The innovations in health technology, in the past decades, promise a better healthcare, but this has been accompanied by higher costs that challenge rapid and sustainable access to health services .
Medicine and medical equipment are the main reason for this increase in costs . Studies show that 12 percent of total hospital costs are dedicated to medical equipment , which in Iran includes more than one third of the total capital of various educational, medical, and health centers, and entry of these devices into hospitals has experienced a significant growth in recent years with the introduction of new generations of medical equipment [4, 5].
Health-technology assessment (HTA), has emerged in health systems, mainly in response to these increases in cost and to ensure efficiency of the resources in health systems , that have an acceptable approach and provide a global structure for generating evidence for costs and clinical effectiveness along with ethical and justice considerations as a basis for setting priorities based on evidence and political determinations [7, 8].
In recent years, numerous international organizations such as World Health Organization (WHO), the World Bank, European Union, and professional networks such as the Health Technology Assessment international (HTAi) have improved the value and importance of HTA around the globe [9, 10]. This improvement has attracted more attention from governments and policy makers towards HTA and has forced many governments and health institutes to establish HTA institutions in order to support decisions, resulting in efficient and effective allocation of health resources to the maximum population of the world possible .
Previous studies suggest that HTA is not merely a research instrumentation, but an ordered, rigorous, and repeatable evaluation process that can be considered as a “communication bridge between the world of research and the world of decision-making, especially policy-making”, and consider its use a necessity in the meso level , and specially its implementation in the hospital level (defined as hospital-based HTA) when accepting or rejecting the technology .
Studies show that the value of technology to health care is not dependent on clinical and economic considerations alone , and in a study conducted in 2017, seven features of health technology evaluation in the hospital level, including clinical (92%), economic (77%), socio-ethical (62%), technical (54%), organizational (46%), innovative (31%), and legal (23%), were identified in various countries, although not all of them are examined in all documents; the focus on each characteristic is stated as a percentage .
The majority of studies on HB-HTA have been conducted in high-income countries; the status of HTA in middle- and low- income countries usually remain unsupervised . Iran is a middle-income country , and its HTAs are performed at the national level, and there are currently no active HTA programs at the hospital level. Thus, this study was conducted to propose an HB-HTA model, in the field of medical equipment, for public hospitals in Iran, that can make it possible to take steps towards justice and efficient allocation of health system resources, considering the aging population of Iran and its limited health system resources.
Material and methods
This is a descriptive-analytical research. It is practical with respect to aim and periodical with respect to time, which was performed in 2020.
The method of conducting the research is mixed method (qualitative and quantitative) and it was performed through the following steps.
First, a pilot study was conducted and models and specifications used in the health technology evaluation were identified at the level of hospitals in other countries. Searches were performed in Springer, Prequist, Google Scholar, Cochrane, PubMed, Scopus and Library databases. Four different models and 7 different characteristics of HB-HTA (in the field of diagnostic medical equipment) were identified from the studies in different countries (Saphyr model, Mini HTA model, Committee model and HTA unit model).
After this step, interview questions were designed and the opinions of experts and practitioners of this field were obtained in the qualitative phase of the research. The hospitals under the auspices of Iran universities of medical sciences were selected as the research environment in this study. This stage included individual interviews and analysis of the texts of interviews with a grounded theory approach and the formation of a preliminary model for health technology evaluation (in the field of diagnostic medical equipment) in university hospitals of Iran. A total of 17 experts, including medical equipment managers with at least 10 years of service or senior health technology assessment experts with at least 5 years of experience were interviewed. The individuals were selected using the snowball method, and then the number of qualitative data was saturated and there was no need for further interviews. Each interview lasted an average of 37 minutes. Data analysis was performed within an ordered and continuous process of data comparison and used a three-step process of open coding, fundamental coding, and selective coding. For the sake of reliability, four criteria of acceptability, transferability, consistency, and validity were used in the qualitative studies, and the researchers took steps in this regard by making continuous and long-term contacts with interviewees, recording their voices, presenting them with information regarding the research, review of the data by participants and confirmation of the results of the research with multiple medical equipment experts that were not involved in the study.
Then, in the quantitative part, to confirm the initial model of the research, a researcher made questionnaire was used. The questions in this questionnaire were designed and developed based on the results obtained from analyzing the quantitative data and the dimensions and components identified in interviews with experts with grounded theory approach. The questionnaire includes 6 questions regarding the personal characteristics of the respondents and 5 dimensions (organizational, clinical, economic, technological, and legal aspects) and 18 main questions that were approved by the participants in the interview. The questionnaire was designed in the Likert scale with five levels (strongly agree = 5, agree = 4, have no opinion = 3, disagree = 2, and completely disagree = 1). In the end, the HB-HTA model (in the field of medical equipment) was presented using variance structural analysis, or structural equation modeling (SEM), which is one of the main methods for multivariable analysis. The statistical population at this stage includes experts and managers of medical equipment working in Ministry of Health and Medical Education of Iran, and medical universities and their affiliated centers. The sampling was performed using a stochastic method and a total of 250 individuals completed the questionnaire.
Participants in all stages of the study had at least a bachelor’s degree and individuals with full knowledge and willingness to participate were entered into the study. Moreover, the criterion for exiting the study was the unwillingness of the participants to continue, and questionnaires without any correct answers were also eliminated.
Result and Dissection
Analysis of qualitative data led to understanding the most important factors when evaluating medical equipment in university hospitals under the supervision of Iran’s medical universities. “Clinical features”, “organizational features”, “technology features”, “economic features”, and “legal features” were 5 categories considered while evaluating technology in Iranian UHs, each of which is explained in more details below.
Clinical feature: This feature is related to scientific search. It includes evidence to prove the effectiveness and safety of technology, as well as the impacts of that technology. The side effects are related to technology and determination of the benefits of using technology to improve safety and resolve patients’ problems. Moreover, meeting the special needs of some special patients, including patients with viral infections such as AIDS is considered in this section.
Economic features: The economic value of the clinical effects of a technology and its associated costs are evaluated using various types of economic analysis, which include: cost minimization, cost and benefit analysis, etc.
Organizational features: These features depend on operational procedures and infrastructures of a medical institution, such as specializations existing within an institution, training and communications among a work team, the workflow, potential barriers as well as requirements for responsibility and compliance with the requirements of accreditation.
Technological features: This evaluation includes the performance of a medical device mechanically, and with respect to electrical safety, training for correct use of technology, as well as the need for accessories, equipment, location, repair and maintenance, and adequate storage to use the equipment.
Legal features: Depend on regulations (laws, resolutions and enactments) and various types of requirements defined by law before and after the launch of a technology.
Considering the results obtained from the qualitative stage of the research and in order to design an HB-HTA model for Iranian UHs, a number of questions were designed in accordance with each category, and were approved by the participants in the interview, and in the end a questionnaire with 18 questions was presented; 5 questions related to clinical features, 4 questions regarding the economic features, 3 questions related to the technological features, 3 questions regarding the organizational features and 3 questions related to legal features.
A total of 250 individuals including managers and experts of medical equipment completed the questionnaire, where 66.8% of the participants were women while 33.2% were men. Furthermore, 28.8% of the respondents were individuals with a bachelor’s degree, 60.4% with master’s degree and 10.8% of the respondents had a PhD or higher degree.
To test the conceptual model of the research, the model analysis algorithm in the structural equation method of Smart PLS was used as follows, and the necessary analyses were performed to fit the measurement models and to fit the structural model.
KMO and Bartlett tests were used to investigate the adequacy of the samples. The value of the KMO index was equal to 0.89 (higher than 0.7), which indicates the sufficiency of the number of samples for factor analysis and path analysis with the structural equation model. Moreover, the sig value of the Bartlett test is less than 5%, which indicates a significant relationship between the variables, and thus factor analysis is appropriate to identify the structural model.
Cronbach's alpha is the classic measure of reliability and the index ofinternal sustainability assessment. Internal stability indicates the degree of correlation of a structure and its related indices, with a criterion higher than 0.6 indicating acceptable reliability.
To determine the reliability of each construct, in addition to the traditional Cronbach's alpha criterion, they use the more modern composite criterion (CR). The superiority of this criterion over the Cronbach's alpha coefficient is that the reliability of the structures is calculated not in absolute terms but in relation to the correlation of their structures with each other. Both criteria are used to better assess the reliability of both measures. Factor loadings were higher than 0.7 to confirm convergent validity.
The average variance extracted (AVE) which is one of the main indicators of questionnaire convergence was above 0.7 for all 5 variables, which indicates the existence of convergent validity in the tests applied.
Divergent validity tests in this study included the transverse load test and FornellLarcker test , which were performed and confirmed before implementing the structural model (inter-model). Therefore, the researcher was allowed to present the structural model with B PLS. The structural model of the research was also significantly reviewed and confirmed by the researcher. The communality index was used to evaluate the model quality of each latent variable. The structural model of the research was also significantly reviewed and confirmed by the researcher. The communality index was used to evaluate the model quality of each latent variable.
After fitting the measurement models, the PLS fits according to the data analysis algorithm in the Structural Model Research Method. In contrast to the measurement models in which the relationships between latent variables with explicit variables are considered, in analyzing the structural model of inter-relationships, the values of the present variables were analyzed together and the criteria of R2 significance coefficients for fitting the structural model were investigated.
Several criteria were used to evaluate the suitability of the structural model of the research, the first and most basic of which are the coefficients of Z, or t-values, and are represented by the bootstrapping command on the lanes.
If the t-values are greater than 1.96, it indicates the accuracy of the relationship between the constructs and thus confirms the research hypotheses at a 95% confidence level. Figure 2 shows the t-values for the structural model evaluation. Given that all the numbers on the paths are above 1.96, this indicates that the paths are meaningful, that the structural model is appropriate and that all the research hypotheses are confirmed.
The second criterion necessary to check the fit of the structural model is to examine the coefficients of determination of R2 for the present endogenous (dependent) variables of the model. This criterion was used to connect the measurement and structural components of structural equation modeling and to illustrate the effect of an exogenous variable on an endogenous one. Based on the conceptual model tested in Figure 1, and the numbers on the lines, it shows the path coefficient and the relationship between the present variables. It should be noted that the values of R2 are shown within the model circles and are calculated only for endogenous (dependent) variables of model structures and for exogenous structures; the value of this criterion is zero. Three values of 0.19, 0.33 and 0.67 have been introduced as criteria for model weak, medium and high . The values of the coefficient of determination can be seen in Figure 1. Given these values, the criterion of the suitability of the structural model is confirmed.
In accordance with the data analysis algorithm in the PLS method, after examining the fit of the measurement and structural models, the research hypotheses were tested by examining the Z-coefficients of the paths (t-values) and standardized factor loadings of the paths (Figure 2). If the significance coefficient of each of the paths is more than 1.96, the corresponding paths at 95% confidence level and its related hypothesis are confirmed. To check the significance of the path coefficient, the t-coefficients of each path are considered. Since the required t-value of each route is higher than 1.96, predicted routes are significant at a 95% confidence level. Therefore, the relevance of the present study is confirmed.
HB-HTA is a new perspective in developing countries, including Iran. It was attempted in this research to identify its different aspects in Iran’s university hospitals and to present them in form of a model. The clinical feature, as one of the main aspects in the model proposed for health technology evaluation (in the field of medical equipment) is taken into consideration in the documents related to hospital based HTAs, since it provides main scientific evidence for HTAs and is the strongest characteristic for decision making . Kidholm et al., Muller et al., Poluzzi et al. have also focused on this feature in evaluating health technologies [20, 21, 22]. The results of the study, introduced organizational feature as another main dimension in the proposed model, which was different from the results obtained from research on hospital-based HTAs of French UHs . Moreover, studies by Muller et al. have also shown that organizational data is more important in national HTA agencies and not in the hospital level .
This is while Cacciatore et al., believe that organizational aspects in Health Technology Assessment (HTA) reports play a significant role in managing policies and strategies to implement new health technologies . Roussel et al., suggest that it is necessary to assess the organizational impacts on innovative medical equipment . Poluzzi et al. have also considered the organizational feature in their proposed model for HB-HTA .
The economic feature is one of the main considerations of hospitals with regards to evaluation of medical equipment . Economic aspects have gained the most attention for investments in new treatments , and managers use this information when making decisions . This feature was also introduced as one of the main dimensions of the proposed model in this study.
Technical feature was also introduced as another dimension of the health technology evaluation model (in the field of medical equipment) in university hospitals of Iran. This feature is known as a unique feature for evaluation of medical equipment . This feature is also highly developed in technological evaluation of French UHs . Moreover, the results obtained from the study have introduced the legal feature as one of the main aspects of the proposed model. However, this feature is not considered seriously in the Danish Mini HTA model and in French UHs . The 2017 study by Usakin Peril et al. suggests that the legal feature is considered in only 23% of the health technology evaluation documents at the hospital level . However, the focus on this feature has been very extensive in Iranian UHs.
A model of Health Technology on diagnostic medical equipment for governmental hospitals in Iran has been presented in the present study. The basic dimensions of such a model include clinical, organizational, economic, legal, and technological features. The presented model can be used as a guide in decision making and source allocation for purchasing diagnostic medical equipment.
Ethical issues including plagiarism, informed consent, misconduct, data fabrication and/or falsification, double publication and/or submission, redundancy, etc., have been completely observed by the authors.
The authors of this study thereby appreciate the experts and managers who participated in the study and shared their knowledge
This research did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors.
All authors contributed toward data analysis, drafting and revising the paper and agreed to be responsible for all the aspects of this work.
The authors of this research declared no conflict of interest.