Abstract
Background
On February 19, 2024, approximately 10,000 junior doctors in Republic of Korea (= South Korea) resigned en masse, in protest of newly announced government healthcare policies. This abrupt reduction in the medical workforce may have compromised healthcare accessibility and caused delays in major surgical procedures and critical care. This study aimed to assess the nationwide impact of the resignation on the provision of medical services in Korea.
Methods
Monthly intervention volumes for Diseases & Practices of National Interest (DPNI) were obtained from the Health Insurance Review and Assessment Service for the period from January 2019 to August 2024. The impact of the mass resignation on intervention volumes was evaluated using interrupted time series segmented regression analysis, by level of medical institution.
Results
Of the 20 DPNIs, 16 met the inclusion criteria. Thirteen DPNIs exhibited immediate reductions in intervention volumes at tertiary hospitals following the mass resignation, with decreases ranging from 18.7% to 62.9% relative to pre-resignation monthly averages. In contrast, no immediate decline was observed for hemodialysis for chronic renal failure, cerebral thrombectomy, and liver cancer surgery. No immediate changes were observed in non-tertiary general hospitals. Long-term effects could not be reliably assessed due to the limited number of post-resignation data points.
Conclusion
The mass resignation of junior doctors was associated with substantial and immediate reductions in healthcare service provision across multiple clinical specialties, particularly in tertiary hospitals. The absence of immediate effects for certain DPNIs likely reflects their lower reliance on junior doctors, as well as the urgency or structural characteristics of these interventions. These findings highlight the need for health policies that address unmet healthcare needs and mitigate potential adverse health outcomes resulting from delayed or foregone medical services.
Keywords: Delivery of Health Care, Health Workforce, Policy, Physicians, Public Health Infrastructure, Korea
Graphical Abstract
INTRODUCTION
On February 19, 2024, approximately 10,000 junior doctors in Republic of Korea (= South Korea) resigned collectively in protest against newly announced government healthcare policies, including a substantial expansion of medical student enrollment quotas.1 By December 2024, the number of physicians employed at five major tertiary hospitals had declined from 7,132 in December 2023 to 4,570, representing a 35.9% reduction. This decrease was largely attributable to sharp declines in the numbers of interns and residents, which fell by 92.3% and 89.9%, respectively.2 Korea has historically maintained one of the shortest waiting times among OECD countries,3 with patients being accustomed to this level of accessibility. However, the abrupt contraction of the medical workforce is likely to compromise healthcare accessibility and result in delays in major surgical procedures and the delivery of critical care.
There has been ongoing debate regarding the ethical justification of strikes by medical workforce. It is argued that such actions should be conducted within boundaries of not causing significant harm to patients.4 However, evidence suggests that strikes by medical personnel may lead to reductions in hospital admissions and outpatient visits, as well as delays in treatment delivery.5 In Korea, during the 2020 doctors’ strike, both the length of stay6,7 and the number of consultations6 among patients visiting emergency room declined. Similarly, the mass resignations of junior doctors in 2024 has been associated with patient discomfort,8,9 increased burdens on remaining physicians10,11,12 and other healthcare workers,11,12 diminished research output,11,13 and financial challenges faced by tertiary hospitals.14
Although prior research has examined the effects of mass resignation on healthcare service delivery, most studies have been limited to specific institutions or individual clinical specialties. Reported impacts include reductions in pediatric emergency department visit at a tertiary hospital15 and nationwide decrease in emergency departments visit,16 as well as declines in thoracic surgery volumes17 and claims for high-complexity surgery.18 Although national mortality rates appeared largely unaffected by the residents’ walkout,19 a comprehensive, nationwide analysis of healthcare service provision across diverse specialties remains lacking. Focusing on physician-delivered healthcare services, rather than health outcomes, allows for a more direct evaluation of the influence of mass resignation while minimizing confounding factors, such as patient comorbidities, involvement of other healthcare personnel, and health system resilience. For example, a single-center study conducted at a cerebrovascular specialty hospital reported increases in onset-to-arrival and onset-to-operation times during the crisis, whereas arrival-to-operation intervals and three-month functional outcomes for patients with acute hemorrhagic stroke remained stable.20 Furthermore, in settings where the long-term health consequences of reduced service provision cannot be readily evaluated, monitoring changes in healthcare service supply provides the most direct approach for assessing the impact of such disruptions.
Accordingly, this study aimed to evaluate the nationwide impact of the mass resignation of junior doctors on the provision of major healthcare services. Changes in the volume of physician-delivered medical services were examined using an interrupted time series (ITS) analysis. Through this approach, the study seeks to contribute to a broader understanding of the social consequences associated with mass resignation of junior doctors.
METHODS
Data source
The number of interventions recorded by the Korea Health Insurance Review and Assessment Service (HIRA) served as a proxy for the volume of physician-delivered medical services and was therefore considered representative of nationwide healthcare provision. Monthly intervention counts for Diseases & Practices of National Interest (DPNI) were obtained from the HIRA Healthcare Big Data Open System (https://opendata.hira.or.kr/op/opc/olapMfrnIntrsIlnsBhvInfoTab3.do). HIRA reports 20 DPNIs (Supplementary Table 1), including items requested by the National Assembly, governmental agencies, and the media.21 Definitions of the diseases and practices included in each DPNI are provided in Supplementary Table 2. Data spanning January 2019 through August 2024 were used for analysis.
Statistical analysis
Descriptive statistics for DPNIs were summarized using medians with interquartile ranges or means with standard deviation, as appropriate. Comparisons of continuous variables were performed using the t-test. To estimate the impact of the mass resignation of junior doctors on intervention volumes, ITS segmented regression analysis was conducted. All estimated coefficients were reported with 95% confidence intervals, and the corresponding mathematical equation is provided in Supplementary Data 1. Potential seasonality was adjusted through stepwise autoregression.22 Analyses were performed using PROC AUTOREG code with the option ‘nlag=13 backstep.’
The event date was defined as February 2024, corresponding to the mass resignation that occurred on February 19, 2024. Given that junior doctors were predominantly employed at tertiary hospitals, we assumed that the impact would differ by institution levels; therefore, analyses were stratified by institution type. As ITS analysis requires a minimum of 100 observations per data point,23 DPNIs with fewer than 100 monthly observations at each institutional level were excluded (Supplementary Table 1). Hospitals and clinics were excluded due to insufficient observation counts. Ultimately, 16 out of the 20 DPNIs from tertiary hospitals and non-tertiary general hospitals (hereinafter referred to as general hospitals) were retained for analysis.
Sensitivity analysis was performed to assess the robustness of the findings. The coronavirus disease 2019 (COVID-19) period (February 2020–April 2023) and the 2020 doctors’ strike (August–September 2020) were incorporated into the ITS model to account for potential confounding events. All statistical analyses were conducted using SAS software, version 9.4 (SAS Institute Inc., Cary, NC, USA), and a P value less than 0.05 was considered statistically significant.
Ethics statement
The DPNI data are publicly accessible without administrative restrictions and contains no personally identifiable information. As their use poses no risk to individuals, this study was exempted from Institutional Review Board (IRB) review (reviewing institutions: Catholic Medical Center IRB; No. MC25ZISI0022). No informed consent was required from patients due to the nature of public data.
RESULTS
Characteristics of DPNIs
Table 1 summarizes the monthly intervention volumes for 16 included DPNIs. With the exception of hemodialysis for chronic renal failure, all DPNIs comprised surgical procedures. Intervention volumes varied considerably by institutional levels, with most DPNIs predominantly performed in tertiary hospitals. Among these, ten DPNIs in tertiary hospitals and six in general hospitals had median monthly intervention counts exceeding 500.
Table 1. The number of interventions per month by Diseases & Practices of National Interest.
| Diseases & Practices of National Interest | Tertiary hospitals | Non-tertiary general hospitals |
|---|---|---|
| Liver cancer surgery | 1,666.5 (1,547.0–1,754.5) | 435.0 (395.0–457.5) |
| Pancreatic cancer surgery | 160.0 (134.5–172.0) | 41.5 (36.0–46.5) |
| Thyroid cancer surgery | 1,511.5 (1,382.5–1,599.5) | 735.0 (607.5–811.0) |
| Colorectal cancer surgery | 1,121.5 (1,051.5–1,171.0) | 528.5 (480.0–556.5) |
| Urinary tract stone surgery | 1,073.0 (1,010.5–1,142.0) | 3,913.5 (3,661.5–4,140.0) |
| Benign prostatic hyperplasia surgery | 268.5 (235.0–295.5) | 328.5 (300.5–357.0) |
| Ovarian cancer surgery | 163.0 (147.5–176.5) | 72.0 (62.0–83.0) |
| Endometrial cancer (uterine corpus cancer) surgery | 163.5 (143.5–180.5) | 66.5 (61.5–74.0) |
| Uterine fibroid surgery | 965.5 (853.0–1,049.5) | 1,169.0 (1,054.5–1,267.5) |
| Cervical cancer surgery | 167.0 (154.0–181.0) | 87.0 (77.0–94.5) |
| Cerebral aneurysm surgery | 743.5 (660.0–849.5) | 368.5 (346.0–404.5) |
| Cerebral thrombectomy | 200.0 (181.0–214.5) | 256.5 (217.0–291.0) |
| Hemodialysis for chronic renal failure | 42,191.5 (40,882.5–43,390.5) | 193,288.0 (180,810.5–206,115.5) |
| Gastric cancer surgery | 927.5 (847.0–1,002.5) | 289.5 (262.5–323.5) |
| Breast cancer surgery | 1,991.0 (1,824.0–2,146.0) | 718.5 (656.5–799.5) |
| Lung cancer surgery | 795.5 (707.5–870.0) | 188.5 (174.0–209.0) |
Values are presented as median (Q1–Q3).
Comparison of the monthly intervention volumes before and after mass resignations
Monthly intervention volumes were compared between the pre- and post-resignation periods, stratified by DPNI and institution level (Table 2). Most DPNIs exhibited differences between the two periods; however, no observable changes were identified for three DPNIs in tertiary hospitals and five DPNIs in general hospitals.
Table 2. Comparison of the number of interventions per month by Diseases & Practices of National Interest before and after mass resignation.
| Diseases & Practices of National Interest | Tertiary hospital | Non-tertiary general hospitals | ||||
|---|---|---|---|---|---|---|
| Pre-resignation perioda | Post-resignation periodb | P | Pre-resignation perioda | Post-resignation periodb | P | |
| Liver cancer surgery | 1,676.3 ± 148.9 | 1,445.1 ± 112.9 | < 0.001 | 431.3 ± 45.0 | 394.6 ± 52.3 | 0.049 |
| Pancreatic cancer surgery | 158.1 ± 23.5 | 127.0 ± 10.6 | 0.001 | 40.0 ± 8.2 | 59.1 ± 13.1 | < 0.001 |
| Thyroid cancer surgery | 1,516.1 ± 146.8 | 1,140.7 ± 106.9 | < 0.001 | 698.2 ± 122.7 | 895.4 ± 98.4 | < 0.001 |
| Colorectal cancer surgery | 1,130.0 ± 106.0 | 897.0 ± 55.7 | < 0.001 | 518.3 ± 50.4 | 575.6 ± 61.5 | 0.007 |
| Urinary tract stone surgery | 1,096.1 ± 93.2 | 703.4 ± 67.9 | < 0.001 | 3,920.4 ± 375.7 | 4,091.7 ± 393.6 | 0.259 |
| Benign prostatic hyperplasia surgery | 273.5 ± 35.7 | 156.7 ± 16.1 | < 0.001 | 334.7 ± 48.8 | 318.0 ± 20.6 | 0.113 |
| Ovarian cancer surgery | 165.1 ± 20.6 | 141.3 ± 16.9 | 0.005 | 71.0 ± 13.2 | 81.4 ± 15.5 | 0.057 |
| Endometrial cancer (uterine corpus cancer) surgery | 165.1 ± 24.3 | 140.0 ± 15.2 | 0.010 | 67.1 ± 9.3 | 75.9 ± 14.1 | 0.029 |
| Uterine fibroid surgery | 986.6 ± 142.2 | 512.6 ± 99.1 | < 0.001 | 1,180.0 ± 143.1 | 1,067.4 ± 111.6 | 0.049 |
| Cervical cancer surgery | 171.2 ± 18.3 | 117.9 ± 6.6 | < 0.001 | 86.3 ± 14.2 | 90.0 ± 13.3 | 0.514 |
| Cerebral aneurysm surgery | 765.4 ± 108.6 | 587.9 ± 112.9 | < 0.001 | 368.5 ± 37.5 | 417.7 ± 43.3 | 0.002 |
| Cerebral thrombectomy | 199.4 ± 23.1 | 195.6 ± 11.2 | 0.667 | 250.4 ± 45.3 | 295.3 ± 23.2 | 0.012 |
| Hemodialysis for chronic renal failure | 42,178.8 ± 1,757.4 | 42,006.0 ± 1,433.3 | 0.803 | 190,687.0 ± 14,371.9 | 215,173.0 ± 9,191.9 | < 0.001 |
| Gastric cancer surgery | 939.8 ± 118.3 | 697.4 ± 55.2 | < 0.001 | 287.7 ± 40.0 | 312.4 ± 50.5 | 0.137 |
| Breast cancer surgery | 1,991.3 ± 255.9 | 1,968.0 ± 146.7 | 0.815 | 712.9 ± 105.7 | 1,088.4 ± 180.6 | 0.001 |
| Lung cancer surgery | 796.8 ± 105.5 | 698.4 ± 60.9 | 0.019 | 184.5 ± 23.8 | 242.7 ± 43.3 | 0.012 |
Values are presented as mean ± standard deviation.
aJanuary 2019 to January 2024. bFebruary 2024 to August 2024.
ITS segmented regression for monthly numbers of interventions by DPNIs
The results of ITS analysis are presented in Table 3. In tertiary hospitals, 13 DPNIs exhibited immediate level changes following the mass resignation, whereas liver cancer surgery, cerebral thrombectomy, and hemodialysis for chronic renal failure showed no immediate effect. Among the affected DPNIs, the magnitude of immediate declines ranged from 18.7% to 62.9%. In contrast, no immediate impact was observed for any DPNI in general hospitals. Although trend changes following the mass resignation were observed for several DPNIs in both levels, interpretation of these findings was limited by the small number of post-resignation data points. Figs. 1, 2, 3 illustrate monthly intervention volumes and ITS estimates for each DPNI by the institutional levels. The sensitivity analysis yielded results consistent with the primary analysis after accounting for the COVID-19 period and the 2020 doctors’ strike (Supplementary Table 3), supporting the robustness of the study findings.
Table 3. Results of interrupted time series segmented regression for the number of interventions per month by Diseases & Practices of National Interest.
| Diseases & Practices of National Interest | Baseline trenda | Immediate effect of mass resignationb | Ratio of immediate effect of mass resignation to baseline trendc | Slope change after mass resignationd | |
|---|---|---|---|---|---|
| Tertiary hospital | |||||
| Liver cancer surgery | −4.18 (−5.43 to −2.92)* | −152.88 (−317.97 to 12.21) | −9.1% | 20.79 (−15.23 to 56.80) | |
| Pancreatic cancer surgery | 0.79 (0.52 to 1.06)* | −69.95 (−102.31 to −37.58)* | −44.2% | 3.00 (−3.94 to 9.94) | |
| Thyroid cancer surgery | 1.62 (−0.07 to 3.31) | −464.31 (−707.33 to −221.30)* | −30.6% | 5.09 (−46.86 to 57.04) | |
| Colorectal cancer surgery | −0.67 (−2.34 to 1.00) | −258.42 (−427.02 to −89.83)* | −22.9% | 13.73 (−22.66 to 50.12) | |
| Urinary tract stone surgery | −0.08 (−1.41 to 1.24) | −483.39 (−644.28 to −322.51)* | −44.1% | 23.41 (−11.08 to 57.90) | |
| Benign prostatic hyperplasia surgery | 0.56 (−0.04 to 1.17) | −123.07 (−173.30 to −72.83)* | −45.0% | −4.26 (−14.87 to 6.35) | |
| Ovarian cancer surgery | 0.59 (0.42 to 0.76)* | −59.21 (−89.28 to −29.15)* | −35.9% | 3.81 (−2.79 to 10.41) | |
| Endometrial cancer (uterine corpus cancer) surgery | 0.84 (0.56 to 1.12)* | −60.92 (−94.63 to −27.21)* | −36.9% | 1.84 (−5.39 to 9.07) | |
| Uterine fibroid surgery | −3.19 (−4.77 to −1.61)* | −393.86 (−576.78 to −210.95)* | −39.9% | 2.55 (−35.96 to 41.06) | |
| Cervical cancer surgery | −0.12 (−0.38 to 0.14) | −53.27 (−84.52 to −22.02)* | −31.1% | 1.01 (−5.69 to 7.71) | |
| Cerebral aneurysm surgery | 4.45 (3.37 to 5.54)* | −481.73 (−613.55 to −349.90)* | −62.9% | 38.19 (9.93 to 66.45)* | |
| Cerebral thrombectomy | 0.68 (0.44 to 0.91)* | 0.04 (−30.31 to 30.40) | 0.0% | −6.91 (−13.64 to −0.19)* | |
| Hemodialysis for chronic renal failure | −23.31 (−67.87 to 21.25) | 340.08 (−1,880.25 to 2,560.41) | 0.8% | 129.86 (−371.51 to 631.22) | |
| Gastric cancer surgery | 0.47 (−1.21 to 2.14) | −282.25 (−485.65 to −78.84)* | −30.0% | 6.00 (−37.61 to 49.60) | |
| Breast cancer surgery | 10.94 (8.82 to 13.05)* | −373.30 (−665.91 to −80.69)* | −18.7% | −5.69 (−68.14 to 56.76) | |
| Lung cancer surgery | 4.33 (3.28 to 5.37)* | −282.36 (−408.97 to −155.75)* | −35.4% | 9.21 (−17.93 to 36.35) | |
| Non-tertiary general hospitals | |||||
| Liver cancer surgery | −1.33 (−1.91 to −0.76)* | −52.38 (−121.72 to 16.96) | −12.1% | 15.26 (0.40 to 30.13)* | |
| Thyroid cancer surgery | 5.61 (4.43 to 6.78)* | −117.23 (−237.51 to 3.04) | −16.8% | 28.38 (2.79 to 53.96)* | |
| Colorectal cancer surgery | 0.75 (0.02 to 1.48)* | −6.29 (−94.90 to 82.32) | −1.2% | 9.54 (−9.46 to 28.53) | |
| Urinary tract stone surgery | −5.13 (−10.25 to −0.01)* | −99.49 (−679.20 to 480.22) | −2.5% | 93.85 (−34.08 to 221.78) | |
| Benign prostatic hyperplasia surgery | 0.34 (−0.35 to 1.02) | −28.95 (−112.31 to 54.41) | −8.6% | 0.20 (−17.67 to 18.07) | |
| Uterine fibroid surgery | −1.65 (−3.32 to 0.02) | −189.68 (−395.76 to 16.39) | −16.1% | 29.66 (−14.57 to 73.89) | |
| Cerebral aneurysm surgery | 0.67 (0.26 to 1.08)* | −3.61 (−64.70 to 57.48) | −1.0% | 6.61 (−6.45 to 19.66) | |
| Cerebral thrombectomy | 2.25 (1.97 to 2.53)* | 8.91 (−26.11 to 43.93) | 3.60% | −11.28 (−18.80 to −3.76)* | |
| Hemodialysis for chronic renal failure | 720.83 (643.64 to 798.02)* | −1,846.00 (−9,546.04 to 5,854.04) | −1.0% | 539.98 (−1,140.72 to 2,220.68) | |
| Gastric cancer surgery | −0.16 (−0.82 to 0.49) | −13.97 (−80.49 to 52.55) | −4.9% | 12.24 (−2.12 to 26.59) | |
| Breast cancer surgery | 4.65 (3.51 to 5.78)* | 40.90 (−96.74 to 178.54) | 5.7% | 44.14 (14.63 to 73.64)* | |
| Lung cancer surgery | 0.30 (−0.10 to 0.71) | 3.19 (−37.65 to 44.04) | 1.7% | 9.96 (1.15 to 18.78)* | |
aSlope before February 2024. bLevel change on February 2024. cThe ratio of the immediate effect of mass resignation to the average monthly claims in the pre-resignation period. dSlope change since February 2024.
*P < 0.05.
Fig. 1. Results of interrupted time series segmented regression analysis for the number of (A) liver cancer surgery, (B) pancreatic cancer surgery, (C) thyroid cancer surgery, (D) colorectal cancer surgery, (E) urinary tract stone surgery, and (F) benign prostatic hyperplasia surgery by the level of medical institutions.
N/A = not applicable.
Fig. 2. Results of interrupted time series segmented regression analysis for the number of (A) ovarian cancer surgery, (B) endometrial cancer (uterine corpus cancer) surgery, (C) uterine fibroid surgery, (D) cervical cancer surgery, (E) cerebral aneurysm surgery, and (F) cerebral thrombectomy by the level of medical institutions.
N/A = not applicable.
Fig. 3. Results of interrupted time series segmented regression analysis for the number of (A) hemodialysis for chronic renal failure, (B) gastric cancer surgery, (C) breast cancer surgery, and (D) lung cancer surgery by the level of medical institutions.
DISCUSSION
Our analysis demonstrated a substantial reduction in the provision of 13 DPNIs at tertiary hospitals following the mass resignation of junior doctors. This finding is consistent with prior studies reporting declines in high-complexity procedures in tertiary hospitals during periods of workforce disruption.18 Given that tertiary hospitals rely heavily on junior doctors for surgical procedures, their absence likely disrupted surgical workflows.24 Comparable effects have been documented in previous physician strikes. For example, during the 1999 resident strike in Spain, the number of laboratory tests and radiograph prescriptions declined.25 Likewise, the 2016 junior doctors’ strike in England was associated with reductions in inpatient admissions, emergency department visits, and outpatient consultations.26
Conversely, no immediate effect of mass resignation was observed in general hospitals in Korea. These institutions appeared to experience less disruption, possibly due to their relatively lower dependence on junior doctors. Between the fourth quarter of 2023 and the fourth quarter of 2024, the total number of physicians declined by 34.8% in tertiary hospitals compared with 11.7% in general hospitals, whereas the proportion of junior doctors decreased from 38.6% to 4.0% and from 17.6% to 2.8%, respectively.27 Such reductions in medical personnel may disrupt surgical workflows,28 particularly in tertiary hospitals where complex interventions are concentrated. Consistent with this pattern, our findings align with those of a previous study18 reporting that volumes of high-complexity procedure remained largely unchanged in general hospitals.
The following three DPNIs were not immediately affected by the mass resignation in either tertiary or general hospitals: hemodialysis for chronic renal failure, cerebral thrombectomy, and liver cancer surgery. Unlike most surgical procedures, hemodialysis requires relatively limited physician involvement, which may explain the absence of an immediate impact following the mass resignation. Patients with chronic renal failure typically receive routine management, with established treatment plans and prescriptions. Moreover, renal dialysis in Korea is predominantly managed by nursing staff, further reducing reliance on physician availability.
Cerebral thrombectomy is a time-critical emergency intervention that plays a decisive role in patient survival and prognosis. Given its urgent nature, it is unlikely to have been deliberately postponed or restricted, even amid shortages of surgical personnel, which may explain the absence of immediate level changes in the ITS analysis. Nonetheless, a subsequent decline in cerebral thrombectomy volumes was noted following the mass resignation, potentially reflect the gradual attrition of overburdened healthcare workers, considering a significant number of stroke specialists resigned in 2024.29
Although the visual pattern of liver cancer surgery volume at tertiary hospitals resembled that observed for other DPNIs that demonstrated immediate declines following mass resignation, no statistically significant immediate effect was detected. This discrepancy may be attributable to the heterogeneous composition of the procedures encompassed within the liver cancer surgery DPNI. Specifically, interventions such as ablation and embolization are often performed independently by senior radiologists without the involvement of junior doctors. In addition, although liver transplantation volumes declined markedly,30 this reduction is unlikely to have substantially influenced overall liver cancer surgery volumes, as liver transplantation constitutes a relatively small proportion of all liver cancer procedures.
The personnel deployed to mitigate the negative effects of the mass resignation should be considered when interpreting our findings, as they may have functioned as buffers. In Korea, physician assistants11,31 and medical specialists11 were deployed to address workforce gap created by the resignation. However, these measures were insufficient to accommodate the increased workload. Consequently, senior physicians suspended research activities,11,13 and remaining nurses and physicians experienced burnout,32 with some ultimately resigning or leaving their positions.32,33
The magnitude of disruption to medical interventions at tertiary hospitals varied across DPNIs. Among the thirteen DPNIs that experienced an immediate impact, reduction ranged from18.7% for breast cancer surgery to 62.9% for cerebral aneurysm surgery. This pattern aligns with previous research18 reporting procedure claim reductions of 11% to 39%, although a wider range was observed in our study. This greater variability may reflect the diverse characteristics of the interventions examined. These findings suggest that the consequences of mass resignation should be addressed through tailored and specialty-specific approaches, rather than adopting uniform strategies.
Our analysis primarily focused on the immediate effects of the mass resignation on the provision of DPNIs due to data constraints, which are discussed in detail below. However, in light of previous studies and reports, we suggest that the impact of the mass resignation is unlikely to be limited to short-term reductions in healthcare service supply; therefore, further investigation is needed.
First, the reduction in physician workforce may have contributed to delays in treatment and worse health outcomes. In Korea, waiting times have not been a major concern.34 However, as of 2024, the average waiting time until hospitalization reached 17.5 days—the longest since the survey began in 2017—representing an increase of 3.9 days compared with 2023, prior to the mass resignation.35 Similarly, admission delays for stroke patients increased relative to 2023.29 When hospitalization or medical intervention are postponed or canceled, patients may be admitted in more advanced disease states, potentially leading to poorer health outcomes.3,28 The stage of liver cancer at diagnosis increased following the mass resignation, with delayed diagnosis likely contributing to this trend.30
Second, previous research indicates that the effects of medical strikes vary according to access to alternative healthcare options,4 with disadvantaged populations being more severely affected.5 In Korea, regional disparities in the medical workforce have intensified as remaining residents following the mass resignation became concentrated in the capital area.36 Consistent with this pattern, an increase in the time to surgery after cancer diagnosis was observed only in non-capital regions following the mass resignation.9 Furthermore, changes in cancer-related procedure volumes differed across Seoul, the surrounding capital region, and the non-capital areas.18
This study had several limitations. First, the analysis was restricted to services covered by the National Health Insurance system; therefore, trends in non-covered services may differ. Second, as the data were aggregated monthly at the national level, more granular analyses by region or shorter time intervals were not feasible. Third, the limited number of post-resignation data points constrained our ability to assess long-term effects. Fourth, this study did not encompass all diseases or medical practices in Korea; consequently, disorders and practices not included may have exhibited different patterns. Nevertheless, as DPNIs were selected based on high data demand and consensus between HIRA and academic societies, they are likely representative for assessing the impact of the mass resignation. Fifth, although sensitivity analysis was conducted to account for coinciding events, residual confounding cannot be entirely excluded. Potential sources of confounding encompass hospital-level workforce adjustments, such as the hiring physical assistants or senior physicians, as well as government responses, including the operation of emergency medical systems37 and the deployment of military and public health doctors.38
In conclusion, this study examined the impact of the mass resignation of junior doctors in Korea on the provision of DPNIs using ITS analysis. Of the sixteen DPNIs examined, thirteen exhibited an immediate reduction in intervention volumes at tertiary hospitals following the resignation, highlighting these institutions’ reliance on junior doctors. These findings emphasize the need for health policies that address unmet healthcare needs and mitigate potential adverse health outcomes arising from delayed or foregone medical services.
ACKNOWLEDGMENTS
We thank Yewon Lee, Jiwon Park, Bo Sung Jung, Jin Ju Yang for their advice regarding Korean tertiary hospitals.
Footnotes
Disclosure: The authors have no potential conflicts of interest to disclose.
- Conceptualization: Kim SJ, Kim S.
- Formal analysis: Kim Y.
- Methodology: Kim Y, Kim S.
- Project administration: Kim S.
- Visualization: Kim Y.
- Writing - original draft: Kim Y.
- Writing - review & editing: Kim SJ, Ban TH, Kim S.
SUPPLEMENTARY MATERIALS
Mathematical equation for the Interrupted Times Series segmented regression model
The minimum number of interventions per month for Diseases & Practices of National Interest by the level of medical institution
Diseases and practices defining each Diseases & Practices of National Interest
Sensitivity analysis for interrupted time series segmented regression for the number of interventions per month by Diseases & Practices of National Interest, with additional variants for COVID-19 and 2020 doctor’s strike
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Associated Data
This section collects any data citations, data availability statements, or supplementary materials included in this article.
Supplementary Materials
Mathematical equation for the Interrupted Times Series segmented regression model
The minimum number of interventions per month for Diseases & Practices of National Interest by the level of medical institution
Diseases and practices defining each Diseases & Practices of National Interest
Sensitivity analysis for interrupted time series segmented regression for the number of interventions per month by Diseases & Practices of National Interest, with additional variants for COVID-19 and 2020 doctor’s strike