One of the changes in the next Medidata Rave release, Rave 2018.1.0, is that standard fields in Edit Checks must have a Record Position of 0. This has long been a recommended best practice but up till now has not been required. Rave will now check that the Record Position is correct when saving an edit check in Architect, when uploading an Architect Loader spreadsheet and when publishing a Draft. If you try to publish a Draft with invalid Record Positions you'll see this error message:

There is a good reason for enforcing this rule - it means that there will be no confusion between standard fields and log fields when executing the Edit Check. But if you have existing studies or libraries it may take hours of work for each Draft to locate and update Edit Checks. Unless you're using TrialGrid!

TrialGrid's Diagnostic 0027 analyses all Edit Checks and Derivations, quickly showing you which ones need to be updated:

and then updating them is as simple as clicking the 'Fix' button. In minutes you can have reviewed and corrected them all!

Diagnostic 0027 is one of the 79 Diagnostics available now to all existing TrialGrid users. We have Diagnostics to help with other upcoming changes in Rave 2018.1.0 and with upgrading to RaveX. As and when Medidata introduce new features and enhancements in Rave Architect, we ensure that TrialGrid is up to date and compatible with the latest changes, and look for ways we can help with upgrades.

Contact us if you would like a demo or to know more.

If you haven't heard of Unicode you have certainly seen it. You are seeing it now since Unicode is the standard for the encoding of characters viewable in Web Browsers and on computers in general. As of this writing, version 10 of the standard includes more then 136,000 characters from multiple writing systems and Medidata Rave supports the Unicode standard both for study designs and for data collection. So what is the problem?

Actually, there is no problem so long as you know what characters from the Unicode standard are being used in your study, where they are and how they display and appear in outputs.

Unicode in Study Design

If you are building your study in Japanese or localizing it to Russian, Armenian or Greek then having the full set of Unicode characters to use is vital. For studies in English you may want to stick to the set of 128 characters known as ASCII (a-Z, 0-9 and symbols). But sometimes you can be surprised by characters that aren՚t what you think they are…

Did you spot those alternative characters hiding in the last sentence?

characters that aren՚t what you think they are…

vs:

characters that aren't what you think they are...

Still can't see it? Hint: It's the ՚ and the … The differences are (or at least, may be) subtle on the screen but when we render them in a Rave PDF they appear quite different:

It is very hard for the human eye to distinguish between these characters the way they are rendered in Browsers but they are different characters and the font that Rave uses to display characters won't have a way to render all 135,000 possible characters so it is best (in English studies at least) to stick to characters that appear in the limited ASCII set of characters that all fonts cover well.

Be especially wary of text that is cut and pasted from web pages, Word and Excel or from PDF documents. It is very tempting to copy verbatim from a Protocol document but word processors use all kinds of character variants to make writing look better on the screen or in print. You can't even trust the spaces in these documents because Unicode defines at least 20 different "empty" space characters of different widths including one that has no width at all (i.e. it is invisible!)

Tip: TrialGrid Diagnostic 70 will identify and highlight non-ASCII characters, even invisible ones

Unicode in Study Data

If unexpected characters in study design can cause strange PDF outputs, unexpected or unwanted characters in the clinical data can be real poison. A study that collects data in the English language might expect that all the text data in the study is in ASCII. However, Rave will accept data input to text fields of any Unicode character so the same problems of cut & pasted content can occur. Rave is 100% Unicode compatible so it will happily take, store and output any Unicode content but SAS and other analysis programs may have to be set to accept non-ASCII content.

In English studies you want to identify non-ASCII content at the point of entry. This can only be done with a Custom Function that looks at the content of a text field and determines if any of the characters are outside the ASCII range. A quick search of the web will throw up simple code which will return true if it finds a non-ASCII character in the input string:

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    //Take string from datapoint.Data or datapoint.StandardValue
    string s = "characters that aren՚t what you think they are…";  

    foreach (char c in s)
    { 
        if (((int)c) > 127) 
        { 
            return true; 
        } 
    } 
    return false;

Tip: TrialGrid contains a CQL extension that makes this as easy as using FieldName.IsNotAscii in an Edit Check.

Summary

Rave handles Unicode really well and web browsers are very good at displaying a wide range of Unicode characters but not all characters can be displayed by all systems so be careful what you put into your study design and what you collect in your study data. Being able to cut and paste text between systems is great for productivity but can have unintended consequences.

One of the main functions of TrialGrid is to identify issues in a Medidata Rave study build before it goes to production since corrective migrations are time consuming and costly to manage. TrialGrid Diagnostics automate best practice guidelines to provide assurance that these guidelines have been considered and applied where applicable. But beyond ensuring a minimum level of quality, Diagnostics can also help a Study Team determine if their edit check coverage is adequate.

A recent Diagnostic we developed, 0068 : Date Fields should have at least one Edit Check that creates a query examines the study design looking for Date Fields on Forms which do not have any associated Edit Checks which would raise a query on that Field. This is an indicator that this Field is not being compared to other dates in the study and that an additional Edit Check might be a good idea. For example, if a date of a test does not have an Edit Check that compares it to another date then any date would be valid which is not intended.

Performing this kind of check manually is certainly possible but it is time-consuming and error prone. The easiest way, besides using TrialGrid or writing your own tooling to perform this check, is to:

1. Download the Architect Loader Spreadsheet
2. Filter the DataFormat column to only DataFormats containing "y" (a year component). Date/Time fields in Rave can be used to collect just a time component so we want only those dates that actually capture a year.
3. Filter the Field list to just Visible and Active Fields since checking on inactive or invisible Field isn't really meaningful.
4. Check that Fields are not present on Inactive Forms. A review of the Forms sheet of the spreadsheet can help us determine that.
5. Filter the CheckActions sheet of the spreadsheet looking for the VariableOID of our candidate Fields
6. Filter the CheckActions for just the OpenQuery check action.
7. Check that the Edit Check is active by review the Active column in the Checks worksheet
8. Review the Derivations sheet to ensure that this Field is not being derived. It makes no sense to raise a query on a derived date Field.

The list of Fields you are left with are all candidates for additional edit checks.

The steps to perform this check manually are not complicated but they do require switching between different worksheets of the spreadsheet. It's time-consuming work and not very rewarding for the Study Builder so organizations may choose to take a risk-based approach and perform this level of check only infrequently.

Alternatively you can eliminate the risk and the drudgery by using TrialGrid to automate these kinds of quality and conformance checks for your Study Builders and free them up to do more valuable work.