Data Dictionary and E-Discovery

Section2.1 Utilize – Implement

Section 2.1 Utilize – Implement – Data Dictionary and e-Discovery -1

Data Dictionary and e-Discovery

Understand the importance of the data dictionary—both for using the system as well as part of the e-discovery process in a potential legal action. Some health care organizations are able to maintain the data dictionary themselves.Even if your organization does not have the ability to maintain its own data dictionary, understand the complexity and level of detail involved in its maintenance. This will help you appreciate why the vendor may be reluctant to make certain changes or why a change is costly to make.

Data Dictionary Maintenance

Data dictionary maintenance is a painstaking, critical process. Maintenance is best left to one person in an organization to ensure consistency. Changes should be determined and approved by the stakeholders who will be impacted by them to prevent confusion and data errors. For example, if you have a computerized physician order entry (CPOE) system which uses a set of data elements to describe orders for patient monitoring, with the choices of routine monitoring, heightened monitoring, and intensive monitoring, all providers and nurses would understand what these terms mean and how to use them. Adding regular monitoring in addition to routine monitoring in the data dictionarywould cause confusion.

The following tool lists the standard attributes for a data element in a data dictionary and provides change management tracking for system maintenance (noted by ). In the example in italics, this data element is set for recording whether or not someone is a tobacco user and the number of packs of cigarettes smokedper day. Reporting in the tobacco use field is mandatory, with the default set at 0for the number of packs smoked and an option to enter a number of packs smoked per day. This is a mandatory field because this data element feeds a health maintenance rule. In order for the rule to fire correctly, it needs to know whether the patient is a tobacco user or not. Anything other than 0 in the valid values will cause the rule trigger.If the patient is a pipe smoker or chewed tobacco, this value would be left at 0 and the provider would invoke the “See Other Tobacco” rule. This new data element might be only a comment field for describing other forms of tobacco use.

Attributes / Attribute Example /  Requested by /  Approved by /  Performed by /  Tested by /  Implement Date
Name / Current tobacco use
Table / Social history
DB Name / TOBUSE
Synonyms / Smoker
Definition / Currently smokes tobacco every day
Reference / AHRQ Guideline
Source / EHR
Derivations / N/A
Valid Values / NN.NN (packs of cigarettes per day) or See Other Tobacco
Conditionality / Mandatory
Default / 0
Lexicon / SNOMED
Relationship / HXSMKG
Access restrictions / None
Process Rule / Health maintenance: smoking cessation
Derivations / N/A

e-Discovery

Realize that the nature of the attributes can have an impact on subsequent legal action. E-discovery refers to any process in which electronic data is sought, located, secured, and searched with the intent of using it as evidence in a civil or criminal legal case. This electronic data may includemetadata, audit trails, access logs, information system activity logs, etc. Amendments to the Federal Rules of Civil Procedure have already been adopted to codify the purpose and process of e-discovery. Several states have had or are enacting similar rules.

Let’s use the tobacco use data element as an example for e-discovery. While thismay seem far-fetched,similar examples are occurring in legal practicetoday. If the tobacco use data element was made optional, it could either not have a rule associated with it or the rule would only fire when data are present—potentially missing many patients who may use tobacco but the organization failed to ask about it or record the information. If a patient is diagnosed later with lung cancer and the patient or family sues the organization for not providing smoking cessation guidance or counseling, the organization may be called upon during the discovery phase of the litigation process to produce the systems in place that might have led to smoking cessation. Many attorneys are now recognizing that health care organizations that have electronic health records (EHR) or other health information technology (HIT) systems are likely to have clinical decision support (CDS), and can draw upon that in a legal case. Some organizations have considered not including CDS in the belief that it might reduce their liability. Given that CDS is a capability in EHR and other HIT products today, andCDS is described in the HL7 EHR-System Functional Description standard, not using CDS may ultimately put the organization at as much, if not more, risk.

For support using the toolkit

Stratis Health Health Information Technology Services

952-854-3306 

Section 2.1 Utilize – Implement – Data Dictionary and e-Discovery - 1