The purpose of this study was to determine whether components of the ProVent model can predict the high medical costs in Korean patients requiring at least 21 days of mechanical ventilation (prolonged mechanical ventilation [PMV]).
Retrospective data from 302 patients (61.6% male; median age, 63.0 years) who had received PMV in the past 5 years were analyzed. To determine the relationship between medical cost per patient and components of the ProVent model, we collected the following data on day 21 of mechanical ventilation (MV): age, blood platelet count, requirement for hemodialysis, and requirement for vasopressors.
The mortality rate in the intensive care unit (ICU) was 31.5%. The average medical costs per patient during ICU and total hospital (ICU and general ward) stay were 35,105 and 41,110 US dollars (USD), respectively. The following components of the ProVent model were associated with higher medical costs during ICU stay: age <50 years (average 42,731 USD vs. 33,710 USD, p=0.001), thrombocytopenia on day 21 of MV (36,237 USD vs. 34,783 USD, p=0.009), and requirement for hemodialysis on day 21 of MV (57,864 USD vs. 33,509 USD, p<0.001). As the number of these three components increased, a positive correlation was found betweeen medical costs and ICU stay based on the Pearson's correlation coefficient (γ) (γ=0.367, p<0.001).
The ProVent model can be used to predict high medical costs in PMV patients during ICU stay. The highest medical costs were for patients who required hemodialysis on day 21 of MV.
Advances in critical care intervention have led to improvements in short-term survival for intensive care unit (ICU) patients with acute critical illness
To identify PMV patients with a high 1-year mortality risk, the Prognosis for Prolonged Ventilation (ProVent) model
We investigated whether components of the ProVent model are predictive of high medical costs during ICU and total hospital stay in Korean patients requiring PMV.
This retrospective study was performed in the ICUs of a 1,100-bed university-affiliated tertiary care hospital in Busan, Korea. This hospital has six functionally separate ICUs with a total of 85 beds (medical, 12 beds; surgical, 10 beds; cardiostroke, 14 beds; neurosurgical, 13 beds; emergency, 20 beds; trauma, 16 beds). All of the ICUs have full cardiovascular and close airway monitoring equipment, as well as one full-time ICU specialist; the nurse-to-bed ratio is 1:3. All patients are managed according to the lung-protective ventilator strategy
The following demographic and clinical data were gathered from the medical records of each patient: age, sex, ICU admission diagnosis, and comorbidities prior to ICU admission based on Charlson Comorbidity Index
Continuous variables are expressed as median (range). Categorical variables are presented as number (%). Depending on the normality of the respective distribution, the Student's t-test or Mann-Whitney U test was used for comparisons of continuous variables. One-way analyses of variance or the Kruskal-Wallis test was used for three-group comparisons of continuous variables. The chi-square or Fisher exact test (for small numbers) was used to compare categorical variables. To evaluate the relationship between total medical costs per person and components of the ProVent model, Pearson's correlation coefficient (γ) was calculated. To evaluate factors independently predictive of ICU and hospital mortality, logistic regression analyses were performed on all components of the ProVent model. Model discrimination was assessed by the area under the receiver operating characteristic curve (AUC), and model calibration was assessed using the Hosmer-Lemeshow test. The β-coefficient values derived from multiple logistic regressions were simplified as natural numbers >0, and the ProVent models for predicting ICU and hospital mortality were calculated as the sum of these simplified β-coefficient values, which was same as the previous studies
This study was approved by the IRB of Pusan National University Hospital (H-1707-011-061). The requirement for informed consent from the patients was waived due to the observational and retrospective nature of this study.
During the study period, a total of 18,413 patients were admitted to the six ICUs. Of these, 302 patients (1.6%) were eligible for the study. The data of these 302 patients were retrieved and included in the analyses. The median age of the cohort was 63 years (range, 18–89 years), and 186 of the cohort (61.6%) were males. Of the patients, 152 (50.3%) were from surgical departments. In descending order, the three main indications for PMV were neurological disease, pulmonary disease, and multiple traumas. The ICU and hospital mortality rates were 31.5% and 33.1%, respectively. The demographic and clinical characteristics and the clinical and mortality outcomes of the study cohort are summarized in
The median total medical costs per patient during ICU and total hospital stay were 35,105 USD (range, 9,913–204,829 USD) and 41,110 USD (range, 13,605–204,829 USD), respectively. A positive correlation was found between medical costs during ICU stay and LOS in the ICU; and medical costs during total hospital stay and hospital LOS (γ=0.590, p<0.001 and γ=0.616, p<0.001, respectively). Medical costs per patient during ICU and hospital stay were negatively correlated with age (γ=−0.177, p=0.002 and γ=−0.171, p=0.003, respectively).
As the number of these three components (age <50 years, thrombocytopenia, and hemodialysis on day 21 of MV) increased, a positive correlation with medical costs was found for both ICU and total hospital stay (γ=0.367, p<0.001 and γ=0.284, p<0.001, respectively). A total of 156 patients (51.7%) had one of these three ProVent components. Of them, patients requiring hemodialysis had significantly higher medical costs during ICU and total hospital stay than patients with the other components (
We evaluated the predictive power of the ProVent components for ICU and hospital mortality. Multivariate logistic analyses indicated that three components (requirement for vasopressors, requirement for hemodialysis, and thrombocytopenia [platelet count <150×109/L]) were significantly associated with ICU and hospital mortality (
To the best of our knowledge, this is the first comprehensive investigation of the association between medical costs and clinical variables in Korean patients requiring PMV. In light of the financial pressures associated with health-care costs in these patients
Our results showed that PMV patients require high resource investment during ICU admission, and that three components of the ProVent model (age <50 years, and thrombocytopenia and hemodialysis on day 21 of MV) were associated with high medical costs. In addition, three ProVent components (requirement for vasopressors, requirement for hemodialysis, and thrombocytopenia on day 21 of MV) were associated with higher ICU and hospital mortality rates based on multivariate regression analyses. Based on the performance of predicting mortality in previous studies
In our enrolled patients, younger patients (<50 years) had higher medical costs than older patients (≥50 years), but their ICU (25.8% vs. 33.1%, p=0.296) and hospital (27.3% vs. 34.7%, p=0.301) mortality rates were not significantly different. However, patients <50 years old had a lower APACHE II score at ICU admission (median, 16 [range 3–36] vs. 18 [6–41]; p=0.006). Our findings imply that younger patients tended to use more of various medical resources during their ICU stay. In addition, among the components of the ProVent model, hemodialysis on day 21 was associated with the highest medical costs. Thus, to predict high medical costs in patients with PMV, attending physicians should evaluate whether patients will require hemodialysis on day 21.
In addition to components of the ProVent model, we hypothesized other clinical and demographic variables could be associated with high medical costs, because staffing levels in the ICUs of university and teaching hospitals in Korea are lower, and critical care delivery systems are underdeveloped compared to Western countries
Although we could not evaluate in our study due to its retrospective design, medical costs may be influenced by the degree of self-ventilator use at home or at other hospitals at post intensive care settings in patients with PMV. Also, their medical costs may be associated with distinct Korean cultural factors, such as family support, the concept of death, and social customs, as these can impact physician-family discussions regarding life support
This study had several limitations. First, no estimates could be made of the medical costs of patients who were not covered by the Korean National Health Insurance coverage because of the retrospective nature of the study. Second, we hypothesized that homogeneous subgroup analyses (e.g., underlying diseases, main reasons for ventilator care, and main department at ICU admission) with the ProVent model would be more useful for estimating medical costs, because our study was troubled by heterogeneity resulting from pooling of data from six different ICUs and inter-department health care support systems particularly in surgical, medical, and trauma. We also hypothesized that medical costs could be quite different depending on the level of end-of-life care in these groups of total enrolled patients. However, we did not obtain significant findings, possibly due to the small sample size. Third, the retrospective design of the study may have resulted in selection bias. Fourth, the data were obtained at a single center and the sample size was small, so the results may not be representative of the wider PMV population in Korea.
In conclusion, patients with PMV had high medical costs during ICU and total hospital stay. Three components of the ProVent model (age <50 years, thrombocytopenia, and hemodialysis on day 21 of MV) were associated with high medical costs during ICU stay. The highest costs were found in patients requiring hemodialysis on day 21 of MV. To facilitate effective resource utilization, further studies to identify predictors of high medical costs in patients requiring PMV are warranted.
This work was supported by the National Research Foundation of Korea (NRF) grant funded by the Korean government (Ministry of Science and ICT) (2016R1C1B1008529).
Variable | Value (n=302) |
---|---|
Age, yr | 63 (18–89) |
Male sex | 186 (61.6) |
Body mass index, kg/m2 | 22.5 (14.2–58.6) |
Charlson comorbidity index | 2 (0–9) |
Major diagnoses leading to MV | |
Neurological | 127 (42.1) |
Pulmonary, including pneumonia | 69 (22.8) |
Multiple traumas | 41 (13.6) |
Infections other than pneumonia | 20 (6.6) |
Septic shock secondary to infection | 13 (4.3) |
Drug intoxication | 12 (4.0) |
Cardiogenic pulmonary edema | 11 (3.6) |
Postoperative state | 8 (2.6) |
Severity of illness on day of ICU admission | |
APACHE II score | 18 (3–41) |
SOFA score | 9 (1–16) |
MV LOS, day | 29 (21–199) |
ICU LOS, day* | 40 (15–201) |
Hospital LOS, day | 50 (21–387) |
Tracheostomy during ICU stay | 229 (75.8) |
ICU mortality | 95 (31.5) |
Hospital mortality | 100 (33.1) |
Values presented as average (range) for continuous variables and number (%) for categorical variables.
*Two patients were maintained receiving MV in a general ward after ICU discharge (ICU LOS of them were 15 and 18 days, respectively).
MV: mechanical ventilation; ICU: intensive care unit; APACHE II: Acute Physiology and Chronic Health Evaluation II; SOFA: Sequential Organ Failure Assessment; LOS: length of stay.
Categorical variable | ICU stay | Total hospital stay (ICU and general ward) | ||
---|---|---|---|---|
Costs (USD) | Length of stay (day) | Cost (USD) | Length of stay (day) | |
Age, yr | ||||
<50 (n=66) | 42,731 (13,605–204,829)* | 49 (21–394)* | 48,000 (13,605–204,829)* | 57 (21–387)* |
50–64 (n=97) | 35,753 (15,337–153,172)† | 41 (21–155)† | 44,775 (18,615–174,779) | 57 (24–384) |
≥65 (n=139) | 32,182 (9,913–95,888)† | 37 (15–139)† | 37,621 (15,496–117,001)† | 41 (22–227)† |
Thrombocytopenia | ||||
Yes (n=95) | 36,237 (9,913–204,829)* | 35 (18–99)† | 40,114 (18,985–204,829) | 38 (22–384)† |
No (n=207) | 34,783 (11,111–135,318)† | 42 (15–394)* | 41,286 (13,605–135,318) | 55 (22–387)* |
Required vasopressors | ||||
Yes (n=83) | 32,663 (9,913–135,318) | 31 (18–201)† | 37,732 (13,605–135,318) | 33 (21–220)† |
No (n=219) | 36,156 (11,111–204,829) | 42 (15–394)* | 43,191 (15,496–204,829) | 56 (22–387)* |
Required hemodialysis | ||||
Yes (n=31) | 57,864 (19,258–204,829)* | 36 (23–201) | 62,460 (19,258–204,829)* | 37 (24–384)† |
No (n=271) | 33,509 (9,913–153,172)† | 40 (15–394) | 39,669 (13,605–174,779)† | 51 (21–387)* |
Values are presented as median (range).
*,†Values recorded as superscript * have significantly higher medical costs compared to other vaules(s) recorded as superscript † (p<0.05).
ICU: intensive care unit; USD: U.S. dollars.
Component | ICU stay (USD) | Total hospital stay (USD) |
---|---|---|
None (n=146) | 32,059 (11,111–95,888) | 38,444 (15,496–109,976) |
One component (n=122) | 36,284 (9,913–153,172) | 43,450 (13,605–174,779) |
Thrombocytopenia (n=62) | 32,616 (9,913–153,172)† | 37,199 (18,985–174,779)† |
Age <50 yr (n=54) | 43,543 (13,605–122,303)† | 48,495 (13,605–122,303)† |
Hemodialysis (n=6) | 55,405 (38,995–68,364)* | 55,405 (38,995–68,364)* |
Two components (n=32) | 49,814 (19,258–135,318) | 52,870 (19,258–135.318) |
Age <50 yr and hemodialysis or thrombocytopenia and hemodialysis (n=23) | 54,703 (19,258–135,318)* | 62,460 (19,258–135,318)* |
Age <50 yr and thrombocytopenia (n=9) | 37,271 (21,846–124,785)† | 35,061 (21,846–124,785)† |
All three components (n=2) | 166,317 (127,806–204,829) | 166,317 (127,806–204,829) |
Values are presented as median (range).
*,†Values recorded as superscript * have significantly higher medical costs compared to other vaules(s) recorded as superscript † (p<0.05).
ICU: intensive care unit; USD: U.S. dollars.
Variable | ICU mortality | Hospital mortality | ||||
---|---|---|---|---|---|---|
Adjusted OR (95% CI) | β value | p-value | Adjusted OR (95% CI) | β value | p-value | |
Age ≥65 yr | 1.347 (0.695–2.609) | 0.298 | 0.378 | 1.569 (0.822–2.995) | 0.451 | 0.172 |
Age 50-64 yr | 1.057 (0.495–2.257) | 0.055 | 0.886 | 1.150 (0.554–2.388) | 0.139 | 0.708 |
Vasopressors | 4.505 (2.476–8.195) | 1.505 | <0.001 | 3.882 (2.157–6.988) | 1.356 | <0.001 |
Hemodialysis | 5.429 (2.204–14.562) | 1.692 | 0.001 | 5.036 (1.894–13.393) | 1.617 | 0.001 |
Platelet count <150×109/L | 3.755 (2.057–6.855) | 1.323 | <0.001 | 3.495 (1.940–6.299) | 1.251 | <0.001 |
The Hosmer-Lemeshow goodness-of-fitness statics were 4.578 (
ICU: intensive care unit; OR: odds ratio, CI: confidence interval.