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Common Framework for Networked Personal Health Information: Technology Overview Appendix A: Data Flow Scenarios The following scenarios are designed to illustrate electronic data streams for the most common transaction in health care: a drug prescription. The first scenario describes a common and simplified set of transactions stemming from a small clinical practice. The second scenario adds sophistication and complexity, depicting transactions that are less common today (although they may become more common in the emerging electronic environment). The additional transactions increase potential value for many stakeholders, including the consumer, but also heighten the risk to privacy and security due to multiple round trips across data sources and copies being held by an increasing array of parties. Note: The numeric sequence of “copies” below is designed to help the reader understand the parties that create and receive information related to a prescription transaction. A real-world chronology would be different than the sequence reflected here, as some transactions are batched with longer lag times than others. Scenario 1 (SIMPLE) Radhika Parekjhi, MD, works for a small practice that does not have an electronic health record (EHR) or e-prescribing application. The practice does, however, utilize practice management software for electronic claims submittal. Steve Jones, a pharmacist with ACME Pharmacy Chain, performs his work using a pharmacy information system that includes e-prescribing functionality. • In follow-up to receiving abnormal blood test results at a health fair, Millie Robin makes an appointment to see Dr. Radhika Parekjhi. • At the appointment, Dr. Parekjhi reviews Millie’s current health status and health history (including her abnormal lab results), performs an exam, and orders additional tests. Based on this information, Dr. Parekjhi diagnoses a medical condition and decides to prescribe a new medication. (Millie’s doctor’s office stores this information, copy I-1, in the paper chart for Millie at the practice. The “I” designates a copy that includes “identifiable” data.) Source of Data Personal Data Transferred Transfer Reason Transaction Detail (Source --> Recipient) Recipient Copy # What Other Personal Data May the Recipient Have? Millie (patient) • Demographic/Contact • Insurance • Employment • Provider seen/referred • Biometric data (e.g., blood pressure) • Diagnoses/Problem list • Procedures • Medications • Allergies • Immunizations • Hospitalization history • Laboratory results • Other health history (e.g., family history of heart disease) • Lifestyle history (e.g., smoker) • Social history (e.g., married) Information provided by Millie in the context of her appt. w/ Dr. Parekjhi Millie --> Patient Registration (Paper chart) Millie --> Dr. Parekjhi and staff (Paper chart) I-1 (paper) • Visit history • Doctor progress notes • Other information specific to care received at this practice 4 Connecting for Health Common Framework | www.connectingforhealth.org | June 2008
Common Framework for Networked Personal Health Information: Technology Overview • After reviewing Millie’s current medications, problem list, and medication allergies, Dr. Parekjhi finds no contraindications or interactions and decides to prescribe medication “X” to treat Millie’s newly diagnosed medical condition. • Dr. Parekjhi writes a paper prescription for medication “X” and hands it to Millie. • Dr. Parekjhi completes documentation for Millie’s encounter, and the following day a coder employed by the practice electronically submits a claim to Millie’s Health Plan (Payer) for payment. This information includes Millie’s diagnosis, procedural and other personal health information. 1 o A Claims Clearinghouse entity receives the claim, processes it, and sends it to Millie’s Payer in the Payer’s required format. (Clearinghouse stores copy I-2.) Source of Data Personal Data Transferred Transfer Reason Transaction Detail (Source --> Recipient) Recipient Copy # What Other Personal Data May the Recipient Have? Doctor office paper chart • Demographic/Contact • Insurance • Health claim type (e.g., Workman's Comp) • Prescriber ID (e.g., DEA#) • Employment • Diagnoses • Procedures (including the CPT code that contains the prescribed medication) Health claim submitted to Payer Doctor’s office --> Claims Clearninghouse I-2 Other claims submitted to same Clearinghouse o The Clearinghouse sells aggregated de-identified data to research companies as part of its revenue model. (A Health Care Market Research Company stores de-identified copy DI-1. “DI” stands for data that has been “de-identified”.) Source of Data Personal Data Transferred Transfer Reason Transaction Detail (Source --> Recipient) Recipient Copy # What Other Personal Data May the Recipient Have? Clearinghouse De-identified data Generate revenue Claims Clearninghouse -> Health Care Market Research Company DI-1 n/a 1 Example of a Payer claim form: https://www.lifewisewa. com/lwwa/groups/public/documents/pdfs/002636.pdf. 5 Connecting for Health Common Framework | www.connectingforhealth.org | June 2008
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