A human resource planning model for hospital/medical technologists: an analytic hierarchy process approach

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.

Potential pros and cons of external healthcare performance evaluation systems: real-life perspectives on Iranian hospital evaluation and accreditation program

BACKGROUND

Performance evaluation is essential to quality improvement in healthcare. The current study has identified the potential pros and cons of external healthcare evaluation programs, utilizing them subsequently to look into the merits of a similar case in a developing country.

METHODS

A mixed method study employing both qualitative and quantitative data collection and analysis techniques was adopted to achieve the study end. Subject Matter Experts (SMEs) and professionals were approached for two-stage process of data collection.

RESULTS

Potential advantages included greater attractiveness of high accreditation rank healthcare organizations to their customers/purchasers and boosted morale of their personnel. Downsides, as such, comprised the programs' over-reliance on value judgment of surveyors, routinization and incurring undue cost on the organizations. In addition, the improved, standardized care processes as well as the judgmental nature of program survey were associated, as pros and cons, to the program investigated by the professionals.

CONCLUSION

Besides rendering a tentative assessment of Iranian hospital evaluation program, the study provides those running external performance evaluations with a lens to scrutinize the virtues of their own evaluation systems through identifying the potential advantages and drawbacks of such programs. Moreover, the approach followed could be utilized for performance assessment of similar evaluation programs.

Multicriteria decision analysis in oncology

BACKGROUND

There has been a growing interest in the development and application of alternative decision-making frameworks within health care, including multicriteria decision analysis (MCDA). Even though the literature includes several reviews on MCDA methods, applications of MCDA in oncology are lacking.

AIM

The aim of this paper is to discuss a rationale for the use of MCDA in oncology. In this context, the following research question emerged: How can MCDA be used to develop a clinical decision support tool in oncology?

METHODS

In this paper, a brief background on decision making is presented, followed by an overview of MCDA methods and process. The paper discusses some applications of MCDA, proposes research opportunities in the context of oncology and presents an illustrative example of how MCDA can be applied to oncology.

FINDINGS

Decisions in oncology involve trade-offs between possible benefits and harms. MCDA can help analyse trade-off preferences. A wide range of MCDA methods exist. Each method has its strengths and weaknesses. Choosing the appropriate method varies depending on the source and nature of information used to inform decision making. The literature review identified eight studies. The analytical hierarchy process (AHP) was the most often used method in the identified studies.

CONCLUSION

Overall, MCDA appears to be a promising tool that can be used to assist clinical decision making in oncology. Nonetheless, field testing is desirable before MCDA becomes an established decision-making tool in this field.

Determining patient preferences for remote monitoring

This paper presents the patient preferences for an application in remote health monitoring. The data was collected through a mobile service prototype. Analytical Hierarchy Process and Conjoint Analysis were used to extract the patient preferences. The study was limited to diabetes and obesity patients in Istanbul, Turkey. Results indicated that sending users' data automatically, availability of technical support, and price are key factors impacting patient's decisions. This implies that e-health service providers and designers should focus on the services that enable users to send measurement results automatically instead of manually.

[Evaluation factors for CR system introduction using AHP and simulation]

Medical institutions usually find it difficult to select computed radiography (CR) equipment because of the involvement of many complicated factors such as operability, processing time, and price. The analytic hierarchy process (AHP) is often applied in complex decision and evaluation situations. This study quantitatively evaluates the institution's selection criteria of equipment using AHP. The AHP model of this study consisted of 3 levels: the goal, 6 evaluations, and 3 alternatives. Processing time, price operability, picture quality, connectivity, and equipment size were considered as the criteria for decision marking. We simulated alteration of priority of evaluations by changing the weight of pricing between 0 and 1. Results showed that price and connectivity accounted for 60% of the total weight. On excluding operability, the difference in weight between equipment was 1.16 times; the priority of processing time was 1.36 times; and the priority of price was 1.37 times. In the same way, when considering operability, the difference in weight between equipment was 0.36 times, the priority of processing time was 0.45 times, and the priority of price was 0.11 times.

Information technology in the future of health care

Technology advances have changed the face of health care. This paradigm shift blurred the boundaries between public health, acute care, and prevention. Technology's role in the diagnosis, treatment assignment, follow-ups, and prevention will be reviewed and future impact projected. The understanding of shift in our expectation for each aspect of health care is critical so that levels of success are understood. Technology advances in health care delivery will be discussed. Specific applications are presented and explained and future trends discussed. Four applications are defined, and related to categories of technologies and their attributes.

Technology transfer with system analysis, design, decision making, and impact (Survey-2000) in acute care hospitals in the United States

This paper provides the results of the Survey-2000 measuring technology transfer for management information systems in health care. The relationships with systems approaches, user involvement, usersatisfaction, and decision-making were measured and are presented. The survey also measured the levels Internet and Intranet presents in acute care hospitals, which will be discussed in future articles. The depth of the survey includes e-commerce for both business to business and customers. These results are compared, where appropriate, with results from survey 1997 and changes are discussed. This information will provide benchmarks for hospitals to plan their network technology position and to set goals. This is the first of three articles based upon the results of the Srvey-2000. Readers are referred to a prior article by the author that discusses the survey design and provides a tutorial on technology transfer in acute care hospitals.

Tutorial on technology transfer and survey design and data collection for measuring Internet and Intranet existence, usage, and impact (survey-2000) in acute care hospitals in the United States

This paper provides a tutorial of technology transfer for management information systems in health care. Additionally it describes the process for a national survey of acute care hospitals using a random sample of 813 hospitals. The purpose of the survey was to measure the levels of Internet and Intranet existence and usage in acute care hospitals. The depth of the survey includes e-commerce for both business to business and with customers. The relationships with systems approaches, user involvement, user satisfaction and decision-making will be studied. Changes with results of a prior survey conducted in 1997 can be studied and enabling and inhabiting factors identified. This information will provide benchmarks for hospitals to plan their network technology position and to set goals.

Decision-making with and without information technology in acute care hospitals: survey in the United States

These survey results are from a national survey of acute care hospitals. A random sample of 813 hospitals was selected with 115 responding and 33 incorrect addresses resulting in a 15% response rate. The purpose of the study was to measure the extent of information systems integration in the financial, medical, and administrative systems of the hospitals. Decision making with and without information technology is explored based upon the survey data. The results indicate why and how meetings are held. Necessary changes in the decision-making environment are identified for decision making utilizing information technology to be successful. These results will provide a benchmark for hospitals to determine their technology transfer position and to set goals for computer assisted decision-making.