Decision Support System Software Research Articles

Effect of a Computer-Based Decision Support Intervention on Autism Spectrum Disorder Screening in Pediatric Primary Care Clinics

Universal early screening for autism spectrum disorder (ASD) is recommended but not routinely performed. To determine whether computer-automated screening and clinical decision support can improve ASD screening rates in pediatric primary care practices. This cluster randomized clinical trial, conducted between November 16, 2010, and November 21, 2012, compared ASD screening rates among a random sample of 274 children aged 18 to 24 months in urban pediatric clinics of an inner-city county hospital system with or without an ASD screening module built into an existing decision support software system. Statistical analyses were conducted from February 6, 2017, to June 1, 2018. Four clinics were matched in pairs based on patient volume and race/ethnicity, then randomized within pairs. Decision support with the Child Health Improvement Through Computer Automation system (CHICA) was integrated with workflow and with the electronic health record in intervention clinics. The main outcome was screening rates among children aged 18 to 24 months. Because the intervention was discontinued among children aged 18 months at the request of the participating clinics, only results for those aged 24 months were collected and analyzed. Rates of positive screening results, clinicians' response rates to screening results in the computer system, and new cases of ASD identified were also measured. Main results were controlled for race/ethnicity and intracluster correlation. Two clinics were randomized to receive the intervention, and 2 served as controls. Records from 274 children (101 girls, 162 boys, and 11 missing information on sex; age range, 23-30 months) were reviewed (138 in the intervention clinics and 136 in the control clinics). Of 263 children, 242 (92.0%) were enrolled in Medicaid, 138 (52.5%) were African American, and 96 (36.5%) were Hispanic. Screening rates in the intervention clinics increased from 0% (95% CI, 0%-5.5%) at baseline to 68.4% (13 of 19) (95% CI, 43.4%-87.4%) in 6 months and to 100% (18 of 18) (95% CI, 81.5%-100%) in 24 months. Control clinics had no significant increase in screening rates (baseline, 7 of 64 children [10.9%]; 6-24 months after the intervention, 11 of 72 children [15.3%]; P = .46). Screening results were positive for 265 of 980 children (27.0%) screened by CHICA during the study period. Among the 265 patients with positive screening results, physicians indicated any response in CHICA in 151 (57.0%). Two children in the intervention group received a new diagnosis of ASD within the time frame of the study. The findings suggest that computer automation, when integrated with clinical workflow and the electronic health record, increases screening of children for ASD, but follow-up by physicians is still flawed. Automation of the subsequent workup is still needed. ClinicalTrials.gov identifier: NCT01612897.

Rekomendasi Penentuan Target Pemasangan Iklan Facebook Ads Menggunakan Metode SAW

In determining the interest of potential customers on Facebook, so far there are no tools and basic benchmarks as indicators that can be used as a reference for them to determine the target of online advertising. There is also no tool found in the form of software in the form of a decision support system that can help business people to process data and make decisions.
 The purpose of this study was to create a decision support system software for determining Facebook ads using the SAW method, with 6 criteria, namely the preferred page, likes, comments, shared, redeemed ads, ads clicked.
 The results of calculations using the system as well as those that have been manually calculated indicate that recreation is the best interest because it is based on a value of 14.60, with a percentage of suitability of 100%. So that the designed system can be used as a decision-making tool.

Architecture for a Multimodal and Domain-Independent Clinical Decision Support System Software Development Kit.

Digitalization of the decision-making process in healthcare has been promoted to improve clinical performance and patient outcomes. The implementation of Clinical Practice Guidelines (CPGs) using Clinical Decision Support Systems (CDSSs) is widely developed in order to achieve this purpose within clinical information systems. Nevertheless, due to several factors such as (i) incompleteness of CPG clinical knowledge, (ii) out-of-date contents, or (iii) knowledge gaps for specific clinical situations, guideline-based CDSSs may not completely satisfy clinical needs. The proposed architecture aims to cope with guideline knowledge gaps and pitfalls by harmonizing different modalities of decision support (i.e. guideline-based CDSSs, experience-based CDSSs, and data mining-based CDSSs) and information sources (i.e. CPGs and patient data) to provide the most complete, personalized, and up-to-date propositions to manage patients. We have developed a decisional event structure to retrieve all the information related to the decision-making process. This structure allows the tracking, computation, and evaluation of all the decisions made over time based on patient clinical outcomes. Finally, different user-friendly and easy-to-use authoring tools have been implemented within the proposed architecture to integrate the role of clinicians in the whole process of knowledge generation and validation. A use case based on Breast Cancer management is presented to illustrate the performance of the implemented architecture.

PENERAPAN METODE 360 DERAJAT DAN ANALYTICAL HIERARCHY PROCESS (AHP) DALAM SISTEM PENILAIAN KINERJA PEGAWAI (STUDI KASUS : RUMAH SAKIT FADILAH PRABUMULIH)

Decision support System software is very useful in the assessment process of employee performance. This study implements a method known as method name 360 degrees. This method conducts feedback evaluation by combining various feedback obtained from coworkers, employees, subordinates, officers and company customers, results of the feedback assessment process will continue with the process Assessment by using the Analytic Hierarchy Process (AHP) method which results in the decision by comparing the priority criteria so that the weight value of each criterion has been obtained by the decision. Are sorted from the largest value to the smallest. The results of the study obtained the performance value of employees in the company derived from the assessments given to all employees involved in the assessment.

OPTIMALISASI PENGAMBILAN KEPUTUSAN PENILAIAN KINERJA DOSEN PADA PERGURUAN TINGGI ISLAM XYZ MENGGUNAKAN AHP (ANALYTICAL HIERARCHY PROCESS)

In a decision-making process, decision makers are often faced with various problems that come from the diversity criteria. Related to this, the Analytical Hierarchy Process (AHP) can be used to resolve such issues. One is the assessment of islamic university lecturer performance who rely on the criteria of integrity, professional competence, and performance. For the sake of effectiveness of an islamic higher education institution, required a software decision support system such as EC (Expert Choice) that can process data in order to recommend a decision regarding the performance of lecturers that will affect the class and salary increment.

Prospects for Using of Decision Support Systems for Assessment and Control of Technogenic Pressure on the Environment

Purpose. Designing the database concerning level of technogenic load on the environment. Development of the software for database control and zoning Ukrainian area by the techonogenic load. Methods. The GIS free software QGIS is used as main tool for spatial data analysis and designing the digital maps. The secondary tool is Environmental Decision Support Systems software which has been developed by author of the research. The main mathematical algorithms are cluster and factor analysis. Results. The comprehensive approach to multidimensional zoning has been introduced. The integral index of technogenic load on the environment has been defined. The integral index is based on particular indexes which describes technodenic impacts on atmosphere, water and soils. The territory of Ukraine has been zoned by the level of technogenic load on the environment. There has been calculated comprehensive map of spatial distribution for technogenic load on the environment of Ukraine. There have been designed The digital map database, which describes conditions of the environment of Ukraine, and appropriate database control system. Author has developed the comprehensive software Envoronmental Decision Support systems by utilizing objectice-oriented language C++. The core of the application is geoinrormational models and appropriate mathematical algorithms for spatial data analysis. Conclusions. The areas with high levels of technogenic load on the environment have been outlined. The developed approach and software might be useful for state and local authority institutions control activities which directed to reduction of negative impacts on the environment.

A decision support tool to enhance agricultural growth in the Mékrou river basin (West Africa)

We describe in this paper the implementation of E-Water, an open software Decision Support System (DSS), designed to help local managers assess the Water Energy Food Environment (WEFE) nexus. E-Water aims at providing optimal management solutions to enhance food crop production at river basin level. The DSS was applied in the transboundary Mékrou river basin, shared among Benin, Burkina Faso and Niger. The primary sector for local economy in the region is agriculture, contributing significantly to income generation and job creation. Fostering the productivity of regional agricultural requires the intensification of farming practices, promoting additional inputs (mainly nutrient fertilizers and water irrigation) but, also, a more efficient allocation of cropland.In order to cope with the heterogeneity of data, and the analyses and issues required by the WEFE nexus approach, our DSS integrates the following modules: (1) the EPIC biophysical agricultural model; (2) a simplified regression metamodel, linking crop production with external inputs; (3) a linear programming and a multiobjective genetic algorithm optimization routines for finding efficient agricultural strategies; and (4) a user-friendly interface for input/output analysis and visualization.To test the main features of the DSS, we apply it to various real and hypothetical scenarios in the Mékrou river basin. The results obtained show how food unavailability due to insufficient local production could be reduced by, approximately, one third by enhancing the application and optimal distribution of fertilizers and irrigation. That would also affect the total income of the farming sector, eventually doubling it in the best case scenario. Furthermore, the combination of optimal agricultural strategies and modified optimal cropland allocation across the basin would bring additional moderate increases in food self-sufficiency, and more substantial gains in the total agricultural income.The proposed software framework proves to be effective, enabling decision makers to identify efficient and site-specific agronomic management strategies for nutrients and water. Such practices would augment crop productivity, which, in turn, would allow to cope with increasing future food demands, and find a balanced use of natural resources, also taking other economic sectors—like livestock, urban or energy—into account.

Decision Support System for Selecting of Radiotherapy Methods: Case Study of Breast Cancer

Radiotherapy is a recognized therapy to achieve healing as much as 45–50% of cancer patients, the cancer that dominates 30% in Indonesia is Breast Cancer. Radiotherapy methods include 3D-CRT, IMRT, VMAT. Decision-making in the selection of radiotherapy methods in case of breast cancer is unique to each patient so doctors need consideration. Aim: Selection of radiotherapy methods for breast cancer patients so that it becomes optimal with support of decision support system. Decision support system based Analytical Hierarchy Process helps solve complex problems by structuring a hierarchy of criteria, stakeholders, outcomes and displaying considerations to develop possible options. Software Decision Support System resulting from this research in the form of decision support system based AHP that can be utilized by doctors as a tool of selection alternative radiotherapy methods existing and educational facilities of prospective expert doctors in learning about radiotherapy methods in breast cancer patients. Conclusions and suggestion: The resulting of decision support system is used in the selection of radiotherapy methods in breast cancer patients that greatly assist the physician in selecting decisions. Suggested Further research software can be made and more complex.

Comparison of Software Decision Support Systems for Solving a Multicriteria Optimization Problem

Abstract This article describes in details how multicriteria optimization can be applied to solve a typical business problem for resources planning and manufacturing process optimization in a battery factory. We solve the problem by using an interactive software decision support system WebOptim developed at the Institute of information and communication technologies. The entire problem solving process is described step by step in order to point out the problem specific features as well as to demonstrate the capabilities of the WebOptim software system. For comparison, we have solved the same problem by means of another popular decision support system WWW NIMBUS and both solutions are analyzed and discussed.

The Benefit of Decision Support System as Sustainable Environment Technology to Utilize Coastal Abundant Resources in Indonesia

Being the largest archipelagic state in the world (± 81 000 km of coastline), Indonesia has a great potential for developing the aquaculture industry. But, the accomplishment of sustainable practices and management systems are still in its infancy. Therefore, it is vital to improve aquaculture technology and develop management tools that address the need for an eco-friendly production process. In this manuscript, the Decision Support System software is applied for the management of sustainable floating net cage finfish cultures. This software integrates physical, chemical, biological properties and information on coastal uses to determine site selection, production carrying capacity, ecological carrying capacity and socio-economic assessment of 18 cases, focusing on the economic viability of Tiger grouper [Epinephelus fuscoguttatus (Forsskål, 1775)], Humpback grouper [Cromoliptes altivelis (Valenciennes, 1828)] and Leopard Coral grouper [Plectropomeus leopardus (Lacepède, 1802)] at three remote areas in Indonesia, including: Ekas Bay, Talise and Galang Island. The outcomes demonstrate that only Galang Island provides a suitable area of 12 940 ha with the estimated production carrying capacity of (0.5 to 366) t/annual per fish farm along with ecological carrying capacity are limited of (18 393 to 21 727) t/annual and economic evaluation highlighted that all cultures development are economically viable.

Land Suitability Analysis for Public Parks using the GIS Application

The provision of public facilities including public parks is a major urban planning issue in various cities of the developing world. Thus, the city of District Larkana, Sindh, Pakistan is selected as a case area. In this research, an Analytic Hierarchy Process (AHP) framework as a multi-criteria decision approach of integrating with Geographic Information System (GIS) was carried-out to indicate different parameters for selection of a suitable site of public parks. While the selection of optimal site for public parks, land suitability model was applied. The Exert Choice (decision support system) software was used for calculating the weights from alternative scenarios asked by different experts. Computed weights were introduced into GIS through spatial analysis tools, produced land suitability maps, and proposed different sites around the city for public parks. In the end, the findings were made and suggested suitable locations for public parks to provide amusement facilities in Larkana city. This study may assist and benefit to city planners, real estate developers, and government officials in examining the public facilities including parks & their accessibility related issues at urban level and act as to ensure proper land use planning and management of the urban areas.

A Suitable Tool for Sustainable Groundwater Management

Artificial recharge is used to increase the availability of groundwater storage and reduce saltwater intrusion in coastal aquifers, where pumping and droughts have severely impaired groundwater quality. The implementation of optimal recharge methods requires knowledge of physical, chemical, and biological phenomena involving water and wastewater filtration in the subsoil, together with engineering aspects related to plant design and maintenance operations. This study uses a novel Decision Support System (DSS), which includes soil aquifer treatment (SAT) evaluation, to design an artificial recharge plant. The DSS helps users make strategic decisions on selecting the most appropriate recharge methods and water treatment technologies at specific sites. This will enable the recovery of safe water using managed aquifer recharge (MAR) practices, and result in reduced recharge costs. The DSS was built using an artificial intelligence technique and knowledge-based technology, related to both quantitative and qualitative aspects of water supply for artificial recharge. The DSS software was implemented using rules based on the cumulative experience of wastewater treatment plant engineers and groundwater modeling. Appropriate model flow simulations were performed in porous and fractured coastal aquifers to evaluate the suitability of this technique for enhancing the integrated water resources management approach. Results obtained from the AQUASTRESS integrated project and DRINKADRIA IPA CBC suggest the most effective strategies for wastewater treatments prior to recharge at specific sites.

Assessing the social impacts of nano-enabled products through the life cycle: the case of nano-enabled biocidal paint

Assessment of the social aspects of sustainability of products is a topic of significant interest to companies, and several methodologies have been proposed in the recent years. The significant environmental health and safety concerns about nano-enabled products calls for the early establishment of a clear benefit-risk framework in order to decide which novel products should be developed further. This paper proposes a method to assess the social impacts of nano-enabled products through the life cycle that is (a) quantitative, (b) integrates performance and attitudinal dimensions of social impacts and (c) considers the overall and stakeholder balance of benefits and costs. Social life cycle assessment (s-LCA) and multi-criteria decision analysis (MCDA) are integrated to address this need, and the method is illustrated on a case study of a nano-enabled product. The s-LCA framework comprises 15 indicators to characterize the social context of the product manufacture placed within the classification structure of benefit/cost and worker/community. The methodology includes four steps: (a) normalization of company level data on the social indicator to country level data for the year, (b) nested weighting at stakeholder and indicator level and its integration with normalized scores to create social indicator scores, (c) aggregation of social indicator scores into benefit score, cost score and net benefit scores as per the s-LCA framework and (d) classification of social indicator scores and aggregated scores as low/medium/high based on benchmarks created using employment and value-added proxies. A prospective production scenario involving novel product, a nano-copper oxide (n-CuO)-based paint with biocidal functionality, is assessed with respect to its social impacts. The method was applied to 12 indicators at the company level. Classification of social indicator scores and aggregated scores showed that the n-CuO paint has high net benefits. The framework and method offer a flexible structure that can be revised and extended as more knowledge and data on social impacts of nano-enabled products becomes available. The proposed method is being implemented in the social impact assessment sub-module of the SUN Decision Support (SUNDS) software system. Companies seeking to improve the social footprint of their products can also use the proposed method to consider relevant social impacts to achieve this goal.

Decision support based on simulation

The paper deals with a possible solution to the problem of choosing the best variant of a simulation model from a finite set of alternatives in the process of decision-making support. Evaluation of possible solutions is carried out via methods of multi-criteria analysis of alternatives. The integration of simulation models and models of decision support is set-theoretically formalized. The problem of choosing the rational set of simulation model parameters, considering restrictions imposed by experts, is solved by heuristic optimization method based on the local search strategy. Developed algorithms and software form a separate module in the decision support system (DSS) "Space" that makes it possible to rank alternatives submitted by simulation models. DSS software architecture is developed by means of object-oriented paradigm and is built of C# and T-SQL code. Combined with client-server model via thin-client architecture it gives additional flexibility to the users due to their option preferences of hardware and software. DSS “Space” allows ranking of simulation results using both traditional methods, such as weight and multiplicative function, ideal value and fuzzy and hybrid models of user’s preferences identification.Designed software allows applying it for variable scientific and technical civil and military problems due to its universality.

Implementation and Outcomes of an Advanced Antimicrobial Stewardship Program at a Quaternary Care Hospital in the United Arab Emirates

BackgroundAntimicrobial stewardship programs (ASPs) are pivotal in healthcare facilities to curb antimicrobial resistance, improve patient outcomes and decrease healthcare costs. There is lack of literature on integrating the electronic medical record and electronic surveillance into antimicrobial stewardship in the Middle East. We describe our experience with implementing an advanced antimicrobial stewardship program using computerized clinical decision support system (CDSS) and electronic real-time surveillance software at a newly operated quaternary care hospital in the United Arab Emirates.MethodsThe ASP was implemented at hospital inception in April 2015. ASP utilized strategies described in the IDSA/SHEA guidelines including the use of rapid diagnostics, CDSS and electronic real-time surveillance. Antimicrobial therapy consumption was monitored monthly and reported in days of therapy per (DOT) per 1,000 inpatient days. Antimicrobial cost was analysed as total antimicrobials dispensed (AED) per 1,000 inpatient days. Antimicrobial therapy consumption and cost were analysed from the third-quarter of 2015 until the first quarter of 2017.ResultsAlthough our program has only been active for a little over 2 years, it has achieved significant decrease in the use of targeted antimicrobials. Carbapenem use decreased by 32%, from 105 to 71 DOT/1,000 inpatient days (P = 0.05). Anti-MRSA agents use decreased by 57% from 109 to 46 DOT/1,000 inpatient days (P = 0.003), and anti-pseudomonal β-lactam use decreased by 49% from 84 to 43 DOT/1,000 inpatient days (P = 0.015). Total cost of antimicrobial therapy decreased as well by 67% from 323 AED/1,000 inpatient days to 105 AED/1,000 inpatient days, (P = 0.01), with a hard cost total saving of 943,324 AED (256,338 USD) since program inception. There was no change in the severity of illness scores as measured by the hospital Case Mix Index (CMI) during the study period.ConclusionTo our knowledge this is the first advanced ASP program in the United Arab Emirates utilizing CDSS and electronic real-time surveillance. Our program demonstrated a significant decrease in the use and total cost of antimicrobials since hospital inception despite a significant increase in patient volume.Disclosures All authors: No reported disclosures.

Optimizing cultivation of agricultural products using socio-economic and environmental scenarios

The combination of degrading natural conditions and resources, climate change, growing population, urban development, and competition in a global market complicate optimization of land for agricultural products. The use of pesticides and fertilizers for crop production in the agricultural fields has become excessive in the recent years and Golestan Province of Iran is no exception in this regard. For this, effective management with an efficient and cost-effective practice should be undertaken, maintaining public service at a high level and preserving the environment. Improving the production efficiency of agriculture, efficient use of water resources, decreasing the use of pesticides and fertilizers, improving farmer revenue, and conservation of natural resources are the main objectives of the allocation, ranking, and optimization of agricultural products. The goal of this paper is to use an optimization procedure to lower the negative effects of agriculture while maintaining a high production rate, which is currently a gap in the study area. We collected information about fertilizer and pesticide consumption and other data in croplands of eastern Golestan Province through face-to-face interviews with farmers to optimize cultivation of the agricultural products. The toxicity of pesticides according to LD50 was also included in the optimization model. A decision-support software system called multiple criteria analysis tool was used to simultaneously minimize consumption of water, chemical fertilizers, and pesticides and maximize socio-economic returns. Three scenarios for optimization of agricultural products were generated that alternatively emphasized on environmental and socio-economic goals. Comparing socio-economic and environmental performance of the optimized agricultural products under the three scenarios illustrated the conflict between social, economic, and environmental objectives. Of the six crops studied (wheat, barley, rice, soybeans, oilseed rape, and maize), rice ranked second in the social and fifth in the economic scenarios. Soybeans had the lowest rank for economic and social scenarios and its cultivation in the study area, in terms of economic and social goals, was rejected by the model. However, cultivation of soybeans continues in the area as a responsibility to cater for the major need of the country. Because of subsidized prices of water, fertilizers, and pesticides, the use of these items are far from optimized in the current agricultural practices in the area.

Design and implementation of wireless dose logger network for radiological emergency decision support system.

A decision support system (DSS) is implemented in Radiological Safety Division, Indira Gandhi Centre for Atomic Research for providing guidance for emergency decision making in case of an inadvertent nuclear accident. Real time gamma dose rate measurement around the stack is used for estimating the radioactive release rate (source term) by using inverse calculation. Wireless gamma dose logging network is designed, implemented, and installed around the Madras Atomic Power Station reactor stack to continuously acquire the environmental gamma dose rate and the details are presented in the paper. The network uses XBee-Pro wireless modules and PSoC controller for wireless interfacing, and the data are logged at the base station. A LabView based program is developed to receive the data, display it on the Google Map, plot the data over the time scale, and register the data in a file to share with DSS software. The DSS at the base station evaluates the real time source term to assess radiation impact.

Formal analysis of the surgical pathway and development of a new software tool to assist surgeons in the decision making in primary breast surgery

BackgroundThe increased complexity of the decisional process in breast cancer surgery is well documented. With this study we aimed to create a software tool able to assist patients and surgeons in taking proper decisions. MethodologyWe hypothesized that the endpoints of breast cancer surgery could be addressed combining a set of decisional drivers. We created a decision support system software tool (DSS) and an interactive decision tree. A formal analysis estimated the information gain derived from each feature in the process. We tested the DSS on 52 patients and we analyzed the concordance of decisions obtained by different users and between the DSS suggestions and the actual surgery. We also tested the ability of the system to prevent post breast conservation deformities. ResultsThe information gain revealed that patients preferences are the root of our decision tree. An observed concordance respectively of 0.98 and 0.88 was reported when the DSS was used twice by an expert operator or by a newly trained operator vs. an expert one. The observed concordance between the DSS suggestion and the actual decision was 0.69. A significantly higher incidence of post breast conservation defects was reported among patients who did not follow the DSS decision (Type III of Fitoussi, N = 4; 33.3%, p = 0.004). ConclusionThe DSS decisions can be reproduced by operators with different experience. The concordance between suggestions and actual decision is quite low, however the DSS is able to prevent post- breast conservation deformities.

Building a Decision Support System for Inpatient Admission Prediction With the Manchester Triage System and Administrative Check-in Variables.

The usage of decision support tools in emergency departments, based on predictive models, capable of estimating the probability of admission for patients in the emergency department may give nursing staff the possibility of allocating resources in advance. We present a methodology for developing and building one such system for a large specialized care hospital using a logistic regression and an artificial neural network model using nine routinely collected variables available right at the end of the triage process.A database of 255.668 triaged nonobstetric emergency department presentations from the Ramon y Cajal University Hospital of Madrid, from January 2011 to December 2012, was used to develop and test the models, with 66% of the data used for derivation and 34% for validation, with an ordered nonrandom partition. On the validation dataset areas under the receiver operating characteristic curve were 0.8568 (95% confidence interval, 0.8508-0.8583) for the logistic regression model and 0.8575 (95% confidence interval, 0.8540-0. 8610) for the artificial neural network model. χ Values for Hosmer-Lemeshow fixed "deciles of risk" were 65.32 for the logistic regression model and 17.28 for the artificial neural network model. A nomogram was generated upon the logistic regression model and an automated software decision support system with a Web interface was built based on the artificial neural network model.

Strategic Planning in Population Health and Public Health Practice: A Call to Action for Higher Education.

Scarce resources, especially in population health and public health practice, underlie the importance of strategic planning. Public health agencies' current planning and priority setting efforts are often narrow, at times opaque, and focused on single metrics such as cost-effectiveness. As demonstrated by SMART Vaccines, a decision support software system developed by the Institute of Medicine and the National Academy of Engineering, new approaches to strategic planning allow the formal incorporation of multiple stakeholder views and multicriteria decision making that surpass even those sophisticated cost-effectiveness analyses widely recommended and used for public health planning. Institutions of higher education can and should respond by building on modern strategic planning tools as they teach their students how to improve population health and public health practice. Strategic planning in population health and public health practice often uses single indicators of success or, when using multiple indicators, provides no mechanism for coherently combining the assessments. Cost-effectiveness analysis, the most complex strategic planning tool commonly applied in public health, uses only a single metric to evaluate programmatic choices, even though other factors often influence actual decisions. Our work employed a multicriteria systems analysis approach--specifically, multiattribute utility theory--to assist in strategic planning and priority setting in a particular area of health care (vaccines), thereby moving beyond the traditional cost-effectiveness analysis approach. (1) Multicriteria systems analysis provides more flexibility, transparency, and clarity in decision support for public health issues compared with cost-effectiveness analysis. (2) More sophisticated systems-level analyses will become increasingly important to public health as disease burdens increase and the resources to deal with them become scarcer. The teaching of strategic planning in public health must be expanded in order to fill a void in the profession's planning capabilities. Public health training should actively incorporate model building, promote the interactive use of software tools, and explore planning approaches that transcend restrictive assumptions of cost-effectiveness analysis. The Strategic Multi-Attribute Ranking Tool for Vaccines (SMART Vaccines), which was recently developed by the Institute of Medicine and the National Academy of Engineering to help prioritize new vaccine development, is a working example of systems analysis as a basis for decision support.