The validation rules

The DB(B)C FZ validation rule set is the last product that guides the DB(B)C registration and specification for the forensic care sector. The rule set contains technical rules which define low level limitations that ensure the technical quality of the registration. It contains business rules which assess the registration quality based on in-depth business knowledge.

Like the registration model and the code lists the validation rules are an internal data acquisition and management capability as it is used in setting up the validation of the DGAAO data. The product is also tailored as deliverable capability package for forensic care institutes. In this form the product and the supporting documentation offer a common language and implementation guidance towards forensic care institutes and their software suppliers.

In line with the registration model and the code lists the identified performance areas and example measures are:

Funding

The funding of the DB(B)CFZ BICC consists of a yearly forecasted project budget for all BICC tasks and products. Therefore the funding performance area is project funding.

The identified performance measure for project funding in relation to the validation rule development is total cost spent on hiring personnel because this is the main cost driver.

Economy

The transition from funding to input is limited to hiring the personnel which is needed for the development and organizational alignment of the validation rules. Because all members of the DB(B)C FZ BICC are hired externally the identified performance area is vendor management on external personnel.

The identified performance measure for vendor management on external personnel is rate per discipline.

Input

Like the code lists the input for the development of the validation rules is limited to personnel and internal capabilities. The hired team members come with sufficient

knowledge, required tooling and hardware for their role. Therefore no additional (external) input is required. The internal capability which is used as input basis for the validation rules is a previous version of the validation rules.

The identified personnel performance measures are:

 Hours spent on (project) management for coordination and alignment within forensic sector

 Hours spent on account management for internal knowledge transfer and external business alignment

 Hours spent on development for translating requirements into a validation rules and supporting SQL code

 The identified performance measure for the internal capability is the existence of a previous version of the code lists (yes / no)

Efficiency

The efficiency of transforming input means into new validation rules and documentation updates is mainly affected by the nature of the updates and the underlying requirements. The nature characteristics like number of changes and complexity of the changes determine how much time is needed. The characteristics of the requirements determine the potential need for rework and extra time needed on clarifying the requirements.

The identified performance measures for the demand performance area are:

 The total numbers of changes which the validation rule update cycle contains  The complexity of these updates; each update is identified as simple, medium or

complex

 The stability of the requirements is measured by the number of requirement changes during the update cycle

 The timeliness of requirements is measured by the number of additional requirements which arise after the development is started

 The quality of the requirements is measured by the number of requirement alignment sessions that are needed during implementation and the number of revision cycles which are needed before a new version of the validation rules is completed

Output

As described earlier the output of the validation rule update process is a new revision of the validation rules with the related documentation and support. These validation rules are used as an internal capability for the validation of the data which is uploaded towards the DGAAO and it is shipped as deliverable capability package towards the forensic care organization and their software suppliers for the development of registration systems

The identified performance measures for the internal capability and the deliverable capability package are:

 The total number versions of the validation rules which are developed over time  The size (number of pages) of the supporting usage guidance and documentation

products.

Effectiveness

Like the code lists and the registration model the effectiveness of the validation rules is mainly influenced by the product adoption rate of the forensic care organizations. Product characteristics like usability and support are indirect performance areas which influence the adoption (use) rate of the forensic care organizations.

The indentified performance measures for the product performance area are:  The usage of the product is measured by the number of organizations which

implemented the latest version of the validation rules

 The user satisfaction is measured with a survey which assesses the products score on timeliness, usability and quality

 The support effectiveness is measured by the number of support calls and account management questions

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Effect

The identified performance measure in the political effect performance area is the number of forensic care organizations which have implemented the validation rules in their registration software. This indicates the percentages of forensic care organizations which are aligned to the somatic care DBC registration approach.

The identified performance measure in the productivity enhancement performance area is the number of DB(B)C’s which are registered according to the latest version of the validation rules. Each DB(B)C that is registered according to the new validation rules enhances transparency as it is available for comparisons and analytical research.