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achieve lower costs through rationing assets (eg, ambulatory service and real ime forecasting of resources) The purpose of this case was to develop and test a valid survey instrument for measuring user evaluations of VAMTA, as a novel means to expedite smart data delivery, in preventive healthcare [3] The ndings of the case study were used to test the instrument that was used in a preliminary assessment of the effectiveness of the VAMTA system and the applicability of smart data in the TTF model to the VAMTA application The development of the instrument was carried out in two stages The rst stage was item creation The objective of this rst stage was to ensure face and content validity of the instrument An item pool was generated by interviewing two end-users of IT, obtained from a pool of medical technicians The end-users were given training on the module for 2 days and invited to participate in the study These subjects were selected for reasons of geographical proximity of the sample and, in many cases, the existence of personal contacts onboard ship An interview was also conducted with one of the authors of this study, who has approximately 10 years experience as an IT end-user In addition, the domain coverage of the developed pool of items was assessed by three other end-users from three different ship environments covered in the survey None of the end-users, who were a part of the scale development, completed the nal survey instrument All the items were measured on a ve-point Likert scale ranging from strongly agree to strongly disagree Next, the survey instrument was utilized in a pilot study in which end-users tested the VAMTA This pilot study provided face validity, in that the perceptions of end-users could be measured, and evaluation of the system from a conceptual viewpoint could be documented A total of 33 end-users were used in this phase to test the VAMTA They reported their perceptions of the VAMTA in the survey instrument, which was provided after their training and testing The pilot study results were analyzed using SPSS and Microsoft Excel to determine whether TTF, along with individual characteristics, had an impact on user evaluations of the VAMTA For the case, the original TTF model was modi ed to ensure adequate domain coverage of medical and preventive healthcare applications The third smart data dimension revolves around data-aligned methods and algorithms that utilize data with pointers for best practices, data with built-in intelligence, autonomics, an automated regulatory environment (ARE), and an automated contracting environment (ACE) Our case used data-aligned methods for the 33 individuals who participated in the testing of the VAMTA, including 11 females and 22 males, with various levels of experience and education Experience ranged from test subjects who had never seen the application before they tested it, to developers who built the application A number of test subjects had limited medical backgrounds Education ranged from high school graduates to people with doctorate degrees Data with pointers for best practices was utilized so that each test subject was shown a demonstration of the VAMTA prior to testing Test subjects were then required to build a new user account and speech pro le Subjects ran through the application once using a test script to become familiar with.

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the application Next, the test subjects went through the application again while being videotaped No corrections were made to dictated text during the videotaping This allowed the tracking of voice dictation accuracy for each user with a new speech pro le Test subjects completed the entire process in an average of 2 hours Afterward, each test subject completed a questionnaire to determine user demographics, utility and quality performance, system interface, hardware, information management, and overall system satisfaction and importance This survey instrument also allowed the test subjects to record any problems and suggest improvements to the system Data with built-in intelligence techniques recorded any problems that the test subjects encountered in the survey instrument Autonomics were employed by the VAMTA development team, to document bugs in the tracking system, and targeted by the test architect for the appropriate problem solving action The performance of VAMTA during testing was measured in terms of voice accuracy, voice accuracy total errors, duration with data entry by voice, and duration with data entry by keyboard and mouse Viewed together, these statistics provide a snapshot of the accuracy, speed, and overall effectiveness of the VAMTA system Each test subject s printout was compared with a test script printout for accuracy When discrepancies occurred between the subject s printout and the est script, the printouts were compared with the automated video recordings to determine whether the test subjects said the words properly, stuttered or mumbled words, and/or followed the test script properly Misrecognitions occurred when the test subject said a word properly and the speech program recorded the wrong word This automated regulatory environment provided a solid baseline for the lab experiments and led to the following results The accuracy of voice recognition, con rmed by videotaped records of test sessions, averaged 976%, with 6 misrecognitions (Table 41) The minimum average voice recognition was 85%, with 37 misrecognitions The maximum average voice recognition was 996% with 1 misrecognition Median voice recognition was 984%, with 4 misrecognitions.

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tralization of company-wide data into a data warehouse (see the preceding best practice) This is no small task, since the information needed by each state may vary slightly from the requirements of other states, calling for subtle changes in the storage of data throughout the company that will yield the appropriate information for reporting purposes The next step is to obtain tax rate information and store it in a central database This information can be manually located by accessing the tax agency websites of all fifty states, but is more easily obtained in electronic format from any of the national tax reporting services This information can then be stored in the forms/rates data warehouse An additional step is to create a separate program for each of the tax reports, so that a computer report is issued that mimics the reporting format used by each state Then the information can be manually transferred from the computer report to a printout of the PDF Portable Document Format) file of each state s tax form For those programming staffs with a large amount of available time, it is also possible to create a report format that exactly mirrors each state tax form, which can be printed out, with all tax information enclosed within it, and immediately mailed out The trouble with this best practice is the exceptionally high programming cost associated with obtaining a complete automated solution There are so many tax forms to be converted to a digital format that the development task is considerable Accordingly, it is more cost-effective to determine those tax forms that share approximately the same information, and to develop an automated solution for them first Any remaining tax forms that would require special programming to automate should be reviewed on a case-by-case basis to determine if it is cost-beneficial to complete further programming work, or to leave a few stray reports for the tax preparation staff to complete by hand.

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