Online Data Entry Jobs

Data Entry Direct

Data Entry Direct refers to an online platform that provides individuals with opportunities for accessing an online data entry job. Individuals are provided with a variety of tasks from which they can choose the ones they deem suitable depending on their conditions. What is more, each and every detail of the work is being explained to them before they are handed over the tasks. Importantly, people are provided with a chance of working with various organizations irrespective of their location. To access the opportunities, one is required to log in to the site and provide a username and password. The pay given depends on a number of factors, even though individuals' efforts play a significant role. Since the details of the tasks are well explained before one begins the work, the chances of the task accomplished being rejected are very minimal. This is a real and dependable program with worldwide acceptance. Join the millions who have already subscribed to it and have the chance of working despite the circumstances surrounding you. Read more here...

Data Entry Direct Summary


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Online Data Entry Jobs

The product is an opportunity to earn money by participating in online data entry jobs, private panels, discussion groups, clinical trials, online bulletin boards, taste and mystery investigations. This product will put you in touch with the best-paid research studies available, allowing you to earn extra-income for life, as well as being your own leader. The product is a reliable basic tool. This product was launched by Tim after discovering on the market the need for user-friendly online data entry. Since then, the product has taken a life of its own. This product offers a great dedication to its improvement and provides personalized support to customers who use it. What follows is what the product contains; The desire to earn money by participating in online data entry work, How to increase your income by participating in online data entry jobs, The benefits of participating in online data entry jobs. Almost 90% of people working in their office suffer from stress-related problems. The chances of getting infections, the flu or fever are more important when traveling by public transport. And being sick, lying on the bed, would, in turn, cause your medical expenses and other losses. On the other hand, using this product, you would be safer. Your stress level will automatically decrease and you will be able to give 100% to your work. Therefore, using this product, you are guaranteed to work less freely. Read more here...

Online Data Entry Jobs Summary

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Paper Data Collection with Centralized Interactive Data Entry

In this design, data are collected on paper forms and shipped to the coordinating center where data coordinators enters them directly into a centralized data management system. SCs complete the paper forms and ship them to the coordinating center. The data coordinator visually checks received forms as in pure paper-based DMS. However, forms are not entered by double-key high-speed data entry. Instead, they are entered directly into a customized data management system through computerized screens. A second data coordinator reviews the fully marked entered forms and compares the entries against the paper forms, flagging any discrepancies. The first data coordinator checks and rectifies these discrepancies. Range and consistence errors flagged upon entry are reported to the SCs for rectification as monthly error reports. Corrections are then applied to the database and added to the audit trail. Flagged entries that are valid are marked as uncorrectables so that they will not be flagged...

Paper Data Collection with Centralized Batch Data Entry

In this approach data are collected on paper forms. Completed forms are mailed to the coordinating center, where they go through visual inspections. Forms that pass the visual inspections are sent to the data entry department, where they are entered with high-speed double-key data entry. Created text data batches are processed through a customized centralized data management system. Range and consistency errors flagged upon entry are reported to the SCs for rectification as monthly error reports. Corrections are then applied to the database and added to the audit trail. Flagged entries that are valid are marked as uncorrectables so that they will not be flagged again. This method is also being used at the Hines VA CSPCC for a number of trials. It appears to be superior to the paper data collection with centralized interactive data entry. It is not time consuming because data are entered with high-speed double-key data entry, which expedites processing of received forms and thus the...

Data entry checking

The level of data entry checking may be a trials group policy, affecting a number of trials, or may be trial-specific, the size and complexity of the trial, the training and experience of the data management staff, and the software and programming support available influencing this level 1 . Different approaches to data-entry checking are adopted by different trials groups. These approaches are complementary and can include automatic consistency checks, double data entry, and checking computer output against information on report forms. One method of checking data input is to use double data entry for all forms. Two people independently enter the data and the two sets of data are compared. Any inconsistencies are then checked against the original forms. This is time-consuming and can be an inefficient use of resource. A study of double data entry in which the person initially entering the data did not know that double entry was to be undertaken, showed that the number of differences...

Gaining A Foothold The 1970s

The spread of technology at pharmaceutical companies also meant that secretaries were given word processors (such as the Wang machines) to use in addition to typewriters, which were still needed for filling out forms. Key-boarding was the domain of the secretaries, the data entry technicians, and the computational chemists. Only a few managers and scientists would type their own memos and articles.

Calculating log P from Structures

In 1969, Leo, being acutely aware of the demand and need for log P values, slowly began to collect, curate, and collate physicochemical data from in-house and various literature sources. His passion for this outcome led to the creation of the 24-pound bulky ledgers that made their way all over the world. Eventually with the College's acquisition of an IBM 360, collection of this data was streamlined and stored on tapes or microfiche. During this time, Leo's germ of an idea about calculating partition coefficients from computer-generated structural fragments took hold. This led to the development and evolution of the CLOGP program that displaced the error-prone manual procedures.62-64 With the addition of Weininger to the Medchem team, the WLN system for computerized chemical structure storage was supplanted by a new information system, SMILES (Simplified Molecular Input Line Systems) and a thesaurus-oriented database system, THOR, for data entry and retrieval was added.65,66 Today,...

Bayesian Modeling and Computation in Bioinformatics Research

For treating a statistical problem, with an emphasis on using the missing data formulation to construct scientifically meaningful models. Section 2.4 describes several popular algorithms for dealing with statistical computations the EM algorithm, the Metropolis algorithm, and the Gibbs sampler. Section 2.5 demonstrates how the Bayesian method can be used to study a sequence composition problem. Section 2.6 gives a further example of using the Bayesian method to find subtle repetitive motifs in a DNA sequence. Section 2.7 concludes the chapter with a brief discussion. tical models were not sufficiently well known and the computer hardware was not yet as powerful. Recently, an extensive use of probabilistic models (e.g., the hidden Markov model and the missing data formalism) has contributed greatly to the advance of computational biology.

Clinical trials manager

For a large or data-intensive trial, it can be useful to appoint a further person or persons who works with the clinical trials manager and maybe responsible for data entry, data management, maintaining the database, chasing up overdue data, and for raising queries about data with collaborating centres. Many trials will also require computing (see Section 8.11), administrative and secretarial support.

Daytoday conduct of the trial and data management

Because obtaining complete and reliable data is crucial to the successful completion of a trial, compliance in the provision of data by centres and accuracy of data entry need to be monitored. If centres send forms to the trial coordinators as soon as they have been completed, and if data management staff conversant with the trial check the information on the forms on arrival, and the data are then entered onto the trial database and subjected to checks, this may be sufficient as a routine method of monitoring for most trials. It is likely, however, that at least for some trials, further monitoring and checking will be desirable. It is, of course, important to ensure that the local centre is contacted about missing or inconsistent data.

Finding The Critical Path

This may still not be the end of the story however. Improvements can also be found by moving events out of the critical path. This involves removing the dependency between events such that they can overlap or run in parallel. This may involve an assumption of success (eg importing drug before local ethics approval obtained), alternative methodology (eg real-time remote data entry), or decoupling of tasks (eg completing non-clinical section of study report before database lock).

Tactical Decision Making

The focus of technology has been largely in data entry. Since the adoption of web-based data entry systems (commonly called EDC, though the term is much more broad) over the past five years, the promise of faster development times has been found to be elusive. As with previous technologies (such as faxback systems) that made the same promise, product timelines have not improved. Overall, development timelines continue to increase, and some companies have forayed into this technology with disastrous results, most often the consequence of inadequate planning and failure to appreciate the changes that must surround technology itself. The high cost of such systems has also made them prohibitive for smaller research groups, and a lesson from industry's experience is that it takes a good deal of training and change of processes to make these systems work well. For example, training must be provided to sites and internal staff, technical and user support must be available, and conflicts with...

Analysing the Kindlr Questionnaire

The following instructions for analysing the six sub-scales that make up the KINDLR questionnaire and for determining the total score, contain general information about the analysis and describe the necessary steps from data entry through to analysis. These steps are the same for all forms - Kiddy, Rid and Riddo - and for the children's teenagers' and parents' versions of the KINDLr questionnaire. Formulas will then be described for summarising the items and for converting the results into sub-scale scores. Finally, the possible ways of dealing with missing data will be dealt with. 22 Data Entry The next step following data entry is to recode the responses. Recoding is the process by which item scores are deduced which will then be used in calculating the sub-scale scores. This process consists of several steps Before the final item scores are assigned, all items should be checked to see whether answers occur that he outside the possible range. Answers outside the valid range are...

Design and Implementation

Validation of the data management system is typically done in two rounds. First, correctly completed data forms are entered to ensure that the system is not flagging any good data. In the second round, completed data forms with intentional data errors are entered. All errors must be identified by the system. Personnel who will be doing the actual data collection must be trained in understanding the protocol and in the completion and submission of the data forms before actual data collection. In paper-based systems it is important to establish a routine schedule for submission of data forms to the central location. A shipping log is included with each submission to record the actual forms being submitted. Figure 25.2 shows an example of a shipping log form. Pure paper-based data collection systems are inefficient in that they require large data editing overhead. Personnel at the central location must perform visual inspections of forms, compare them against the shipping log, convey...

Electronicbased Systems

Include their ability to (1) provide cleaner data faster, thus significantly reducing query rates and eliminating double data entry, (2) provide up-to-date interim progress reports in a timely fashion, and (3) dramatically reduce the time from last patient visit to final database lock out. These advantages provide for quick access of up-to-date data for feedback to the appropriate stakeholders, which allows them to make timely critical decisions and enables them to easily monitor protocol compliance, enrollment rates, and performance metrics of participating sites. Analysis has underlined the value of electronic data capture (EDC) as a cost- and time-saving approach in modern clinical research 17, 18 .

Form and System Design

The success of any clinical research trial depends greatly on the quality of its collected data. Collecting high-quality data begins with developing well-designed data collection forms. Well-designed forms simplify the data collection and management processes. They also simplify the building of analysis data sets. All of these are essential to the success of any clinical trial. They greatly reduce the time and effort of data collection and management and drastically simplify the data analysis phase. Forms should be designed to accurately and consistently capture the data points defined by the protocol and provide ease of review, data entry, and analysis.

Development Of Case Report Forms

As pointed out by Grobler et al. (2001), the trial project statistician programmer should be involved in the development of CRF design by providing the following input (1) Find the best balance between effective data collection and structuring the CRF to facilitate data entry, (2) design a CRF in such a way that the resulting datasets would be programmable with the least amount of data manipulation, (3) collect the minimum amount of necessary data, (4) data should be collected in a manner that facilitates data analysis, (5) calculated data should not be recorded in the CRF, but all data needed to perform the calculation should be included in the CRF, and (6) multiple clinical trials conducted for one submission should have consistent databases. During the development of CRF, it is essential to discuss the developed CRF with the relevant personnel who will be involved in the process after data have been collected. In practice, it would be beneficial if the statistician is consulted and...

Data Validation And Quality

Data quality may be measured by the error rate defined as the number of errors divided by the total number of data. Quality can be attributed to all variables, or to a group of variables whose quality is deemed to be critical to the final conclusions. During database inspection, the error rate can be simply estimated by the number of errors found divided by the number of data inspected. The choice of an acceptable error rate for a database varies in the industry, but a popular choice was 0.5 overall, 0 to 0.1 for critical variables, and 0.2 to 1.0 for noncritical variables (see, e.g., SCDM, 2000 Shea, 2000). The methods of estimating the error rate should be documented in the Data Management Master File. Note that an estimated error rate obtained as 5 errors out of 1000 fields inspected bears a different precision to that obtained as 50 errors out of 10,000 fields inspected. The letter is a more precise estimate. There are different data quality inspection procedures for tracking...

Individual patient data

Range and consistency checks should be carried out for all data irrespective of whether they were supplied electronically or were entered manually into the meta-analysis database (in which case it is important to audit the data entry process). Any missing data, obvious errors, inconsistencies between variables or extreme values should be queried and rectified as necessary. If details of the trial have been published, these also should be checked against the raw data and any inconsistencies similarly queried. All of the changes made to the data originally supplied by the trialists, and the reasons for these changes, should be recorded.

Pharmaceutical Sop Clinical Trial Termination Or Suspension

Issues of study protocols and clinical data management are provided in Chapters 14 and 15, respectively. Chapter 14 focuses on the development of a clinical protocol. This chapter discusses the structure and components of an adequate and well-controlled clinical trial protocol, issues that are commonly encountered in protocol development, commonly seen deviations in the conduct of a clinical trial, clinical monitoring, regulatory audit and inspection, and assessment of the quality and integrity of clinical trials. Chapter 15 summarizes basic standard operating procedures for good clinical data management practice. These standard operating procedures cover the development of case report forms (CRF), database development and validation, data entry, validation and correction, database final-ization and lock, CRF flow and tracking, and the assessment of clinical data quality.


For a clinical trial, if the sponsor is to monitor the study and to perform in-house data management and statistical analysis, then the clinical trial typically involves three parties the patient, the study center or investigator, and the sponsor. The patient is the most important participant in the clinical trial. No clinical trial is possible without the patient's dedicated participation, endurance, corporation, and sacrifice. The study center, in a broad sense, is referred to as those individuals who are either directly in contact with the patient or perform various evaluations for the patient. Among these individuals is the investigator, who usually is the patient's primary care physician and members of the patient's care team such as the pathologist for histopathological evaluation, the radiologist for imaging assessment, a staff nurse who may also serve as the coordinator for the study center, the pharmacist who dispenses the study medicines, and other health care personnel at...

Clique detection

Another pattern recognition method useful in docking was originally developed for recognizing partially occluded objects in camera scenes.253,254 A hashing function is used to map the addresses of the data entry into a smaller address space. In the case of geometric hashing, distance features are used to create the hashing key. As a result, objects with certain geometric features (for example the sphere representation of DOCK) can be rapidly accessed through a geometric hashing table.

Data Collection

Clinical trial data collection and management is, therefore, the integration of data collection and data management. The data management system depends on the data collection method. Data collection methods are of three major types The first method is pure paper-based systems. With this approach data are collected on paper forms and sent to a central location. There they are entered into electronic files by the traditional double-key high-speed data entry method. The resulting electronic files are read into a centralized database through a data management system using specific computer hardware and software. The second method is electronic-based systems in which data are entered electronically into a computer system. The system can be centralized or distributed at participating sites. Electronic-based systems can utilize various technologies for data entry. Laptops and desktops use modem connections to transfer remotely collected data to the centralized location, whereas some handheld...

Centralized Systems

The user logs into the system with valid user id and password credentials from any computer connected to the network. The instantaneous access of the user to the centralized database enables direct entry of the data into a centralized database, whether with LAN, WAN, or VPN. Remote data entry

Distributed Systems

The local user performs data entry by directly entering data into the system's database stored on the local computer with customized electronic forms. The system performs edit checks, which include range, across-form, and across-visit checks at the time of entry. This feature greatly reduces data error rates.

Wireless Systems

The use of wireless computer systems has gain popularity in data collection for clinical trials. They have been used as a substitute for normal paper-based patient diaries (Koop et al. 19 ) to increase data quality and shorten the time needed to close the database. They have also been used for mobile interviewing 20 and for bedside data collection 21 . In patient-directed data entry, subjects are given handheld computers to answer the trial's questions (Clarke et al. 22 ).

Web Based Systems

Web-based data collection and management systems provide a mechanism for remote data entry, where entered data are added to a centralized database once the submit button is pressed. They can be designed to automate the various aspects of clinical trials such as eligibility evaluation, data collection, and tracking specimens. They also serve as a resource site for participating sites to access trial-specific information, facilitate communication, track data queries and their resolutions, and allow administrative management of trials 28, 29 . For these reasons, they play an important role in facilitating the conduct of international clinical trials.

System Development

A great deal of planning is required for system development. The development phases depend on the start of the trial and the type of the system. Very often the development of a fully functioning system may not be possible before the start of the trial. Therefore, system modules are identified and assigned priorities according to their functions with reference to the trial. For example, in pure paper-based systems, the highest priority is given to the development of the module that reads the raw data batches created by the double-key data entry staff. Next in line is the module that checks the major identifiers. Then the module that performs the range and consistency checks is developed, and so on. Integrated systems such as distributed and Internet- based systems usually consist of discrete database modules for data management functions such as registration, randomization, and data entry. Modules can be categorized based on their users. Most often, system users consist of the...

Staff Training

No matter what type of system is used, staff training is a must. In distributed data entry settings, SCs are typically trained on the developed system during the kickoff meeting of the trial. The training involves going through the protocol, regulatory requirements, data collection forms, medication dispensing

Data Retention

Data collected at each participating site must be stored in a read-only format at that site for future reference. The Institutional Review Board (IRB) at each participating site requires that the site retain its local database after trial closeout. Data retention can be achieved in various ways. However the method should ensure that (1) participating sites are not be able to modify retained data (2) data are presented in a way that allows sites to easily locate any data form for any subject at any trial visit and (3) the site PI is solely responsible for the retained data. Abdellatif et al. reported a method for data retention 56 in which collected electronic data forms of each participating site are saved on a read-only CD as PDF files after the site's database has been locked. SAS Output Delivery System (ODS), PROC Template, and PROC Forms were used to construct a read-only CD of the data forms in a PDF format for each site and then sent to the site's PI.


As mentioned above, currently there is no uniform definition for adverse events. As a result, no internationally accepted medical terminology exists for evaluation of safety information for regulatory purpose. However, most pharmaceutical companies as well as regulatory agencies employ one of the international adverse drug reaction terminologies in combination with morbidity terminology. For example, regulatory agencies in Europe use a combination of WHOART and ICD-9th Revision (ICD-9). The COSTART adopted by the U.S. FDA is usually used in conjunction with ICD-9-CM (a clinical modification of ICD-9). On the other hand, the Japanese have developed their own version of the international terminologies, namely, J-ART and MEDIS. These established international medical terminologies and coding systems have been criticized for the lack of specificity of terms provided at the data entry level, limited data retrieval capability, and inability to handle syndromes effectively. As a result,...

Database Development

As indicated by Grobler et al. (2001), a database should be designed to facilitate data entry and the extraction of data for analysis. Database development includes database design (or setup) and database edit check specifications, which are briefly outlined In practice, for a given clinical trial, to facilitate data entry and the extraction of data for analysis, a protocol-specific database is set up using standard templates (e.g., modules and format libraries or data dictionaries) where available. The use of standard templates enhances the efficiency of the database development process and facilitates subsequent aggregation of the data. The steps in developing a protocol-specific database are illustrated in Figure 15.4.1 (reproduced from Fig. 1 of Madison and Plaunt, 2003). As it can be seen from Figure 15.4.1, once the applicable standard templates are identified, the protocol-specific database can be built by creating the following associated structures of (1) data entry screens,...

The New Trend

Contract research organizations (CROs) may choose to acquire one of the many already established and well-developed proprietary data collection and management systems known as e-clinical software from various vendors in the field as an alternative to developing their own systems in-house. These systems tend to be comprised of integrated components using various technologies that allow flexibility in the methods of data entry, data submission, and data management. They can support paper-based and interactive data collection. Data submission can be done through fax technology or through the Internet. Data management aspects such as error reporting and correction depend on the type of the system and the way it is configured. Some vendors indicate that their products comply with FDA regulations for computerized systems, including 21 CFR Part 11 33 . A CRO might ask the vendor to customize its system to address issues that were not addressed in the vendor's original design. So a great deal...

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