Step one to diagnosis

Over the last century, diagnostic testing has evolved into an essential component of standard medical practice with diagnosis becoming one of the important keys to treatment. Diagnostic testing involves a series of steps with the first one being sample collection and transportation to the testing facility.

To describe it further, diagnostic testing occurs in five phases: pre-pre-analytic, pre-analytic, analytic, post-analytic, and post-post-analytic phase. Errors related to diagnostic testing can occur in any of these five phases. The pre-analytic phase which involves sample collection, patient identification, sample transportation, and sample preparation has been identified as a key point of error and vulnerability in the workflow, contributing to 70% of all mistakes in laboratory diagnostics[1][2]. These errors can be attributed to various reasons including delays in sample transportation, inadequate sample quality and quantity, and lack of compliance by technicians to good laboratory practices.

Sample storage and transportation, the Indian scenario

In India, an individual with symptoms suggestive of any disease usually makes multiple visits to the peripheral health institutes (PHI) before a definitive disease diagnosis is made and treatment is initiated. Delay occurs in every phase in the continuum of care, the critical one being diagnosis. For example, as per a systematic review, delays in diagnosis and treatment of pulmonary tuberculosis in India ranged from 36.0 to 118.0 days, out of which diagnostic delays were a significant contributor.[3] The time lag in transporting samples from the collection point to the diagnostic lab can be a significant factor in overall diagnostic delays.[4] Also, these samples may not be stored

under proper conditions, leading to degradation and loss of viability. Such multifaceted challenges in diagnostic sample logistics, as outlined below, are behind the country’s 38th rank in the World Bank’s Logistic Performance Index 2023.[4]

Lack of access to diagnostics in remote areas

Nearly 80% of the enumerated laboratories in India are in urban areas, highlighting the urban bias in concentration and the potential lack of access to diagnostic services in rural areas.[5] As a result of the uneven distribution, the capability to conduct medical diagnostics rapidly drops in remote regions leaving out a large rural population. A recent report also highlights the fact that those in rural areas seeking healthcare services must often travel distances of up to 100 km to access them.[6]  

Dependency on cold chain

While central diagnostic laboratories are well equipped to conduct high throughput and high-quality tests, their potential is often underutilized, in large part because of the absence of efficient cold chains for sample transportation, that results in poor sample quality. Maintenance of cold chain, especially in the rural, hilly, and small towns is a major challenge. In addition to the limited resources, electricity supply is often erratic, further exacerbating inequity in the access to diagnostics services. For example, the temperature range for cold chain used in TB sputum transportation is between 12-20°C. Disrupting the cold chain during specimen transport activities can lead to specimen degradation and decrease the accuracy of testing or therapeutic potency.[7] Maintenance of cold chain equipment also poses significant challenges in terms of high energy cost, power deficit in rural areas, uneven distribution of capacity and logistical support.  

Sample transportation issues

Transportation challenges include safety hazards during transit, leaks, breakage, and temperature fluctuations, all of which can compromise the integrity of diagnostic specimens.[8] Laboratory samples are exposed to various risks, including contamination, during transportation, which can affect the accuracy of diagnostic results.[9] A study conducted in 2022-2023 on TB sputum samples revealed a contamination rate of 4.1%, 7.1% and 8.3% for Optimal (0-7 days), Delayed (8-14 days), and Extended delay (>15 days) samples respectively, i.e., culture contamination rate tended to increase with number of days taken for sample movement from collection to processing.[10] Pneumatic tubes, commonly used for efficient medical sample transport, pose a risk of preanalytical errors due to the samples experiencing rapid accelerations, gravitational forces, and sudden decelerations, potentially causing stress or rupture of plasma membranes in erythrocytes and lymphocytes.[11] A study that aimed to identify indicators affecting laboratory turnaround time (TAT refers to the time interval from when the sample is received at the laboratory to when the verified and released report is dispatched) showed that the most common reason for the delay was found to be the transport delay followed by machine breakdown followed by problems in machine maintenance and oversight by technical staff.[12] Transport delays to the laboratory can give rise to clinically important errors if transport conditions are not optimized.[13]

Sample storage issues

Inadequate storage conditions, such as temperature, humidity, or lighting, can lead to sample contamination by external factors such as bacteria or other substances which can cause samples to degrade, leading to inaccurate test results. In certain cases, changes might occur in biomarker concentrations, which can cause stress or rupture of plasma membranes of cells, such as erythrocytes and lymphocytes, impacting the accuracy of test results.[14]

Opportunities and way forward

  • Strengthening the specimen referral system
The specimen referral process in India involves a systematic approach to transferring clinical specimens from collection points to diagnostic laboratories. Ensuring timely specimen collection and transportation to the nearest diagnostic center is a key challenge to be tackled in many states in India.  Tuberculosis is an excellent example of the value of efficient and reliable specimen referral systems. A definitive tuberculosis diagnosis often has to rely on sputum smear microscopy in conditions without specimen transit networks, a technique that misses up to half of all tuberculosis cases. For those patients who miss it, accessible options include self-transport to a higher level of care (sometimes at a cost of more than a week’s income per trip), empiric treatment (with 6 months of medications for an unconfirmed diagnosis) or accepting the disease’s natural fatal consequences. While efforts are being made to develop more sensitive diagnostic tests that can be done at the point of care, the cost of decentralization is likely to prevent these tests from being implemented for decades. In short, a lack of appropriate specimen transport systems is responsible for hundreds of thousands of tuberculosis deaths each year.[15] Thus, strategies to make sure each and every medical sample reaches the diagnostic facility must be implemented at every level and periodically monitored to ensure its success.

 

  • Developing and supporting innovative technological solutions
There is a need for the development of innovative solutions for the preservation of the quality and the integrity of the specimens during their referral to the testing site as well as for the elimination of the cold-chain dependency.  These tools should allow the preservation of clinical specimens at ambient temperature and be compatible with both conventional and molecular diagnostics. Funding and continued research and development will be key pillars for these solutions to become a reality. Recent focus has been around developing optimal transport media/devices for preservation of the sample to be used for molecular diagnosis.[16]

For Example, the TB SendCard is an innovative sputum storage and transportation device which can be used for DNA extraction in all NAAT based TB testing platforms. It is currently being evaluated for its biosafety feature with the support of India Health Fund.[17] Efforts to include temperature and humidity data recorders in these tools as a mechanism of monitoring sample quality may also be explored. Another recent example is from a study in Nepal which evaluated the impact of a novel transport reagent OMNIgene SPUTUM (OMS) in resource-limited settings: a zonal hospital and a national tuberculosis reference laboratory based in Nepal. The study findings revealed that OMS reduced culture contamination from 12% to 2%, and improved TB detection by 9%. The results also suggested that OMS could perform well as a no cold chain, long-term transport solution for smear and culture testing.[18]

Overall, these efforts seem promising in terms of the ability of these innovations to reduce the biosafety risk by minimizing, inactivating, or neutralizing the disease-causing microbe without compromising diagnostic sensitivity of the testing platform. Additional potential benefits of developing such solutions may include their use in drug resistance surveys where samples need to be collected also from remote and hard to reach areas and where logistic problems related to sample storage and transportation often affect the quality of the survey results. These steps have important implications for National health programs by significantly reducing the costs related to sample storage and transport, increasing access to testing, improving quality of testing and shortening the turn-around-time and time to treatment. This in turn can lead to increasing the program capacity to reach populations living in settings with poor access to diagnostic facilities and ultimately by improving the management of patients by reducing the likelihood of providing multiple samples for disease testing.

About the Author:

Dr Aishwarya is a public health professional who is currently working in the diagnostics vertical as an Associate: Portfolio & Programs at India Health Fund. She is a physiotherapy graduate from Seth GS Medical College & KEM Hospital, Mumbai & a Master’s in Public Health in Health Administration from the Tata Institute of Social Sciences, Mumbai. She has worked in various domains of healthcare such as physiotherapy, program implementation, program monitoring, research & community engagement.

Views expressed are personal.

References:

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  2.  Alavi, N., Khan, S. H., Saadia, A., & Naeem, T. (2020). Challenges in Preanalytical Phase of Laboratory Medicine: Rate of Blood Sample Nonconformity in a Tertiary Care Hospital. EJIFCC, 31(1), 21–27.
  3. Sreeramareddy, C. T., Qin, Z. Z., Satyanarayana, S., Subbaraman, R., & Pai, M. (2014). Delays in diagnosis and treatment of pulmonary tuberculosis in India: a systematic review. The international journal of tuberculosis and lung disease : the official journal of the International Union against Tuberculosis and Lung Disease, 18(3), 255–266. https://doi.org/10.5588/ijtld.13.0585

  4. 2023 | Logistics Performance Index (LPI). (n.d.). https://lpi.worldbank.org/international/global

  5. Gupta, P., & Nandraj, S. (2023). Challenges and gaps in regulating medical laboratories in India. Medical Law International, 23(4), 351-367. https://doi.org/10.1177/09685332231194199
  6. Player, J. (2023, July 26). Healthcare access in rural communities in India – Ballard Brief. Ballard Brief. https://ballardbrief.byu.edu/issue-briefs/healthcare-access-in-rural-communities-in-india

  7.  Lowe, D. E., Pellegrini, G., LeMasters, E., Carter, A. J., & Weiner, Z. P. (2020). Analysis and modeling of coolants and coolers for specimen transportation. PloS one, 15(4), e0231093. https://doi.org/10.1371/journal.pone.0231093

  8. https://www.cdc.gov/safelabs/resources-tools/Safety_Challenges_Specimen_Collection_Transport_Accessioning_Storage.html
  9. https://www.labmate-online.com/news/laboratory-products/3/breaking-news/sample-transportation-in-laboratory-explained/57329
  10.  Eliya, T. T., Ugwu, C., John, B., Emmana, B., Jonathan, K., Adeoola, A. B., … James, E. (2023). Impact of Sputum Transit Time on TB Isolation and Culture Contamination Rate. The Global Health Network Collections. https://doi.org/10.21428/3d48c34a.c7202307
  11. Felder, Robin. (2011). Preanalytical Errors Introduced by Sample-Transportation Systems: A Means to Assess Them. Clinical chemistry. 57. 1349-50. 10.1373/clinchem.2011.172452.

  12.  Bhartia, S., Wahi, P., & Goyal, R. (2019). Reducing delay in laboratory reports for outpatients from 16% to <3% at a non-profit hospital in New Delhi, India. BMJ open quality, 8(4), e000547. https://doi.org/10.1136/bmjoq-2018-000547

  13. Astion ML, Shojania KG,Hamill TR. Classifying laboratory incident reports to identify problems that jeopardize patient safety. Am J Clin Pathol2003; 120:18- 26.

  14. A, E. (n.d.). Pre analytical errors as quality indicators in clinical laboratory. https://austinpublishinggroup.com/public-health-epidemiology/fulltext/ajphe-v3-id1048.php#Top

  15. David W. Dowdy, Minding the Gap: Specimen Referral Systems for Diagnosis of Infectious Diseases, Clinical Infectious Diseases, Volume 64, Issue 6, 15 March 2017, Pages 804–805, https://doi.org/10.1093/cid/ciw820

  16. Saini, V., Kalra, P., Sharma, M., Rai, C., Saini, V., Gautam, K., Bhattacharya, S., Mani, S., Saini, K., & Kumar, S. (2021). A Cold Chain-Independent Specimen Collection and Transport Medium Improves Diagnostic Sensitivity and Minimizes Biosafety Challenges of COVID-19 Molecular Diagnosis. Microbiology spectrum, 9(3), e0110821. https://doi.org/10.1128/Spectrum.01108-21

  17. https://www.indiahealthfund.org/annual-report/
  18.  Maharjan, B., Shrestha, B., Weirich, A., Stewart, A., & Kelly-Cirino, C. D. (2016). A novel sputum transport solution eliminates cold chain and supports routine tuberculosis testing in Nepal. Journal of epidemiology and global health, 6(4), 257–265. https://doi.org/10.1016/j.jegh.2016.04.002

Publication Date: 11th Jan 2021

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