengthening training of physicians at public hospitals and health workers at nursing homes might improve the efficiency and timeliness of tuberculosis diagnosis and treatment in Taiwan.

Tuberculosis’ Total Health care system and patient side diagnosis and Treatment Delay and Associated Factors Among Pulmonary Tuberculosis Patients At Hadiya Zone Public Health Facilities, Southern Ethiopia.

Background: Delay in TB treatment is significant to both disease prognoses at the individual level and within the community. Even though studies conducted in TB treatment delay there is result inconsistencies due to differences in culture, environment and infrastructure. Objective: the aim of the study is to assess the tuberculosis treatment Delay and associated factor among pulmonary tuberculosis patients. Method: Facility based cross sectional study triangulated by Qualitative study was employed on 340 PTB patients in Hadiya zone public health facilities. Three woredas and health facilities were selected by Simple random sampling method. DOTS user at the beginning of data collection was consecutively recruited in to the study until the intended sample size was fulfilled. Multivariable binary Logistic regression was used. A P-value < 0.05 at 95 % CI was considered statistical significance between dependent and predictors variables. Result: Among 340 PTB patients enrolled in the study, of which 49.1% experienced patient delay, 30% health system delay and 49.8% total delay. Unable to read and write, Poor knowledge of TB (AOR 3.96, 95% CI (2.28 6.86), self-treatment (AOR: 2, 95% CI (1.14, 3.93), financial constraint (AOR: 2.092, 95% CI (1.11, 3.945) , Visiting two or more health care providers (AOR: 3.40, 95% CI (1.910 – 6.07), prolonged referral (AOR: 3.004, 95% CI (1.59, 5.67) were independent predictors of delay. Conclusion: Nearly half of the total delay was contributed by patient delay. Unable to read and write, Poor knowledge of TB, self-treatment, financial constraints, prolonged referral, several visit of health care provider of two or more and ever used other drugs rather than Anti-TB drugs were found to have association with patient delay and health system delay. Keywords: Tuberculosis treatment delay, PTB, patient delay and health system delay, Hadiya zone, Ethiopia.