Quantitative results
1.
The implementation outcomes of the Essential Medicines System in the county-level public hospitals
1.1
Storage, usage and supply of essential medicines in the hospitals
Prior to the implementation of the Essential Medicines System, the average number of different types of essential medicines maintained in the stocks of the hospitals was 124, and the average proportion of sales that were essential medicines was 9.74 %. After implementation, the average number of stocked essential medicines increased significantly to 250, and the average proportion of sales that were essential medicines increased to 19.4 %.
In terms of the supply of essential medicines, the average delivery delay was 5.5 days. The delays were much shorter for seven hospitals and ranged from two to three days. The delays were four to five days at eight hospitals and much longer in the other five hospitals, ranging from seven to 15 days. These delays were due to the low profits available to the distributing companies, which made them reluctant to distribute. Elsewhere, distribution companies had limited capabilities, or delays were reported of manufacturing hold-ups. It was also possible that traffic, weather and other objective factors affected supply.
1.2
The implementation statuses of the supporting policies (compensation mechanism and medical insurance policy)
1.2.1
Changes to the financial subsidy income before and after implementation
We surveyed financial assistance before and after the implementation of the Essential Medicines System including all levels of financial subsidies and the total grants. The results are displayed in Table
2.
Table 2
The financial subsidies of the county-level public hospitals across all levels before and after the implementation of the Essential Medicines System
A | 957.15 | 100 | 0 | 0 | 1378.7 | 100 | 0 | 0 |
B | 127.29 | 100 | 0 | 0 | 309.03 | 100 | 0 | 0 |
C | 88 | 100 | 0 | 0 | 700 | 0 | 28.6 | 71.4 |
D | 177.75 | 100 | 0 | 0 | 70 | 100 | 0 | 0 |
E | 100 | 0 | 100 | 0 | 539 | 34.7 | 65.3 | 0 |
F | 197.5 | 100 | 0 | 0 | 264 | 72.7 | 27.3 | 0 |
G | 74.86 | 100 | 0 | 0 | 74.92 | 68.0 | 32.0 | 0 |
H | 399 | 39.9 | 42.6 | 17.5 | 456 | 59.9 | 40.1 | 0 |
I | 470.44 | 100 | 0 | 0 | 401.38 | 84.9 | 15.1 | 0 |
J | 125 | 100 | 0 | 0 | 490 | 73.3 | 26.7 | 0 |
K | 236.18 | 100 | 0 | 0 | 320 | 100 | 0 | 0 |
L | 65.38 | 100 | 0 | 0 | 680.83 | 63.3 | 36.7 | 0 |
M | 5.28 | 100 | 0 | 0 | 124.1 | 16.2 | 83.8 | 0 |
N | 37.5 | 100 | 0 | 0 | 351 | 69.5 | 30.5 | 0 |
O | 151.03 | 100 | 0 | 0 | 210.56 | 100 | 0 | 0 |
P | 175.88 | 100 | 0 | 0 | 112.3 | 100 | 0 | 0 |
Q | 363.83 | 100 | 0 | 0 | 362.83 | 100 | 0 | 0 |
R | 16.2 | 100 | 0 | 0 | 12 | 100 | 0 | 0 |
S | 335.5 | 100 | 0 | 0 | 400 | 100 | 0 | 0 |
T | 62.5 | 100 | 0 | 0 | 240 | 37.5 | 62.5 | 0 |
In order of high to low, the levels of the financial subsidies were the central, province, municipal and county subsidies. Before implementation, most of the hospitals were assisted only by the county finance subsidies, although one hospital received all of its assistance at provincial level and another obtained financial assistance from the central, provincial and county governments. None of the hospitals received municipal financial assistance. After implementation, the strength of the financial assistance increased significantly, primarily at the provincial level. Eleven county hospitals had access to financial assistance from the province and county. The proportions of provincial financial assistance ranged from 15.1 % to 83.8 %, which represented a large change from the pre-implementation situation. However, the central and municipal financial assistance efforts were still quite weak or non-existent.
To further understand the specific differences in the levels of financial assistance, we compared the relevant statistical data about the total financial assistance for all hospitals. Before implementation, the income from financial assistance across the 20 hospitals averaged 2,083,100 yuan, and specific grant funds ranged from 52,800 to 9,571,500 yuan. After implementation, financial assistance income averaged 3,748,300 yuan, and the specific amounts ranged from 120,000 to 13,787,000 yuan. The hospitals’ financial assistance income data were not completely normally distributed before and after implementation, so a Mann–Whitney Test was conducted to compare the difference. The result turned out to be significant (u = 116,
p = 0.023 < 0.05). After implementation, the average increase was 1,665,200 yuan (79.94 %). Fifteen hospitals exhibited very different degrees of growth, and eight hospitals increased by more than 100 %. However, income from financial subsidies at four of the hospitals fell, and the maximum decrease was 60.62 %. One hospital exhibited almost no change in financial assistance income after implementation.
1.2.2
Changes in the total cost of medical insurance compensation before and after implementation
The total costs of medical insurance compensation at the county hospitals before and after the implementation of the Essential Medicines System were compared to understand the changes in the medical insurance funds Table
3.
Table 3
Changes in the total costs of health insurance compensation at the county hospitals before and after the implementation of the Essential Medicines System
A | 1144.53 | 1064.15 | −80.38 | −7.02 % |
B | 2974.36 | 3648.45 | 674.09 | 22.66 % |
C | 3479.5 | 3355 | −124.5 | −3.58 % |
D | 1061.07 | 1497.58 | 436.51 | 41.14 % |
E | 4998 | 7112 | 2114 | 42.30 % |
F | 1121.55 | 1569.86 | 448.31 | 39.97 % |
G | 153.37 | 158.53 | 5.16 | 3.36 % |
H | 2882.38 | 3324.14 | 441.76 | 15.33 % |
I | 916.09 | 1118.17 | 202.08 | 22.06 % |
J | 2489.11 | 2562.42 | 73.31 | 2.95 % |
K | 892.5 | 1023.32 | 130.82 | 14.66 % |
L | 2189.44 | 3034.28 | 844.84 | 38.59 % |
M | 559.94 | 1294.3 | 734.36 | 131.15 % |
N | 1310.37 | 1104.16 | −206.21 | −15.74 % |
O | 1300.5 | 1415 | 114.5 | 8.80 % |
P | 794.26 | 1095.61 | 301.35 | 37.94 % |
Q | 782.25 | 1305.7 | 523.45 | 66.92 % |
R | 1057.42 | 1450.62 | 393.2 | 37.18 % |
S | 1111.73 | 1230.73 | 119 | 10.70 % |
T | 2760 | 2017 | −743 | −26.92 % |
Average | 1698.92 | 2019.05 | 320.13 | 18.84 % |
Before implementation, the total cost of health insurance compensation averaged 16,989,200 yuan, and specific compensation funds ranged from 1,533,700 to 49,980,000 yuan. After implementation, the total cost of medical insurance compensation averaged 20,190,500 yuan, and ranged from 1,585,300, to 71,120,000 yuan. The two groups of data were not normally distributed, and comparison with a Mann–Whitney Test revealed that the difference was of no significance (u = 153,
p = 0.204 > 0.05). The average cost of medical insurance compensation had gone up by 3,201,300 yuan (18.84 %) after implementation. Only four hospitals witnessed larger growth rates which were more than 40 %, while others experienced small fluctuations, mostly with an increase or decrease rate between 3 % and 30 %.
1.3
Effects on the operation of the hospitals of implementing the policy (i.e., the hospitals’ incomes, service amounts and fees)
1.3.1
Changes in income from medicine sales and proportion of income derived from medicines at the county hospitals before and after implementation
After implementation, the average income from medicines changed from 23,859,400 yuan to 24,703,400 yuan. Overall, the difference was small, and the increase was only 844,000 yuan (3.54 %). The index values of each hospital were similar before and after implementation, but there were still slight fluctuations post-implementation. Eight hospitals exhibited declines in income from medicines after implementation, and this decline was most obvious in hospital F, which experienced a 30.76 % decline. The other 12 hospitals experienced increases, and hospital M experienced the largest increase of 67.1 %.
We also analyzed the proportion of income derived from medicines and the results are displayed in Table
4.
Table 4
Changes in proportions of income derived from medicines at the county hospitals before and after the implementation of the Essential Medicines System
A | 41.61 | 37.12 | −4.49 | −10.79 |
B | 46.21 | 36.29 | −9.92 | −21.47 |
C | 44.39 | 40.91 | −3.48 | −7.84 |
D | 33.65 | 31.39 | −2.26 | −6.72 |
E | 48.31 | 35.67 | −12.64 | −26.16 |
F | 49.66 | 36.29 | −13.37 | −26.92 |
G | 49.86 | 42.02 | −7.84 | 15.72 |
H | 50.09 | 42.57 | −7.52 | −15.01 |
I | 49.98 | 42.43 | −7.55 | −15.11 |
J | 51.45 | 49.02 | −2.43 | −4.72 |
K | 46.21 | 42.22 | −3.99 | −8.63 |
L | 50.89 | 44.73 | −6.16 | −12.1 |
M | 59.73 | 55.95 | −3.78 | −6.33 |
N | 48.82 | 42.59 | −6.23 | −12.76 |
O | 56.72 | 48.97 | −7.75 | −13.66 |
P | 72.16 | 77.07 | 4.91 | 6.8 |
Q | 44.36 | 44.79 | 0.43 | 0.97 |
R | 66.64 | 65.11 | −1.53 | 2.3 |
S | 46.21 | 47.75 | 1.54 | 3.33 |
T | 38.54 | 32.57 | −5.97 | 15.49 |
Average | 49.77 | 44.77 | −5 | 10.05 |
Before implementation, the average proportion of income derived from medicines was 49.77 % with a range of 33.65 % to 72.16 %. After implementation, the average proportion of income derived from medicines was 44.77 %, which represented a reduction of 5 % (10.05 %). These proportions ranged from 31.39 % to 77.07 %. The proportion of income derived from medicines declined in 17 hospitals, and hospital F exhibited the largest decline of 26.92 %. Only hospitals P and S exhibited slight increases of 6.8 % and 3.33 %, respectively. One hospital exhibited almost no change.
1.3.2
Changes in the amounts of service before and after implementation
The amounts of service of the hospitals were measured in terms of inpatient, outpatient and emergency visits. Before implementation, the average number of outpatient and emergency visits was 98,460. After implementation, this number was 120,547, which represented an increase of 22,087 (22.43 %). This number increased in all but one of the hospitals, and the largest increase was 83.77 %. Only hospital N experienced a decline of 4.85 %.
Before implementation, the average number of inpatient visits was 8,614. After implementation, this number was 10,230, which represented an increase of 1,616 (18.76 %). The number of inpatient visits increased in 17 hospitals, and the highest increase was 67.61 %. Inpatient visits in three hospitals were reduced after implementation; hospitals G, F and N experienced reductions of 23.46 %, 9.98 % and 5.83 %, respectively.
1.3.3
Changes in service fees before and after implementation
Before implementation, the average outpatient per-visit fee was 170.28 yuan, and these fees ranged from 89.42 to 314 yuan. After implementation, the average fee was 159.49 yuan, and no large differences before and after implementation were observed. Only two hospitals exhibited obvious declines; fees in hospital I were reduced by 46.62 %, and fees in hospital K were reduced by 37.97 %. Hospital T’s costs increased by 25.29 %, but the changes in the other hospitals were small.
Before implementation, the average per-visit hospitalization fee was 4,182.84 yuan, and these fees ranged from 3,109.6 to 5,665.5 yuan. After implementation, the average per-visit hospitalization fee was 3,695.44 yuan, and these fees ranged from 2,358.91 to 4,781 yuan. These two sets of data were normally distributed, and a two-sample paired
t test revealed a significant difference (t = 4.392,
p = 0.000 < 0.05). After implementation, the per-visit hospitalization fee was 487.41 yuan lower than before, and the average decline was 11.65 %. Fifteen of the hospitals’ costs declined to different degrees, and hospital B exhibited the largest decline of 29.2 %. The specific results are illustrated in Table
5.
Table 5
Changes in the per-visit hospitalization fees at the county hospitals before and after the implementation of the Essential Medicines System
A | 5665.5 | 4781 | −884.5 | −15.61 |
B | 4679.95 | 3313.4 | −1366.55 | −29.2 |
C | 4672 | 3323 | −1349 | −28.87 |
D | 3411.93 | 3453.9 | 41.97 | 1.23 |
E | 4645.5 | 3953 | −692.5 | −14.91 |
F | 4183.4 | 3340.2 | −843.2 | −20.16 |
G | 3109.6 | 3137.2 | 27.6 | 0.89 |
H | 4801.4 | 4343.62 | −457.78 | −9.53 |
I | 4149.5 | 4573.5 | 424 | 10.22 |
J | 5370.68 | 4590.9 | −779.78 | −14.52 |
K | 4060.57 | 3312.1 | −748.47 | −18.43 |
L | 4477.5 | 4223 | −254.5 | −5.68 |
M | 3590 | 2871 | −719 | −20.03 |
N | 3908 | 3586 | −322 | −8.24 |
O | 2867.22 | 2358.91 | −508.31 | −17.73 |
P | 4163.37 | 3463.78 | −699.59 | −16.8 |
Q | 3126.96 | 3528.46 | 401.5 | 12.84 |
R | 3665.28 | 3697.79 | 32.51 | 00.89 |
S | 4819.5 | 4116 | −703.5 | −14.6 |
T | 4289 | 3942 | −347 | −8.09 |
Average | 4182.84 | 3695.44 | −487.41 | −11.65 |
2.
Analysis of the factors that influenced the implementation outcomes of the Essential Medicines System
The service fees directly reflect the level of expense control by the hospital, have a close relation with the vital interests of the masses and can be the easiest to perceive. Reducing service fees was precisely one of the key purposes of implementing the Essential Medicines System. Therefore, we focused on changes in the service fees, which were used as direct and effective measurement instruments of the system outcomes, and explored the potential factors that caused the transformation. Because the differences in per-visit outpatient fees were not statistically significant, the per-visit hospitalization fees were analyzed.
We first identified the conceivable influential factors, which included a total of seven variables: financial assistance income, total medical insurance compensation, income from medicines while hospitalized, hospital examination income, examination charges for large scale medical equipment, the actual number of types of stocked essential medicines, and the proportion of sales that were essential medicines. Next, we conducted a single factor linear regression analysis. The results are illustrated in Table
6.
Table 6
Linear regression analysis of the factors that affected per-visit hospitalization fees
Financial assistance income | Per-visit hospitalization fees | 0.029* |
Total medical insurance compensation | 0.086 |
Income from medicines while hospitalized | 0.006* |
Income from hospital examinations | 0.906 |
Examination charge of large scale medical equipment | 0.145 |
Actual number of varieties of essential medicines | 0.015* |
Proportion of actual sales of medicines that were essential medicines | 0.046* |
The results revealed that three elements, medical insurance compensation, hospital examination income and examination charges for large-scale medical equipment were statistically of no significance to the changes of per-visit hospitalization fees. In contrast, the remaining four variables seemed to be associated with per-visit hospitalization fees to some degree, with financial assistance revenue (p = 0.029 < 0.05), income from medicines during hospitalization (p = 0.006 < 0.05), the actual number of types of essential medicines (p = 0.015 < 0.05) and the proportion of sales that were essential medicines (p = 0.046 < 0.05), respectively.
Based on the single factor analysis, multiple linear regression analysis was used to further explore the causal relationships between the variables. The per-visit hospitalization fees was still used as the dependent variable. Financial assistance revenue, income from medicines during hospitalization, the actual number of types of essential medicines and the proportion of sales that were essential medicines, all proven to be significant in the univariate analysis, were considered as variables in the second round. The regression model produced F = 5.502 and
p = 0.002 and was thus statistically significant. The results are shown in Table
7.
Table 7
Multiple linear regression analysis of the factors that affected per-visit hospitalization fees
(Constant) | 3879.162 | 331.453 | | 11.704 | 0.000 |
Financial assistance revenue | 0.905 | 0.355 | 0.347 | 2.550 | 0.015* |
Hospitalization medicine income | 0.239 | 0.113 | 0.302 | 2.122 | 0.041* |
Number of types of essential medicines | −2.008 | 1.850 | −0.239 | −1.085 | 0.285 |
Proportion of actual sales that were essential medicines | −15.216 | 22.174 | −0.144 | −0.686 | 0.497 |
Seen from the results, only two variables, financial assistance revenues and income from medicines during hospitalization, should be included in the regression equation. The regression coefficient for the financial assistance revenue was r = 0.347 (p = 0.015 < 0.05), and the regression coefficient for the income from medicines during hospitalization was r = 0.302 (p = 0.041 < 0.05). Thus, increases in income from medicines during hospitalization led to increases in per-visit hospitalization costs. Unexpectedly, greater financial assistance revenue also led to higher average per-visit hospitalization costs.
Discussion
1.
The guiding principle of the National Essential Medicines List remains to be reinforced, and specific lists for county hospitals should be developed.
We learned from the interviews that, currently, the drug directory for the county-level public hospitals in Anhui Province seems to be in some disorder and this may weakened the leading position and the guiding principle of the National Essential Medicines List. We therefore suggest the abolishment of province-level supplement directories of essential medicines, which are not convenient for unified management and standard medication. Additionally, due to the large patient populations encountered by county hospitals, these hospitals may have to deal with various diseases and a wide variety of drugs are in need. Successful experiences in Delhi [
12] and South Africa [
13] have shown that the development of different levels of the List can be effective on the policy improvement. Thus, it is worthwhile to develop the specialized Essential Medicines List for county hospitals.
2.
Supervision was required for the implementation process; the supply mechanism for the essential medicines requires further improvement.
Although the average stock levels and sales of essential medicines at the county hospitals increased after implementation, these sales still did not reach the required standards, which was issued in the previous provincial documents, claiming that the types of essential medicines that are used by secondary-level general hospitals should not be less than 95 % of the total number of essential medicines and that the proportion of total sales that are essential medicines should not be less than 30 %. This finding revealed a serious lack of policy execution strength. Without powerful supervision, the enthusiasm of the hospitals could not be fully mobilized. Follow-up investigations and timely feedback are needed.
Serious problems existed in the supply chain, which resulted in untimely and incomplete distributions of essential medicines. Previous studies [
14,
15] have shown that uncertainties about national policy, low profit levels for essential medicines and the internal problems of distribution companies lead to problems in the distribution chains. Clear and adequate supplies resulted in a significant higher usage rate of essential medicines [
16]. In response, state and local government could directly specify that the manufacturers and distributors of essential medicines establish a fast and efficient supply chain.
3.
The compensation mechanism was far from sound and adequate, and the leverage of the health insurance policy was not obvious.
Financial assistance from the government is considered as the most essential factor for the System implementation. Without sufficient investment, hospitals will struggle to survive [
17]. Currently, as required by the policy, 25 % of the loss of income for the county public hospitals in Anhui is subsidized by the provincial government, and another 75 % is subsidized by the examination fees that are charged by the hospital. Some of the county hospitals reported that since the implementation, their revenues had decreased significantly and that the additional financial assistance and examination fees were not enough to compensate for this decrease. As solutions, various compensation methods and flexible policies, such as performance grants, should be made available. Moreover, medical services price adjustment rights could be unified by municipal departments and the progress of implementation.
After implementation, when payments for the examination fees were accepted by the medical insurance funds, the policy resulted in a significant increase in the burden of medical insurance. However, the total capital in the system increased very little. The medical insurance compensation alone is not responsible for the promotion of the smooth operation of the Essential Medicines System. Thus, rather than relying on increasing compensation, the leverage role of medical insurance should be further developed. Multiple payment methods ought to be implemented in our country because the payment methods in developed countries, such as Australia and the UK, are based on the type of disease or the effect [
18], and Australia had also set up copayments and safety nets for essential medicines for outpatients [
19‐
21].
4.
The policy was partially successful because of the reduction in the proportion of income from medicines and the average inpatient fees of the county hospitals.
The average proportion of income from medicines, which is an important indicator of the comprehensive management capabilities of hospitals, was reduced by 5 % after implementation. This reduction may have been due to the levels of rational drug use by the hospitals, which were improved, and this finding partially suggests that the implementation of the Essential Medicines System was successful. However, the proportion of income from medicines remained as high as 44.77 %, which indicates that this remains one of the most important sources of income for the hospitals.
After implementation, outpatient and emergency visits and inpatient visits increased likely due to the reduction in medicine prices and the increase in the reimbursement ratio, which attracted more patients. These results are consistent with another Chinese report in which outpatient and inpatient visits to hospitals increased by 0.74 % and 16.39 %, respectively [
22]. To some extent, these increases alleviated the pressure on to the masses to see doctors.
A survey of three provinces in China found that the costs of outpatient and inpatient visits decreased by 4.9–14.6 % and 7.4–13.4 %, respectively, after the implementation of the Essential Medicines System [
23]. However, our survey found that the per-visit outpatient fees were not significantly different after implementation. In contrast to the study of Wang Jincai, which found that the per-visit outpatient and inpatient fees increased by 18.46 % and 3.74 % [
22], respectively, the per-visit hospitalization fees were found to be reduced by an average of 11.65 % after implementation in our research, which indicates that the issue of expensive treatment is likely being successfully addressed.
5.
The actual usage of the subsidies in the hospitals should be given more attention.
In the univariate analysis of the potential influential factors, the stock levels of essential medicines and the proportions of sales that were essential medicines were both found to have an impact on the per-visit hospitalization fees. Theoretically, higher proportions of stock levels and usage of essential medicines should lead to lower per-visit hospitalization costs. However, the effects of these two variables were eliminated in the multivariate analysis. It may be that the effects of these two factors on the reduction in the medical fees of the hospitals were insufficient at the present and should be further strengthened.
Our analyses resulted in the surprising conclusion that the per-visit hospitalization fees increased with increasing financial assistance incomes, which was the opposite of the intention of the policy. This finding suggests that the specific usage of assistance income by the hospitals was not clear. Indeed, the subsidies should be provided directly to doctors. Only by guaranteeing doctors’ incomes and mobilizing their motivation can we avoid high profits on prescription medicines. Therefore, after the establishment of a more sound hospital compensation mechanism, more attention should be given to the use of compensation funds. We suggest specifying the proportion of personnel expenditures in the hospitals for prevention of blind expansion and reduction on the staff remuneration.
Authors’ contributions
SMX designed the study, collected the data, provided input regarding the data analyses and interpretation and drafted the manuscript. CB contributed to the data analyses and helped to draft the manuscript. HW led and supervised the study, contributed to the study design, and assisted in the drafting of the manuscript. NNL, HL and PL participated in the design and quality control of the study. JYW helped with the data input. All authors have read and approved the final manuscript.