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Association between health insurance and antibiotics prescribing in four counties in rural China
Health Policy 48 (1999) 29 – 45
Association between health insurance and antibiotics prescribing in four counties in rural China Hengjin Dong a,*, Lennart Bogg b, Clas Rehnberg c, Vinod Diwan b,d a
Department of Hospital Management, School of Public Health, Shanghai Medical Uni6ersity, Shanghai 200032, People’s Republic of China b Di6ision of International Health Care Research (IHCAR), Department of Public Health Science, Karolinska Institutet, Stockholm S-171 76, Sweden c Stockholm School of Economics, Stockholm S-113 83, Sweden d Nordic School of Public Health, Box 12133, Go¨teborg S-402 42, Sweden Received 8 December 1998; accepted 29 March 1999
Abstract A cross-sectional study was carried out at county, township and village health care facilities in four counties in rural China in order to describe and compare the effects of health financing systems on antibiotic prescribing in outpatient care. A total of 1232 outpatients at the health care facilities was selected by multi-stage random sampling and were interviewed over 2 weeks. The results showed that health financing systems appeared to influence antibiotic prescribing in outpatient care, both in terms of frequency and of the types prescribed. The insured group had lower prescribing of antibiotics at township and village health care facilities, and for respiratory tract infections, but had higher prescribing of newer antibiotics at county and village health care facilities, for respiratory tract and g-i infections. Because there was a high patient compliance rate (94.3%) in this study the prescribing of antibiotics (supply side behavior) reflected the use of antibiotics (demand side behavior) to a great extent. Thus the results imply that antibiotics prescribing and using might be biased by the patient’s health financing systems and antibiotic prescribing was the result of the interaction between physicians and patients. © 1999 Elsevier Science Ireland Ltd. All rights reserved. Keywords: Health insurance; Antibiotics; Prescribing; Utilization; China * Corresponding author. Tel.: +86-21-64041900; fax: + 86-21-64169552. E-mail address: [email protected] (H. Dong) 0168-8510/99/$ - see front matter © 1999 Elsevier Science Ireland Ltd. All rights reserved. PII: S 0 1 6 8 - 8 5 1 0 ( 9 9 ) 0 0 0 2 6 - 3
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H. Dong et al. / Health Policy 48 (1999) 29–45
1. Introduction Drugs are an important element of health care in all countries. In many countries drugs are also important economic products, often quite profitable. In China, the production value of drugs (current prices) increased from 27.5 billion yuan (1 US$= 5.8 yuan) in 1990 to 51.2 billion yuan in 1993 [1]. In rural health care facilities, nearly 70% of the outpatient care revenue and 55% of the inpatient care revenue come from drugs [2]. In urban health care facilities, about 50% of the revenue is from drugs. There are over 5000 types of drugs and preparations available in China [3]. The most commonly used drugs are antibiotics, drugs for the digestive system, antipyretics and vitamins. The most commonly used antibiotics are penicillin, ampicillin and cephalosporine [1]. Antibiotics constitute about 16% of the total drug products and the production of antibiotics increased from about 35 797 tons in 1990 to 42 645 tons in 1992. Among the first 50 commonly used drugs, 23 were antibiotics [4]. Drugs are financed by government insurance, labor insurance, and also by out-of-pocket payments (nearly 80% of the drugs). China has developed and implemented medical reforms since the 1980s. The basic principles in the reforms are to cut government costs for health care facilities, to encourage health care facilities to use fee-for-service to raise funds, to introduce a competitive mechanism in the production and distribution of drugs and to introduce a copayment scheme by the government and labor insurance. These principles are much in line with the World Bank recommendations [5 – 7] in its 1987 policy document. In the document, after identifying three main problems in the health sector (insufficient allocation spending on cost-effective health activities, internal inefficiency of public programs and inequity in the distribution of benefits from health services), the World Bank suggested an agenda for reform and a health financing policy package, consisting of user fees, health insurance, decentralization and privatization [5]. The agenda for reform reflected the market-oriented trends of the 1980s and has influenced health sector reform in most developing countries. With the collapse of rural cooperative health insurance in China in the early 1980s due to the rural economic system reforms, currently, only about 5% of rural villages remain covered by insurance. The majority (86%) of the rural population has to pay for health care out of their own pockets. Only a small number (about 9%) of rural inhabitants can enjoy coverage by government insurance, labor insurance, semi-government or labor insurance and private health insurance. Government insurance is financed by the central government (general tax) and covers all staff in central or local government facilities. Prior to 1986 the government health insurance covered all medical costs including drugs, except physician fees. Since then it has been reformed, increasing copayment, and reducing the coverage for drugs. At present government insurance covers about 1400 types of drugs and preparations. The labor health insurance financed by
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central or local government enterprises covers personnel working in central or local government companies. Prior to 1986 it covered all medical costs, including drugs and physician fees. Since then the coverage has been reduced to 50–90% of the cost, according to the enterprise’s profits. The semi-labor or government insurance covers about 50% of medical costs, including drugs, for the dependants of those with government or labor health insurance. Cooperative health insurance is financed by the village or township and the participants. The participants pay part of the medical costs. Uninsured (out-of-pocket) people have to pay 100% of medical costs themselves. As part of the reform, the drug distribution network has also been changed, from a centrally-controlled supply system to a market-oriented demand system [8]. Prior to 1980 over 90% of the county hospitals’ drugs and nearly 100% of the township hospitals’ drugs were supplied by the county drug companies, while 100% of the village health stations’ drugs came from the township hospitals. The hospitals can now purchase drugs from drug companies, factories and drug retailers. The reform has also given patients easier access to drugs, as more drugs are available on the market. The system of reimbursement from the government budget to rural health care facilities has also been reformed. Previously, the government financed the whole budget of the county and township health facilities, including salaries, supplies and equipment. Currently, it finances only 60% of salaries and some equipment. The remaining 40% of the salaries and the cost of supplies are funded from fee-for-service revenue, including drug sales. Another paper of ours shows that this change has already influenced the providers’ prescribing behavior [9]. It was found that most of the clinical doctors said they prescribed more expensive antibiotics for insured patients and changed prescriptions according to patient demands, financial ability and health financing systems in the treatment for some diseases, such as chronic bronchitis, tuberculosis and hypertension. There is only limited information available about the effect of health financing systems on drug prescribing (supply side behavior) and use (demand side behavior). Drug use and prescribing are influenced by many factors: patient demand, information on drugs, payment methods for the prescribers, the illness itself [10– 16], and, indeed, the health financing system. A study in the USA has shown that a change in the rate of copayment from 3 to 5 US$ per prescription was associated with a 5% decrease in the number of prescriptions [17]. Ghana’s ‘cash and carry’ system reduced clinic attendance by 25% [18]. User fees in New Zealand may provide a barrier for prescription medicines to children, students and people living in areas of high social need [19]. In China our earlier studies suggested that health financing had an effect on the use of health care, particularly the use of drugs: a macro-analysis in two rural counties showed that fee-for-service-based health care financing led to higher expenditure for drugs and curative health care [6]; and an outpatient care study in five rural counties showed that compared with the uninsured patients, the insured patients had significantly higher drug costs per outpatient visit [20].
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H. Dong et al. / Health Policy 48 (1999) 29–45
From the above evidences it is hypothesized that antibiotics prescribing is influenced to some degree by health financing systems in rural China because of insurance policies and policy-related prescription behavior. The aim of this study is to describe and compare the effects of health financing systems on antibiotics prescribing in outpatient care in rural China.
2. Methods
2.1. Sampling and sample size Fig. 1 shows the sampling process and sample size. Multi-stage sampling was used to select the county, township and village health care facilities. First, two provinces (Jiangsu and Anhui) in central China were purposely chosen. The two provinces were selected on the grounds of having different economic parameters, Jiangsu having the higher economic level, Anhui a lower level. Secondly, two counties in each province (Tongling and Fanchang in Anhui, Jurong and Jintan in Jiangsu) were purposely chosen according to their gross national product (GNP) and health status. The two counties within each province were selected on the
Fig. 1. Sampling and sample size. Note: *, sample/total of the four counties; †, only complete the sample size decided before interview, do not emphasize how to select the interviewees.
H. Dong et al. / Health Policy 48 (1999) 29–45
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grounds of having as similar socio-economic parameters as possible. Thirdly, one town and four townships in each county were chosen. At this stage (a) we randomly selected one middle income town, (b) divided the townships into two groups according to their income levels (above or below a mean level), and (c) randomly selected two townships in each group. Before sampling, all towns and townships were listed according to their income levels. Fourthly, we randomly selected five villages in each township. Before sampling, all villages were listed. Fifthly, a quota method was used to select the outpatients. It was estimated that in each county 300 outpatients needed to be interviewed, distributing 100 at county hospitals, 100 at township hospitals and 100 at village health stations. In 1994, the average population in the four counties was 480 000 (range from 340 000 to 600 000). GNP per capita in Anhui and Jiangsu was 2499 and 5775 yuan, respectively. The GNP per capita at Tongling, Fanchang, Jurong and Jintan was, respectively, 2897, 2001, 5272 and 6313 yuan; and the reported infant mortality rate (IMR) per 1000 live births was 32.3, 17.3, 12.7 and 16.2, respectively. It seems that the two provinces had different economic parameter, and the two counties in each province had similar parameters and the parameters are consistent with their provincial level. The IMR was a reported figures, maybe not completely correct.
2.2. Outpatient inter6iew Exit interview was used to obtain—for each outpatient—information on age, sex, occupation, education, per capita income, health financing systems, reasons for seeing a doctor, diagnosis, number and types of antibiotics prescribed, usage (oral, muscle injection or vein injection), reasons for prescribing antibiotics and the number and kinds of other drugs prescribed. The outpatients were interviewed in the selected county, township and village health care facilities. The outpatients at county and township hospitals were distributed proportionally to the departments where they were being treated. The outpatients were interviewed over 2 weeks in August – September 1995. Exit interview means to interview the outpatients at the time they have completed visiting the doctor, have got prescriptions and drugs (if the patients want to buy them) and are going to leave the hospital. A five-page questionnaire was used during interviewing. The questionnaire was revised four times and following a pilot study, tested in the counties 3 months before the formal interviews began. Fifteen interviewers, teachers or health workers in the preventive health facilities in the local areas were trained by research assistants from Shanghai Medical University (SMU), China, for 2 days just before the interviewing started. The interview was face-to-face, the questions were answered by the patient himself. If the patient was a child or the health condition was serious, the questions were answered by the accompanying person. Each interview lasted about 15 min. The outpatients were mixed, including any visits (first or second) and any diseases (acute or chronic). During the interview two research assistants from SMU, in each county, were responsible for quality control. The questionnaires were requested to be handed to the county health bureau every 2
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days and examined by the two assistants. If the questionnaires did not qualified (especially in not recording each drug name), the questionnaires were returned and the interviewers were asked to interview more outpatients to fill the gaps. About 10% of the questionnaires were returned because of missing drug names or other items, such as type of insurance, age, etc.
2.3. Analysis methods and indicators The interview data were entered into a computer using the Epi-Info program and analyzed using the SPSS program. x 2-Tests for the differences in proportions and Fisher’s exact test were carried out. The following indicators were chosen to reflect the prescribing of antibiotics in outpatient services: prescribing or not prescribing of antibiotics, average number of antibiotics prescribed per visit, the reasons for prescribing antibiotics, usage of antibiotics and the types of antibiotics (newer or older drugs) prescribed. The indicators were analyzed according to the health financing systems, the levels of health care facility (county, township and village) and two common systemic diseases, infections of the respiratory tract and of the digestive system, respectively.
3. Results
3.1. General information A total of 1232 outpatients were interviewed in the four counties, of which 398 outpatients were at county hospitals, 468 at township hospitals, and 366 at village health stations. Table 1 shows the outpatients’ socio-demographic characteristics and other information. Male outpatients made up a littler more than female ones, about half of the outpatients were farmers, most of them only had secondary school education and the majority of them were not covered by any health insurance. The main reasons for their coming to hospital were disease or injury, but Jintan (82.1%) is significantly lower than all the other three counties in the proportion of disease or injury (x 2 =25.22, P B 0.01). Their average age was 32.7 years (34.1 for male and 31.3 for female), and average income per capita in 1994 was 1558 yuan. The numbers in Table 1 are not consistent in some items because of missing data, e.g. the sum of male and female is not equal to the total number of cases.
3.2. Prescribing of antibiotics Table 2 shows the prescribing of antibiotics among the insured (covered by the government insurance, labor insurance, dependants and cooperative insurance) and uninsured groups (out-of-pocket). Out of 1223 outpatients, 585 (47.8%) were prescribed antibiotics. The uninsured group had higher antibiotic prescribing than the insured. The difference was statistically significant. At county hospital level, the prescribing of antibiotics was 34.3%. The uninsured group had a little lower
Table 1 Socio-demographic characteristics of outpatients in four counties in China Provinces
Anhui
Jiangsu
Counties
Tongling (%)
Fanchang (%)
Total (%)
Jurong (%)
Jintan (%)
284 95 (33.5) 78 (27.5) 111 (39.1)
323 103 (31.9) 130 (40.2) 90 (27.9)
320 100 (31.3) 151 (47.2) 69 (21.6)
1232 398 (32.3) 468 (38.0) 366 (29.7)
Male Female
177 (58.0) 128 (42.0)
165 (58.1) 119 (41.9)
175 (54.3) 147 (45.7)
137 (43.2) 180 (56.8)
654 (53.3) 574 (46.7)
Occupation Farmers Workers Students Cadres Others
153 43 32 18 57
(50.5) (14.2) (10.6) (5.9) (18.8)
136 50 19 16 63
(47.9) (17.6) (6.7) (5.6) (22.2)
169 52 23 18 61
(52.3) (16.1) (7.1) (5.6) (18.9)
141 73 21 17 66
(44.3) (23.0) (6.6) (5.3) (20.7)
599 218 95 69 247
(48.7) (17.8) (7.7) (5.6) (20.1)
Education Pre-school No schooling Primary school Middle school High and above
22 60 76 95 49
(7.3) (19.9) (25.2) (31.5) (16.2)
32 32 67 97 44
(11.3) (11.3) (23.6) (34.2) (15.5)
28 36 86 118 55
(8.7) (11.1) (26.6) (36.5) (17.0)
13 21 75 124 85
(4.1) (6.6) (23.6) (39.0) (26.7)
95 149 304 434 233
(7.7) (13.1) (24.8) (35.4) (19.0)
Health financing Governmenta Cooperative Private insurance Out-of-pocket
55 5 11 231
(18.2) (1.7) (3.6) (76.5)
53 0 3 228
(18.7) (0.0) (1.1) (80.3)
31 34 41 216
(9.6) (10.6) (12.7) (67.1)
96 164 6 54
(30.0) (51.3) (1.9) (16.9)
235 203 61 729
(19.1) (16.5) (5.0) (59.4)
Reasons for seeking hospital care Diseases and injury Others
275 (91.1) 27 (8.9)
258 (93.5) 18 (6.5)
292 (91.5) 27 (8.5)
261 (82.1) 57 (17.9)
1086 (89.4) 129 (10.5)
35
305 100 (32.8) 109 (35.7) 96 (31.5)
H. Dong et al. / Health Policy 48 (1999) 29–45
n County hospital Township hospital Village station
36
Provinces
Anhui
Counties
Tongling (%)
Age (years old) (low to high) B1 1–14 15–34 35–64 ]65 Income/capita (yuan)b (low to high) a b
Jiangsu Fanchang (%)
Jurong (%)
Total (%) Jintan (%)
32.6 (0–80) 5 (1.6) 41(13.4) 131(43.0) 111(36.4) 17(5.6)
30.7 (0–82) 3 (1.1) 37 (13.0) 140 (49.3) 97 (34.2) 7 (2.4)
33.8 (0–89) 6 (1.9) 38 (11.8) 142 (44.0) 119 (36.8) 18 (5.6)
33.5 (0–80) 0 (0.0) 24 (7.5) 165 (51.6) 118 (36.9) 13 (4.0)
32.7 (0–89) 14 (1.1) 140 (11.4) 578 (46.9) 445 (36.1) 55 (4.5)
1557 (100–8000)
1946 (50–8000)
2490 (50–10000)
4124 (200–15000)
2558 (50–15000)
Government, government insurance+labor insurance+semi-labor or government. 1 US$= 5.8 yuan in 1994.
H. Dong et al. / Health Policy 48 (1999) 29–45
Table 1 (Continued)
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Table 2 Antibiotic prescribing by financing groups Systems
Insurance (%)
Out-of-pocket (%)
Total (%)
x2
P
Total cases (n) Yesa
499 209 (42.3)
729 376 (51.6)
1228 585 (47.8)
10.1
0.002
County hospital (n) Yes
191 69 (36.3)
207 67 (32.4)
398 136 (34.3)
0.9
0.41
Township hospital (n) Yes
217 103 (47.5)
248 139 (56.0)
465 242 (52.0)
3.4
0.06
91 37 (42.5)
274 170 (62.0)
365 207 (57.3)
10.3
0.001
258
408
8.0
0.005
0.7
0.39
Village health station (n) Yes Respiratory tract infections (n) Yes
150 89 (59.3)
188 (72.9)
277 (67.9)
Digestive system infections (n) Yes
74
134
208
47 (63.5)
77 (57.5)
124 (59.6)
Number of antibiotics per encounter with antibiotics prescriptions County 1.19 1.09 Township 1.28 1.25 Village 1.14 1.26
1.14 1.26 1.24
0.24† 0.004† 0.46†
0.63 0.95 0.23
Total
1.23
0.07†
0.79
a †
1.22
1.23
Yes, prescribing antibiotics. F-value.
antibiotic prescribing than the insured, but the difference was not statistically significant. At township hospital level, the prescribing was 52%, higher than that at the county hospital level, the uninsured had higher prescribing than the insured, but the difference was not statistically significant. At village health stations, prescribing was 57.3%, higher than that at county and township hospitals; the uninsured also had higher prescribing than the insured, and the difference was statistically significant. Among the different insurance schemes, the prescribing of antibiotics was 36.8% (86/234) for government and labor insurance, 48.2% (96/199) for cooperative insurance, and 44.3% (27/61) for private insurance. In the study 91.9% of insured patients bought drugs and 95.7% of uninsured patients bought drugs, the total compliance rate was 94.3%. This high compliance rate implies that the prescribing of antibiotics (supply side behavior) reflect the use of antibiotics (demand side behavior) to a great extent. Respiratory tract and g-i infections are common causes of outpatient attendance. In this study there were 408 cases of respiratory tract infections and 208 cases of g-i infections, exactly 50% of the total number of outpatients. Antibiotics are commonly used for infections in these two systems. For respiratory infections, the
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prescribing of antibiotics was 67.9%. The uninsured group had higher prescribing than the insured, and the difference was statistically significant. For g-i infections, the prescribing was 59.6%. The uninsured group had lower prescribing than the insured, but the difference was not significant (Table 2).
3.3. A6erage number of antibiotics prescribed per 6isit In the outpatients prescribed antibiotics, the average number of antibiotics per visit was 1.2. The insured and the uninsured groups both had a similar average level and there was no significant difference between them (Table 2). Most (74.6%) of them received one antibiotic, 25.6% had two or more.
3.4. Usage of antibiotics Over 70% of the prescriptions were for injectable antibiotics, and 26.2% for oral ones. The usage of antibiotics was significantly different between the insured and the uninsured groups, and the uninsured had a higher frequency of injections. At county hospital level, the uninsured also had a higher frequency of injections than the insured, and the difference was statistically significant. But at township and village health care facilities, the difference was not significant between the groups (Table 3). From the county to the village level, the frequency of injection increased gradually, and the difference among the levels was significant (PB 0.001).
3.5. Reasons for prescribing antibiotics The reasons of prescribing antibiotics were cough, diarrhoea and fever (Table 4). Although fever, cough and diarrhoea are symptoms, antibiotics are usually preTable 3 Antibiotic usage by financing groups Systems
Insurance (%)
Out-of-pocket (%)
Total (%)
x2
P
Total cases (n) Oral Injection
209 64 (31.1) 142 (68.9)
376 86 (23.5) 280 (76.5)
585 150 (26.2) 422 (73.8)
3.9
0.04
69 38 (57.6) 28 (42.4)
67 20 (32.3) 42 (67.7)
136 58 (45.3) 70 (54.7)
8.3
0.004
103 20 (19.4) 83 (80.6)
139 38 (27.7) 99 (72.3)
242 58 (24.2) 182 (75.8)
2.2
0.14
37 6 (16.2) 31 (83.8)
170 28 (16.8) 139 (83.2)
207 34 (16.7) 170 (83.3)
0.01
0.94
County hospital (n) Oral Injection Township hospital (n) Oral Injection Village health station (n) Oral Injection
H. Dong et al. / Health Policy 48 (1999) 29–45
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Table 4 Reasons for prescribing antibiotics by financing groups Systems
Insurance (%)
Out-of-pocket (%) Total (%)
x2
P
Total cases (n) Fever Diarrhoea Cough Others
209 19 39 62 87
376 68 44 86 170
0.002
(18.5) (12.0) (23.4) (46.2)
585 87 83 148 257
14.7
(9.2) (18.8) (30.0) (42.0)
(15.1) (14.4) (25.7) (44.7)
69 4 6 16 42
67 13 6 11 34
0.09
(20.3) (9.4) (17.2) (53.1)
136 17 12 27 76
6.4
(5.9) (8.8) (23.5) (61.8)
(12.9) (9.1) (20.5) (57.6)
103 12 19 32 40
139 24 19 30 64
0.18
(17.5) (13.9) (21.9) (46.7)
242 36 38 62 104
4.9
(11.7) (18.4) (31.1) (38.8)
(15.0) (15.8) (25.8) (43.3)
37 3 14 14 5
(8.3) (38.9) (38.9) (13.9)
170 31 19 45 72
(18.6) (11.4) (26.9) (43.1)
207 34 33 59 77
(16.7) (16.3) (29.1) (37.9)
County hospital (n) Fever Diarrhoea Cough Others Township hospital (n) Fever Diarrhoea Cough Others Village health station (n) Fever Diarrhoea Cough Others
23.8
0.00003
scribed according to symptoms in rural China and these three symptoms are, in fact, the common ones for the use of antibiotics. The reasons for prescribing antibiotics were significantly different between the uninsured and the insured groups. At village health stations the reasons for prescribing antibiotics between the two groups were also significantly different. At county and township hospitals, the reasons were not significantly different. In the insured group the main reasons were cough and diarrhoea, but in the uninsured group the main reasons were cough and fever.
3.6. Types of antibiotics The most commonly prescribed antibiotics in outpatient care were penicillin, gentamicin, norfloxacin, cephalosporins, sulfonamides and streptomycin. Penicillin, gentamicin and sulfonamides are older antibiotics, norfloxacin and cephalosporins are newer ones. Usually the newer drugs are more expensive and effective. The result showed that the difference in the prescribing of the newer antibiotics between the two groups was statistically significant. The proportion of patients prescribed the newer antibiotics in the insured group was higher than that in the uninsured group. The difference at the village health station was significant as well, with the insured group prescribed the newer drugs to a greater extent. But the differences were not significant at the county and the township hospitals. For respiratory tract
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infections, the difference in the prescribing of the newer drugs between the two groups was significant, and the insured group had a higher proportion of new-drug users than the uninsured group. For the g-i infections the difference was not significant. The results also showed that the health care facility was another factor influencing the prescribing of the newer drugs. From village to county, the prescribing of the newer drugs in the uninsured group increased gradually (Table 5).
4. Discussion This is one of few studies in this area in China, and also in other countries, to describe antibiotic prescribing, particularly the prescribing of newer or older antibiotics, in outpatient care in relation to the patients’ health financing systems by interviewing outpatients at exit [21–30]. The main finding from this study was that the patients’ health financing systems appeared to influence the prescribing of antibiotics in outpatient care in rural China, both in frequency and in type. In general the uninsured patients had higher prescribing of antibiotics and higher Table 5 Types of antibiotics by financing groups Systems
Insurance (%)
Out-of-pocket (%) Total (%)
Total cases Penicillin Gentamicin Norfloxacin Cephalosporins Sulfonamides Others
97 35 27 22 13 62
County hospital Newer drugs Old drugs
25 (30.5) 57 (69.5)
15 (20.5) 58 (79.5)
40 (25.8) 115 (74.2)
16 (12.1) 116 (87.9)
30 (17.2) 144 (82.8)
46 (15.0) 260 (85.0)
Village health station Newer drugs Old drugs
8 (19.0) 34 (81.0)
10 (4.7) 204 (95.3)
18 (7.0) 238 (93.0)
Respiratory infections Newer drugs Old drugs
20 (18.9) 86 (81.1)
19 (8.5) 205 (91.5)
39 (11.8) 291 (88.2)
Digestive system infections Newer drugs Old drugs
14 (23.0) 47 (77.0)
18 (16.7) 90 (83.3)
32 (18.9) 137 (81.1)
Township hospital Newer drugs Old drugs
a
(37.9) (13.7) (10.5) (8.6) (5.1) (24.2)
209 74 37 17 21 103
(45.3) (16.1) (8.0) (3.7) (4.6) (22.3)
306 109 64 39 34 165
x2
P
11.6
0.04
2.0
0.16
1.5
0.21
(42.7) (15.2) (8.9) (5.4) (4.7) (23.0)
0.003a
Fisher’s exact test (two-tailed).
7.5
0.01
1.0
0.32
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injection ratio than the insured patients. They also had higher prescribing of antibiotics at village health stations and for respiratory tract infections, and a higher injection ratio at county hospitals than the insured patients. The insured patients, however, had higher prescribing of the newer antibiotics in general and for some diseases than the uninsured patients. The differences in the prescribing of antibiotics between the uninsured and the insured group are likely to be related to the insurance policies and the policy-related prescription behavior, of both patients and providers, and is also likely to be related to the case mix, care-seeking behavior. The uninsured patients may have attend later and were more ill and needed antibiotics more than the insured patients. This could account for the differing rates of antibiotic prescribing and the ratios of injection use. We believe that insurance coverage works both on the supply and demand side. On the part of the patients, they request more expensive drugs if they do not have to pay the full cost themselves. We also believe that the fee-for-service system gives the providers an incentive to over-prescribe and to prescribe drugs with a higher unit revenue (and cost). These could be potential topics for future research. Government, labor and cooperative health insurance all have similar regulations for drugs, but there are some differences in the types of drugs and the coverage of drug. For example, government insurance introduced a policy limiting the insurance coverage to only about 1400 drugs or preparations. In order to control drug costs the policy also put a ceiling on the number of drugs (5 3) and on the total cost (30 yuan or less) per prescription. Together with patient demand, this explains why the insured patients had a higher proportion of the newer antibiotics. Newer drugs are usually more expensive. Compared with the insured people, there are no restrictions on the choice of drugs of the uninsured people apart from their own financial situation. Uninsured people in China are relatively poor and their ability to pay for health care is lower. This might be a reason why their access to newer drugs and expensive drugs was lower. This also suggests that people when paying out-of-pocket are more concerned about the price of drugs. The results also showed that the difference in prescribing of newer antibiotics between the insured and the uninsured groups at county and township hospitals was not significant, but at the village health stations it was, with the insured group having a higher proportion of newer drugs. For respiratory tract infections the difference in the prescribing of newer drugs between the two groups was significant too, the insured group had a higher proportion of the newer ones, but for g-i infections it was not significant. Uninsured people, most of them farmers, usually go to the village health station as their first visit due to illness. If the illness is not cured, the patients will be referred to the township or county hospital. Before they go to the township or county hospital they have to arrange for more money in any way possible (borrowing money, withdrawing money from the bank or selling their belongs). This could explain why at the township or county hospital there were no significant differences in the prescribing of newer drugs between the two groups. But our earlier study showed that the difference in the drug costs per visit were significant between the two groups [20]. In peoples’ minds respiratory tract infections are less serious than g-i infections. The patients with g-i infections are usually
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H. Dong et al. / Health Policy 48 (1999) 29–45
referred to township or county hospitals for treatment. More serious diseases and more advanced care facilities make it necessary for people to arrange for more money for treatment. This explains why there was no difference in the prescribing of newer antibiotics between the two groups treated for g-i infections. Drug utilization can be influenced by many factors, e.g. the patient’s income, age, sex, health status, occupation, social and cultural context; drug quality and information, prescriber’s knowledge, level of health care facilities and disease patterns. All illnesses occur within a cultural context, which may shape perceptions of whether drugs are needed or not. Patients have specific ideas about what illness will benefit from what kind of drug therapy [10,11]. People often believe in the power of injections due to the fact that the medicine is injected directly into the blood [31], and has a more rapid onset. In this study, 73.8% of antibiotics were injectable. As mentioned above, via interviews with providers in rural China, we found that physicians prescribed and even changed their prescriptions according to patients’ demands and even according to how much money the patients had in their pocket [9]. First they asked what kind of drugs did the patient want and how much money the patient had in the pocket and then decided on types and amount of drugs or changed the prescriptions. This indicates that the demand factor may be the stronger determinant behind the findings reported here. The drug companies’ information about their products and sales commission or gifts to prescribers might also have influenced the prescribers’ behavior [8,10], and the choice of drugs by prescribers and patients [13]. As far as we know little information is available about the influence of health financing systems on the prescribing and use of drugs, including antibiotics, in outpatient services in China, as well as in other developing countries. Previous studies have focused on essential drug use according to the guidelines recommended by WHO, not on the financing systems, but some information in developed countries is available to support our finding that the insured group has higher access to expensive drugs. The copayment policy introduced in the UK by the NHS has led to a significant reduction in the use of prescribed drugs among non-exempt patients [32]. The result of the Rand Health Insurance Experiment showed that people with free medical care used antibiotics 85% more than those required to pay some portion of their medical bills [22]. The Rand study can be used to address price elasticity of demand for antibiotics but our study cannot. As indicated above, many factors can influence the prescribing and using of drugs. Our study showed that the main factors were health financing systems and the level of health care facilities. Health financing systems are related to people’s ability and willingness to pay for medical services. If people were covered by a comprehensive insurance scheme they could get free medical services, and would have greater access to the services than those paying out-of-pocket. Even if there was a relatively high level of copayment in the insurance, they would still have a greater ability to pay than those who were uninsured as at least some payment would be covered by the insurance. The financial incentive of the patients have an impact on physician behavior through their communication. The patients release their private information on whether they have insurance or not and the amount of
H. Dong et al. / Health Policy 48 (1999) 29–45
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funds they have available, and the physician takes this information into account while making the prescription decision [9]. The level of health care facilities is related to the availability of newer drugs. The higher the level of the health facility, the greater the availability of newer drugs. A health insurance system with a limited population coverage and unequal allocation of health resources will result in inequity in health care, including access to care and the quality of care. In China, over 85% of the rural population are not covered by any health insurance, and their health status is relatively poor. In 1992, the infant mortality rate was 15.8 per 1000 live births in the major cities and 71.8 per 1000 live births in poor rural counties [6]; life expectancy was 71.6 years in the cities and 68.7 years in rural areas [2]. The health resources are concentrated in big cities and even in rural areas the resources are also similarly concentrated in the county capitals. The number of physicians per 1000 people in 1990 was about four in the big cities and less than two in other areas [33]. These conditions could, together, result in inequity in health care in China. Equity in health care is defined by Margaret Whitehead as equal access to available care for equal need, equal utilization for equal need and equal quality of care for all [34]. Although this study is not focused on the equity issue, the results suggest that — compared to the insured patients—the uninsured cannot get equal access to antibiotics for equal need, implying that they do not have equal quality of care. The results show that the commonly used antibiotics in outpatient care were penicillin, gentamicin, norfloxacin, cephalosporins and sulfonamides and differed from those reported from other countries. In Bangladesh the most commonly used antibiotics were penicillin, tetracycline, sulfonamides and chloramphenicol [28]. In Denmark and Finland cephalosporins, tetracycline, macrolides, penicillin and trimethoprim were the most commonly used. In Estonia the most commonly used antibiotics were tetracycline, macrolides, penicillin, aminoglycosides and chloramphenicols [29]; in Sri Lanka they were penicillin and tetracycline [30]. The reasons for these differences are not clear. They could be due to differences in disease patterns, patient characteristics, and levels of health care facilities in different countries. The rational use of antibiotics is also an important issue in the drug use field of study. The rational use of drugs is a complex issue, which we did not study in this research, but some data of this study implied that there were problems in the rational use of antibiotics in rural China. For example, 67.9% of outpatients with respiratory tract infections (59.3% in the insured group and 72.9% in the uninsured) were given antibiotics. In all, 73.8% of the antibiotics were injectables (68.9% in the insured group and 76.5% in the uninsured). The study also implied that the insured group might have higher drug costs than the uninsured group because the insured group had greater access to newer antibiotics (newer antibiotics are usually more expensive) than the uninsured group. This is consistent with the results of our previous report that the insured patients have significantly higher drug costs than the uninsured patients as indicated above [20].
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H. Dong et al. / Health Policy 48 (1999) 29–45
5. Conclusion The results in this study showed that health financing systems appeared to have effects on the prescribing of antibiotics, not only on the rate of antibiotics prescribed but also on the types of antibiotics (newer or older). In outpatient services, the uninsured people (out-of-pocket) had higher prescribing of antibiotics, a higher proportion of prescribing of older types of antibiotics, and a higher proportion of prescribing of injections than the insured people. Because there was a high patient compliance rate (94.3%) in this study the prescribing of antibiotics reflected the use of antibiotics to a great extent. Thus, the results imply that antibiotics prescribing and use might be biased by the patient’s health financing systems and antibiotic prescribing was the result of interaction between physicians and patients.
Acknowledgements This article resulted from a collaborative research project between IHCAR, the Karolinska Institutet, and the School of Public Health, Shanghai Medical University, financially supported by the Swedish International Development Agency (Sida/SAREC).
References [1] Chinese Pharmacy Year Book Editorial Board, Chinese Pharmacy Year Book 1991 – 1994, Beijing: Chinese Medical Science Press, 1992 – 1995. [2] Ministry of Health. Research on National Health Service, — An Analysis Report of the National Health Services Survey in China. Beijing: Ministry of Health, 1994. [3] Chinese Health Year Book Editorial Board. Chinese Health Year Book 1983. Beijing: People Health Press, 1984. [4] Chinese Medicine Year Book Editorial Board, Chinese Medicine Year Book 1991 – 1993, Chinese Medical Science Press, Beijing, 1992 – 1994. [5] Akin JS, Birdsall N, De Ferranti D. Financing Health Services in Developing Countries: An Agenda for Reform. Washington DC: The World Bank, 1987. [6] Bogg L, Dong HJ, Wang KL, Cai WW, Diwan V. The cost of coverage: rural health insurance in China. Health Policy Plan 1996;11:238 – 52. [7] Gu XY, Bloom G, Tang SH, Zhu YY, Zhou SQ, Chen YB. Financing health care in rural China: preliminary report of a nationwide study. Soc Sci Med 1993;36:385 – 91. [8] Dong HJ, Bogg L, Rehnberg C, Diwan V. Drug policy in China: pharmaceutical distribution in rural areas. Soc Sci Med 1999;48:777 – 86. [9] H.J. Dong, L. Bogg, C. Rehnberg, V. Diwan, Health financing policies: providers’ opinions and prescribing behavior in rural China. Int. J. Technol. Assess. Health Care (in press). [10] Avorn J, Harvey K, Soumerai SB, Herxheimer A, Plumridge R, Bardelay G. Information and education as determinants of antibiotics use: report of Task Force 5. Rev Infect Dis 1987;9:s286 – 96. [11] Soumerai SB. Factors influencing prescription. Aust J Hosp Pharm 1988;18(3):9 – 16 Suppl. [12] McConnell TS, Cushing AH, Bankhurst AD, Healy JL, Mcivema PA, Skipper BJ. Physician behavior modification using claim data: tetracycline for the upper respiratory infection. West J Med 1982;137:448–50.
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[13] Avorn J, Chen M, Hartley R. Scientific versus commercial sources of influence on the prescribing behavior of physicians. Am J Med 1982;73:4 – 8. [14] McGavock H. Some patterns of prescribing by urban general practitioners. Br Med J 1988;296:900–2. [15] Chinburaapa V, Larson LN, Brucks M, Draugalis J, Bootman JL, Puto CP. Physician prescribing decision: the effects of situational involvement and task complexity on information acquisition and decision making. Soc Sci Med 1993;36:1473 – 82. [16] Hux JE, Levinton CM, Naylor CD. Prescribing propensity: influence of life-expectancy gains and drug cost. J Gen Intern Med 1994;9:195 – 201. [17] Smith DG. The effects of copayments and generic substitution on the use and costs of prescription drugs. Inquiry 1993;30:189–98. [18] Biritwum RB. The cost of sustaining the Ghana’s ‘‘Cash and Carry’’ system of health care financing at a rural health center. West Afr J Med 1994;13:124 – 7. [19] Jones N, Purdie G. The effects of user charges on the dispensing of prescription medicine: a survey of prescription charge payment in the Wellington Region. N Z Med J 1993;106:225 – 6. [20] Dong HJ, Bogg L, Wang KL, Rehnberg C, Diwan V. A description of outpatient drug use in rural China: evidence of differences due to insurance coverage. Int J Health Plan Manag 1999;14:41 – 56. [21] Dong HJ, Yan F. Antibiotics utilization analysis in outpatient services at two counties in China (in Chinese). Chin Prim Health Care 1997;11(5):25 – 7. [22] Foxman B, Valdez RB, Lohr KN, et al. The effect of cost sharing on the use of antibiotics in ambulatory care: results from a population-based randomized controlled trial. J Chronic Dis 1987;40:429–37. [23] Massele AY, Ofori-Adjei O, Laing RO. A study of prescribing patterns with special reference to drug use indicators in Dar es Salaam Region, Tanzania. Trop Dr 1993;23:104 – 7. [24] Gilson L, Jaffar S, Mwankusye S, Teuscher T. Assessing prescribing practice: a Tanzanian example. Int J Health Plan Manag 1993;8:37– 58. [25] Action Programme on Essential Drugs, World Health Organization, How to Investigate Drug Use in Health Facilities, Selected Drug Use Indicators, WHO/DAP/93.1, 1993. [26] Walker GJ, Hogerzeil HV, Sallami AO, Alwan AA, Fernando G, Kassem FA. Evaluation of rational drug prescription in Democratic Yemen. Soc Sci Med 1990;31:823 – 8. [27] Naja SA, Idris MZ, Khan A. Drugs cost more at primary health clinics, an experience from Libya. Health Policy Plan 1988;3:69–73. [28] Hossain MM, Glass LI, Khan MR. Antibiotic use in a rural community in Bangladesh. Int J Epidemiol 1982;11:402–5. [29] Kiivet RA, Bergman U, Sjo¨qvist F. The use of drugs in Estonia compared to the Nordic countries. Eur J Clin Pharmacol 1992;42:511–5. [30] Angunawela I, Diwan VK, Tomson G. Experimental evaluation of the effects of drug information on antibiotic prescribing: a study in outpatient care in an area of Sri Lanka. Int J Epidemiol 1991;20:558–64. [31] H. Anita, Why are injections so popular? World Health, March – April (1992) 18 – 19. [32] Ryan M, Birch S. Charging for health care: evidence on the utilization of NHS prescribed drugs. Soc Sci Med 1991;33:681–7. [33] Ministry of Health, P.R. China. Selected Edition on Health Statistics of China (1978 – 1990). Beijing: Ministry of Health, 1991. [34] Whitehead M. The concepts and principles of equity and health. Int J Health Serv 1992;22:429 – 45.
.
.
Association between health insurance and antibiotics prescribing in four counties in rural China Hengjin Dong a,*, Lennart Bogg b, Clas Rehnberg c, Vinod Diwan b,d a
Department of Hospital Management, School of Public Health, Shanghai Medical Uni6ersity, Shanghai 200032, People’s Republic of China b Di6ision of International Health Care Research (IHCAR), Department of Public Health Science, Karolinska Institutet, Stockholm S-171 76, Sweden c Stockholm School of Economics, Stockholm S-113 83, Sweden d Nordic School of Public Health, Box 12133, Go¨teborg S-402 42, Sweden Received 8 December 1998; accepted 29 March 1999
Abstract A cross-sectional study was carried out at county, township and village health care facilities in four counties in rural China in order to describe and compare the effects of health financing systems on antibiotic prescribing in outpatient care. A total of 1232 outpatients at the health care facilities was selected by multi-stage random sampling and were interviewed over 2 weeks. The results showed that health financing systems appeared to influence antibiotic prescribing in outpatient care, both in terms of frequency and of the types prescribed. The insured group had lower prescribing of antibiotics at township and village health care facilities, and for respiratory tract infections, but had higher prescribing of newer antibiotics at county and village health care facilities, for respiratory tract and g-i infections. Because there was a high patient compliance rate (94.3%) in this study the prescribing of antibiotics (supply side behavior) reflected the use of antibiotics (demand side behavior) to a great extent. Thus the results imply that antibiotics prescribing and using might be biased by the patient’s health financing systems and antibiotic prescribing was the result of the interaction between physicians and patients. © 1999 Elsevier Science Ireland Ltd. All rights reserved. Keywords: Health insurance; Antibiotics; Prescribing; Utilization; China * Corresponding author. Tel.: +86-21-64041900; fax: + 86-21-64169552. E-mail address: [email protected] (H. Dong) 0168-8510/99/$ - see front matter © 1999 Elsevier Science Ireland Ltd. All rights reserved. PII: S 0 1 6 8 - 8 5 1 0 ( 9 9 ) 0 0 0 2 6 - 3
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1. Introduction Drugs are an important element of health care in all countries. In many countries drugs are also important economic products, often quite profitable. In China, the production value of drugs (current prices) increased from 27.5 billion yuan (1 US$= 5.8 yuan) in 1990 to 51.2 billion yuan in 1993 [1]. In rural health care facilities, nearly 70% of the outpatient care revenue and 55% of the inpatient care revenue come from drugs [2]. In urban health care facilities, about 50% of the revenue is from drugs. There are over 5000 types of drugs and preparations available in China [3]. The most commonly used drugs are antibiotics, drugs for the digestive system, antipyretics and vitamins. The most commonly used antibiotics are penicillin, ampicillin and cephalosporine [1]. Antibiotics constitute about 16% of the total drug products and the production of antibiotics increased from about 35 797 tons in 1990 to 42 645 tons in 1992. Among the first 50 commonly used drugs, 23 were antibiotics [4]. Drugs are financed by government insurance, labor insurance, and also by out-of-pocket payments (nearly 80% of the drugs). China has developed and implemented medical reforms since the 1980s. The basic principles in the reforms are to cut government costs for health care facilities, to encourage health care facilities to use fee-for-service to raise funds, to introduce a competitive mechanism in the production and distribution of drugs and to introduce a copayment scheme by the government and labor insurance. These principles are much in line with the World Bank recommendations [5 – 7] in its 1987 policy document. In the document, after identifying three main problems in the health sector (insufficient allocation spending on cost-effective health activities, internal inefficiency of public programs and inequity in the distribution of benefits from health services), the World Bank suggested an agenda for reform and a health financing policy package, consisting of user fees, health insurance, decentralization and privatization [5]. The agenda for reform reflected the market-oriented trends of the 1980s and has influenced health sector reform in most developing countries. With the collapse of rural cooperative health insurance in China in the early 1980s due to the rural economic system reforms, currently, only about 5% of rural villages remain covered by insurance. The majority (86%) of the rural population has to pay for health care out of their own pockets. Only a small number (about 9%) of rural inhabitants can enjoy coverage by government insurance, labor insurance, semi-government or labor insurance and private health insurance. Government insurance is financed by the central government (general tax) and covers all staff in central or local government facilities. Prior to 1986 the government health insurance covered all medical costs including drugs, except physician fees. Since then it has been reformed, increasing copayment, and reducing the coverage for drugs. At present government insurance covers about 1400 types of drugs and preparations. The labor health insurance financed by
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central or local government enterprises covers personnel working in central or local government companies. Prior to 1986 it covered all medical costs, including drugs and physician fees. Since then the coverage has been reduced to 50–90% of the cost, according to the enterprise’s profits. The semi-labor or government insurance covers about 50% of medical costs, including drugs, for the dependants of those with government or labor health insurance. Cooperative health insurance is financed by the village or township and the participants. The participants pay part of the medical costs. Uninsured (out-of-pocket) people have to pay 100% of medical costs themselves. As part of the reform, the drug distribution network has also been changed, from a centrally-controlled supply system to a market-oriented demand system [8]. Prior to 1980 over 90% of the county hospitals’ drugs and nearly 100% of the township hospitals’ drugs were supplied by the county drug companies, while 100% of the village health stations’ drugs came from the township hospitals. The hospitals can now purchase drugs from drug companies, factories and drug retailers. The reform has also given patients easier access to drugs, as more drugs are available on the market. The system of reimbursement from the government budget to rural health care facilities has also been reformed. Previously, the government financed the whole budget of the county and township health facilities, including salaries, supplies and equipment. Currently, it finances only 60% of salaries and some equipment. The remaining 40% of the salaries and the cost of supplies are funded from fee-for-service revenue, including drug sales. Another paper of ours shows that this change has already influenced the providers’ prescribing behavior [9]. It was found that most of the clinical doctors said they prescribed more expensive antibiotics for insured patients and changed prescriptions according to patient demands, financial ability and health financing systems in the treatment for some diseases, such as chronic bronchitis, tuberculosis and hypertension. There is only limited information available about the effect of health financing systems on drug prescribing (supply side behavior) and use (demand side behavior). Drug use and prescribing are influenced by many factors: patient demand, information on drugs, payment methods for the prescribers, the illness itself [10– 16], and, indeed, the health financing system. A study in the USA has shown that a change in the rate of copayment from 3 to 5 US$ per prescription was associated with a 5% decrease in the number of prescriptions [17]. Ghana’s ‘cash and carry’ system reduced clinic attendance by 25% [18]. User fees in New Zealand may provide a barrier for prescription medicines to children, students and people living in areas of high social need [19]. In China our earlier studies suggested that health financing had an effect on the use of health care, particularly the use of drugs: a macro-analysis in two rural counties showed that fee-for-service-based health care financing led to higher expenditure for drugs and curative health care [6]; and an outpatient care study in five rural counties showed that compared with the uninsured patients, the insured patients had significantly higher drug costs per outpatient visit [20].
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From the above evidences it is hypothesized that antibiotics prescribing is influenced to some degree by health financing systems in rural China because of insurance policies and policy-related prescription behavior. The aim of this study is to describe and compare the effects of health financing systems on antibiotics prescribing in outpatient care in rural China.
2. Methods
2.1. Sampling and sample size Fig. 1 shows the sampling process and sample size. Multi-stage sampling was used to select the county, township and village health care facilities. First, two provinces (Jiangsu and Anhui) in central China were purposely chosen. The two provinces were selected on the grounds of having different economic parameters, Jiangsu having the higher economic level, Anhui a lower level. Secondly, two counties in each province (Tongling and Fanchang in Anhui, Jurong and Jintan in Jiangsu) were purposely chosen according to their gross national product (GNP) and health status. The two counties within each province were selected on the
Fig. 1. Sampling and sample size. Note: *, sample/total of the four counties; †, only complete the sample size decided before interview, do not emphasize how to select the interviewees.
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grounds of having as similar socio-economic parameters as possible. Thirdly, one town and four townships in each county were chosen. At this stage (a) we randomly selected one middle income town, (b) divided the townships into two groups according to their income levels (above or below a mean level), and (c) randomly selected two townships in each group. Before sampling, all towns and townships were listed according to their income levels. Fourthly, we randomly selected five villages in each township. Before sampling, all villages were listed. Fifthly, a quota method was used to select the outpatients. It was estimated that in each county 300 outpatients needed to be interviewed, distributing 100 at county hospitals, 100 at township hospitals and 100 at village health stations. In 1994, the average population in the four counties was 480 000 (range from 340 000 to 600 000). GNP per capita in Anhui and Jiangsu was 2499 and 5775 yuan, respectively. The GNP per capita at Tongling, Fanchang, Jurong and Jintan was, respectively, 2897, 2001, 5272 and 6313 yuan; and the reported infant mortality rate (IMR) per 1000 live births was 32.3, 17.3, 12.7 and 16.2, respectively. It seems that the two provinces had different economic parameter, and the two counties in each province had similar parameters and the parameters are consistent with their provincial level. The IMR was a reported figures, maybe not completely correct.
2.2. Outpatient inter6iew Exit interview was used to obtain—for each outpatient—information on age, sex, occupation, education, per capita income, health financing systems, reasons for seeing a doctor, diagnosis, number and types of antibiotics prescribed, usage (oral, muscle injection or vein injection), reasons for prescribing antibiotics and the number and kinds of other drugs prescribed. The outpatients were interviewed in the selected county, township and village health care facilities. The outpatients at county and township hospitals were distributed proportionally to the departments where they were being treated. The outpatients were interviewed over 2 weeks in August – September 1995. Exit interview means to interview the outpatients at the time they have completed visiting the doctor, have got prescriptions and drugs (if the patients want to buy them) and are going to leave the hospital. A five-page questionnaire was used during interviewing. The questionnaire was revised four times and following a pilot study, tested in the counties 3 months before the formal interviews began. Fifteen interviewers, teachers or health workers in the preventive health facilities in the local areas were trained by research assistants from Shanghai Medical University (SMU), China, for 2 days just before the interviewing started. The interview was face-to-face, the questions were answered by the patient himself. If the patient was a child or the health condition was serious, the questions were answered by the accompanying person. Each interview lasted about 15 min. The outpatients were mixed, including any visits (first or second) and any diseases (acute or chronic). During the interview two research assistants from SMU, in each county, were responsible for quality control. The questionnaires were requested to be handed to the county health bureau every 2
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days and examined by the two assistants. If the questionnaires did not qualified (especially in not recording each drug name), the questionnaires were returned and the interviewers were asked to interview more outpatients to fill the gaps. About 10% of the questionnaires were returned because of missing drug names or other items, such as type of insurance, age, etc.
2.3. Analysis methods and indicators The interview data were entered into a computer using the Epi-Info program and analyzed using the SPSS program. x 2-Tests for the differences in proportions and Fisher’s exact test were carried out. The following indicators were chosen to reflect the prescribing of antibiotics in outpatient services: prescribing or not prescribing of antibiotics, average number of antibiotics prescribed per visit, the reasons for prescribing antibiotics, usage of antibiotics and the types of antibiotics (newer or older drugs) prescribed. The indicators were analyzed according to the health financing systems, the levels of health care facility (county, township and village) and two common systemic diseases, infections of the respiratory tract and of the digestive system, respectively.
3. Results
3.1. General information A total of 1232 outpatients were interviewed in the four counties, of which 398 outpatients were at county hospitals, 468 at township hospitals, and 366 at village health stations. Table 1 shows the outpatients’ socio-demographic characteristics and other information. Male outpatients made up a littler more than female ones, about half of the outpatients were farmers, most of them only had secondary school education and the majority of them were not covered by any health insurance. The main reasons for their coming to hospital were disease or injury, but Jintan (82.1%) is significantly lower than all the other three counties in the proportion of disease or injury (x 2 =25.22, P B 0.01). Their average age was 32.7 years (34.1 for male and 31.3 for female), and average income per capita in 1994 was 1558 yuan. The numbers in Table 1 are not consistent in some items because of missing data, e.g. the sum of male and female is not equal to the total number of cases.
3.2. Prescribing of antibiotics Table 2 shows the prescribing of antibiotics among the insured (covered by the government insurance, labor insurance, dependants and cooperative insurance) and uninsured groups (out-of-pocket). Out of 1223 outpatients, 585 (47.8%) were prescribed antibiotics. The uninsured group had higher antibiotic prescribing than the insured. The difference was statistically significant. At county hospital level, the prescribing of antibiotics was 34.3%. The uninsured group had a little lower
Table 1 Socio-demographic characteristics of outpatients in four counties in China Provinces
Anhui
Jiangsu
Counties
Tongling (%)
Fanchang (%)
Total (%)
Jurong (%)
Jintan (%)
284 95 (33.5) 78 (27.5) 111 (39.1)
323 103 (31.9) 130 (40.2) 90 (27.9)
320 100 (31.3) 151 (47.2) 69 (21.6)
1232 398 (32.3) 468 (38.0) 366 (29.7)
Male Female
177 (58.0) 128 (42.0)
165 (58.1) 119 (41.9)
175 (54.3) 147 (45.7)
137 (43.2) 180 (56.8)
654 (53.3) 574 (46.7)
Occupation Farmers Workers Students Cadres Others
153 43 32 18 57
(50.5) (14.2) (10.6) (5.9) (18.8)
136 50 19 16 63
(47.9) (17.6) (6.7) (5.6) (22.2)
169 52 23 18 61
(52.3) (16.1) (7.1) (5.6) (18.9)
141 73 21 17 66
(44.3) (23.0) (6.6) (5.3) (20.7)
599 218 95 69 247
(48.7) (17.8) (7.7) (5.6) (20.1)
Education Pre-school No schooling Primary school Middle school High and above
22 60 76 95 49
(7.3) (19.9) (25.2) (31.5) (16.2)
32 32 67 97 44
(11.3) (11.3) (23.6) (34.2) (15.5)
28 36 86 118 55
(8.7) (11.1) (26.6) (36.5) (17.0)
13 21 75 124 85
(4.1) (6.6) (23.6) (39.0) (26.7)
95 149 304 434 233
(7.7) (13.1) (24.8) (35.4) (19.0)
Health financing Governmenta Cooperative Private insurance Out-of-pocket
55 5 11 231
(18.2) (1.7) (3.6) (76.5)
53 0 3 228
(18.7) (0.0) (1.1) (80.3)
31 34 41 216
(9.6) (10.6) (12.7) (67.1)
96 164 6 54
(30.0) (51.3) (1.9) (16.9)
235 203 61 729
(19.1) (16.5) (5.0) (59.4)
Reasons for seeking hospital care Diseases and injury Others
275 (91.1) 27 (8.9)
258 (93.5) 18 (6.5)
292 (91.5) 27 (8.5)
261 (82.1) 57 (17.9)
1086 (89.4) 129 (10.5)
35
305 100 (32.8) 109 (35.7) 96 (31.5)
H. Dong et al. / Health Policy 48 (1999) 29–45
n County hospital Township hospital Village station
36
Provinces
Anhui
Counties
Tongling (%)
Age (years old) (low to high) B1 1–14 15–34 35–64 ]65 Income/capita (yuan)b (low to high) a b
Jiangsu Fanchang (%)
Jurong (%)
Total (%) Jintan (%)
32.6 (0–80) 5 (1.6) 41(13.4) 131(43.0) 111(36.4) 17(5.6)
30.7 (0–82) 3 (1.1) 37 (13.0) 140 (49.3) 97 (34.2) 7 (2.4)
33.8 (0–89) 6 (1.9) 38 (11.8) 142 (44.0) 119 (36.8) 18 (5.6)
33.5 (0–80) 0 (0.0) 24 (7.5) 165 (51.6) 118 (36.9) 13 (4.0)
32.7 (0–89) 14 (1.1) 140 (11.4) 578 (46.9) 445 (36.1) 55 (4.5)
1557 (100–8000)
1946 (50–8000)
2490 (50–10000)
4124 (200–15000)
2558 (50–15000)
Government, government insurance+labor insurance+semi-labor or government. 1 US$= 5.8 yuan in 1994.
H. Dong et al. / Health Policy 48 (1999) 29–45
Table 1 (Continued)
H. Dong et al. / Health Policy 48 (1999) 29–45
37
Table 2 Antibiotic prescribing by financing groups Systems
Insurance (%)
Out-of-pocket (%)
Total (%)
x2
P
Total cases (n) Yesa
499 209 (42.3)
729 376 (51.6)
1228 585 (47.8)
10.1
0.002
County hospital (n) Yes
191 69 (36.3)
207 67 (32.4)
398 136 (34.3)
0.9
0.41
Township hospital (n) Yes
217 103 (47.5)
248 139 (56.0)
465 242 (52.0)
3.4
0.06
91 37 (42.5)
274 170 (62.0)
365 207 (57.3)
10.3
0.001
258
408
8.0
0.005
0.7
0.39
Village health station (n) Yes Respiratory tract infections (n) Yes
150 89 (59.3)
188 (72.9)
277 (67.9)
Digestive system infections (n) Yes
74
134
208
47 (63.5)
77 (57.5)
124 (59.6)
Number of antibiotics per encounter with antibiotics prescriptions County 1.19 1.09 Township 1.28 1.25 Village 1.14 1.26
1.14 1.26 1.24
0.24† 0.004† 0.46†
0.63 0.95 0.23
Total
1.23
0.07†
0.79
a †
1.22
1.23
Yes, prescribing antibiotics. F-value.
antibiotic prescribing than the insured, but the difference was not statistically significant. At township hospital level, the prescribing was 52%, higher than that at the county hospital level, the uninsured had higher prescribing than the insured, but the difference was not statistically significant. At village health stations, prescribing was 57.3%, higher than that at county and township hospitals; the uninsured also had higher prescribing than the insured, and the difference was statistically significant. Among the different insurance schemes, the prescribing of antibiotics was 36.8% (86/234) for government and labor insurance, 48.2% (96/199) for cooperative insurance, and 44.3% (27/61) for private insurance. In the study 91.9% of insured patients bought drugs and 95.7% of uninsured patients bought drugs, the total compliance rate was 94.3%. This high compliance rate implies that the prescribing of antibiotics (supply side behavior) reflect the use of antibiotics (demand side behavior) to a great extent. Respiratory tract and g-i infections are common causes of outpatient attendance. In this study there were 408 cases of respiratory tract infections and 208 cases of g-i infections, exactly 50% of the total number of outpatients. Antibiotics are commonly used for infections in these two systems. For respiratory infections, the
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H. Dong et al. / Health Policy 48 (1999) 29–45
prescribing of antibiotics was 67.9%. The uninsured group had higher prescribing than the insured, and the difference was statistically significant. For g-i infections, the prescribing was 59.6%. The uninsured group had lower prescribing than the insured, but the difference was not significant (Table 2).
3.3. A6erage number of antibiotics prescribed per 6isit In the outpatients prescribed antibiotics, the average number of antibiotics per visit was 1.2. The insured and the uninsured groups both had a similar average level and there was no significant difference between them (Table 2). Most (74.6%) of them received one antibiotic, 25.6% had two or more.
3.4. Usage of antibiotics Over 70% of the prescriptions were for injectable antibiotics, and 26.2% for oral ones. The usage of antibiotics was significantly different between the insured and the uninsured groups, and the uninsured had a higher frequency of injections. At county hospital level, the uninsured also had a higher frequency of injections than the insured, and the difference was statistically significant. But at township and village health care facilities, the difference was not significant between the groups (Table 3). From the county to the village level, the frequency of injection increased gradually, and the difference among the levels was significant (PB 0.001).
3.5. Reasons for prescribing antibiotics The reasons of prescribing antibiotics were cough, diarrhoea and fever (Table 4). Although fever, cough and diarrhoea are symptoms, antibiotics are usually preTable 3 Antibiotic usage by financing groups Systems
Insurance (%)
Out-of-pocket (%)
Total (%)
x2
P
Total cases (n) Oral Injection
209 64 (31.1) 142 (68.9)
376 86 (23.5) 280 (76.5)
585 150 (26.2) 422 (73.8)
3.9
0.04
69 38 (57.6) 28 (42.4)
67 20 (32.3) 42 (67.7)
136 58 (45.3) 70 (54.7)
8.3
0.004
103 20 (19.4) 83 (80.6)
139 38 (27.7) 99 (72.3)
242 58 (24.2) 182 (75.8)
2.2
0.14
37 6 (16.2) 31 (83.8)
170 28 (16.8) 139 (83.2)
207 34 (16.7) 170 (83.3)
0.01
0.94
County hospital (n) Oral Injection Township hospital (n) Oral Injection Village health station (n) Oral Injection
H. Dong et al. / Health Policy 48 (1999) 29–45
39
Table 4 Reasons for prescribing antibiotics by financing groups Systems
Insurance (%)
Out-of-pocket (%) Total (%)
x2
P
Total cases (n) Fever Diarrhoea Cough Others
209 19 39 62 87
376 68 44 86 170
0.002
(18.5) (12.0) (23.4) (46.2)
585 87 83 148 257
14.7
(9.2) (18.8) (30.0) (42.0)
(15.1) (14.4) (25.7) (44.7)
69 4 6 16 42
67 13 6 11 34
0.09
(20.3) (9.4) (17.2) (53.1)
136 17 12 27 76
6.4
(5.9) (8.8) (23.5) (61.8)
(12.9) (9.1) (20.5) (57.6)
103 12 19 32 40
139 24 19 30 64
0.18
(17.5) (13.9) (21.9) (46.7)
242 36 38 62 104
4.9
(11.7) (18.4) (31.1) (38.8)
(15.0) (15.8) (25.8) (43.3)
37 3 14 14 5
(8.3) (38.9) (38.9) (13.9)
170 31 19 45 72
(18.6) (11.4) (26.9) (43.1)
207 34 33 59 77
(16.7) (16.3) (29.1) (37.9)
County hospital (n) Fever Diarrhoea Cough Others Township hospital (n) Fever Diarrhoea Cough Others Village health station (n) Fever Diarrhoea Cough Others
23.8
0.00003
scribed according to symptoms in rural China and these three symptoms are, in fact, the common ones for the use of antibiotics. The reasons for prescribing antibiotics were significantly different between the uninsured and the insured groups. At village health stations the reasons for prescribing antibiotics between the two groups were also significantly different. At county and township hospitals, the reasons were not significantly different. In the insured group the main reasons were cough and diarrhoea, but in the uninsured group the main reasons were cough and fever.
3.6. Types of antibiotics The most commonly prescribed antibiotics in outpatient care were penicillin, gentamicin, norfloxacin, cephalosporins, sulfonamides and streptomycin. Penicillin, gentamicin and sulfonamides are older antibiotics, norfloxacin and cephalosporins are newer ones. Usually the newer drugs are more expensive and effective. The result showed that the difference in the prescribing of the newer antibiotics between the two groups was statistically significant. The proportion of patients prescribed the newer antibiotics in the insured group was higher than that in the uninsured group. The difference at the village health station was significant as well, with the insured group prescribed the newer drugs to a greater extent. But the differences were not significant at the county and the township hospitals. For respiratory tract
H. Dong et al. / Health Policy 48 (1999) 29–45
40
infections, the difference in the prescribing of the newer drugs between the two groups was significant, and the insured group had a higher proportion of new-drug users than the uninsured group. For the g-i infections the difference was not significant. The results also showed that the health care facility was another factor influencing the prescribing of the newer drugs. From village to county, the prescribing of the newer drugs in the uninsured group increased gradually (Table 5).
4. Discussion This is one of few studies in this area in China, and also in other countries, to describe antibiotic prescribing, particularly the prescribing of newer or older antibiotics, in outpatient care in relation to the patients’ health financing systems by interviewing outpatients at exit [21–30]. The main finding from this study was that the patients’ health financing systems appeared to influence the prescribing of antibiotics in outpatient care in rural China, both in frequency and in type. In general the uninsured patients had higher prescribing of antibiotics and higher Table 5 Types of antibiotics by financing groups Systems
Insurance (%)
Out-of-pocket (%) Total (%)
Total cases Penicillin Gentamicin Norfloxacin Cephalosporins Sulfonamides Others
97 35 27 22 13 62
County hospital Newer drugs Old drugs
25 (30.5) 57 (69.5)
15 (20.5) 58 (79.5)
40 (25.8) 115 (74.2)
16 (12.1) 116 (87.9)
30 (17.2) 144 (82.8)
46 (15.0) 260 (85.0)
Village health station Newer drugs Old drugs
8 (19.0) 34 (81.0)
10 (4.7) 204 (95.3)
18 (7.0) 238 (93.0)
Respiratory infections Newer drugs Old drugs
20 (18.9) 86 (81.1)
19 (8.5) 205 (91.5)
39 (11.8) 291 (88.2)
Digestive system infections Newer drugs Old drugs
14 (23.0) 47 (77.0)
18 (16.7) 90 (83.3)
32 (18.9) 137 (81.1)
Township hospital Newer drugs Old drugs
a
(37.9) (13.7) (10.5) (8.6) (5.1) (24.2)
209 74 37 17 21 103
(45.3) (16.1) (8.0) (3.7) (4.6) (22.3)
306 109 64 39 34 165
x2
P
11.6
0.04
2.0
0.16
1.5
0.21
(42.7) (15.2) (8.9) (5.4) (4.7) (23.0)
0.003a
Fisher’s exact test (two-tailed).
7.5
0.01
1.0
0.32
H. Dong et al. / Health Policy 48 (1999) 29–45
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injection ratio than the insured patients. They also had higher prescribing of antibiotics at village health stations and for respiratory tract infections, and a higher injection ratio at county hospitals than the insured patients. The insured patients, however, had higher prescribing of the newer antibiotics in general and for some diseases than the uninsured patients. The differences in the prescribing of antibiotics between the uninsured and the insured group are likely to be related to the insurance policies and the policy-related prescription behavior, of both patients and providers, and is also likely to be related to the case mix, care-seeking behavior. The uninsured patients may have attend later and were more ill and needed antibiotics more than the insured patients. This could account for the differing rates of antibiotic prescribing and the ratios of injection use. We believe that insurance coverage works both on the supply and demand side. On the part of the patients, they request more expensive drugs if they do not have to pay the full cost themselves. We also believe that the fee-for-service system gives the providers an incentive to over-prescribe and to prescribe drugs with a higher unit revenue (and cost). These could be potential topics for future research. Government, labor and cooperative health insurance all have similar regulations for drugs, but there are some differences in the types of drugs and the coverage of drug. For example, government insurance introduced a policy limiting the insurance coverage to only about 1400 drugs or preparations. In order to control drug costs the policy also put a ceiling on the number of drugs (5 3) and on the total cost (30 yuan or less) per prescription. Together with patient demand, this explains why the insured patients had a higher proportion of the newer antibiotics. Newer drugs are usually more expensive. Compared with the insured people, there are no restrictions on the choice of drugs of the uninsured people apart from their own financial situation. Uninsured people in China are relatively poor and their ability to pay for health care is lower. This might be a reason why their access to newer drugs and expensive drugs was lower. This also suggests that people when paying out-of-pocket are more concerned about the price of drugs. The results also showed that the difference in prescribing of newer antibiotics between the insured and the uninsured groups at county and township hospitals was not significant, but at the village health stations it was, with the insured group having a higher proportion of newer drugs. For respiratory tract infections the difference in the prescribing of newer drugs between the two groups was significant too, the insured group had a higher proportion of the newer ones, but for g-i infections it was not significant. Uninsured people, most of them farmers, usually go to the village health station as their first visit due to illness. If the illness is not cured, the patients will be referred to the township or county hospital. Before they go to the township or county hospital they have to arrange for more money in any way possible (borrowing money, withdrawing money from the bank or selling their belongs). This could explain why at the township or county hospital there were no significant differences in the prescribing of newer drugs between the two groups. But our earlier study showed that the difference in the drug costs per visit were significant between the two groups [20]. In peoples’ minds respiratory tract infections are less serious than g-i infections. The patients with g-i infections are usually
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H. Dong et al. / Health Policy 48 (1999) 29–45
referred to township or county hospitals for treatment. More serious diseases and more advanced care facilities make it necessary for people to arrange for more money for treatment. This explains why there was no difference in the prescribing of newer antibiotics between the two groups treated for g-i infections. Drug utilization can be influenced by many factors, e.g. the patient’s income, age, sex, health status, occupation, social and cultural context; drug quality and information, prescriber’s knowledge, level of health care facilities and disease patterns. All illnesses occur within a cultural context, which may shape perceptions of whether drugs are needed or not. Patients have specific ideas about what illness will benefit from what kind of drug therapy [10,11]. People often believe in the power of injections due to the fact that the medicine is injected directly into the blood [31], and has a more rapid onset. In this study, 73.8% of antibiotics were injectable. As mentioned above, via interviews with providers in rural China, we found that physicians prescribed and even changed their prescriptions according to patients’ demands and even according to how much money the patients had in their pocket [9]. First they asked what kind of drugs did the patient want and how much money the patient had in the pocket and then decided on types and amount of drugs or changed the prescriptions. This indicates that the demand factor may be the stronger determinant behind the findings reported here. The drug companies’ information about their products and sales commission or gifts to prescribers might also have influenced the prescribers’ behavior [8,10], and the choice of drugs by prescribers and patients [13]. As far as we know little information is available about the influence of health financing systems on the prescribing and use of drugs, including antibiotics, in outpatient services in China, as well as in other developing countries. Previous studies have focused on essential drug use according to the guidelines recommended by WHO, not on the financing systems, but some information in developed countries is available to support our finding that the insured group has higher access to expensive drugs. The copayment policy introduced in the UK by the NHS has led to a significant reduction in the use of prescribed drugs among non-exempt patients [32]. The result of the Rand Health Insurance Experiment showed that people with free medical care used antibiotics 85% more than those required to pay some portion of their medical bills [22]. The Rand study can be used to address price elasticity of demand for antibiotics but our study cannot. As indicated above, many factors can influence the prescribing and using of drugs. Our study showed that the main factors were health financing systems and the level of health care facilities. Health financing systems are related to people’s ability and willingness to pay for medical services. If people were covered by a comprehensive insurance scheme they could get free medical services, and would have greater access to the services than those paying out-of-pocket. Even if there was a relatively high level of copayment in the insurance, they would still have a greater ability to pay than those who were uninsured as at least some payment would be covered by the insurance. The financial incentive of the patients have an impact on physician behavior through their communication. The patients release their private information on whether they have insurance or not and the amount of
H. Dong et al. / Health Policy 48 (1999) 29–45
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funds they have available, and the physician takes this information into account while making the prescription decision [9]. The level of health care facilities is related to the availability of newer drugs. The higher the level of the health facility, the greater the availability of newer drugs. A health insurance system with a limited population coverage and unequal allocation of health resources will result in inequity in health care, including access to care and the quality of care. In China, over 85% of the rural population are not covered by any health insurance, and their health status is relatively poor. In 1992, the infant mortality rate was 15.8 per 1000 live births in the major cities and 71.8 per 1000 live births in poor rural counties [6]; life expectancy was 71.6 years in the cities and 68.7 years in rural areas [2]. The health resources are concentrated in big cities and even in rural areas the resources are also similarly concentrated in the county capitals. The number of physicians per 1000 people in 1990 was about four in the big cities and less than two in other areas [33]. These conditions could, together, result in inequity in health care in China. Equity in health care is defined by Margaret Whitehead as equal access to available care for equal need, equal utilization for equal need and equal quality of care for all [34]. Although this study is not focused on the equity issue, the results suggest that — compared to the insured patients—the uninsured cannot get equal access to antibiotics for equal need, implying that they do not have equal quality of care. The results show that the commonly used antibiotics in outpatient care were penicillin, gentamicin, norfloxacin, cephalosporins and sulfonamides and differed from those reported from other countries. In Bangladesh the most commonly used antibiotics were penicillin, tetracycline, sulfonamides and chloramphenicol [28]. In Denmark and Finland cephalosporins, tetracycline, macrolides, penicillin and trimethoprim were the most commonly used. In Estonia the most commonly used antibiotics were tetracycline, macrolides, penicillin, aminoglycosides and chloramphenicols [29]; in Sri Lanka they were penicillin and tetracycline [30]. The reasons for these differences are not clear. They could be due to differences in disease patterns, patient characteristics, and levels of health care facilities in different countries. The rational use of antibiotics is also an important issue in the drug use field of study. The rational use of drugs is a complex issue, which we did not study in this research, but some data of this study implied that there were problems in the rational use of antibiotics in rural China. For example, 67.9% of outpatients with respiratory tract infections (59.3% in the insured group and 72.9% in the uninsured) were given antibiotics. In all, 73.8% of the antibiotics were injectables (68.9% in the insured group and 76.5% in the uninsured). The study also implied that the insured group might have higher drug costs than the uninsured group because the insured group had greater access to newer antibiotics (newer antibiotics are usually more expensive) than the uninsured group. This is consistent with the results of our previous report that the insured patients have significantly higher drug costs than the uninsured patients as indicated above [20].
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5. Conclusion The results in this study showed that health financing systems appeared to have effects on the prescribing of antibiotics, not only on the rate of antibiotics prescribed but also on the types of antibiotics (newer or older). In outpatient services, the uninsured people (out-of-pocket) had higher prescribing of antibiotics, a higher proportion of prescribing of older types of antibiotics, and a higher proportion of prescribing of injections than the insured people. Because there was a high patient compliance rate (94.3%) in this study the prescribing of antibiotics reflected the use of antibiotics to a great extent. Thus, the results imply that antibiotics prescribing and use might be biased by the patient’s health financing systems and antibiotic prescribing was the result of interaction between physicians and patients.
Acknowledgements This article resulted from a collaborative research project between IHCAR, the Karolinska Institutet, and the School of Public Health, Shanghai Medical University, financially supported by the Swedish International Development Agency (Sida/SAREC).
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