| Literature DB >> 30782889 |
Archana Siddaiah1, Mohammad Naseer Ahmed2, Ajay M V Kumar3,4, George D'Souza5, Ewan Wilkinson6, Thae Maung Maung7, Rashmi Rodrigues1,8,9.
Abstract
OBJECTIVES: India contributes approximately 25% of the 'missing' cases of tuberculosis (TB) globally. Even though ~50% of patients with TB are diagnosed and treated within India's private sector, few are notified to the public healthcare system. India's TB notification policy mandates that all patients with TB are notified through Nikshay (TB notification portal). We undertook this study in a private hospital to assess the proportion notified and factors affecting TB notifications. We explored barriers and probable solutions to TB notification qualitatively from health provider's perspective. STUDYEntities:
Keywords: TB notification; mixed-methods research; operational research; private medical college; qualitative research
Mesh:
Year: 2019 PMID: 30782889 PMCID: PMC6377518 DOI: 10.1136/bmjopen-2018-023910
Source DB: PubMed Journal: BMJ Open ISSN: 2044-6055 Impact factor: 2.692
Figure 1Flow of patients seeking TB care at a private tertiary care teaching hospital in Bengaluru, India. AFB, acid-fast bacilli; AKT4, anti-TB medication; DOT, direct observed treatment; ICD-10, International Classification of Diseases 10th Revision; MRD, Medical Records Department; RNTCP, Revised National Tuberculosis Control Programme; TB, tuberculosis; TBHV, TB health visitor.
Figure 2Flow chart showing various data sources and proportion of tuberculosis (TB) notified to Revised National Tuberculosis Control Programme (RNTCP) from a private tertiary care teaching hospital in Bengaluru, India, 2015–2016. DMC, designated microscopy centre; DOT, direct observed treatment; EPTB, extrapulmonary tuberculosis register; LIS H, laboratory information system-histopathology; LIS R, laboratory information system-radiology; MRD, Medical Records Department; PIS, pharmacy information system; Xpert, GenXpert MTB/RIF.
Demographic profile of patients with TB diagnosed and/or treated from 2015 to 2016 at a private tertiary care teaching hospital in Bengaluru, India
| Variable | n (%) | Notified (%) |
| Total | 3820 (100) | 885 (23.2) |
| Age (years) | ||
| 0–14 | 264 (6.9) | 24 (9.1) |
| 15–24 | 476 (12.5) | 118 (24.8) |
| 25–34 | 802 (21.0) | 166 (20.7) |
| 35–44 | 670 (17.5) | 159 (23.7) |
| 45–54 | 598 (15.7) | 160 (26.8) |
| 55–64 | 503 (13.2) | 129 (25.6) |
| 65 and above | 507 (13.3) | 129 (25.4) |
| Sex | ||
| Male | 2320 (60.7) | 559 (24.1) |
| Female | 1500 (39.3) | 326 (21.7) |
| Residence | ||
| Within state | 2362 (61.8) | 567 (24.0) |
| Outside state | 1358 (35.5) | 293 (21.6) |
| Not available | 100 (2.6) | 25 (25.0) |
| Marital status | ||
| Unmarried | 1008 (26.4) | 183 (18.2) |
| Married | 2604 (68.2) | 653 (25.1) |
| Others | 208 (5.4) | 49 (23.6) |
| Year diagnosed | ||
| 2015 | 2071 (54.2) | 482 (23.3) |
| 2016 | 1749 (45.8) | 403 (23.0) |
| Inpatient | ||
| Yes | 1009 (26.4) | 137 (13.6) |
| No | 2811 (73.6) | 748 (26.6) |
| Department (n=1009) | ||
| Medicine | 484 (48.0) | 64 (13.2) |
| Pulmonary medicine | 141 (14.0) | 21 (14.9) |
| Paediatrics | 81 (8.0) | 16 (19.8) |
| Neurology | 88 (8.7) | 5 (5.7) |
| General surgery | 41 (4.1) | 5 (12.2) |
| Orthopaedics | 50 (5.0) | 8 (16.0) |
| Others | 124 (12.3) | 15 (12.1) |
| Source of patients with TB* | ||
| Sputum microscopy register | 747 (19.6) | 481 (64.4) |
| Extrapulmonary TB positive register | 124 (3.2) | 24 (19.4) |
| Histopathology database | 203 (5.3) | 53 (26.1) |
| Radiology database | 92 (2.5) | 13 (13.7) |
| Pharmacy database | 1754 (45.9) | 341 (19.4) |
| Culture register | 227 (5.9) | 72 (31.7) |
| GenXpert MTB/RIF register | 91 (2.4) | 38 (41.8) |
| Inpatient database | 1009 (26.4) | 137 (13.6) |
*Cumulative percentage may add up to more than 100 since one patient could have tested positive by more than one diagnostic method.
TB, tuberculosis;
Factors associated with TB notification at a private tertiary care teaching hospital in Bengaluru, India, from 2015 to 2016
| Variable | Total | Notification | Crude PR | P value | Adjusted PR | P value |
| Total | 3820 | 885 (23.2) | – | – | – | – |
| Age (years) | – | – | – | – | – | – |
| Children (<15) | 264 | 24 (9.1) | 1 | – | 1 | – |
| Adults (≥15) | 3556 | 861 (24.2) | 2.6 (1.8 to 3.9) | 0.000* | 1.5 (1.0 to 2.2) | 0.039* |
| Sex | – | – | – | – | – | – |
| Female | 1500 | 326 (21.7) | 1 | – | – | – |
| Male | 2320 | 559 (24.1) | 1.1 (0.9 to 1.2) | – | – | – |
| Marital status | – | – | – | – | – | – |
| Unmarried | 1008 | 183 (18.2) | 1 | – | 1 | – |
| Married | 2604 | 653 (25.1) | 1.3 (1.1 to 1.5) | 0.000* | 1.0 (0.9 to 1.2) | 0.240 |
| Others | 208 | 49 (23.6) | 1.2 (0.9 to 1.7) | 0.066 | 1.1 (0.8 to 1.4) | 0.346 |
| Inpatient | – | – | – | – | – | – |
| No | 2811 | 748 (26.6) | 1 | – | 1 | – |
| Yes | 1009 | 137 (13.6) | 0.4 (0.4 to 0.5) | 0.000* | 1.0 (0.8 to 1.2) | 0.925 |
| Residence | – | – | – | – | – | – |
| Within state | 2362 | 567 (24.0) | 1 | – | ||
| Outside state | 1358 | 293 (21.6) | 0.8 (0.7 to 1.0) | 0.092 | – | – |
| Not recorded | 100 | 25 (25.0) | 1.0 (0.7 to 1.4) | 0.819 | – | – |
| Year diagnosed | – | – | – | – | – | – |
| 2015 | 2071 | 482 (23.3) | 1 | – | – | – |
| 2016 | 1749 | 403 (23.0) | 0.9 (0.8 to 1.1) | 0.866 | – | – |
| Sputum smear microscopy | – | – | – | – | – | – |
| Positive | 747 | 481 (64.4) | 4.8 (4.4 to 5.4) | 0.000* | 4.7 (4.1 to 5.3) | 0.000* |
| Others | 3073 | 404 (13.1) | 1 | – | 1 | – |
| EPTB microscopy register | – | – | – | – | – | – |
| Positive | 124 | 24 (19.4) | 0.8 (0.5 to 1.1) | 0.318 | – | – |
| Others | 3696 | 861 (23.3) | 1 | – | – | – |
| Culture | – | – | – | – | – | – |
| Positive | 227 | 72 (31.7) | 1.4 (1.1 to 1.7) | 0.001* | 1.0 (0.8 to 1.2) | 0.855 |
| Others | 3593 | 813 (22.6) | 1 | 1 | ||
| GenXpert MTB/RIF | – | – | – | – | – | – |
| Positive | 91 | 38 (41.8) | 1.8 (1.4 to 2.3) | 0.000* | 1.1 (0.9 to 1.3) | 0.295 |
| Others | 3729 | 847 (22.7) | 1 | – | 1 | |
| Histopathology database | – | – | – | – | – | – |
| Present | 203 | 53 (26.1) | 1.1 (0.8 to 1.4) | 0.299 | – | – |
| Others | 3617 | 832 (23.0) | 1 | – | – | – |
| Radiology database | – | – | – | – | – | – |
| Present | 92 | 13 (13.7) | 0.5 (0.3 to 0.9) | 0.038* | 0.7 (0.4 to 1.2) | 0.285 |
| Others | 3725 | 872 (23.4) | 1 | – | 1 | – |
| Pharmacy database | – | – | – | – | – | – |
| Present | 1754 | 341 (19.4) | 0.7 (0.6 to 0.8) | 0.000* | 0.9 (0.8 to 1.0) | 0.839 |
| Others | 2066 | 544 (26.3) | 1 | 1 |
*Significant p value.
EPTB, extrapulmonary tuberculosis; PR, prevalence ratio; TB, tuberculosis.
Barriers and solutions identified for TB notification at a private tertiary care teaching hospital in Bengaluru, India, 2015–2016
|
| Solutions |
| Patients with TB diagnosed by culture, histopathology, radiology, BAL usually missed | Integration of LIS |
| Incomplete notification among inpatients | Triangulation of TB data from all possible sources |
| MDR TB missed | Proper documentation and communication which helps in notification |
| Lack of dedicated manpower | Appointment of notification officer |
| Non-DOT not notified | Referral of all patients started on ATT by the treating doctor to the notification officer |
| Knowledge issues | Awareness about notification communicated |
| Lack of capacity building | Refresher trainings about Nikshay |
| Absence of hospital notification policy and standard operating procedure | Institutional notification policy |
| Inadequate networking between stakeholders | Having single notification desk with dedicated telephone number |
| Patient confidentiality concerns | Patient counselling about the importance of notification, ensuring adequate cyber security |
| Duplication of data | Unique identifier (such as social security number, Aadhaar number in India) to prevent duplication that helps notify, track and retain patient in care |
ATT, anti-TB treatment; BAL, bronchoalveolar lavage; DOT, directly observed treatment short course; LIS, laboratory information system; MDR TB, multidrug-resistant tuberculosis.
A brief description of the framework used in the qualitative data analysis for understanding TB notification at a private tertiary care teaching hospital in Bengaluru, India, 2015–2016
| Thematic framework components and quotes | Codes | Summary | Categories | Subthemes | Themes* |
|
| Perception that confirmation from IRL is a must for putting on MDR regimen, without which such patients cannot be notified and hence will be put on non-DOT. | Inability of RNTCP staff to notify patients positive for MDR by GenXpert MTB/RIF due to unclear instructions related to RNTCP accreditation of laboratory. | MDR TB not notified due to unclear instructions. | Quality issues interfere with multidrug-resistant TB notification. | 1 |
|
| Standard operating procedures involved in notification unknown. | Lack of knowledge about the process of notification and assuming somebody else has to notify. | Lack of knowledge regarding notification. | Notification is someone else’s responsibility. | 2 |
|
| Gaps in notification. | Refresher training on Nikshay has not been given to the RNTCP staff involved in notification even when new forms have been updated in the software. | Lack of basic training in Nikshay. | Gaps in user training for the notification portal Nikshay. | 3 |
|
| Triangulation of patients diagnosed or treated from all departments. | Scope for integrating electronic medical records with case diagnosis which will ease notification. | Technical solutions to improve notification. | Record linkage through unique identification numbers. | 4 |
*Theme 1—traditional diagnostic procedures promote notification of patients with TB. Theme 2—misconceptions regarding notification and its process are common in healthcare providers. Theme 3—despite a national notification system, other factors prevented notification of all patients. Theme 4—establishing hospital systems for notification will go a long way in improving notifications.
ATT, anti-TB treatment; DOT, directly observed treatment short course; IRL, Intermediate Reference Laboratory; MDR TB, multidrug-resistant tuberculosis; RNTCP, Revised National Tuberculosis Control Programme.