Magazine article Behavioral Healthcare Executive

EMRs AND DATABASE STRUCTURES

Magazine article Behavioral Healthcare Executive

EMRs AND DATABASE STRUCTURES

Article excerpt

Behavioral healthcare providers at all types are implementing electronic medical records (EMRs). justifiably, much attention is being paid to issue's of client/patient privacy, clinician work How, and the EMR's impact on resources and procedures. A sometimes underemphasized element of EMR implementation is content design-how to capture and manage information. To he successtul in their EMR deployments, organizations must devote adequate time and resources to designing an EMR that exploits the underlying database to advance the organizations goals, embody its culture, and execute its policies.

Clinical care, business and efficiency goals, and policy considerations should he reflected in the structure of information (tables and types of fields within tallies) and the How of inlorimtion through the database structure to the outputs (e.g., reports). Questions and implications associated with EMR data management fall into a number of categories:

Specialized Versus Integrated

Questions. Concerning the overall database structure, should you create separate assessments, treatment plans, and progress notes (e.g., by discipline or level ol care), or create multidisciplinary forms used across the spectrum of care? Is the clinical culture best represented by a documentation process focused on specialised roles or one that emphasizes collaboration? Does the assessment and treatment information belong to the individual clinician or to the patient?

Implications. EMRs either can support or challenge staffs professional idemiiy and program loyalties. It is important to consider the above questions in the content design process. The use of several forms for a clinical operation, lor example, may result in data duplication with the risk of data discrepancies. The database's structure (specialized versus integrated) aJso affects the user's ease m navigating the EMR, as well as data flow. The flow ot information from data entry 10 reports and decision support tools is a major benefit ot databases and should be a priority during content design.

Standardized Versus Individualized

Questions. At the level of discrete data fields, when is it best to use "dictionary" data-type formats with standardized choices, and when are free-text narrative formats better? Is there essentially identical information in different components that can be formatted in the same way (e.g., scales for assessing risk or formats for capturing family history)? What might we want to learn about what we do?

Implications. Dictionary data types ensure data consistency. In addition, dictionary formats make intormation available for aggregated reporting, while free-text data are difficult to aggregate. therefore. data-type decisions impact the capacity to aggregate content across programs and populations for efficient report production and more robust analysis. Reducing the number of Formats simplifies software development, the creation of user documentation, and staff training.

Focused Versus Comprehensive

Questions. With the entire dataset's scope in mind, how do you decide which data to include and where to draw the line? Must you include an individual item lor corporate-compliance with your clinical care mission? Do you want to include a data element because it is useful for outcome reporting or because a specialty team wants to include it? Should you use extensive standardized information, or develop a set of required screening questions with optional narrative details as needed?

Implications. It is easy for an EMR design team to have enthusiasm for capturing data while losing sight of the burdens of data gathering being created for line stall. …

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