Section 2.1 Utilize Implement Data Dictionary and E-Discovery - 1

Section 2.1 Utilize – Implement 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 dictionary would 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 smoked per day. Reporting in the tobacco use field is mandatory, with the default set at 0 for 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 to 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 Approved Performed Tested Implement by by by by Date Name Current tobacco use

Table Social history

DB Name TOBUSE

Synonyms Smoker

Definition Currently smokes tobacco every day Reference AHRQ Guideline

Section 2.1 Utilize – Implement – Data Dictionary and e-Discovery - 1 △ △ △ △ △ Attributes Attribute Example Requested Approved Performed Tested Implement by by by by Date 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 None restrictions 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 include metadata, 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 this may seem far-fetched, similar examples are occurring in legal practice today. 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, and CDS 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  [email protected] www.stratishealth.org

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