User needs elicitation via analytic hierarchy process (AHP). A case study on a Computed Tomography (CT) scanner

Integrated Approach Using Intuitionistic Fuzzy Multicriteria Decision-Making to Support Classifier Selection for Technology Adoption in Patients with Parkinson Disease: Algorithm Development and Validation

Background

Parkinson disease (PD) is reported to be among the most prevalent neurodegenerative diseases globally, presenting ongoing challenges and increasing burden on health care systems. In an effort to support patients with PD, their carers, and the wider health care sector to manage this incurable condition, the focus has begun to shift away from traditional treatments. One of the most contemporary treatments includes prescribing assistive technologies (ATs), which are viewed as a way to promote independent living and deliver remote care. However, the uptake of these ATs is varied, with some users not ready or willing to accept all forms of AT and others only willing to adopt low-technology solutions. Consequently, to manage both the demands on resources and the efficiency with which ATs are deployed, new approaches are needed to automatically assess or predict a user's likelihood to accept and adopt a particular AT before it is prescribed. Classification algorithms can be used to automatically consider the range of factors impacting AT adoption likelihood, thereby potentially supporting more effective AT allocation. From a computational perspective, different classification algorithms and selection criteria offer various opportunities and challenges to address this need.

Objective

This paper presents a novel hybrid multicriteria decision-making approach to support classifier selection in technology adoption processes involving patients with PD.

Methods

First, the intuitionistic fuzzy analytic hierarchy process (IF-AHP) was implemented to calculate the relative priorities of criteria and subcriteria considering experts' knowledge and uncertainty. Second, the intuitionistic fuzzy decision-making trial and evaluation laboratory (IF-DEMATEL) was applied to evaluate the cause-effect relationships among criteria/subcriteria. Finally, the combined compromise solution (CoCoSo) was used to rank the candidate classifiers based on their capability to model the technology adoption.

Results

We conducted a study involving a mobile smartphone solution to validate the proposed methodology. Structure (F5) was identified as the factor with the highest relative priority (overall weight=0.214), while adaptability (F4) (D-R=1.234) was found to be the most influencing aspect when selecting classifiers for technology adoption in patients with PD. In this case, the most appropriate algorithm for supporting technology adoption in patients with PD was the A3 - J48 decision tree (M3=2.5592). The results obtained by comparing the CoCoSo method in the proposed approach with 2 alternative methods (simple additive weighting and technique for order of preference by similarity to ideal solution) support the accuracy and applicability of the proposed methodology. It was observed that the final scores of the algorithms in each method were highly correlated (Pearson correlation coefficient >0.8).

Conclusions

The IF-AHP-IF-DEMATEL-CoCoSo approach helped to identify classification algorithms that do not just discriminate between good and bad adopters of assistive technologies within the Parkinson population but also consider technology-specific features like design, quality, and compatibility that make these classifiers easily implementable by clinicians in the health care system.

Study on the Association between anterior tooth Colour Preference based on the FAHP and individual factors

BACKGROUND

The relationship between tooth colour and individual satisfaction in oral aesthetics has long been a topic of interest. In this study, we utilized the fuzzy analytic hierarchy process (FAHP) to investigate the impacts of sex and age on tooth colour preference. The findings of this study should provide a scientific basis for oral aesthetic practice.

METHODS

In the current study, a random selection method was employed, and a survey was completed by 120 patients. To obtain tooth colour data, standard tooth colour charts were used. Smile photos were taken as template images using a single-lens reflex camera. The FAHP was utilized to conduct a weight analysis of tooth colour preferences among patients of different sexes and age groups.

RESULTS

There were significant differences in tooth colour preference based on sex and age. Men tend to prefer the B1 colour, while women may prioritize the aesthetic effects of other colours. Additionally, as patients age, their preferences for tooth colour become more diverse. These findings offer valuable insights for oral aesthetics practitioners, enabling them to better address the aesthetic needs of patients across different sexes and ages. This knowledge can aid in the development of more personalized treatment plans that align with patients' expectations.

CONCLUSION

In this study, we utilized scientific analysis methods to quantify the popularity of different tooth colours among various groups of people. By doing so, we established a scientific foundation for clinical practice. The findings of this study offer valuable insights for oral aesthetic research, enhancing our understanding of tooth colour. Additionally, these findings have practical applications in the field of oral medicine, potentially improving patients' quality of life and overall oral health.

Study on decision-making for orthodontic treatment plans based on analytic hierarchy process

BACKGROUND

Orthodontics is a common treatment for malocclusion and is essential for improving the oral health and aesthetics of patients. Currently, patients often rely on the clinical expertise and professional knowledge of doctors to select orthodontic programs. However, they lack their own objective and systematic evaluation methods to quantitatively compare different programs. Therefore, there is a need for a more comprehensive and quantitative approach to selecting orthodontic treatment plans, aiming to enhance their scientific validity and effectiveness.

METHODS

In this study, a combination of the analytic hierarchy process (AHP) and semantic analysis was used to evaluate and compare different orthodontic treatment options. An AHP model and evaluation matrix were established through thorough research and semantic analysis of patient requirements. This model considered various treatment factors. Expert panels were invited to rate these factors using a 1-9 scale. The optimal solution was determined by ranking and comparing different orthodontic treatment plans using the geometric mean method to calculate the weights of each criterion.

RESULTS

The research indicates a higher preference for invisible correction compared to other orthodontic solutions, with a weight score that is 0.3923 higher. Factors such as comfort and difficulty of cleaning have been given significant attention.

CONCLUSION

The Analytic Hierarchy Process (AHP) method can be utilized to effectively develop orthodontic treatment plans, making the treatment process more objective, scientific, and personalized. The design of this study offers strong decision support for orthodontic treatment, potentially improving orthodontic treatment outcomes in clinical practice and ultimately enhancing oral health and patients' quality of life.

Design of a multiple criteria decision analysis framework for prioritizing high-impact health technologies in a regional health service

OBJECTIVES

This study aims to develop a framework for establishing priorities in the regional health service of Murcia, Spain, to facilitate the creation of a comprehensive multiple criteria decision analysis (MCDA) framework. This framework will aid in decision-making processes related to the assessment, reimbursement, and utilization of high-impact health technologies.

METHOD

Based on the results of a review of existing frameworks for MCDA of health technologies, a set of criteria was proposed to be used in the context of evaluating high-impact health technologies. Key stakeholders within regional healthcare services, including clinical leaders and management personnel, participated in a focus group (n = 11) to discuss the proposed criteria and select the final fifteen. To elicit the weights of the criteria, two surveys were administered, one to a small sample of healthcare professionals (n = 35) and another to a larger representative sample of the general population (n = 494).

RESULTS

The responses obtained from health professionals in the weighting procedure exhibited greater consistency compared to those provided by the general public. The criteria more highly weighted were "Need for intervention" and "Intervention outcomes." The weights finally assigned to each item in the multicriteria framework were derived as the equal-weighted sum of the mean weights from the two samples.

CONCLUSIONS

A multi-attribute function capable of generating a composite measure (multicriteria) to assess the value of high-impact health interventions has been developed. Furthermore, it is recommended to pilot this procedure in a specific decision context to evaluate the efficacy, feasibility, usefulness, and reliability of the proposed tool.

Comparative Analysis of Three Predictive Models of Performance Indicators with Results-Based Management: Cancer Data Statistics in a National Institute of Health

Predictive models play a crucial role in RBMs to analyze performance indicator results to manage unexpected events and make timely decisions to resolve them. Their use in Mexico is deficient, and monitoring and evaluation are among the weakest pillars of the model. In response to these needs, the aim of this study was to perform a comparative analysis of three predictive models to analyze 10 medical performance indicators and cancer data related to children with cancer. To accomplish these purposes, a comparative and retrospective study with nonprobabilistic convenience sampling was conducted. The predictive models were exponential smoothing, autoregressive integrated moving average, and linear regression. The lowest mean absolute error was used to identify the best model. Linear regression performed best regarding nine of the ten indicators, with seven showing p < 0.05. Three of their assumptions were checked using the Shapiro-Wilk, Cook's distance, and Breusch-Pagan tests. Predictive models with RBM are a valid and relevant instrument for monitoring and evaluating performance indicator results to support forecasting and decision-making based on evidence and must be promoted for use with cancer data statistics. The place numbers obtained by cancer disease inside the main causes of death, morbidity and hospital outpatients in a National Institute of Health were presented as evidence of the importance of implementing performance indicators associated with children with cancer.

Shared decision making in recurrent ovarian cancer: Implementation of patient decision aids across three departments of oncology in Denmark

Objective

Patients with relapsed ovarian cancer are offered multiple treatment options. To match treatment with the individual patient's life situation and preferences, healthcare professionals can apply shared decision making (SDM) including patient decision aids (PtDAs).This study aimed to evaluate the implementation of two different PtDAs in consultations with patients suffering from relapsed ovarian cancer.

Methods

We analyzed the following data before and after implementation of the PtDAs: 1) observed SDM using the OPTION instrument, 2) physician treatment recommendations, and 3) patients' and physicians' evaluations of SDM in consultations using the CollaboRATE, SDM-Q-9, and SDM-Q-Doc.

Results

Significant improvement in observed SDM was found after the implementation (p = 0.002). Improvement of SDM was detected in consultations conducted by physicians reporting more than two hours of SDM-training (p < 0.001), but not when physicians reported less than two hours of SDM-training.No before/after differences in treatment recommendations and in patients' and physicians' evaluations were found.

Conclusion

Implementation of PtDAs improved the level of observed SDM. Training of physicians in SDM is necessary for improved SDM practice.

Innovation

Discussing oncological treatment options with the use of PtDAs is not standard practice in Denmark. The present study is one of the first Danish studies focusing on how to implement SDM and PtDAs in oncological consultations.

Medical decision-making with tables and graphs: The role of cognition, emotions, and analytic thinking

The shift from one-way to two-way communication in healthcare decision-making has heightened the need to understand the role of display formats including tables and graphs as decision aids. In this paper, we investigate cognitive and affective influences on decision-making involving display formats. We find that a display format's impact on decision quality is mediated by two distinct components of cognition (verbatim and gist knowledge), and that tables compared to bar graphs improve decision quality. We also find evidence that analytic thinking and lower negative affect can improve decision quality. Implications for marketers, better engaging patients, and encouraging improved decision-making are discussed.

Design and Definition of a New Decision Support System Aimed to the Hierarchization of Patients Candidate to Be Admitted to Intensive Care Units

The triage processes prior to the assignation of healthcare resources in hospitals are some of the decision-making processes that more severely affect patients. This effect gets even worse in health emergency situations and intensive care units (ICUs). Aiming to facilitate the decision-making process, in this work the use of vague fuzzy numbers is proposed, aiming to define a multi-attribute patient hierarchization method to be used in emergency situations at hospital ICUs. The incorporation of fuzzy models allows for modelling the vagueness and uncertainty associated with decision criteria evaluation, with which more efficient support is provided to the decision-making process. After defining the methodology, the effectiveness of this new system for patient hierarchization is shown in a case study. As a consequence of that, it is proved that the integration of decision-support systems into healthcare environments results to be efficient and productive, suggesting that if a part of the decision process is supported by these systems, then the errors associated with wrong interpretations and/or diagnoses might be reduced.

A Dispatching-Fuzzy AHP-TOPSIS Model for Scheduling Flexible Job-Shop Systems in Industry 4.0 Context

Scheduling flexible job-shop systems (FJSS) has become a major challenge for different smart factories due to the high complexity involved in NP-hard problems and the constant need to satisfy customers in real time. A key aspect to be addressed in this particular aim is the adoption of a multi-criteria approach incorporating the current dynamics of smart FJSS. Thus, this paper proposes an integrated and enhanced method of a dispatching algorithm based on fuzzy AHP (FAHP) and TOPSIS. Initially, the two first steps of the dispatching algorithm (identification of eligible operations and machine selection) were implemented. The FAHP and TOPSIS methods were then integrated to underpin the multi-criteria operation selection process. In particular, FAHP was used to calculate the criteria weights under uncertainty, and TOPSIS was later applied to rank the eligible operations. As the fourth step of dispatching the algorithm, the operation with the highest priority was scheduled together with its initial and final time. A case study from the smart apparel industry was employed to validate the effectiveness of the proposed approach. The results evidenced that our approach outperformed the current company’s scheduling method by a median lateness of 3.86 days while prioritizing high-throughput products for earlier delivery.

Evaluation of hospital disaster preparedness by a multi-criteria decision making approach: The case of Turkish hospitals

Considering the unexpected emergence of natural and man-made disasters over the world and Turkey, the importance of preparedness of hospitals, which are the first reference points for people to get healthcare services, becomes clear. Determining the level of disaster preparedness of hospitals is an important and necessary issue. This is because identifying hospitals with low level of preparedness is crucial for disaster preparedness planning. In this study, a hybrid fuzzy decision making model was proposed to evaluate the disaster preparedness of hospitals. This model was developed using fuzzy analytic hierarchy process (FAHP)-fuzzy decision making trial and evaluation laboratory (FDEMATEL)-technique for order preference by similarity to ideal solutions (TOPSIS) techniques and aimed to determine a ranking for hospital disaster preparedness. FAHP is used to determine weights of six main criteria (including hospital buildings, equipment, communication, transportation, personnel, flexibility) and a total of thirty-six sub-criteria regarding disaster preparedness. At the same time, FDEMATEL is applied to uncover the interdependence between criteria and sub-criteria. Finally, TOPSIS is used to obtain ranking of hospitals. To provide inputs for TOPSIS implementation, some key performance indicators are established and related data is gathered by the aid of experts from the assessed hospitals. A case study considering 4 hospitals from the Turkish healthcare sector was used to demonstrate the proposed approach. The results evidenced that Personnel is the most important factor (global weight = 0.280) when evaluating the hospital preparedness while Flexibility has the greatest prominence (c + r = 23.09).

AHP-Like Matrices and Structures—Absolute and Relative Preferences

Aggregation functions are extensively used in decision making processes to combine available information. Arithmetic mean and weighted mean are some of the most used ones. In order to use a weighted mean, we need to define its weights. The Analytical Hierarchy Process (AHP) is a well known technique used to obtain weights based on interviews with experts. From the interviews we define a matrix of pairwise comparisons of the importance of the weights. We call these AHP-like matrices absolute preferences of weights. We propose another type of matrix that we call a relative preference matrix. We define this matrix with the same goal—to find the weights for weighted aggregators. We discuss how it can be used for eliciting the weights for the weighted mean and define a similar approach for the Choquet integral.

A multi-criteria methodology for evaluating alternative ultrasound devices

Several surveys and clinical studies report high prevalence of work-related musculoskeletal disorders (WMSDs) among sonographers and sonologists. Better performing ultrasound devices can increase the number and quality of examinations, but also reduce the user comfort and increase the risk of WMSDs. This should lead the choice of the device to buy and use. To support hospitals or diagnostic centres in selecting the best ultrasound device, this study provides a structured methodology based on a multi-criteria approach, the Analytic Hierarchy Process. It has a Goal (to optimise workers' well-being and satisfy company production objectives) and 45 evaluation elements. It was applied in an Italian hospital comparing 3 alternatives: wireless, portable, and cart-based. The latter proved to be the best in satisfying the Goal, whereas a previous study obtained that the wireless device was preferable considering only the ergonomic point of view. The case study validated the applicability of the methodology. Practitioner summary: This paper provides the decision-makers of hospitals or diagnostic centres with a multi-criteria methodology to select the best ultrasound device capable of optimising workers' well-being and satisfying company production objectives. The methodology can also support manufacturers of ultrasound devices in improving their products. Abbreviations: AHP: analytic hierarchy process; AIUM: American Institute of Ultrasound in Medicine; BSI: British Standards Institution; CEN: European Committee for Standardisation; EU-OSHA: EU Agency for Occupational Safety and Health; ISO: International Organisation for Standardisation; MCMD: multiple criteria decision-making; NIOSH: US National Institute for Occupational Safety and Health; SDMS: society of diagnostic medical sonography; WHO: World Health OrganizationWMSD: work-related musculoskeletal disorder.

Health technology assessment (HTA) of optoelectronic biosensors for oncology by analytic hierarchy process (AHP) and Likert scale

BACKGROUND

The multicriteria decision method (MCDM) aims to find conflicts among alternatives by comparing and evaluating them according to various criteria to reach the best compromise solution. The evaluation of a new health technology is extremely important in the health sciences field. The aim of this work is to evaluate a new health technology to assay thyroglobulin in patients with differentiated thyroid cancer to improve its service from an organizational point of view, by planning new and appropriate training activities, ensuring proper use of resources and satisfying the needs of different users.

METHODS

The evaluation was performed using two methodologies: the analytic hierarchy process (AHP) and the Likert scale. The AHP is a multicriteria decision approach that assigns a weight to each evaluation criterion according to the decision maker's pairwise comparisons of the criteria. The Likert scale is a psychometric scale employed to study the degree of user satisfaction by measuring opinions.

RESULTS

Results show the need of particularly improving clinical efficiency, effectiveness, and return on sales (ROS) related to the technology; technological safety, human resources and other parameters do not need to be improved because of the high satisfaction results of the users.

CONCLUSIONS

The application of both methods provided the necessary information to improve the quality of the service, allowing the decision maker to identify the most valuable service features and to improve these to ensure user satisfaction and to identify possible service improvements.

User-testing an interactive option grid decision aid for prostate cancer screening: lessons to improve usability

OBJECTIVE

To user-test a web-based, interactive Option Grid decision aid 'prostate-specific antigen (PSA) test: yes or no?' to determine its usability, acceptability and feasibility with men of high and low health literacy.

DESIGN

A semi-structured interview study.

SETTING

Interviews were conducted at a senior centre, academic hospital or college library in New Hampshire and Vermont.

PARTICIPANTS

Individuals over 45 years of age with no history of prostate cancer who voluntarily contacted study authors after viewing local invitations were eligible for inclusion. Twenty interviews were conducted: 10 participants had not completed a college degree, of which eight had low health literacy, and 10 participants had high health literacy.

INTERVENTION

An interactive, web-based Option Grid patient decision aid for considering whether or not to have a PSA test.

RESULTS

Users with lower health literacy levels were able to understand the content in the tool but were not able to navigate the Option Grid independent of assistance. The tool was used independently by men with high health literacy. In terms of acceptability, the flow of questions and answers embedded in the tool did not seem intuitive to some users who preferred seeing more risk information related to age and family history. Users envisioned that the tool could be feasibly implemented in clinical workflows.

CONCLUSION

Men in our sample with limited health literacy had difficulty navigating the Option Grid, thus suggesting that the tool was not appropriately designed to be usable by all audiences. The information provided in the tool is acceptable, but users preferred to view personalised risk information. Some participants could envision using this tool prior to an encounter in order to facilitate a better dialogue with their clinician.

ETHICS APPROVAL

The study received ethical approval from the Dartmouth College Committee for the Protection of Human Subjects (STUDY00030116).

Optimization of Decision Making in the Supply of Medicinal Gases Used in Health Care

Systems that supply medicinal gases—oxygen, nitrous oxide and medical air—serve all care units of a hospital; for example, they feed distribution systems for operating theatres, neonatal and pediatric units, dialysis, X-ray, casualty, special tests, outpatients, etc. Systems for the provision of medicinal gases are therefore critical in guaranteeing hospital sustainability, since the functionality or availability of other hospital systems depends on them. Availability of 100% in these systems would avoid the need to reschedule patient appointments. It would also eliminate repeat testing, which poses risk to staff and patients, and could avoid affecting people’s lives through unavailability of, for example, operating theatres or intensive care units. All this contributes to a more rational resource consumption and an increase in quality of care both for the hospital itself and for patients and visitors. Although these systems are of vital importance to health care organizations, no previous work has been found in the literature that optimizes the technical decisions on supply in these systems. This research describes a model for these systems via continuous-time Markov chains. The results obtained are used in a multicriteria model constructed with the measuring attractiveness by a categorical-based evaluation technique (MACBETH) approach. In order to assess reliability when incorporating doubt or uncertainty via the MACBETH approach, the model has been validated by means of the fuzzy analytic hierarchy process. The aim is to obtain the best objective decision, with respect to the design of these systems, by analyzing the use of economic resources, the risks, and the impact on hospital activity, all with the aim of guaranteeing the best quality of care. The models constructed by means of MACBETH and the fuzzy analytic hierarchy process give, as the most suitable alternatives, duplicate the external supply in medical oxygen systems and maintain the original design conditions for supply systems of nitrous oxide and medicinal air.

How do health service professionals consider human factors when purchasing interactive medical devices? A qualitative interview study

We present findings of a UK study into how those involved in purchasing interactive medical devices go about evaluating usability, the challenges that arise, and opportunities for improvement. The study focused on procurement of infusion devices because these are used by various professionals across healthcare. A semi-structured interview study was carried out involving a range of stakeholders (20 in total) involved in or impacted by medical device procurement. Data was analysed using thematic analysis, a qualitative method designed to support the identification, analysis and reporting of patterns. In principle, health service purchasing was found to accommodate consideration of equipment usability. In practice, the evaluation process was driven primarily by engineering standards; assessment of local needs did not accommodate substantive assessment of usability; and choice was limited by the availability of equipment on the marketplace. We discuss ways in which purchasing could be improved through techniques that account for social circumstances.

Determination of the most important risk factors of gestational diabetes in Iran by group analytical hierarchy process

BACKGROUND

The outbreak of gestational diabetes has a significant increase during recent years. This disease has complications for mother and her baby. Screening is an opportunity for preventing of gestational diabetes complications.

OBJECTIVE

The aim of this research was to determine the most important risk factors for Gestational Diabetes Mellitus (GDM) in Iran according to the expert's views by Group Analytical Hierarchy Process.

MATERIALS AND METHODS

In this cross-sectional study, papers related to the prevalence and risk factors of GDM in Iran from 1992-2015 were reviewed. By studying texts and Up to Date databases, 10 risk factors for gestational diabetes were collected. Among these 10 items, the risk factors that have become significant based on studying literature in Iran were selected for analysis. Group Analytical Hierarchy Process (GAHP) questionnaire distributed among all experts.

RESULTS

8 risk factors of gestational diabetes were significant in Iran. The analysis of experts' views showed that "History of GDM or disorder in glucose tolerance in pregnancy" is the most important risk factor for developing GDM (40.7%). The second and third most important risk factors were "History of macrosomia (infant birth weight > 4.1 Kg)" (20.2%) and" History of diabetes in first degree relatives" (10.7%).

CONCLUSION

Suggesting screening based on the determined order of these risk factors can reduce the cost and stress in pregnant women. Also, it makes patient identifying faster. The healthcare sector can consider these priorities determined in experts' views to prevent gestational diabetes.

A multicriteria decision making approach applied to improving maintenance policies in healthcare organizations

BACKGROUND

Healthcare organizations have far greater maintenance needs for their medical equipment than other organization, as many are used directly with patients. However, the literature on asset management in healthcare organizations is very limited. The aim of this research is to provide more rational application of maintenance policies, leading to an increase in quality of care.

METHODS

This article describes a multicriteria decision-making approach which integrates Markov chains with the multicriteria Measuring Attractiveness by a Categorical Based Evaluation Technique (MACBETH), to facilitate the best choice of combination of maintenance policies by using the judgements of a multi-disciplinary decision group. The proposed approach takes into account the level of acceptance that a given alternative would have among professionals. It also takes into account criteria related to cost, quality of care and impact of care cover.

RESULTS

This multicriteria approach is applied to four dialysis subsystems: patients infected with hepatitis C, infected with hepatitis B, acute and chronic; in all cases, the maintenance strategy obtained consists of applying corrective and preventive maintenance plus two reserve machines.

CONCLUSIONS

The added value in decision-making practices from this research comes from: (i) integrating the use of Markov chains to obtain the alternatives to be assessed by a multicriteria methodology; (ii) proposing the use of MACBETH to make rational decisions on asset management in healthcare organizations; (iii) applying the multicriteria approach to select a set or combination of maintenance policies in four dialysis subsystems of a health care organization. In the multicriteria decision making approach proposed, economic criteria have been used, related to the quality of care which is desired for patients (availability), and the acceptance that each alternative would have considering the maintenance and healthcare resources which exist in the organization, with the inclusion of a decision-making group. This approach is better suited to actual health care organization practice and depending on the subsystem analysed, improvements are introduced that are not included in normal maintenance policies; in this way, not only have different maintenance policies been suggested, but also alternatives that, in each case and according to viability, provide a more complete decision tool for the maintenance manager.

Applying the Analytic Hierarchy Process in healthcare research: A systematic literature review and evaluation of reporting

Background

The Analytic Hierarchy Process (AHP), developed by Saaty in the late 1970s, is one of the methods for multi-criteria decision making. The AHP disaggregates a complex decision problem into different hierarchical levels. The weight for each criterion and alternative are judged in pairwise comparisons and priorities are calculated by the Eigenvector method. The slowly increasing application of the AHP was the motivation for this study to explore the current state of its methodology in the healthcare context.

Methods

A systematic literature review was conducted by searching the Pubmed and Web of Science databases for articles with the following keywords in their titles or abstracts: “Analytic Hierarchy Process,” “Analytical Hierarchy Process,” “multi-criteria decision analysis,” “multiple criteria decision,” “stated preference,” and “pairwise comparison.” In addition, we developed reporting criteria to indicate whether the authors reported important aspects and evaluated the resulting studies’ reporting.

Results

The systematic review resulted in 121 articles. The number of studies applying AHP has increased since 2005. Most studies were from Asia (almost 30 %), followed by the US (25.6 %). On average, the studies used 19.64 criteria throughout their hierarchical levels. Furthermore, we restricted a detailed analysis to those articles published within the last 5 years (n = 69). The mean of participants in these studies were 109, whereas we identified major differences in how the surveys were conducted. The evaluation of reporting showed that the mean of reported elements was about 6.75 out of 10. Thus, 12 out of 69 studies reported less than half of the criteria.

Conclusion

The AHP has been applied inconsistently in healthcare research. A minority of studies described all the relevant aspects. Thus, the statements in this review may be biased, as they are restricted to the information available in the papers. Hence, further research is required to discover who should be interviewed and how, how inconsistent answers should be dealt with, and how the outcome and stability of the results should be presented. In addition, we need new insights to determine which target group can best handle the challenges of the AHP.

Using the Analytic Hierarchy Process (AHP) to understand the most important factors to design and evaluate a telehealth system for Parkinson's disease

BACKGROUND

The assessment of a new health technology is a multidisciplinary and multidimensional process, which requires a complex analysis and the convergence of different stakeholders into a common decision. This task is even more delicate when the assessment is carried out in early stage of development processes, when the maturity of the technology prevents conducting a large scale trials to evaluate the cost effectiveness through classic health economics methods. This lack of information may limit the future development and deployment in the clinical practice. This work aims to 1) identify the most relevant user needs of a new medical technology for managing and monitoring Parkinson's Disease (PD) patients and to 2) use these user needs for a preliminary assessment of a specific system called PERFORM, as a case study.

METHODS

Analytic Hierarchy Process (AHP) was used to design a hierarchy of 17 needs, grouped into 5 categories. A total of 16 experts, 6 of them with a clinical background and the remaining 10 with a technical background, were asked to rank these needs and categories.

RESULTS

On/Off fluctuations detection, Increase wearability acceptance, and Increase self-management support have been identified as the most relevant user needs. No significant differences were found between the clinician and technical groups. These results have been used to evaluate the PERFORM system and to identify future areas of improvement.

CONCLUSIONS

First of all, the AHP contributed to the elaboration of a unified hierarchy, integrating the needs of a variety of stakeholders, promoting the discussion and the agreement into a common framework of evaluation. Moreover, the AHP effectively supported the user need elicitation as well as the assignment of different weights and priorities to each need and, consequently, it helped to define a framework for the assessment of telehealth systems for PD management and monitoring. This framework can be used to support the decision-making process for the adoption of new technologies in PD.

Analytic Hierarchy Process to Define the Most Important Factors and Related Technologies for Empowering Elderly People in Taking an Active Role in their Health

Successful management of health conditions in older population is determined by strategic involvement of a professional team of careers and by empowering patients and their caregivers to take over a central role and responsibility in the daily management of condition. Identifying, structuring and ranking the most important needs related to these aspects could pave the way for improved strategies in designing systems and technological solutions supporting user empowerment. This paper presents the preliminary results of a study aiming to elicit these needs. Healthcare professionals, working together in the European and Innovation Partnership on Active and Healthy Ageing (EIP-AHA) initiative, have defined a set of needs and factors that have been organized in two hierarchies around the concepts of patient activation and proactive and prepared care team, defined in the Chronic Care Model. The two hierarchies have been mapped, by a team of experts in computer science, with technologies and solutions that could facilitate the achievement of the identified needs.

Selection of reference standard during method development using the analytical hierarchy process

Reference standard is critical for ensuring reliable and accurate method performance. One important issue is how to select the ideal one from the alternatives. Unlike the optimization of parameters, the criteria of the reference standard are always immeasurable. The aim of this paper is to recommend a quantitative approach for the selection of reference standard during method development based on the analytical hierarchy process (AHP) as a decision-making tool. Six alternative single reference standards were assessed in quantitative analysis of six phenolic acids from Salvia Miltiorrhiza and its preparations by using ultra-performance liquid chromatography. The AHP model simultaneously considered six criteria related to reference standard characteristics and method performance, containing feasibility to obtain, abundance in samples, chemical stability, accuracy, precision and robustness. The priority of each alternative was calculated using standard AHP analysis method. The results showed that protocatechuic aldehyde is the ideal reference standard, and rosmarinic acid is about 79.8% ability as the second choice. The determination results successfully verified the evaluation ability of this model. The AHP allowed us comprehensive considering the benefits and risks of the alternatives. It was an effective and practical tool for optimization of reference standards during method development.

Single-Access Laparoscopic Rectal Resection Versus the Multiport Technique

Background. Single-access laparoscopic surgery is not used routinely for the treatment of colorectal disease. The aim of this retrospective cohort study is to compare the results of single-access laparoscopic rectal resection (SALR) versus multiaccess laparoscopic rectal resection with a mean follow-up of 24 months. Methods. This retrospective cohort study enrolled 42 patients. Between January 2010 and June 2012, 21 SALRs were performed. These patients were compared with a group of 21 other patients who had undergone multiport laparoscopic rectal resection. This control group had the same exclusion criteria and patient demographics. Short-term outcomes were reassessed with a mean follow-up of 2 years. Statistical analysis included the Student t test and Fisher’s exact test. Finally, we performed a differential cost analysis between the 2 procedures. Results. Exclusion criteria, patient demographics, and indication for surgery were similar in both groups. The conversion rate was 0% in both groups. There were no intraoperative complications or deaths. Bowel recovery was similar in both groups. No interventions, readmissions, or deaths were recorded at 30 days’ follow-up. At a mean follow-up of 24 months, all the patients with a preoperative diagnosis of cancer are still alive and disease free. Considering the selected 3 items, the mean cost per patient for single-access laparoscopic surgery and multiple-access laparoscopic surgery were estimated as 7213 and 7495 Euros, respectively. Conclusion. We think that SALR could be performed in selected patients by surgeons with high multiport laparoscopic skills. It is compulsory by law to evaluate outcomes and cost-effectiveness by using randomized controlled trials.

Integration of Personalized Healthcare Pathways in an ICT Platform for Diabetes Managements: A Small-Scale Exploratory Study

The availability of new tools able to support patient monitoring and personalized care may substantially improve the quality of chronic disease management. A personalized healthcare pathway (PHP) has been developed for diabetes disease management and integrated into an information and communication technology system to accomplish a shift from organization-centered care to patient-centered care. A small-scale exploratory study was conducted to test the platform. Preliminary results are presented that shed light on how the PHP influences system usage and performance outcomes.

Systematic assessment of benefits and risks: study protocol for a multi-criteria decision analysis using the Analytic Hierarchy Process for comparative effectiveness research

BACKGROUND

Regulatory decision-making involves assessment of risks and benefits of medications at the time of approval or when relevant safety concerns arise with a medication. The Analytic Hierarchy Process (AHP) facilitates decision-making in complex situations involving tradeoffs by considering risks and benefits of alternatives. The AHP allows a more structured method of synthesizing and understanding evidence in the context of importance assigned to outcomes. Our objective is to evaluate the use of an AHP in a simulated committee setting selecting oral medications for type 2 diabetes. 

METHODS

This study protocol describes the AHP in five sequential steps using a small group of diabetes experts representing various clinical disciplines. The first step will involve defining the goal of the decision and developing the AHP model. In the next step, we will collect information about how well alternatives are expected to fulfill the decision criteria. In the third step, we will compare the ability of the alternatives to fulfill the criteria and judge the importance of eight criteria relative to the decision goal of the optimal medication choice for type 2 diabetes. We will use pairwise comparisons to sequentially compare the pairs of alternative options regarding their ability to fulfill the criteria. In the fourth step, the scales created in the third step will be combined to create a summary score indicating how well the alternatives met the decision goal. The resulting scores will be expressed as percentages and will indicate the alternative medications' relative abilities to fulfill the decision goal. The fifth step will consist of sensitivity analyses to explore the effects of changing the estimates. We will also conduct a cognitive interview and process evaluation. 

DISCUSSION

Multi-criteria decision analysis using the AHP will aid, support and enhance the ability of decision makers to make evidence-based informed decisions consistent with their values and preferences.