Take home message
  • Bed occupancy rate is a critical indicator of hospital utilization.
  • Kuwait’s Ministry of Health (MOH) should explore patients’ opinions and views on cancer care.
  • Using precision medicine technologies to guide treatment may improve patient outcomes.

Introduction

Cancer morbidity and mortality cases in Kuwait are reported to be 3,582 and 1,658 cases respectively in 2018, and projected to constitute 5.38 % of all-mortalities by 2030.1 The Ministry of Health (MOH) in Kuwait provides universal healthcare at two levels. Firstly, care is delivered through local affiliated hospitals and secondly, further care is delivered through overseas treatment which paid by the MOH. Cancer cases treated abroad compromised 28% of all overseas treatment cases and the reasons for preferring overseas treatment over local care have been well explored by a previous Kuwaiti study in 2018.2 At local level, cancer care is delivered mainly through Kuwait Cancer Control Center (KCCC) which includes 199 fixed beds and distributed as 72 beds for radiotherapy, 62 beds for chemotherapy, 45 beds for surgical oncology, 8 beds for bone marrow transplantation and 12 beds for palliative and intensive care unit (ICU). However, a detailed investigation about the utilization of these services and related health expenditures in Kuwait is lacking. We aim to fill this gap in literature by investigating the expenditure and utilization patterns of cancer care in Kuwait.

Methods

We obtained utilization and expenditure data from the KCCC in MOH for three consecutive years from 2015 to 2017. The utilization data were obtained from the hospital administration department. The utilization data were sorted into four categories; Inpatient care, outpatient care, operating room and ancillary departments. Indicators from inpatients care included admissions, average length of stay (LOS) and occupancy rate which is calculated as percentage ratio of total inpatient-days/number of bed days in one calendar year.3 Indicators from outpatient care and operating room were number of visits and number of hours spent operating on cases respectively. The main indicators for ancillary departments such as radiology, laboratory and pharmacy were number of films, tests and drugs dispensed respectively.

Expenditure data were obtained from Budget Control and Financial Affairs Department in MOH which followed a top-down approach for cost estimation and reported in both Kuwaiti Dinars (KWD) and United States Dollars (USD). The expenditure was sorted into five categories; total MOH and hospital expenditures, inpatient care expenditure, outpatient care expenditure, operating room and ancillary departments expenditures.

In addition, hospital expenditure was adjusted for both inflation rate and population growth to identify any significant changes in the size of expenditure over study period. Conversely, total admission rate and total outpatient visits were adjusted for population growth to identify any significant changes in the level of utilization over study period.

In order to add more clarity to the overall results of the study, we investigated past records from the National Center for Health Information in MOH to identify the most common causes of admissions and mortalities due to cancers in the years 2015, 2016 and 2017.

Results

The most common causes for admissions for the three consecutive years were consistently the same. They are ranked in descending order as follow; Firstly, blood cancers including leukemias and lymphomas, secondly, breast cancers, thirdly, metastases and fourthly, colorectal cancers. On the other hand, the most common causes of mortalities due to cancer are ranked and compiled in Table-1, which shows varying trends while collectively the same.

Table 1.Most common cancer mortalities
Rank 2015 2016 2017
1 Colorectal Breast Lung
2 Lung Colorectal Colorectal
3 Breast Lung Breast
4 Blood Blood Blood
5 Liver Liver Liver

Utilization indicators are shown in Table-2. Within the inpatient care, chemotherapy ward beds had been the most occupied beds compared to beds in other wards, next was ICU beds and surgical ward beds followed by radiotherapy ward beds. This high occupancy rate in chemotherapy ward is attributed to high admission and turnover rates, which is clearly seen at the background of having the lower LOS. Meanwhile radiotherapy wards consistently had the highest LOS among all inpatient wards. Furthermore, the busiest outpatient clinics in descending order were chemotherapy, radiotherapy and surgery clinics. The most striking change in the utilization patterns seems to be the very sharp increase in operating hours in 2017, despite having the rate of admissions and LOS slightly changed.

Table 2.Utilization indicators
Category Indicator Care type 2015 2016 2017
Inpatient care Occupancy rate (%) Radiotherapy wards 47.9 61.1 60.2
Chemotherapy wards 73.9 76.1 74.7
Surgical oncology wards 62.3 64.2 66.1
Spinal marrow transplant wards 43.9 33.6 46.4
Intensive care Unit wards 65.2 73 65.6
Average Length of Stay (days) Radiotherapy wards 12.7 12.4 12.5
Chemotherapy wards 9.6 10.6 9.9
Surgical wards 5.9 6.4 6.6
Spinal marrow wards 10.9 12.6 9.6
Intensive Care Unit wards 4.2 6.2 5.5
Admissions Radiotherapy wards 12,594 16,094 15,825
Chemotherapy wards 16,718 17,265 16,903
Surgical wards 10,226 10,577 10,857
Spinal marrow wards 1,281 984 1,354
Intensive Care Unit wards 2,855 3,208 2,875
Outpatient care Visits Radiotherapy clinic 20,917 22,379 20,438
Surgical clinic 9,874 11,607 11,939
Nuclear medicine clinic 6,878 6,139 5,828
Chemotherapy clinic 22,844 24,263 22,013
Haemato-oncology clinic 6,642 6,782 7,318
Endocrine-oncology clinic 6,525 6,133 2,865
Operating Room Hours 3,830 3,945 11,749
Ancillary departments Films Radiology 42,554 47,778 49,076
Tests Laboratory 309,778 675,990 2,186,291
Drug dispensed Pharmacy 17,635,285 19,460,104 20,850,902

On the other hand, findings from expenditure data are shown in Table-3. In 2015, the hospital expenditure represented 2.6% of the total MOH expenditure which increased to 3% in 2016 before it decreases again to 2.8% in 2017. Chemotherapy and radiotherapy inpatient as well as outpatient care had consistently incurred the highest costs compared to other forms of care. The surgical care costs exhibited a slight increase over the years but no striking change.

Table 3.Expenditure and costs in KWD (and USD)
Category Care type 2015 2016 2017
Ministry of Health 1,643,372,456
(5,308,093,033)
1,547,189,971
(4,997,423,606)
1,676,416,166
(5,414,824,216)
KCCC 42,575,479
(137,518,797)
45,974,355
(148,497,167)
47,248,386
(152,612,287)
Inpatient care Radiotherapy wards 4,039,170
(13,046,519)
4,838,719
(15,629,062)
4,835,673
(15,619,224)
Chemotherapy wards 9,285,848
(29,993,289)
10,961,151
(35,404,518)
11,302,333
(36,506,536)
Surgical wards 2,860,966
(9,240,920)
3,250,411
(10,498,828)
3,226,540
(10,421,724)
Spinal marrow wards 761,285
(2,458,951)
605,235
(1,954,909)
585,171
(1,890,102)
Intensive Care Unit wards 1,470,710
(4,750,393)
1,574,096
(5,084,330)
1,530,927
(4,944,894)
Outpatient care Radiotherapy clinic 4,265,329
(13,777,013)
4,770,859
(15,409,875)
5,027,693
(16,239,448)
Surgical clinic 2,588,361
(8,360,406)
2,911,774
(9,405,030)
3,033,757
(9,799,035)
Nuclear medicine clinic 2,849,180
(9,202,851)
2,945,752
(9,514,779)
3,124,100
(10,090,843)
Chemotherapy clinic 7,584,667
(24,498,474)
7,514,671
(24,272,387)
8,006,676
(25,861,564)
Haemato-oncology clinic 715,560
(2,311,259)
796,691
(2,573,312)
845,061
(2,729,547)
Endocrine-oncology clinic 679,864
(2,195,961)
762,374
(2,462,468)
846,271
(2,733,455)
Operating room 3,146,357
(10,162,733)
3,343,436
(10,799,298)
3,566,426
(11,519,556)
Ancillary department Radiology 1,574,489
(5,085,599)
1,672,232
(5,401,309)
1,893,149
(6,114,871)
Laboratory 5,205,351
(16,813,284)
6,983,952
(22,558,165)
7,607,631
(24,572,648)
Pharmacy 785,755
(2,537,989)
812,839
(2,625,470)
874,914
(2,825,972)

When utilization indicators in the forms of total inpatient admissions rate and total outpatient visits were adjusted for population growth, the lines pattern clearly shows that utilization increased in the period 2015-16 before it declined in 2017 as shown in figure 1. Further, a sharp decline was strikingly evident in the outpatient services utilization.

Figure 1
Figure 1.Utilization rates before and after adjustment

Similarly, the expenditure data in terms of total hospital expenditure was adjusted for population growth and inflation growth as shown in figure 2. Expenditure pattern was found consistent with the utilization pattern. We observed an increase in expenditure by 1.1% in 2016, before it declined by 1.9% in 2017.

Figure 2
Figure 2.Hospital expenditure before and after adjustment

Discussion

Bed occupancy rate is a critical indicator of hospital utilization. Larger hospitals can entertain higher occupancy rates than smaller ones because smaller hospitals need to maintain a protection level or safety margin for a swift variation in admissions and urgent needs for beds in acute cases.4 During our study period, the National Health Services in England reported a bed occupancy rate between 87-90% for their general and acute care, raising concerns about the impact on quality of care and protection level.5 In another report the average occupancy rate was found to be around 51.3% in a tertiary care hospital in Pakistan, with variation in rates among different wards from as high as 66.2% to as low as 17.5%, the latter raises concerns about inefficiency and underutilization of hospital beds.6 While in Thailand, a study investigated 16 general hospitals and reported an average occupancy rate of 81%.7 Our utilization data seems to follow a middle pattern among the aforementioned reported rates, while exhibiting a potential room for improvement. More importantly, occupancy rate is also an indicator of patient outcomes. One percent increase in occupancy rate was found to increase the probability of pressure ulcers and hospital-acquired pneumonia by 4.3% and 2.4% respectively.7 In addition, higher occupancy rate was associated with higher mortality rate in a study from 39 hospitals in the United States.8 An occupancy rate of 80-100%, showed 55% higher rate of hospital-acquired infectious diarrhea compared to 0-69.9% baseline occupancy rate in a study from the United Kingdom.9 Nevertheless, some authors argue that obsessing about occupancy rate alone and giving it a universal benchmark rate around which resources are either under or overutilized is wrong view. Instead, the tradeoff between occupancy rate and access to bed should be viewed at the background of dynamic variations in contributing factors such as number of admissions and length of stay in a way that when there are lower variations then a high occupancy rate can be operated.10 We think latter view is also incomplete and missing a key point which is perspective. One perspective is wider and retrospectively looking at and judging one-year overall performance, while the other perspective is narrower and looking at day-to-day operational efficiency. Both perspectives complement and complete each other.

The adjusted expenditure and utilization graphs clearly show that year 2016-17 had lower hospital utilizations and expenditures compared to 2015-16. The decline can be the result of shifting of utilization and costs from KCCC to Overseas treatment as cancer patients constituted 28% of overseas treated patients provided by the government in 2018. About 64% of those patients reported their choice for overseas treatment was due to the availability of more advanced medical technology abroad.2 Precision medicine technology and usage of real-world data provide wide diagnostic and therapeutic applications that can significantly improve patients’ outcomes and satisfaction.11 One such application is genetic testing to identify chemotherapy drug resistance, therefore avoiding unnecessary toxicity and side effects from ineffective treatment and matching patients based on their genotype profile to the right treatment from the first time, rather than going through trials of different lines of treatment sequentially as per clinical guidelines.12 Currently, KCCC follows rigid clinical guidelines in the treatment of patients as no specialized infrastructure or research for precision medicine is available.13 It is imperative for MOH to invest in these technologies to retain more patients at local level.

Our data also indicate the impact of costing method used in healthcare setting. While the operating hours spent in operating room have dramatically increased threefold in 2017 compared to previous years perhaps due to increased complexity of cases, this was not reflected on the costs incurred in that same year. The reason for this is costing method used was top-down costing, thus time was not factored into the cost estimation as should be done in other methods such as time-driven activity-based costing (TDABC) leading to underestimation of the actual service costs.14 A cost analysis study of surgical cases where TDABC was used showed variation in the actual costs of same surgical procedure across different hospitals. The variation of costs for the same procedure was mainly attributed to hours spent by the operating surgeon in each case.15

One major limitation in this study is that we were examining data from 5 to 7 years ago. However, it may also be a strength of this study, since the data is from pre-COVID-19 pandemic era, which rules out data distortion and disruption caused by the pandemic.

Another limitation of this study is that some surgical cancer cases are performed in other major hospitals requiring no further care or referral to KCCC which were not included in the presented data of this study.

Conclusion

This study is the first of its kind in Kuwait. Several recommendations can be made to improve patients’ retention, hospital utilization, efficiency and public trust in cancer care in Kuwait. Firstly, MOH needs to explore patients’ opinions and views specifically on cancer care in Kuwait. Secondly, we call for implementation of precision medicine technologies and patient outcomes research to guide physicians for optimal patient care. Consequently, we believe this will lead to improvements to the financial and operational performance of cancer care in Kuwait.


Conflict of Interest

None

Funding information

N/A

Ethical statements

N/A

Acknowledgment

N/A

Author contribution

  • Salem Abuhadida and Saud Alzaid: conception and design
  • Barrak Alhindal: data collection and assembly
  • Salem Abuhadida: data analysis
  • All authors: manuscript writing

All authors have approved the manuscript.