INTRODUCTION:

All kinds of healthcare activities like diagnosis, treatment or immunization of human beings or animals, and research activities pertaining to that or in the production or testing of biologicals lead to generation of waste. Such wastes are termed as biomedical waste. Improper disposal of such wastes can lead to spread of communicable diseases as pathogens present in the waste infiltrate land and water bodies in the environment, contaminating them. Another problem caused by improper management is pilferage of disposable needles and other medical equipment, which may repackaged and sold, putting unsuspecting people at risk. For these reasons, proper management of BMW is crucial.

Healthcare in India is a booming business. It is growing at a rate of 17% annually and is expected to reach revenues of $300bn by 2022. It contributes roughly 6% to the country’s GDP. This huge economic growth comes with growing volumes of waste generated. The number of HCFs is on the rise, making healthcare accessible to more people and also generating more waste in their treatment. According to CPCB Annual Report Information 2017, There are 2,38,254 healthcare facilities in India, out of which 87,282 are bedded facilities with 20,94,858 beds^[1]. Biomedical waste is being generated at each of these facilities and at each bed. Collecting, moving, and disposing of biomedical waste from each of these locations is an enormous challenge.

Government of India notified the first set of rules governing BMW in July 1998, and it was put forth by the Ministry of environment and forest. These set of rules dealt with issues such as definition, categories of segregation of waste, protection of those handling the waste, treatment of waste etc. ^[2] An amendment to Biomedical Waste Management (BMWM) rules was passed in 2016, These new rules simplified the categorization of BMW and authorization, and improved the segregation, transportation and disposal methods to make it more effective. It also introduced barcoding system to track biomedical waste ^[3]. However, the government regulations are not being met in many healthcare facilities around the country. The reason for the gap needs to be identified.

LITERATURE REVIEW:

Mathur, et al. ^[4] discussed the need for a biomedical waste management system. The sources of biomedical waste, its categorization and disposal are expounded upon. Ira F Salkin et al. ^[5] listed all the health impacts which could occur due to spread of microbial hazards and biomedical waste. A market research report by Velocity MR ^[1]shed light on the healthcare industry and the quanta of waste generated in India. Greesham Tony et al. ^[6] carried out a system analysis of biomedical waste management process in clinics in Udupi Taluk in 2018. The study revealed that majority of the clinics had inadequate biomedical waste management equipment, training and failed to meet the biomedical waste management guidelines.

Sridevi et al. ^[7] discussed the case of study of hepatitis B outbreak in Gujarat in 2009. Over 240 people were infected and 70 succumbed to the disease during the outbreak. The cause of outbreak was identified as use of unsterilized syringes and needles, which were pilfered from used medical equipment. A study was carried out by INCLEN Program Evaluation Network (IPEN) Study Group ^[8]to evaluate the state of biomedical waste management system all over the country. Data was collected from across 20 states of India and found that 82% of primary health centers 60% of secondary, and 54% of tertiary care health facilities had inadequate biomedical waste management. Dr. SushmaRudraswami et al. ^[9] looked into the global statistics of biomedical waste generation. High income regions were found to generate more biomedical waste than low income regions.

A Kumar et al. ^[10] examined the transportation of biomedical waste within a healthcare institution. It was found that waste bags from various locations were not being cleared on time, uncovered trolleys were in use and sharp containers were improperly closed, and only 0.66-1.12% of staff used protective equipment while handling waste.

K Usha Krishnan et al. ^[11]tested the efficacy of the training for biomedical waste management. The results showed that participants found an improvement in practices post training. Matthew et al. ^[12] studied the knowledge, attitude and practices related to BMWM among healthcare personnel and found that healthcare workers were ignorant to biomedical waste management practices and yet injury reporting was low for all groups of healthcare personnel.

Shyam et al. ^[13]and Soni et al. ^[14]implemented IoT Technology in waste management by integrating sensors which collect various types of information into the garbage bin for live monitoring of the state of the waste. Hong et al. ^[15]developed and implemented an IoT based smart garbage system for food waste management and the pilot project showed that food waste could be reduced by 33%. Raundale et al. ^[16]discussed various technologies available to automate management and handling of biomedical waste. IoT based sensors are proposed to collect and store data on biomedical waste which can be used to improve the process.

RESEARCH METHODOLOGY:

The exploratory study of biomedical waste management system was conducted following market research methodology framework. A pilot study was conducted and the changes were incorporated before conduction of final survey. Final survey was conducted for a sample size of 110 and the results were analyzed for relative importance of the factors causing pain points in the biomedical waste management process.

Table 1: Steps in conduction of survey

Survey objectives

· To identify the pain points in existing Biomedical waste management system.

· To establish current market perception of smart solutions in biomedical waste management.

Design and Development of Survey

· Questionnaire - 6 sections :
- General information
- Information on risk awareness and disposal methods
- Factors affecting segregation
- Factors affecting collection
- Factors affecting movement and storage
- Market perception

· Likert 5 point scale used to measure factors.

Content Validity and Pilot Study

• Experts examining the survey items for ambiguity and redundancy

• Survey answered by hospital administrators in charge of biomedical waste management

• Administering Questionnaire

• Questionnaire administered online on smartphones by hospital administrators

• Total Hospitals Approached – 170

• Response received - 110

• Rejected questionnaires - 60

Data Analysis

· Relative importance of each factor in the three categories

· Data stratified into Small HCFs and large HCFs. Differences in median of factors for the two subsets tested using Mann - Whitney U test.

OBJECTIVE OF THE SURVEY:

The objective of the survey is to study pain points in the existing system; perception of IoT enabled waste management systems, and their interest in buying such products or services

Preliminary Study:

For the preliminary study, a survey designed by World Healthcare Organization (WHO) for assessment of biomedical waste management systems around the world was used as the base.A preliminary study was conducted with a sample size of 10 and these were in-depth interviews carried out using the preliminary survey questionnaire. Many changes were suggested by the hospital administrators and doctors. Suggestions were incorporated in the survey. From the pilot study, a generalized biomedical waste management system which is followed by almost all hospitals and clinics was built.

Development and Conduction of Survey:

The development of the survey to identify pain points in the existing system at HCF level was structured on a survey for rapid assessment of biomedical waste management, also developed by WHO. The survey contained questions which categorized the hospital, like private or public and the number of beds in the hospital, collected information on waste generation statistics and Likert scale type questions to test if participants agree that certain factors cause problems in various steps of BMWM occurring in the healthcare facility. Furthermore, they were asked about their perception of smart solutions for BMWM and their interest in availing such product or service if it was within their budgets. These questions were designed to study if HCFs are ready for digitization or automation of BMWM, and how they would respond if one such solution was presented to them.

A convenience sampling approach was used. Clinics or hospitals in areas covering Bangalore North, Bangalore South and Bangalore East were approached for survey, and surveys were conducted in any HCFs willing to participate. Anonymity was ensured in the surveys. 110 responses were collected for the survey. The survey was recorded online and each respondent were approached personally and the survey was filled on smartphones.

Survey Analysis:

The complete set of responses was first analyzed and frequency distributions, means, standard deviations and medians of the various types of questions were arrived at. Then, the responses were stratified based on capacity. Complete analysis which was carried out on the complete set was then carried out on the two subsets. The results were studied comparatively to identify differences.

For the Likert type data, as it is does not assume normal distribution, Kruskal Wallis and Mann Whitney U test (non-parametric tests) was carried out on samples from both subsets to test if the results were statistically different from each other.

RESULTS AND DISCUSSION:

The biomedical waste management was first studied and a general model was built, based on which the survey to identify the pain points was designed. The process is expounded first, and then the results of the survey are tabulated and analyzed.

Biomedical Waste Management – Process:

The following figure depicts the general biomedical waste management process.

Figure 1: Biomedical Waste Management Process

The process begins with waste being generated as a by-product of healthcare functions like treatment, diagnosis etc. It is usually generated by doctors or nurses and the first step of the process – Segregation is carried out by nurses. At the point of generation, the waste is identified and disposed of into the right colored bin according to the color code shown in fig. 2. The Segregated waste in color coded dustbins then undergoes Collection. Wastes from all the bins are collected and moved to a temporary storage, usually outside the hospital premises or in the basement. The waste is moved by healthcare workers from the different locations to the temporary storage. The waste is stored in temporary storage until time for disposal. Regulatory requirements state that waste cannot be stored for more than 48 hours ^[3].

The disposal process may be carried out in on-site or off-site facilities owned by hospitals, if CBWTFs are not available in a radius of 75km.. The right kind of disposal method has to be carried out for each color coded bag as listed in figure 3.

This is the general biomedical waste management process. A bar coding system which is aimed at ensuring waste is accounted for from generation to disposal so that waste is not disposed of illegally or using wrong methods has been introduced by law. It also brings accountability for the waste as any bag of waste can be traced back to the hospital it was generated at. Any discrepancies in the bag of waste have to be reported to the respective state PCB. However, this law is not in enforcement yet and most HCFs have not adopted this system.

Findings of the Survey:

The survey had 110 participants from across Bangalore – Urban district. Fig 4 shows the breakdown of the participants. 101 participants were from private HCFs and 9 were from the public sector. For analysis, the sample was subdivided into small HCFs (Clinics and hospitals under 30 beds) and Large HCFs (Hospitals with more than 30 beds).

Figure 4: Category of HCF and number of beds in HCF

Awareness of risks among personnel handling waste:

The participants were asked to rate the awareness of risks among the person(s) who directly handle BMW, the average rating was 70.68 with a standard deviation of 21.48. Fig. 5 shows the frequency distribution of the responses recorded. These figures are however representative of what the administrators think the awareness of their employees is. These numbers need to be higher as the risk posed by BMW is really high, including contracting fatal diseases and infections.

Figure 5: Awareness of risks among waste handling personnel

Table 2 summarizes the awareness ratings for all HCFs, small HCFs and large HCFs. One can observe that large HCFs have a higher average rating than small HCFs.

Table 2: Summary - Awareness rating

	All HCFs	Small HCFs	Large HCFs
No. of participants	106	73	33
Average	70.68	68.16	76.24
Mean Absolute Deviation	17.16	18.80	12.99
Standard Deviation	21.48	21.10	16.34

Waste Collection Frequency:

The regulatory requirements state that BMW must be stored in the HCF for a maximum of only 2 days. However it was discovered that most small HCFs are storing their BMW for up to 3 days as the waste is being taken by the CBWTFs only every three days, as shown in figure 6, the waste collection by the CBWTF is therefore not meeting regulatory requirements. Clinics and small hospitals have contracts with their CBWTFs asking for collection only every three days to reduce costs. The problem is operational in nature and if costs for collection of waste from hospitals for CBWTFs can be reduced, this cost saving can be passed on to the HCFs by reducing price of a more frequent collection period of every two days. This operational cost reduction can be achieved by smart routing of dispatch trucks to increase collection efficiency.

Table 3 shows the summary percentage of responses for each option for all HCFs, small HCFs and large HCFs. Most of the Small HCFs have collection frequency of every three days, with only 1.42% with everyday collection of waste whereas large HCFs have collection within 2 days for over 75% of them. The waste collection frequency can brought down using IoT technology to track fill level of bins and optimizing collection routing.

Table 3: Waste Collection frequency – Summary table

How often is waste collected by vendor?	All HCFs (%)	Small HCFs (%)	Large HCFs (%)
Everyday	18.5	1.6	51.6
Every 2 days	26.1	26.2	25.8
Every 3 days	45.7	59	19.4
Weekly	9.8	13.1	3.2

Segregation of Biomedical Waste:

Segregation of biomedical waste is the first process which the generated waste undergoes. Improper segregation can lead to improper disposal method being used on the waste. This can have many negative consequences as the waste may not get disinfected and the wrong material may damage the treatment equipment. For example, metals in an incinerator will melt when the incinerator is turned on and form a slag which damages the incinerator. Damaged incinerators may incur significant costs for repair. The respondents were asked to record on a scale of 1 to 100, to what extent they agree with the statement “There is trouble in identifying the right bin to dispose the waste in” and the results are shown in figure 7. One can observe from the frequency distribution that some agree on the lower end of the scale, but some agree on the upper end of the scale. It can be inferred that HCFs do face some problems with the segregation of waste.

There are a few responses near the upper end of the scale, but majority of them are near the lower end of the scale. Small HCFs usually have little to no trouble with collection of waste as the bins are less in number and spread over a smaller location. So it is easy to track waste and collect regularly from all locations. However, it becomes significantly harder as the size of hospital increases. To track waste from hundreds of bins in large facilities becomes an operational challenge. Increasing number of healthcare workers increases cost of operations and is not desirable. The factors and opinion of respondents on the importance of these factors are shown in figure 10.

Figure 10: Factors for irregular collection of waste

The primary factor is considered to be human error, an oversight in collection from bins which is the reason for irregular collection. Lack of information may seem like a major issue in collecting of waste in large HCFs, but the survey results say otherwise as larger hospitals have already planned their internal waste collection by periodic collection instead of only when the bins are full. Therefore, information is not considered necessary for collection of waste from bins.

Another aspect of collection of waste is moving the waste from one point in the facility to other. The factors which could cause problems for moving the waste would be Leaking garbage bags, financial constraints and overfilled bins. The results are shown in figure 11. The general opinion is that these factors are not responsible for any problems in moving the waste. However approaching the issue from the healthcare workers’ perspective might yield deeper insight.

Figure 11: Factors affecting movement of BMW

The temporary storage of BMW is the final process carried out within the HCF. This only involves keeping the BMW in a specially designated area, usually outside the premises of the HCF. Yet, simple storage of waste can have a lot of problems. Some factors and their perception are in figure 12. Bad odor is not considered a factor of the problems faced in storage in general, but the other two factors warrant deeper analysis.

Figure 12: Issues in storage of waste

Stratifying the results into small HCFs and large HCFs, it is observed that small HCFs have more of a problem with lack of space and long storage times (due to infrequent collection by CBWTFs).

The mean and standard deviation goes higher on the scale for small HCFs compared to large HCFs for the factors Lack of space and Long storage times. To test if there is actually a difference between small and large HCFs, Mann Whitney U test was carried out on the data. The results for lack of space and long storage times are shown in Figure 13.

Figure 13: Mann Whitney tests

Based on the results of the Mann Whitney U test, it can be said that at a confidence level of 90%, that there is a difference in the median, the median response for small HCFs being higher than the median response for large HCFs. Therefore they face more of a problem with longer storage times. CBWTFs collect waste from small HCFs every three days usually and once a day usually for large HCFs, as mentioned before. This may be the reason for the long storage times faced by small HCFs. This will be resolved if the earlier mentioned problem of infrequent collection of waste from small HCFs is resolved.

Smart Biomedical Waste Management – Market Perception:

Table 4 summarizes and compares the market perception of all HCFs. The percentage of responses to each option is shown side by side. The survey tried to understand the awareness and interest in a smart biomedical waste management system. Over half of the hospitals were not aware of any such products. This means the awareness of the improvements that such products can have on their operations is also low. It can also be observed that the table shows three quarters of the respondents who answered positively to the previous question were only generally aware of such products. The survey described a smart waste management product/service as “An end-to-end smart biomedical waste management system which monitors the system state, increasing information availability, capable of bar-code monitoring as prescribed by CPCB to track waste throughout the system, and also keeps track of auxiliary information and responsibilities of the healthcare facilities like vaccinations of workers, reports and self-auditing.” And the opinions of people of such a solution were collected. 24.5% of respondents claimed such a solution was a must-have as nothing else could solve their problem. Finally, their interest in buying such a product was gauged. The results show that less than 3% of participants showed negative interest. A quarter of the participants were not sure if they were interested in buying the product or not. Over 70% responded positively, with 58.5% being somewhat interested and the rest being very interested in the solution.

There are problems in the healthcare sector regarding waste management and there is a market for smart solutions provided it is priced low and within the budget of the HCFs, which varies depending on the size of the HCF. Therefore, a scalable solution which can be implemented in clinics as well as large hospitals with over 100 beds would be ideal to capture most of the market.

Table 4: Summary - Market perception

Questions and options	All HCFs (%)	Small HCFs (%)	Large HCFs (%)
Are you aware of any smart waste management products in the market?
Yes	44.86	46.6	41.2
No	55.14	53.4	58.8
If yes, how would you best describe your familiarity with a product/service like that described?
Only generally aware	75.5	82.4	60
Have investigated or researched such products	18.4	14.7	26.7
Have been demoed with a product like this	6.1	2.9	13.3
Have purchased or regularly use a product like this	0	0	0
Which of the following best describes your need for the product?
I really need this product because nothing else can solve this problem	24.5	27.4	18.2
This is a minor improvement over what I currently use	56.6	46.6	78.8
Looks okay but is about the same as what I’m using now	12.3	16.4	3.0
My current product would serve me better	1.9	2.7	0
I am not at all interested in this product	4.7	6.8	0
Based on the description, how interested would you be in buying this new product/service if priced within your budget?
Not at all interested	2.8	4.1	0
Not very interested	0.9	1.4	0
Not sure	24.5	27.4	18.2
Somewhat interested	58.5	58.9	57.6
Very interested	13.2	8.2	24.2

CONCLUSION:

In conclusion, the healthcare sector is a rapidly growing sector in the Indian economy, with increased number of healthcare facilities and increased amount of biomedical waste generated. The management of this waste is problem that needs to be tackled as it may have many negative effects on its environment if not handled and disposed effectively. Implementing smart technology like digitization of information, IoT, ERP etc. can go a long way in increasing operational efficiency and decreasing costs in HCFs. However, the challenge is to achieve it in low costs..

The main pain points in BMWM activities carried out within the facilities is in segregation of waste, which is due to lack of experience, training and human error. With simple decision making aids like posters, charts and other visual aids, such problems can be reduced. Collection of waste is challenging in large hospitals with a large number of beds, but such hospitals have excellent operations which can handle the collection effectively, but not efficiently. Storage of waste is a problem encountered in smaller HCFs due to infrequent collection of waste. This is because smaller HCFs sign contracts with CBWTFs requesting pick up once every three days, although guidelines prohibit storing of waste for over 48 hours. High cost is the main reason for this. Improving routing of trucks and scheduling using smart routing algorithms can improve operational efficiency of CBWTFs and this can translate to lowered costs which can be passed on to the HCFs, so waste collection intervals can be reduced.

The HCFs are only generally aware of smart waste management products so education of customers is important in this market. However, they also show positive response to incorporating smart solutions to help their facilities. There is an interest in such solutions and if priced right, the hospitals are willing to buy and adapt such solutions. There is a feasible market for IoT enabled biomedical waste management solutions in both CBWTFs and HCFs.

ACKNOWLEDGEMENT:

The authors are grateful to the authorities of RV College of Engineering for their support.

CONFLICT OF INTEREST:

The authors declare no conflict of interest.

REFERENCES:

1. Velocity MR, (2018) ‘Unearthing the growth and necessities of biomedical waste management’, ASSOCHAM India, March 2018.

2. Bio-Medical Waste (Management and Handling, 1998) Rules. New Delhi: Government of India Publications; 1998. Ministry of Environment and Forests Notification; pp. 276–84

3. Bio-Medical Waste Management Rules. (2016) Published in the Gazette of India, Extraordinary, Government of India Ministry of Environment, Forest and Climate Change. Notification; New Delhi, the 28th March, 2016

4. Mathur, P., Patan, S., &Shobhawat, A. S. (2012). Need of biomedical waste management system in hospitals-An emerging issue-a review. Current World Environment, 7(1), 117.

5. Ira Salkin, WHO, (2004) ‘A Review of Health Impacts from Microbiological Hazards in Health-Care Wastes’. Geneva: World Health Organization.

6. Tony, G., Kumar, N., Dsouza, B., Kamath, R., & Kamath, S. (2018). System Analysis of Biomedical Waste Management Across Health Care Clinics of Udupi Taluk. Journal of DattaMeghe Institute of Medical Sciences University, 13(4), 199.

7. Seetharam S. (2009) ‘Hepatitis B outbreak in Gujarat: A wake-up call’. Indian J Med Ethics, 6; 120.

8. INCLEN, P. E. N. I., & New, D. (2014). Bio-medical waste management: situational analysis & predictors of performances in 25 districts across 20 Indian States. The Indian journal of medical research, 139(1), 141.

9. Dr. SushmaRudraswamy, Dr. Naganandini Sampath, Dr. Nagabhushana Doggalli, (2013). Global Scenario of Hospital Waste Management. International Journal of Environmental Biology, 2013.

10. A Kumar, S Duggal, R Gur, SR Rongpharpi, S Sagar, M Rani, D Dhayal, CM Khanijo, (2015), Safe transportation of biomedical waste in a health care institution, Indian Journal of Medical Microbiology, pg 383-386.

11. Krishnan, K. U., Devamani, T. S. D., &Jayalakshmi, G. (2015). On the path of continual improvement: an evaluation of biomedical waste management training. Indian journal of medical microbiology, 33(5), 119.

12. Mathew, S. S., Benjamin, A. I., &Sengupta, P. (2011). Assessment of biomedical waste management practices in a tertiary care teaching hospital in Ludhiana. Healthline, 2(2), 28-30.

13. G. K. Shyam, S. S. Manvi and P. Bharti,(2017) "Smart waste management using Internet-of-Things (IoT)," 2017 2nd International Conference on Computing andCommunications Technologies (ICCCT), Chennai, pp. 199-203.

14. Soni, G., &Kandasamy, S. (2017, December). Smart garbage bin systems–a comprehensive survey. In International Conference on Intelligent Information Technologies (pp. 194-206).

15. Hong, I., Park, S., Lee, B., Lee, J., Jeong, D., & Park, S. (2014). IoT-based smart garbage system for efficient food waste management. The Scientific World Journal, 2014.

16. Raundale, P., Gadagi, S., & Acharya, C. (2017, July). IoT based biomedical waste classification, quantification and management. In 2017 International Conference on Computing Methodologies and Communication (ICCMC) (pp. 487-490). IEEE.

Received on 11.05.2019 Modified on 16.06.2019

Asian Journal of Management. 2019; 10(3): 181-189.

DOI: 10.5958/2321-5763.2019.00029.5