Introduction
Indonesia is experiencing both a shortage and surplus of nurses. A surplus of Indonesian nurses is created when the number of nurses far exceeds the need and demand. Consequently, there is a high rate of unemployment and low bargaining power for nursing graduates. Currently, the average salary of nurses is only slightly above the national minimum wage.
According to the Ministry of Manpower’s (MOM) 2018 report, Indonesia had 695,248 qualified nurses in the sector. However, only 446,428 are employed while the remaining 248,820 are unemployed or looking for employment. Even if the demand for domestic nurses were met, there would still be an excess of 219,257 graduate nurses that year. The demand for domestic nurses was calculated based on the ratio set by the government.
Despite the surplus in qualified nurses, Indonesia is experiencing a shortage of employed nurses. Recent data revealed that the number of employed nurses compared to Indonesia’s total population is still below the ideal. This is further confounded by the uneven distribution of nurses in several regions. This raises several questions: 1) How can there be a simultaneous surplus and shortage of nurses? 2) Why is the demand for nurses not automatically met with the surplus of nurses? 3) How is this issue being currently addressed?
The Surplus—Shortage Paradox
There are at least two reasons behind the surplus of qualified nurses. First, the continued perception that Indonesia is experiencing a critical shortage of nurses. Second, the high rate of development of nurses in Indonesia.
In 2006, WHO included Indonesia in their list of 57 countries experiencing a human resources for health (HRH) crisis. A country was deemed to be experiencing a critical shortage if it possessed less than 80% of the nursing population needed to serve the country’s needs (needs-based sufficiency). Till today, this data is often referred to when formulating health HR policies.
WHO determined that the ideal ratio of employed nurses is 1.58 nurses per 1,000 population. This is different from the Indonesian government’s standard which is 1.80 nurses per 1,000 residents. Despite the differences, both targets have yet to be met till today. The latest data from the Ministry of Health’s (MOH) HRH Information System shows that the number of employed nurses in Indonesia is 356,960 or around 1.30 per 1,000 population. Therefore, to achieve the respective ideal ratios, an additional 75,000 to 135,000 nurses have to be absorbed into the labour market. When compared with the 2018 MOM report, it must be noted that there is no decrease in the number of employed nurses. The difference in figures is primarily due to the different parameters employed by each to define nurses. MOM’s definition included nurses who were not affiliated with any healthcare facilities and were working independently (for e.g. independent home care nurses, etc) whereas MOH’s data was tabulated by nurses who were registered in their HRH information system.
Unfortunately, this demand cannot be immediately be met despite the high number of nursing job seekers. The main issue stems from the suboptimal capability of the domestic market to absorb available nurses. According to the MOM, Indonesia needs an additional 584 hospitals to achieve the recruitment of nurses as set by the government’s 2024 target. The number of new hospitals would have to be revised to 1,958 to absorb all available nurses. However, achieving the 2024 target is already hampered by the government’s and private sector’s limited budget. Though the COVID-19 pandemic has forced large-scale recruitment of nurses, it would still not satisfy the ideal ratio set out by the government nor is sufficient to absorb the entire surplus of nurses.
It is common practice to use nurse-per-population ratio to formulate health HR policies, especially in low- and middle-income countries. This needs-based approach can indeed reveal the number of health workers needed for a population. However, this approach cannot provide a comprehensive picture of the dynamic nature of labour markets.
In the past, there was a tendency for any shortage to be perceived as a result of insufficient supply. It was the result of overreliance towards nurse-per-population which had been widely used in many countries as well as by the WHO. Consequently, in response to the lack of supply, the government increased the production capacity and to train more health workers. In 2008, Indonesia was able to produce 34,000 nurses annually. A decade later, in 2019, the production capacity increased to 138,206 nurses per year (roughly a four-fold increase). However, the increased capacity was unexpectedly unaligned with the absorption capacity of the labour market, resulting in an oversupply, high number of unemployment and loss of competent nurses.
Inadequate Policy Implementation Perpetuates Overproduction
As the policy to train nurses is closely linked to the tertiary education policy, the government implemented several policies to reduce the overproduction. This included closing non-accredited nursing programmes, reducing the quota for new student admissions, and imposing a moratorium on the establishment of new nursing programmes.
In 2019, the government revoked the permits of 130 private universities because of not meeting accreditation standard, ostensibly in an attempt to reducing the number of nursing programmes. Additionally, the moratorium on new nursing programmes has continued since 2011. This moratorium, however, can be waived for regions experiencing a shortage of nurses. Moreover, the establishment of undergraduate and professional nursing programmes is still permitted so long as the applying college has a vocational nursing programme (D3) that is minimally B-accredited.
Unlike these two policies, there has not been any concrete implementation to reduce the quota for new nursing students. Conversely, there has been a tendency to increase this quota annually as the colleges themselves continue to determine it independently. In fact, the Nursing Act regulates the national quota for new admissions of nursing students, as has been implemented for medical and dentistry programmes. However, to this day, the derivative rules regarding this quota have not been promulgated.
Nurse Migration as a Means to Address Surplus
Despite these policies, the production capacity of nurses cannot be drastically reduced immediately. Similarly, the absorption capacity of the labour market cannot be increased in a short period of time. Therefore, to manage the increasing number of nurses graduating annually while the job market remains limited, the Indonesian government has adopted a policy to encourage nurses to migrate. This policy was feasible as there was a global shortage of nurses. In 2014, it was estimated that there was a shortage of 9 million nurses globally.
Between 2013 and 2018, 3.838 Indonesian nurses found employment overseas. The top five destinations were Taiwan (1,446), Saudi Arabia (932), Kuwait (495), Japan (307) and the United Arab Emirates (112). Despite this, migration is still insignificant to impact the existing surplus of nurses. There are several challenges preventing this from being a viable solution. One challenge is that Indonesia is still a “new player” when compared to neighbouring Philippines which has been a top exporter of nurses globally for more than seven decades.
Need for Accurate Data to Drive Policy Changes
The Indonesian government has relied on nurse migration to address the surplus issue. However, there is a need to improve the health HR data management through an integrated information system.
Currently, conflicting data between institutions is a chronic issue in Indonesia. For example, there is a difference of around 50,000 nursing graduates between the data issued by the Ministry of Health (MOH) and the Higher Education Database (PD DIKTI) in 2019. Additionally, the data on employed nurses in 2018 from the MOH and the MOM also differed significantly (around 36,000 difference). In fact, the author found inconsistencies in the number of nurses from documents released by the MOH.
Such inconsistencies have led the Minister of Health himself to be reluctant in using his ministry’s data to facilitate the COVID-19 vaccination programme. Currently, there is a Health Human Resources Information System which includes data of nurses entering and leaving the labour market, as well as active nurses at the national, provincial, and district / city levels. However, this system requires vast improvements such as integrating data on nursing graduates with PD DIKTI and data on vacancies available in the job market. By ensuring the accuracy of such data, more effective policies on the development and employment of nurses can be formulated.
