Abstract
Purpose: Aging, chronic diseases, and development of expensive and advanced technologies has increased hospitals costs which have necessitated their efficiency in utilization of resources. This systematic review and meta-analysis study has assessed the efficiency of Iranian hospitals before and after the 2011 Health Sector Evolution Plan (HSEP).
Methods: Internal and external databases were searched using specified keywords without considering time limitations. The retrieved articles were entered into EndNote considering inclusion and exclusion criteria, and the final analysis was performed after removing duplicates. Heterogeneity between the studies was assessed using Q and I2 tests. A forest plot with 95% confidence intervals (CI) was used to calculate different types of efficiency. The data were analyzed using STATA 14.
Results: Random pooled estimation of hospitals technical, managerial, and scale efficiencies were 0.84 (95%CI = 0.78, 0.52), 0.9 (95%CI = 0.85, 0.94), and 0.88 (95%CI = 0.84, 0.91), respectively. Sub-group analysis on the basis of study year (before and after HSEP in 2011) indicated that random pool estimation of technical (0.86), managerial (0.91), and scale (0.90) efficiencies of Iranian hospitals for 2011 and before were better than technical (0.78), managerial (0.86), and scale (0.74) efficiencies after 2011.
Conclusion: Type of hospital ownership was effective on hospital efficiency. However, HSEP has not improved hospital efficiency, so it is necessary for future national plans to consider all aspects.
Introduction
Hospitals have an undeniable role in providing healthcare services to society but their increasing costs have become an important challenge for many countries. In other words, utilization of technologies and new methods of diagnosis and treatment of diseases and also increasing numbers of elderly citizens, increasing chronic diseases, increasing demands for healthcare services and specialists, and hospital errors have increased health system costs (1, 2). Because of these issues and problems, hospitals always encounter human and financial resource constraints which have necessitated efficiency in consuming resources more than ever (3).
The efficiency concept has been created from the combination of technical and allocative efficiencies. Technical efficiency means using the lowest amount of input to produce a specified amount of output or using a specified amount of input to produce more output. Allocative efficiency means using the correct amount of input in terms of prices to produce a specified amount of output. Technical efficiency, on the other hand, was created by multiplying scale efficiency and managerial efficiency. Scale efficiency is the ability of an organization unit to perform in or near the most profitable scale to prevent loss in resources. Lastly, managerial efficiency means hard working, correct policymaking, application of the correct number of employees, and the correct combination of production factors (4).
One of the most widely used methods in assessment of different decision-making units (DMUs) such as hospitals and other organizations in terms of the components of efficiency (e.g., technical, scale, and managerial efficiency) is the data envelopment analysis (DEA) method. It is possible, through this method, to create a logical framework to distribute human and financial resources between different wards and sections of studied organizations (5). The DEA method, as a non-parametric programming technique, has been used since the mid 1980s to measure DMU efficiency (6). In other words, linear and multiple programming models are used in this method to assess the relative efficiency of a field, section, unit, or an organization, as a DMU, using multiple input and output indices (7).
Numerous studies have assessed the efficiency of hospital efficiency using the DEA method. These studies can be divided into four categories. In the first category, the efficiency of university, teaching, and public hospitals, as the main providers of healthcare and therapeutic services, has been assessed in studies by Kalhor et al. (8) and Nabi lou et al. (9). In the second category, the efficiency of private hospitals has been studied and their efficiency has been compared with the first-category hospitals (10, 11). The third category includes studies on hospitals affiliated with special entities such as Social Security Organization (12, 13) and Armed Forces (14). The last category measures the efficiency of hospital wards such as radiology (15), dentistry (4), intensive care unit (16), and emergency (17) departments. Because the latter category studies wards of hospitals rather than the hospitals in their entirety and also have not assessed the technical, managerial, and scale efficiency of hospitals wholly, this category was excluded from the current study.
Although many studies have assessed the efficiency of hospitals using the DEA method in Iran, there has been no systematic review and meta-analysis study in this regard to present the final situation of hospital efficiency in Iran. By determining technical, managerial, and scale efficiency of Iranian hospitals, policymakers and planners can improve hospital efficiency through improving distribution and consumption of resources.
The extensive review of the literature by the authors of the current study has resulted in four systematic review and meta-analysis studies on Iranian hospital efficiency using the DEA method. The first study assessed studies in terms of the provinces where they were performed, whether they were input- or output-oriented, and whether they were fixed or variable return to scale models (18). The researchers in another two systematic and meta-analysis studies discussed the methods used to assess hospital efficiency (19, 20). The last study only included a small number of studies on hospital efficiency and did not mention the efficiency subdimensions namely scale, managerial, and technical efficiency (21). As previous systematic review and meta-analysis studies have not assessed hospital efficiency using its subcategories, the current study assessed technical, managerial, and scale efficiency of hospitals through systematic review and meta-analysis.
Regarding PICOS framework or questions, the study included hospitals in Iran which had previously had their efficiency assessed and were entered into the study depending on the inclusion and exclusion criteria. The intervention framework was the assessment of the effect of HSEP on hospital efficiency, comparisons included comparing hospital efficiency before and after HSEP, outcomes included the amount of hospital efficiency, and finally the study design included assessment of hospital efficiency through systematic review and meta-analysis.
Materials and Methods
Search Strategy
The international databases of the Institute for Scientific Information (ISI), PubMed, Scopus, Google Scholar, and Persian databases of Scientific Information Database (SID), Magiran, and Barakat were searched using the combination of “efficiency,” “hospital,” “data envelopment analysis,” “DEA,” and “Iran” keywords in 2018. The references of the retrieved articles were searched to increase the study credibility and precision.
Inclusion and Exclusion Criteria
All published Persian and English language articles about hospital efficiency with a score between 8 and 12 were entered into the study without considering a time limit. If several formats of a research were published (such as a book, article, report, and so on), only one of them was entered into the study. Input-oriented studies were entered into the study. Short reports, letters to editors or editorial comments, one study that was available in two languages, studies on health care facilities other than hospitals, and studies on internal parts of hospitals were removed from the study. Two researchers assessed and extracted data from the studies independently and a third researcher resolved disagreements if they appeared.
This systematic review and meta-analysis utilized Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines to minimize potential sources of bias (22).
Data Collection
A researcher-made checklist in an Excel spreadsheet was created to extract the studies' data including the first author name, year of data collection, place of study, language, sample size, and the score of technical, managerial, and scale efficiency. Another checklist designed previously, whose credibility has been proved by numerous studies, was used to assesses the studies' quality (19, 21). This checklist includes 12 questions regarding the study aim, method, data collection, sample size, and study population. Each question has the score between 0 and 1 and the score for each study is calculated by summing the scores of questions. So that the studies with scores between 8 and 12 were entered into the final analysis. The study protocol was approved by the Ethical Committee of Kerman University of Medical Sciences.
Data Analysis
Efficiency types were considered as a proportion in this study. Therefore, the numerator was the sum of technical, managerial, and efficiency scores and the denominator was the number of study hospitals. Heterogeneity between the studies was assessed using Q and I2 tests. A P-value lower than 0.05 for the Q-test and an I2 higher than 50% were considered as the measures of studies' heterogeneity. Because the studies were heterogeneous, the random effect model was used to estimate hospital efficiency. A forest plot with 95% confidence intervals (CI) was used to calculate different types of efficiency. Egger's and Begg's tests were used to assess publication bias. In order to assess the effect of the 2011 Iran Health Sector Evolution Plan (HSEP) (23) on hospital efficiency, the studies before and after it were compared. The data were entered into Excel 2016 to be edited and then transmitted and analyzed using STATA v.14.2.
Results
Each one of the scientific databases were searched on the basis of a recommended search strategy by the databases themselves using defined keywords. For example, in the PubMed database, 23 articles were retrieved after placing the search query. Search query used for PubMed was: (((data envelopment analysis) OR DEA) AND hospital) AND Iran))). Among retrieved articles, nine articles had assessed efficiency in other areas such as radiology units, intensive care units, and health centers which were excluded from the study. So, finally 14 articles from the PubMed database were entered into the EndNote software. In other databases, after adjusting the search query on the basis of the database guide and then removing unrelated retrieved articles through reading titles, abstracts, and texts, 25 articles from Scopus, 41 from Google Scholar, 8 from Web of Science, 16 from Barakat, 14 from Magiran, and 7 from SID were entered into the EndNote software. After combination of these articles in the EndNote software and removing duplicate articles, 47 final articles remained. Also, the assessment of references of these articles resulted in two new articles. In this way, 49 articles were entered into the final step of the systematic review and meta-analysis. Twelve articles (24.48%) of these were in the Persian language and the remaining were in the English language. A PRISMA flow chart of the study retrieval and selection process with reasons for exclusion at each stage is provided in Figure 1.
Figure 1
Flow chart of systematic search and studies selection.
By attention that some studies have reported efficiency in several forms or in different scenarios and different inputs were used in them, we considered them as separated studies. In this regard, studies of Hatam et al., Karimi et al., Salehzade et al., Raeisian et al., Firouzi Jahantigh et al., and Sheikhzadeh et al. were each considered as two separated studies. Studies of Joshan et al. and Asadi et al. were each considered as three studies and lastly studies of Fazeli et al. and Mahfoozpor et al. were each considered as four studies. The average number of hospitals entered into the studies was 17.59 hospitals. The lowest and the highest number of hospitals belonged to Rezapour et al. with 4 hospitals and Aboulhalaj et al. with 122 hospitals, respectively.
As mentioned before, each type of efficiency was entered into the meta-analysis separately, so that 50 studies for technical efficiency, 36 studies for managerial efficiency, and 41 studies for scale efficiency had entry requirements to the analysis.
The studies were performed from 1996 to 2016. After performing all the steps of study selection, 49 articles were entered into the final phase of the study. The number of hospitals assessed in these articles ranged from 4 to 122. The inputs considered in the studies included number of beds, number of operation rooms, physicians, nurses, support forces and other human resources, costs, education hours, and working days. The outputs were number of surgeries, outpatients, occupancy rate, bed days, admission, inpatients, surgeries, emergencies, bed turnover, mean patient stay, hospital income, bed occupancy rate, SERVQUAL score, number of clinical, paraclinical, and outpatient services, number of discharged patients, number of contracted insurance companies, access to emergency room, confronted with hospital infections, anesthesia problems, employee consent, active to fixed bed ratio, number of deaths, and patient-day. Two studies assessed charity hospitals, four studies assessed private hospitals, and five studies assessed Social Security Organization (SSO) hospitals. The remaining studies assessed hospitals affiliated with universities of medical sciences belonging to the Iran Ministry of Health (Table 1).
Table 1
| Row | Authors | Years of data collection | Language | Location | Affiliation of hospitals | Number of hospital | Inputs | Outputs | Model of DEA |
|---|---|---|---|---|---|---|---|---|---|
| 1 | Joshan et al. (24) | 2011–12 | Persian | Tehran | TUMS | 14 | Number of beds, operation rooms, physicians, nurses, and support forces | Number of surgeries, outpatients, patients, bed occupancy rate, bed day, and admission-inpatient rate | VRS, input-oriented |
| 2 | Joshan et al. (24) | 2011–12 | Persian | Tehran | IUMS | 8 | Number of beds, operation rooms, physicians, nurses, and support forces | Number of surgeries, outpatients, patients, bed occupancy rate, bed day, and admission-inpatient rate | VRS, input-oriented |
| 3 | Joshan et al. (24) | 2011–12 | Persian | Tehran | SBMU | 10 | Number of beds, operation rooms, physicians, nurses, and support forces | Number of surgeries, outpatients, patients, bed occupancy rate, bed day, and admission-inpatient rate | VRS, input-oriented |
| 4 | Sepehrdost et al. (25) | 2007–08 | Persian | Iran | SSO | 28 | Number of medical staff, nurses, other sources, and active beds | Number of outpatients, inpatients, surgeries, and bed turnover | CRS, input-oriented |
| 5 | Sepehrdost et al. (25) | 2007–08 | Persian | Iran | SSO | 37 | Number of medical staff, nurses, other sources, and active beds | Number of outpatients, inpatients, surgeries, and bed turnover | CRS, input-oriented |
| 6 | Ghaderi et al. (26) | 2005–09 | Persian | Tehran & Alborz | IUMS | 26 | Number of beds, nurses, and others | Number of surgeries, outpatients, hospitalization day, and occupied bed day ratios | VRS, input-oriented |
| 7 | Karimi et al. (27) | 2005–06 | Persian | Isfahan | MUI | 23 | Number of physicians, nurses, and beds | Mean patient stay, bed turnover, bed occupancy, number of outpatients, and hospital income | VRS, input-oriented |
| 8 | Mohammadi Ardakani et al. (28) | 2004–06 | Persian | Yazd | SSO | 12 | Number of physicians, paramedics, and active beds | Number of inpatients and outpatients, occupied bed day | Input- and output-oriented |
| 9 | Pourreza et al. (29) | 1996–98 | Persian | Tehran | TUMS | 12 | Number of beds, nurses, physicians, and others | Number of outpatients, hospitalization-day, number of surgeries | VRS, input-oriented |
| 10 | Aboulhalaj et al. (30) | 2009 | Persian | Iran | MHH | 122 | Number of beds, physicians, paramedics, and others | Income and admission | VRS, input-oriented |
| 11 | Salehzade et al. (31) | 2007 | Persian | Qom | MUQ & Self-administered | 8 | Number of physicians, paramedics, and active beds | Number of outpatients and inpatients | VRS, input-oriented |
| 12 | Salehzade et al. (31) | 2007 | Persian | Qom | MUQ & Self-administered | 8 | Number of physicians, paramedics, and active beds | Number of inpatients and outpatients | CRS, input-oriented |
| 13 | Asadi et al. (32) | 2008 | Persian | Yazd | SSO | 13 | Costs, education hours, and staff relocation | SERVQUAL score, ratios, outpatient, inpatient, and emergency patients to physicians score | Input- and output-oriented (input-oriented) |
| 14 | Askari et al. (33) | 2001–08 | Persian | Yazd | SSO | 13 | Number of active beds, nurses, physicians, and others | Number of inpatients, bed occupancies, surgeries | VRS, input-oriented |
| 15 | Ilbeigi et al. (34) | 2009 | Persian | Mashhad | MUMS | 17 | Number of beds, physicians, nurses, paraclinical staff, and support forces | Inpatient-bed day, outpatients, and surgeries | VRS_CRS (VRS), input-oriented |
| 16 | Rahimi et al. (35) | 2009 | Persian | W. Azarbaijan | UMSU | 23 | Number of beds, physicians, and others | Occupied bed-day, outpatient admission | VRS, input-oriented |
| 17 | Najarzadeh et al. (36) | 2006–10 | Persian | Ahvaz | AJUMS | 13 | Number of physicians, nurses, and beds | Occupied bed day, number of surgeries, outpatients, inpatients, mean patient stay | VRS, input-oriented |
| 18 | Akbari et al. (37) | 2005–08 | Persian | Tabriz | TBZMED | 20 | Number of physicians and others, beds, and hospital costs | Number of patient admissions and surgeries, bed occupancy rate | VRS, input-oriented |
| 19 | Azar et al. (38) | 2009–11 | Persian | Tehran | TUMS | 22 | Number of beds, physicians, paramedics, and others | Number of outpatients, emergencies, inpatients, and surgeries, bed occupancy rate | VRS, input-oriented |
| 20 | Safi Aryan et al. (39) | 2009 | Persian | Hamadan | UMSHA | 16 | Number of beds, physicians, nurses, and others | Number of surgeries and outpatients, bed occupancy rate, mean patient stay, inpatient bed stay | VRS, input-oriented |
| 21 | Kazemi et al. (40) | 2006–08 | Persian | East of Iran | Medical Universities, SSO | 11 | Number of beds and all employees | Occupied bed day, outpatient admission | VRS, input-oriented |
| 22 | Raeisian et al. (41) | 2007–11 | Persian | Ahvaz | AJUMS & SSO, Private & Charity | 8 | Number of beds, physicians, nurses, and others | Number of patients and surgeries, bed occupancy rate | VRS, input-oriented |
| 23 | Raeisian et al. (41) | 2007–11 | Persian | Ahvaz | AJUMS & SSO, Private & Charity | 8 | Number of beds, physicians, nurses, and others | Number of patients and surgeries, bed occupancy rate | VRS, input-oriented |
| 24 | Mohebifar et al. (42) | 2006–10 | Persian | Guilan | GUMS | 19 | Number of beds, physicians, nurses, and others | Number of outpatients, inpatients, surgeries, and inpatient days | VRS, input-oriented |
| 25 | Fazeli et al. (43) | 2009–11 | Persian | Ilam | MEDILAM | 9 | Number of beds, physicians, and others | Number of clinical, paraclinical, and outpatient services | Input-oriented |
| 26 | Fazeli et al. (43) | 2009–13 | Persian | Ilam | MEDILAM | 9 | Number of beds, physicians, and others | Number of clinical, paraclinical, and outpatient services | Input-oriented |
| 27 | Mahfoozpor et al. (44) | 2013–14 | Persian | Tehran | SBMU | 10 | Number of physicians and nurses | Number of discharged patients | VRS, input-oriented |
| 28 | Mahfoozpor et al. (44) | 2013–14 | Persian | Tehran | SBMU | 10 | Number of physicians and nurses | Surgery room function | VRS, input-oriented |
| 29 | Mahfoozpor et al. (44) | 2013–14 | Persian | Tehran | SBMU | 10 | Number of physicians and nurses | Number of discharged patients | VRS, input-oriented |
| 30 | Mahfoozpor et al. (44) | 2013–14 | Persian | Tehran | SBMU | 10 | Number of physicians and nurses | Surgery room function | VRS, input-oriented |
| 31 | Ghasemi et al. (45) | 2005–11 | Persian | Kermanshah | KUMS | 7 | Number of beds, physicians, nurses, and others | Number of outpatients, inpatients, occupied bed days, and surgeries | VRS, input-oriented |
| 32 | Firouzi et al. (46) | NA | Persian | Tehran | TUMS | 40 | Number of beds, physicians, paramedics, some costs | Number of contracted insurances, access to emergency, confront with hospital infections, anesthesia problems, employee consent, bed occupancy rate, employee to bed ratio | VRS, input-oriented |
| 33 | Amozadeh et al. (47) | 2012, 13, 15 | Persian | Mazandaran and Babul | Mazandaran & Babol UMS | 21 | Number of beds, physicians, nurses, and others | Number of emergencies, outpatients, and surgeries | VRS, input-oriented |
| 34 | Youzi et al. (48) | 2016 | Persian | Tehran | TUMS | 21 | Number of beds, physicians, and nurses | Percentage of active beds, bed occupancy rate, mean stay, and bed turnover | VRS, input-oriented |
| 35 | Lotfi et al. (49) | 2007–2011 | English | Ahvaz | Affiliated and non-affiliated with AJUMS | 16 | Number of beds, physicians, nurses, and others | Bed occupancy rate, number of patients and operations | Input-oriented |
| 36 | Nabilou et al. (9) | 2009–2014 | English | Tehran | TUMS | 17 | Number of beds, nurses, physicians, and others | Number of outpatient admission, occupied bed days, surgical operations | Input-oriented, variable return to scale |
| 37 | Rezapour et al. (50) | 2009–2012 | English | Tehran | IUMS & TUMS | 19 | Human resources, capital resources | Number of inpatients and admissions and inpatient bed occupancy rate | VRS, input-oriented |
| 38 | Torabipour et al. (51) | 2007–2010 | English | Ahvaz | University, Charity, Private | 12 | Number of nurses, beds, and physicians | Number of outpatients and inpatients, mean hospital stay, number of major operations | Input-oriented |
| 39 | Kiadaliri et al. (19) | 2006 | English | Ahvaz | AJUMS | 19 | Human resources, number of beds | Number of outpatient and inpatient visits, number of surgeries and percentage of occupied beds | VRS, input-oriented |
| 40 | Nabilou et al. (52) | 2013–2014 | Persian | Urmia | UMSU | 23 | Number of nurses, physicians, beds, and others | Number of discharges, surgeries, and bed occupancy percentage | VRS, input-oriented |
| 41 | Rezaei et al. (53) | 2007–2011 | English | Kurdistan | MUK | 12 | Number of beds, nurses, physicians, and others | Number of inpatient admissions and occupied bed days | VRS, input-oriented |
| 42 | Goudarzi et al. (54) | 2001–07 | Persian | Lorestan | LUMS | 13 | Number of beds, nurses, physicians, and others | Number of outpatients, inpatients, surgeries, bed days, and bed occupancy rate | VRS, input-oriented |
| 43 | Askari et al. (55) | 2001–11 | English | Yazd | SSU | 13 | Number of beds, nurses, physicians, and non-clinical staff | Number of admissions and surgeries, bed occupancy percentage | VRS, input-oriented |
| 44 | Sabermahani et al. (56) | 2011 | English | Kerman | KMU | 13 | Full-time physicians and nurses, administrative personnel | Number of outpatient clients, surgeries, and beds per day | VRS, input-oriented |
| 45 | Jahangiri et al. (11) | 2011–13 | Persian | Arak | IAU-ARAK | 31 | Number of day-beds, working days, physicians, and other staff | Number of admissions, surgeries, child birth, and inpatient days | CRS, input-oriented |
| 46 | Najafi et al. (57) | 2001–06 | Persian | Ardabil | TUMS | 10 | Number of beds and physicians | Number of admissions and inpatient beds | VRS, input-oriented |
| 47 | Hatam et al. (58) | 2006–2008 | Persian | Iran | SUMS | 18 | Number of beds and all full-time staff, hospital budget | Bed-day, active to fixed bed, patient mean stay, bed turnover, death, and costs | CRS, input-oriented |
| 48 | Rezapour et al. (50) | 1998–07 | Persian | Qazvin | QUMS | 4 | Number of beds, physicians, nurses, and others | Number of discharges, surgeries, admissions, emergencies, bed turnover, patient days | VRS, input-oriented |
| 49 | Hadian et al. (59) | 2006–11 | Persian | Tehran | IUMS & TUMS | 19 | Number of beds, nurses, physicians, and others | Number of outpatient admissions, inpatient days, occupied bed days, surgeries | VRS, input-oriented |
| 50 | Mehrtak et al. (60) | NA | English | E. Azarbaijan | IUMS | 18 | Number of beds, physicians, and nurses | Number of discharges, surgeries, bed occupancy rate | VRS, input-oriented |
Characteristics of the studies included in the systematic review and meta-analysis.
TUMS, Tehran University of Medical Sciences; IUMS, Iran University of Medical Sciences; SBMU, Shaheed Beheshti University of Medical Sciences; SSO, Social Security Organization; MUI, Isfahan University of Medical Sciences; SSU, Yazd University of Medical Sciences; TUMS, Tehran University of Medical Sciences; MHH, Ministry of Health' hospitals; MUQ, Qom university of Medical Sciences; MUMS, Mashhad University of Medical Sciences; UMSU, Urmia University of Medical Sciences; AJUMS, Ahvaz Jundishapour University of Medical Sciences; TBZMED, Tabriz University of Medical Sciences; UMSHA, Hamedan University of Medical Sciences; GUMS, Guilan University of Medial Sciences; MEDILAM, Ilam University of Medical Sciences; KUMS, Kermanshah University of Medical Sciences; MUK, Kurdistan University of Medical Sciences; LUMS, Lorestan University of Medical Sciences; KMU, Kerman University of Medical Sciences; IAU-ARAK, Islamic Azad University Branch of Arak; SUMS, Shiraz University of medical sciences; QUMS, Qazvin University of Medical Sciences.
The results indicated that there was heterogeneity in studies related to technical efficiency (heterogeneity chi2 = 156, p < 0.001), managerial efficiency (heterogeneity chi2 = 79.58, p < 0.001), and scale efficiency (heterogeneity chi2 = 67.22, p < 0.001). I2 index in technical and managerial efficiency was higher than 50%, which indicates high heterogeneity between the studies. This index was lower than 50% for scale efficiency.
Study publication error using Egger's test indicated that there was publication bias in technical and managerial efficiencies (P < 0.001), but there was no publication bias in scale efficiency (p = 0.19). Table 2 displays the results of Egger's testing for the three types of efficiencies. Begg's test indicated that there was no publication bias in the three types of efficiencies (P < 0.001).
Table 2
| Coefficient | S.E. | P-value | 95% confidence interval | Test of H0: no small-study effects | ||
|---|---|---|---|---|---|---|
| Technical efficiency | Slope | 0.56 | 0.00 | 0.000 | (0.40, 0.73) | P = 0.005 |
| Bias | −1.01 | 0.34 | 0.005 | (0.32, 1.70) | ||
| Managerial efficiency | Slope | 1.00 | 0.00008 | 0.000 | (0.99, 1.00) | p < 0.001 |
| Bias | −1.22 | 0.26 | 0.000 | (−1.76, −0.68) | ||
| Economics of scale efficiency | Slope | 1.00 | 0.00009 | <0.001 | (0.99, 1.00) | p < 0.001 |
| Bias | −1.28 | 0.19 | <0.001 | (−1.67, −0.0.90) |
Egger's test for small-study effects to examine the publication bias.
The results indicated that technical efficiency of Iranian hospitals had high variation, so that it ranged from 0.34 in the Mahfoozpor et al. study to 1 in Raeisian et al. and Najafi et al. On the basis of random effects modeling, random pooled estimation of hospital technical efficiency was 0.84 (95% CI = 0.52, 0.78) (Table 3, Figure 2). The managerial efficiency of Iranian hospitals was between 0.59 in the Aboulhalaj et al. study and 1 in studies of Joshan et al., Raeisian et al., and Najafi et al. Random pooled estimation of managerial efficiency of Iranian hospitals was 0.90 (95% CI = 0.85,0.94) (Table 4, Figure 3). The lowest amount of scale efficiency (0.52) was in the Mahfoozpor et al. study and the highest (1) was in the Raeisian et al. and Torabipour et al. studies. Random pool estimation of scale efficiency for Iranian hospitals was 0.88 (95%CI = 0.84, 0.91) (Table 5, Figure 4). The results of technical, managerial, and scale efficiencies are presented in Tables 2, 4, 5, respectively. In addition, the forest plots for technical, managerial, and scale efficiencies are presented in Figures 1–3, respectively.
Table 3
| Study | Authors | Estimation | 95% confidence intervals | Weight |
|---|---|---|---|---|
| 1 | Joshan et al. (24) | 0.93 | (0.66, 1) | 1.99 |
| 2 | Joshan et al. (24) | 0.88 | (0.47, 1) | 1.58 |
| 3 | Joshan et al. (24) | 0.9 | (0.55, 1) | 1.75 |
| 4 | Sepehrdost et al. (25) | 0.86 | (0.67, 0.96) | 2.42 |
| 5 | Sepehrdost et al. (25) | 0.89 | (0.75, 0.97) | 2.55 |
| 6 | Ghaderi et al. (26) | 0.88 | (0.7, 0.98) | 2.38 |
| 7 | Karimi et al. (27) | 0.91 | (0.72, 0.99) | 2.31 |
| 8 | Alimohammadi Ardakani et al. (28) | 0.75 | (0.43, 0.95) | 1.88 |
| 9 | Pourreza et al. (29) | 0.92 | (0.62, 1) | 1.88 |
| 10 | Aboulhalaj et al. (30) | 0.43 | (0.34, 0.53) | 2.92 |
| 11 | Salehzade et al. (31) | 0.75 | (0.35, 0.97) | 1.58 |
| 12 | Salehzade et al. (31) | 0.88 | (0.47, 1) | 1.58 |
| 13 | Asadi et al. (32) | 0.92 | (0.64, 1) | 1.94 |
| 14 | Askari et al. (33) | 0.92 | (0.64, 1) | 1.94 |
| 15 | Ilbeigi et al. (34) | 0.76 | (0.5, 0.93) | 2.12 |
| 16 | Rahimi et al. (35) | 0.57 | (0.34, 0.77) | 2.31 |
| 17 | Najarzadeh et al. (36) | 0.69 | (0.39, 0.91) | 1.94 |
| 18 | Akbari et al. (37) | 0.95 | (0.75, 1) | 2.22 |
| 19 | Azar et al. (38) | 0.86 | (0.65, 0.97) | 2.28 |
| 20 | Safi Aryan et al. (39) | 0.88 | (0.62, 0.98) | 2.08 |
| 21 | Kazemi et al. (40) | 0.82 | (0.48, 0.98) | 1.82 |
| 22 | Raeisian et al. (41) | 0.88 | (0.47, 1) | 1.58 |
| 23 | Raeisian et al. (41) | 1 | (0.63, 1) | 1.58 |
| 24 | Mohebifar et al. (42) | 0.89 | (0.67, 0.99) | 2.19 |
| 25 | Fazeli et al. (43) | 0.78 | (0.4, 0.97) | 1.67 |
| 26 | Fazeli et al. (43) | 0.78 | (0.4, 0.97) | 1.67 |
| 27 | Mahfoozpor et al. (44) | 0.4 | (0.12, 0.74) | 1.75 |
| 28 | Mahfoozpor et al. (44) | 0.4 | (0.12, 0.74) | 1.75 |
| 29 | Mahfoozpor et al. (44) | 0.3 | (0.07, 0.65) | 1.75 |
| 30 | Mahfoozpor et al. (44) | 0.5 | (0.19, 0.81) | 1.75 |
| 31 | Ghasemi et al. (45) | 0.86 | (0.42, 1) | 1.49 |
| 32 | Firouzi Jahantigh et al. (46) | 0.93 | (0.8, 0.98) | 2.59 |
| 33 | Amozadeh et al. (47) | 0.9 | (0.7, 0.99) | 2.25 |
| 34 | Youzi et al. (48) | 0.86 | (0.64, 0.97) | 2.25 |
| 35 | Lotfi et al. (49) | 0.88 | (0.62, 0.98) | 2.08 |
| 36 | Nabilou et al. (9) | 0.94 | (0.71, 1) | 2.12 |
| 37 | Rezapour et al. (50) | 0.84 | (0.6, 0.97) | 2.19 |
| 38 | Torabipour et al. (51) | 0.92 | (0.62, 1) | 1.88 |
| 39 | Ahmad Kiadaliri et al. (19) | 0.89 | (0.67, 0.99) | 2.19 |
| 40 | Nabilou et al. (52) | 0.87 | (0.66, 0.97) | 2.31 |
| 41 | Rezaei et al. (53) | 0.83 | (0.52, 0.98) | 1.88 |
| 42 | Goudarzi et al. (54) | 0.92 | (0.64, 1) | 1.94 |
| 43 | Askari et al. (55) | 0.92 | (0.64, 1) | 1.94 |
| 44 | Sabermahani et al. (56) | 0.85 | (0.55, 0.98) | 1.94 |
| 45 | Jahangiri et al. (11) | 0.97 | (0.83, 1) | 2.47 |
| 46 | Najafi et al. (57) | 1 | (0.69, 1) | 1.75 |
| 47 | Hatam et al. (58) | 0.89 | (0.65, 0.99) | 2.16 |
| 48 | Rezapour et al. (50) | 0.75 | (0.19, 0.99) | 1.1 |
| 49 | Hadian et al. (59) | 0.95 | (0.74, 1) | 2.19 |
| 50 | Mehrtak et al. (60) | 0.78 | (0.52, 0.94) | 2.16 |
| Random pooled estimation | 0.84 | (0.78, 0.52) | 100 | |
The results of pool estimation for technical efficiency among Iranian hospitals.
Heterogeneity chi2 = 156.97 (d.f. = 49) p = 0.000.
I2 (variation in ES attributable to heterogeneity) = 68.78%.
Estimate of between-study variance Tau2 = 0.12.
Figure 2
Forest plot of estimates and 95% confidence intervals of the technical efficiency among Iranian hospitals.
Table 4
| Study | Authors | Estimation | 95% confidence intervals | Weight |
|---|---|---|---|---|
| 1 | Joshan et al. (24) | 0.93 | (0.66, 1) | 2.71 |
| 2 | Joshan et al. (24) | 1 | (0.63, 1) | 2.01 |
| 3 | Joshan et al. (24) | 0.9 | (0.55, 1) | 2.28 |
| 4 | Sepehrdost et al. (25) | 0.93 | (0.76, 0.99) | 3.59 |
| 5 | Sepehrdost et al. (25) | 0.95 | (0.82, 0.99) | 3.9 |
| 6 | Ghaderi et al. (26) | 0.88 | (0.7, 0.98) | 3.5 |
| 7 | Karimi et al. (28) | 0.96 | (0.78, 1) | 3.35 |
| 8 | Pourreza et al. (29) | 0.92 | (0.62, 1) | 2.51 |
| 9 | Aboulhalaj et al. (30) | 0.59 | (0.5, 0.68) | 4.83 |
| 10 | Askari et al. (33) | 0.92 | (0.64, 1) | 2.61 |
| 11 | Ilbeigi et al. (34) | 0.88 | (0.64, 0.99) | 2.96 |
| 12 | Rahimi et al. (35) | 0.74 | (0.52, 0.9) | 3.35 |
| 13 | Najarzadeh et al. (36) | 0.85 | (0.55, 0.98) | 2.61 |
| 14 | Akbari et al. (37) | 0.95 | (0.75, 1) | 3.17 |
| 15 | Safi Aryan et al. (39) | 0.94 | (0.7, 1) | 2.88 |
| 16 | Kazemi et al. (40) | 0.91 | (0.59, 1) | 2.4 |
| 17 | Raeisian et al. (41) | 1 | (0.63, 1) | 2.01 |
| 18 | Raeisian et al. (41) | 1 | (0.63, 1) | 2.01 |
| 19 | Mohebifar et al. (42) | 0.95 | (0.74, 1) | 3.11 |
| 20 | Mahfoozpor et al. (44) | 0.6 | (0.26, 0.88) | 2.28 |
| 21 | Mahfoozpor et al. (44) | 0.6 | (0.26, 0.88) | 2.28 |
| 22 | Mahfoozpor et al. (44) | 0.7 | (0.35, 0.93) | 2.28 |
| 23 | Mahfoozpor et al. (44) | 0.8 | (0.44, 0.97) | 2.28 |
| 24 | Nabilou et al. (9) | 0.94 | (0.71, 1) | 2.96 |
| 25 | Rezapour et al. (50) | 0.95 | (0.74, 1) | 3.11 |
| 26 | Torabipour et al. (51) | 0.92 | (0.62, 1) | 2.51 |
| 27 | Ahmad Kiadaliri et al. (19) | 0.89 | (0.67, 0.99) | 3.11 |
| 28 | Nabilou et al. (52) | 0.91 | (0.72, 0.99) | 3.35 |
| 29 | Rezaei et al. (53) | 0.83 | (0.52, 0.98) | 2.51 |
| 30 | Goudarzi et al. (54) | 0.92 | (0.64, 1) | 2.61 |
| 31 | Askari et al. (55) | 0.92 | (0.64, 1) | 2.61 |
| 32 | Sabermahani et al. (56) | 0.92 | (0.64, 1) | 2.61 |
| 33 | Najafi et al. (57) | 1 | (0.69, 1) | 2.28 |
| 34 | Rezapour et al. (50) | 0.75 | (0.19, 0.99) | 1.29 |
| 35 | Hadian et al. (59) | 0.95 | (0.74, 1) | 3.11 |
| 36 | Mehrtak et al. (60) | 0.94 | (0.73, 1) | 3.04 |
| Random pooled estimation | 0.9 | (0.85, 0.94) | 100 | |
The results of pool estimation for managerial efficiency among Iranian hospitals.
Heterogeneity chi2 = 79.58 (d.f. = 35), p = 0.000.
I2 (variation in ES attributable to heterogeneity) = 56.02%.
Estimate of between-study variance Tau2 = 0.07.
Test of ES = 0: z = 34.96, p = 0.00.
Figure 3
Forest plot of estimates and 95% confidence intervals of the managerial efficiency among Iranian hospitals.
Table 5
| Study | Authors | Estimation | 95%confidence Intervals | Weight |
|---|---|---|---|---|
| 1 | Joshan et al. (24) | 0.93 | (0.66, 1) | 2.38 |
| 2 | Joshan et al. (24) | 0.88 | (0.47, 1) | 1.64 |
| 3 | Joshan et al. (24) | 0.9 | (0.55, 1) | 1.91 |
| 4 | Sepehrdost et al. (25) | 0.93 | (0.76, 0.99) | 3.46 |
| 5 | Sepehrdost et al. (25) | 0.95 | (0.82, 0.99) | 3.91 |
| 6 | Ghaderi et al. (26) | 0.96 | (0.8, 1) | 3.34 |
| 7 | Karimi et al. (27) | 0.96 | (0.78, 1) | 3.15 |
| 8 | Poureza et al. (29) | 0.92 | (0.62, 1) | 2.16 |
| 9 | Aboulhalaj et al. (30) | 0.75 | (0.66, 0.82) | 5.44 |
| 10 | Salehzade et al. (31) | 0.88 | (0.47, 1) | 1.64 |
| 11 | Salehzade et al. (31) | 0.88 | (0.47, 1) | 1.64 |
| 12 | Askari et al. (33) | 0.92 | (0.64, 1) | 2.27 |
| 13 | Ilbeigi et al. (34) | 0.82 | (0.57, 0.96) | 2.67 |
| 14 | Rahimi et al. (35) | 0.74 | (0.52, 0.9) | 3.15 |
| 15 | Najarzadeh et al. (36) | 0.77 | (0.46, 0.95) | 2.27 |
| 16 | Akbari et al. (37) | 0.95 | (0.75, 1) | 2.92 |
| 17 | Safi Aryan et al. (39) | 0.94 | (0.7, 1) | 2.58 |
| 18 | Kazemi et al. (40) | 0.91 | (0.59, 1) | 2.04 |
| 19 | Raeisian et al. (41) | 0.88 | (0.47, 1) | 1.64 |
| 20 | Raeisian et al. (41) | 1 | (0.63, 1) | 1.64 |
| 21 | Mohebifar et al. (42) | 0.95 | (0.74, 1) | 2.84 |
| 22 | Fazeli et al. (43) | 0.67 | (0.3, 0.93) | 1.78 |
| 23 | Fazeli et al. (43) | 0.91 | (0.59, 1) | 2.04 |
| 24 | Mahfoozpor et al. (44) | 0.5 | (0.19, 0.81) | 1.91 |
| 25 | Mahfoozpor et al. (44) | 0.7 | (0.35, 0.93) | 1.91 |
| 26 | Mahfoozpor et al. (44) | 0.5 | (0.19, 0.81) | 1.91 |
| 27 | Mahfoozpor et al. (44) | 0.6 | (0.26, 0.88) | 1.91 |
| 28 | Nabilou et al. (9) | 0.94 | (0.71, 1) | 2.67 |
| 29 | Rezapour et al. (50) | 0.89 | (0.67, 0.99) | 2.84 |
| 30 | Torabipour et al. (51) | 1 | (0.74, 1) | 2.16 |
| 31 | Ahmad Kiadaliri et al. (19) | 0.95 | (0.74, 1) | 2.84 |
| 32 | Nabilou et al. (9) | 0.91 | (0.72, 0.99) | 3.15 |
| 33 | Rezaei et al. (53) | 0.92 | (0.62, 1) | 2.16 |
| 34 | Goudarzi et al. (54) | 0.92 | (0.64, 1) | 2.27 |
| 35 | Askari et al. (55) | 0.92 | (0.64, 1) | 2.27 |
| 36 | Sabermahani et al. (56) | 0.85 | (0.55, 0.98) | 2.27 |
| 37 | Najafi et al. (57) | 0.9 | (0.55, 1) | 1.91 |
| 38 | Hatam et al. (58) | 0.5 | (0.26, 0.74) | 2.76 |
| 39 | Rezapour et al. (50) | 0.75 | (0.19, 0.99) | 0.98 |
| 40 | Hadian et al. (59) | 0.95 | (0.74, 1) | 2.84 |
| 41 | Mehrtak et al. (60) | 0.78 | (0.52, 0.94) | 2.76 |
| Random pool estimation | 0.88 | (0.84, 0.91) | 100 | |
The results of pool estimation for economies of scale efficiency among Iranian hospitals.
Heterogeneity chi2 = 67.22 (d.f. = 40) p = 0.00.
I2 (variation in ES attributable to heterogeneity) = 40.5%.
Test of ES = 0: z = 40.93 p = 0.00.
Figure 4
Forest plot of estimates and 95% confidence intervals of the economics of scale efficiency among Iranian hospitals.
Sub-group analysis based on study year indicated that random pool estimation of technical efficiency of Iranian hospitals for 2011 and before and after 2011 was 0.86 (95% CI = 0.80, 0.91) and 0.78 (95%CI = 0.64, 0.89), respectively. The status of managerial efficiency for 2011 and before was better than after 2011 (random pool estimation equal to 0.91, compared to 0.86). Random pool estimation of scale efficiency for 2011 and before was 0.90 (95%CI = 0.86, 0.93), while random pool estimation of scale efficiency for after 2011 was 0.74 which is lower (95%CI = 0.61, 0.86) (Table 6).
Table 6
| Subgroup | Estimation | 95% confidence intervals | Weight | Test(s) of heterogeneity | Random Test for heterogeneity between sub-groups: | ||
|---|---|---|---|---|---|---|---|
| I2** | P-value | P-value | |||||
| Technical efficiency | 2011 and before | 0.86 | (0.80, 0.91) | 75.97 | 66.80% | 0.000 | 0.23 |
| After 2011 | 0.78 | (0.64, 0.89) | 24.03 | 75.55% | 0.000 | ||
| Managerial efficiency | 2011 and before | 0.91 | (0.86, 0.95) | 77.89 | 60.74% | 0.000 | 0.27 |
| After 2011 | 0.86 | (0.75, 0.94) | 22.11 | 39.89% | 0.100 | ||
| Economics of scale efficiency | 2011 and before | 0.90 | (0.86, 0.93) | 83.67 | 32.79% | 0.040 | 0.01 |
| After 2011 | 0.74 | (0.61, 0.86) | 16.33 | 35.26% | 0.150 | ||
The random pool estimation of technical, managerial, and economics of scale efficiencies among Iranian hospitals by time of studies.
I2, the variation in ES attributable to heterogeneity.
Discussion
The assessment of hospital efficiency provides the groundwork to assess their performance and increase productivity when using limited resources. One of the ways of assessing allocated resources to obtain specified goals is efficiency studies. In summary, efficiency means using resources to their maximum to produce goods and services (61).
This is the first systematic review and meta-analysis study regarding assessment of the efficiency of Iranian hospitals in terms of its subcategories namely technical, managerial, and scale efficiencies. Different methods have been used to assess Iranian hospital efficiency such as DEA, Pabon-Lasso, and Stochastic Frontier Analysis (SFA) in past decades (21). In this regard, as this study indicates, the DEA method is the most widely applied method to assess hospital efficiency (19).
Our findings showed that the random pool estimations of technical, managerial, and economics of scale efficiency were 0.87, 0.9, and 0.88, respectively. This finding indicates that the resources of the studied hospitals in Iran have been used in an inefficient way. One idea about hospital efficiency is that the expectation from hospitals to work efficiently is far from reality. The reasoning for this claim is the economic theory of firms that declare the hospitals cannot work at full efficiency because of uncertainty in costs and prices of services that they provide. In summary, lack of information on costs and prices is one of the main factors that has a negative effect on hospital efficiency (6, 62).
Most of the studies were implemented in Tehran province (13 studies). Four studies investigated the efficiency of hospitals across all provinces of Iran. However, some provinces such as Sistan and Baluchistan had no individual reports about the efficiency of their hospitals. Therefore, there is an information gap for health policymakers and hospital managers in this field.
As the results indicated, most of the researchers tended to perform analyzes through the input-oriented method, because inputs are in the control of hospital managers, so that by creating changes in the inputs can change the rate of outputs to the desired extent. However, it is suggested that private and for-profit hospitals are excluded from this rule, because the managers of these type of hospitals want to maximize outputs and, as a result, hospital profits (63).
Human and capital resources such as the number of nurses and physicians and the number of beds were the main inputs in all included studies. Number of surgeries, outpatient admissions, inpatient admissions, bed days, and bed occupancy rate were the most frequent outputs considered in the studies to estimate the efficiency of hospitals. Today, the management of all resources, especially human resources in the health care industry is recognized as a vital issue for all healthcare organizations (64). Furthermore, better management of human resources is associated with higher patient outcomes without significant increases in the cost of hospitals (65).
The results indicated that most hospital efficiency studies suffer from some weak points. Therefore, the selection of inputs has been performed on the basis of resource review (e.g., previous published articles) not consideration of each hospital situation. Also, the inputs were not weighted, so that the resources with high specialty and expenditure receive the same weight as others. Hospital case mix has not been considered in this hospital efficiency assessment. This leads to low efficiency assessment in hospitals which have the most complicated cases. Lastly, some studies have not considered the data validity and the appropriate ratio of inputs and outputs with the number of hospitals precisely.
The study of Contor VJM and Poh Kl also provides some theoretical and methodological limitations of the DEA method in capturing the full view of efficiency of healthcare centers (66). However, with a suitable study design, the DEA method is among the most important and most applicable methods in the assessment of health system efficiency, especially hospitals (67).
The results indicated that technical, managerial, and scale efficiency of Iranian hospitals after performing HSEP decreased in comparison with before it. A study on Turkey hospitals from 2001 to 2006, which measured the effect of Turkey health sector reform on hospital efficiency to provide policy implications for policymakers, indicated that this reform had increased the efficiency of public hospitals but the efficiency of private hospitals had decreased (68).
As there was no hospital with full efficiency in the study and the increasing trend of health system costs and scarce resources, it is proposed to design and implement a system to monitor efficiency and consumption of resources especially in hospitals. This can help to identify inefficient hospitals and the causes of it. Health policymakers through cost management planning and increasing outputs can pave the way in this regard.
Strengths and Limitations
This is the first comprehensive systematic review and meta-analysis evaluating efficiency of Iranian hospitals which is applicable for comparison of the efficiency of hospitals before and after HSEP. The methodology adhered to the PRISMA statement (22).
The strength of the study is in performing meta-analysis after the systematic review which has specified the exact amount of technical, managerial, and scale efficiencies of Iranian hospitals. The Cochrane Consumers and Communication Review Group's data extraction template (69) was used to obtain the needed information about the studies included. Nevertheless, the retrieved studies were mainly administered in some easily accessible areas rather than in a balanced distribution all over the country. This limits the generalizability of the results.
Conclusion
This study indicated that many hospitals are inefficient. This implies that there is considerable room for efficiency improvement in hospitals. Hospital management has a unique role in this regard. Health systems have reformed in spite of increasing access and utilization of patients to the services, but have not considered efficiency improvement in hospitals. So, health policymakers and hospital managers should design and implement some related programs in order to monitor and improve the efficiency of hospitals.
Funding
This paper is retrieved from an approved research project. The Deputy of Research of Arak University of Medical Sciences has financially supported this study in different parts of the study including design, data collection, analysis, interpretation, and writing the manuscript (Grant Number: 3382).
Publisher's Note
All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.
Statements
Data availability statement
The original contributions presented in the study are included in the article/supplementary material, further inquiries can be directed to the corresponding author/s.
Ethics statement
This systematic review and meta-analysis study was approved by the Ethical Committee of Arak University of Medical Sciences (Ethical Code Number: IR.ARAKMU.REC.1398.044).
Author contributions
SA, BK, AK-K, and MD: conception and design of study/review/case series. SA, MA, YS, and AA: acquisition of data. YS, AA, MD, BK, and MA: analysis of collected data. SA, AK-K, YS, MD, AA, and YS: interpretation of data and drafting of paper and/or critical revision. All the authors have read and approved the manuscript to be submitted to BMC Health Services Research.
Acknowledgments
The authors would like to acknowledge the Deputy of Research of Arak University of Medical Sciences for financial support of this study and providing the background to perform this study.
Conflict of interest
The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.
- HSEP
Health Sector Evolution Plan
- CI
confidence interval
- DEA
data envelopment analysis
- DMUs
decision making units
- SSO
Social Security Organization
- ISI
Institute for Scientific Information
- SID
Scientific Information Database
- PRISMA
Preferred Reporting Items for Systematic Reviews and Meta-Analyses.
Abbreviations
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Summary
Keywords
efficiency, hospital, ownership, costs, Iran
Citation
Amini S, Karami Matin B, Didehdar M, Alimohammadi A, Salimi Y, Amiresmaili M and Kazemi-Karyani A (2021) Efficiency of Iranian Hospitals Before and After Health Sector Evolution Plan: A Systematic Review and Meta-Analysis Study. Front. Public Health 9:727669. doi: 10.3389/fpubh.2021.727669
Received
19 June 2021
Accepted
27 September 2021
Published
25 November 2021
Volume
9 - 2021
Edited by
Mihajlo Jakovljevic, Hosei University, Japan
Reviewed by
Martin Dlouhy, University of Economics, Czechia; Mariela Deliverska, Medical University Sofia, Bulgaria
Updates
Copyright
© 2021 Amini, Karami Matin, Didehdar, Alimohammadi, Salimi, Amiresmaili and Kazemi-Karyani.
This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
*Correspondence: Ali Kazemi-Karyani alikazemi.k20@gmail.com
This article was submitted to Health Economics, a section of the journal Frontiers in Public Health
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