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| ORIGINAL ARTICLE |
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| Year : 2018 | Volume
: 6
| Issue : 3 | Page : 73-77 |
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An analysis of health economics related to hospital-associated infections: A prospective case–control analysis of 7-year data from a tertiary referral corporate hospital in India
Murali Chakravarthy1, Raj Gore2, Navin Yellappa3, Antony George4, Sukanya Rangaswamy5, Rajathadri Hosur3, Sumant Pargaonkar3, Chidananda Harivelam3, Priyadarshini Senthilkumar6, Tejaswini Saravanan6, Suganya Arul Rose6
1 Director, Clinical Affairs, Fortis Hospitals, BG Road, Bengaluru, Karnataka, India
2 Chief Operating Officer, Fortis Hospitals, BG Road, Bengaluru, Karnataka, India
3 Infection Research Fellow, Fortis Hospitals, BG Road, Bengaluru, Karnataka, India
4 Consultant Anesthesiologist, Fortis Hospitals, BG Road, Bengaluru, Karnataka, India
5 Infection Control Officer, Fortis Hospitals, BG Road, Bengaluru, Karnataka, India
6 Infection Control Nurse, Fortis Hospitals, BG Road, Bengaluru, Karnataka, India
| Date of Web Publication | 4-Mar-2019 |
Correspondence Address:
Dr. Murali Chakravarthy
Fortis Hospitals, Bannerghatta Road, Bengaluru - 560 076, Karnataka
India
 Source of Support: None, Conflict of Interest: None  | Check |
DOI: 10.4103/jpsic.jpsic_20_18
Objective: Healthcare associated infections cause significant morbidity, mortality and escalation of cost of care. It is the responsibility of all concerned to work towards reducing this potentially preventable increase in morbidity, mortality and cost caused by healthcare associated infections. Such data in Indian subcontinent has been studied sparingly. The objective of this study was to understand the degree of the cost escalation, morbidity and mortality associated with healthcare associated infections.
Design: This prospective case controlled observational study was carried out from the year 2007 onwards. All the infections that occurred unto 2014 were included. Cost, morbidity and mortality of two similar matched controls for each infected case were chosen.
Setting: Tertiary referral hospital.
Participants: All patients with healthcare associated infections and twice that number as control.
Interventions: None.
Main outcome measure: Escalation of cost, morbidity and mortality due to healthcare.
Results: There were five hundred fifteen infections during the study period. The escalation of cost due to infection was $ 4611. The mean mortality in the infected group was 8.75% in contrast to 2.5 in the non infected group. The mortality due to central line associated blood stream infection and ventilator associated pneumonia was more than 30% each. The length of stay in the intensive care unit was 8 days in the infected group in contrast to 2.27 days in the non infected group. Length of stay in the hospital was 33.5 days in the infected patients in contrast to 10.3 days in the non infected group.
Conclusions: Healthcare associated infections caused escalation of cost, length of stay in the intensive care unit and hospital. Mortality in the infected cohort was more in contrast to the controls.
Keywords: Catheter-associated urinary tract infection, central line-associated bloodstream infection, cost, healthcare-associated infections, length of stay, mortality, surgical site infection, ventilator-associated pneumonia
How to cite this article:
Chakravarthy M, Gore R, Yellappa N, George A, Rangaswamy S, Hosur R, Pargaonkar S, Harivelam C, Senthilkumar P, Saravanan T, Rose SA. An analysis of health economics related to hospital-associated infections: A prospective case–control analysis of 7-year data from a tertiary referral corporate hospital in India. J Patient Saf Infect Control 2018;6:73-7 |
How to cite this URL:
Chakravarthy M, Gore R, Yellappa N, George A, Rangaswamy S, Hosur R, Pargaonkar S, Harivelam C, Senthilkumar P, Saravanan T, Rose SA. An analysis of health economics related to hospital-associated infections: A prospective case–control analysis of 7-year data from a tertiary referral corporate hospital in India. J Patient Saf Infect Control [serial online] 2018 [cited 2023 Jun 7];6:73-7. Available from: https://www.jpsiconline.com/text.asp?2018/6/3/73/253385 |
| Introduction | |  |
Healthcare-associated infection (HAI) is the bugbear of health-care industry. The HAIs are a major concern more than ever because the treating options of antibiotics are drying out and there are none in the pipeline. In the very near future, the challenge of HAIs could assume Himalayan proportion and threaten the existence of the human race itself. The four HAIs that are typically studied using standardised definitions are surgical site infections (SSI), central line-associated bloodstream infections (CLABSI), ventilator-associated pneumonia (VAP) and catheter-associated urinary tract infections (CAUTI). The HAIs have become topical because of their association with morbidity, mortality and the cost.[1],[2],[3] HAIs are potentially preventable, every HAI levies huge toll on the patients, families, health-care institutions. In contrast to the non-inflected individuals, infected ones suffer from substantial morbidity as well as mortality while simultaneously incurring extra costs. The additional expenses incurred due to HAIs are neither clearly known nor easily measurable. There are many elements that are not measurable surrounding HAIs; they are loss of brand value, loss due to opportunities lost and loss of employee morale. Many countries have studied and understood the economics of infection; it varies from one country to another. However, such data are unknown in India. It is important to know the economics of HAIs not only for the economy sake but to put the issue of HAIs on appropriate priority healthcare. The objective of this case–control study was to assess the additional expenses incurred because of HAI.
| Methods | | |
All the HAIs that were encountered at our centre during the years 2007–2014 were prospectively studied. The HAIs were defined as per the guidelines of the Centers for Disease Control and Prevention (CDC). The prevailing definitions at various time periods were used. The hospital policy (as per CDC guidelines) about change of central lines, endotracheal tubes, ventilator tubing and urinary catheters were followed as applicable at that prevailing time. Every infection was investigated by the hospital infection prevention and control committee. For every infected patient treated as 'case', two non-infected individuals were considered controls; they matched by age, sex, comorbidities, type of surgery and the time period. The following data were collected: patient's details such as inpatient number, age, sex, length of stay (LOS) in the intensive care unit (ICU), hospital and the total bill at the time of discharge. Concessions, discounts and waiver offered to the patients were not taken into consideration for the study. The bill was further sectored under the following headings: Bed charges (as levied by the hospital prevailing at the time of data collection), expenses due to purchase of medications (such as but not restricted to antibiotics), fees paid to the doctors, bedside procedures (such as but not restricted to bronchoscopy, bronchoscopic aspiration lavage, tracheostomy, change of wound dressing and blood transfusion), consumables/disposables used (such as but not restricted to dressing material, suction catheters, change of urinary catheter/central venous line and tracheostomy tube) and laboratory investigations (such as but not restricted to arterial blood gases, chest radiographs, culture sensitivity and organ-specific biomarkers). The same parameters were recorded in the controls as well. The case and control data were collected every quarter. The analysis was made at the end of 8 years.
Statistical methods
The number of patients were tabulated according to the type of HAI and the year of their admission. The percentage increase in cost, compared to 'controls' were estimated. Further, the type of hospital-acquired infections was further broken down based the cost incurred under various heading mentioned above. These subheadings were analysed for cases in contrast to controls. R version 3.3.1 (R foundation for statistical computing, Vienna, Austria) was used for statistical analysis. Further statistical analysis was deemed unnecessary because this study was considered a prospective cost audit.
| Results | | |
During the 8 years of study from 2007 to 2014, there were 133, 241 discharges from the hospital and 515 HAIs. The distribution of infection, total number of discharged patients that year and the attack rate ([number of infections/number of discharges] ×100) mentioned in percentage are as shown in [Table 1]. Although the number of infections annually increased, the attack rate decreased from 1.241 in 2007 to 0.283 in 2014. One thousand four cases without HAIs were then prospectively chosen; they were case, sex, morbidity, surgery and time period of procedure matched. An effort to match at least two controls per case was made. The total mean cost of the cohort is shown in [Table 2]. The difference was $4611 per infected case, and the mean percentage increase in cost due to infections was 217% (range 21%–180%). The increase in the cost of infection ranged from $1017 to 8714. [Table 2] shows the total cost incurred and percentage increase in the total cost due to infection. The cost of infection over the years 2007–2014 is shown in [Table 3]. The mean cost of infection was $7186.5 (range $3249 in 2007 to $19042 in 2014). The mean cost in the non-infected cohort was $2268 (range 465 in 2007–4289 in 2014). The mean percentage difference of infected and non-infected was 344 (ranged from 72% in 2009 to 366% in 2012). [Figure 1] shows the trend of number of infections, the cost of infections and attack rate over the years. [Table 4] shows the break-up of the category of cost in infected, non-infected patients, difference in cost and percentage of difference. The categories were bed charges, pharmacy, doctors' consultation charges, bedside procedures and investigations (laboratory, pathological and radiological). A miscellaneous category was created for billing purpose when disposable items used were not billed on a day-to-day transaction. The cost in all the categories analysed in the infected group was always higher in contrast to the non-infected cohort. The cost difference in descending order was pharmacy, bedside procedures, bed charges and investigations. Interestingly, the consultation fees of doctors did not form a major portion of the increased cost. The miscellaneous cost difference in percentage was high, but the absolute value was not. | Table 3: Costs in infected and non-infected patients, cost due of infection and the percentage difference
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 | Figure 1: The number of hospital-associated infections, attack rate and costs
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 | Table 4: The break-up of cost per category in infected, non-infected patients, difference in cost in US $ and percentage of difference
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[Table 5] shows the mortality, LOS in the hospital and ICU over the years for the infected and non-infected patients. The mean mortality in the infected group was 8.75% in contrast to the non-infected group with 2.5%. The number of deaths decreased from 10 in 2007 to 2 in 2011 but increased in the recent years. The mean LOS-ICU for the infected patients was 8 days in contrast to the non-infected with 2.27 days, and the mean LOS-hospital was 33.5 and 10.3 days, respectively for the infected and non-infected patients. [Table 6] describes the mortality, LOS ICU and hospital with respect each category of infection. It may be noted that the mortality, LOS ICU and hospital for CLABSI and VAP were high in contrast to CAUTI and SSI. It is interesting to note that mortality, LOS ICU and LOS hospital in were higher in each infection in contrast to the non-infected cohort. | Table 5: The mortality, length of stay in the hospital and intensive care unit over the years
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 | Table 6: Mortality, length of stay intensive care unit and hospital in each category of infection
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| Discussion | | |
In this study, cost of care, LOS (in the ICU and hospital) and mortality increased in the patients who suffered HAIs. The mean cost of treatment without infection in our cohort was $ 2268, while it was $ 7186 for HAIs; the additional cost incurred due to infection was $ 4918 (additional cost due to infection was 217% more). LOS hospital and ICU in the infected patients in our study were consistently higher. Mortality was higher in all the HAIs and significantly so with CLABSI (30% with infection vs. 1.4% without) and VAP (34% with infection vs. 3.7 without). The cost of infection is always higher globally in infected patients. An estimated $ 250 million was spent on HAIs at Massachusetts alone.[4] Similar observations were made from other states in the United States.[5],[6],[7] It is known that the rate of HAIs in India is substantially more in contrast to the developed countries.[8],[9] However, there are very few studies from India assessing the cost economics of HAIs. In a study from India, Singh and coworkers noted the costs similar to ours. They observed: VAP with an extra expense of $1358 followed by SSI at $1173; CLABSI at $843 and CA-UTI at $561.[10] Yet another cost analysis from ICU of India showed an increase in the cost by about $ 1880 due to HAIs.[11] The rates of infections are higher in India, and the higher health-care cost due to them make HAIs prohibitive. One could understand the impact of HAIs on a resource-poor country like India. This factor alone perhaps should draw the attention of the hospital administrators and state departments in ensuing infection control at all levels in India.
Although the decreasing trend of attack rate indicated correct direction of the infection control process [Figure 1] and [Table 5], [Table 6], the cost, LOS (in the ICU and hospital) and mortality increased during the study. This brings us to the issue that if HAIs occur despite all the measures and processes to control, loss due to the cost, morbidity and mortality becomes unreasonable. In this study, typically, the morbidity and mortality of VAP and CLABSI stood out, while SSI and CAUTI were neither as expensive nor as morbid. In their study, Chacko and coworker, even CAUTI appeared to significantly cause mortality.[11] Perhaps, these differences occur due to different patient sub-sects. The authors' institute is majorly a surgical centre catering to the surgical needs of those with reasonable health status, but with a surgical problem.
The cost break up of escalation in care is shown in [Table 4]. The excess cost in infections is contributed majorly by bed charges, pharmacy bills and purchase of consumables (single-use devices). There are several other costs that go unmeasured, they are, costs of stay and travel of the relatives of the patient, cost of morbidity and mortality, cost due to loss of earning. In addition, the health-care workers, health-care institutions and the state at large, stand to lose by HAIs. The impact of cost, morbidity and mortality caused by HAIs will perhaps be felt at all levels of healthcare service. Loss of brand and image value of the health-care institution is immeasurable and could impact the healthcare delivery system in the long term.
Limitations of the study
This study did not measure the other costs, such as those due to morbidity and prolonged hospital stay. The mental agony, loss of earning and emotional stress to the patients and their relatives is not only hard to measure, but the cost could be huge.
| Conclusions | | |
HAIs cost patients, health-care institution and the nation. Despite appropriate preventive measures, should HAI occur, the cost of it, morbidity and mortality justify that they are indeed 'deadly and costly'.
Financial support and sponsorship
Nil.
Conflicts of interest
There are no conflicts of interest.
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| 3. | Haley RW, Emori TG. The employee health service and infection control in US hospitals, 1976-1977. II. Managing employee illness. JAMA 1981;246:962-6. |
| 4. | Stone PW, Kunches L, Hirschhorn L. Cost of hospital-associated infections in Massachusetts. Am J Infect Control 2009;37:210-4. |
| 5. | Umscheid CA, Mitchell MD, Doshi JA, Agarwal R, Williams K, Brennan PJ, et al. Estimating the proportion of healthcare-associated infections that are reasonably preventable and the related mortality and costs. Infect Control Hosp Epidemiol 2011;32:101-14. |
| 6. | Anderson DJ, Pyatt DG, Weber DJ, Rutala WA; North Carolina Department of Public Health HAI Advisory Group. Statewide costs of health care-associated infections: Estimates for acute care hospitals in North Carolina. Am J Infect Control 2013;41:764-8. |
| 7. | Amin A. Clinical and economic consequences of ventilator-associated pneumonia. Clin Infect Dis 2009;49 Suppl 1:S36-43. |
| 8. | Singh S, Chakravarthy M, Rosenthal VD, Myatra SN, Dwivedy A, Bagasrawala I, et al. Surgical site infection rates in six cities of India: Findings of the international nosocomial infection control consortium (INICC). Int Health 2015;7:354-9. |
| 9. | Jaggi N, Rodrigues C, Rosenthal VD, Todi SK, Shah S, Saini N, et al. Impact of an international nosocomial infection control consortium multidimensional approach on central line-associated bloodstream infection rates in adult intensive care units in eight cities in India. Int J Infect Dis 2013;17:e1218-24. |
| 10. | Singh S, Kumar RK, Sundaram KR, Kanjilal B, Nair P. Improving outcomes and reducing costs by modular training in infection control in a resource-limited setting. Int J Qual Health Care 2012;24:641-8. |
| 11. | Chacko B, Thomas K, David T, Paul H, Jeyaseelan L, Peter JV, et al. Attributable cost of a nosocomial infection in the intensive care unit: A prospective cohort study. World J Crit Care Med 2017;6:79-84. |
[Figure 1]
[Table 1], [Table 2], [Table 3], [Table 4], [Table 5], [Table 6]
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