The target hospitals for this study are the three Bethesda hospitals. In order to accomplish this work, we will first develop a system to securely manage communication between the target hospitals and a consortium of Pharmacy Benefit Managers (PBMs) who carry the prescription dispensing records of interest. Under appropriate confidentiality agreements and security protection, this system will request the medication profile for patients entering care at the target hospitals from this consortium to assist patient care. The need for information about medication is especially pressing during disasters, when patients are cared for by unfamiliar providers who do not have adequate time to spend with each patient. This study was motivated by the need to obtain a medication history during disasters, without needing much personnel time. Our hypothesis is that when a patient has medication information in the PBM consortiums databases, that information will provide a better medication history obtained from that source more complete and more precise than the corresponding information collected manually from the patient. The value of such data for a population will depend upon the proportion of patients in the population who have medication information within the consortium database. The PBM consortium will have no information about patients without insurance and those with insurance that is not processed by the PBM consortium. We will set a binary variable to identify patients who had no data in the PBM consortium and will collect demographic, administrative variables (arrival mode), and insurance class on all patients. Then we will model the existence of PBM consortium data on these attributes. We will use this model to predict the proportion of patients with data in the PBM based on the above mentioned PBMs and to assess policies that might eliminate this gap. The drug history collected automatically by the PBM, the one collected manually by the hospitals, the patient demographics and other patient characteristics will be linked and then de-identified. The research will be performed only on the de-identified databases. The research will only involve data that is collected for routine care purposes, and there will be no intervention. During FY2009, we used HL7 messages from the Suburban Emergency Department registrations to obtain the patients prescriptions-filled history from SureScripts/RxHub. All of the data was de-identified at Suburban Hospital before delivery to the research team at NLM. We made most of the comparisons between the two sources of medication history (PBM consortium versus direct collection from the patient) via computer methods. To prepare for the comparison, we have mapped the information from the PBMs to a standard list of drug names derived from Rx.Norm. The drug information taken directly from the patient (or their family) came from the hospitals as free text. The free text drug names were mapped to the same list of standard drug names using a combination of text matching and manual inspection. In the hospital history encountered classes, e.g. sulfa med, water pill, or blood pressure med, instead of drug names in some cases, and classified them as such. We are in the process of comparing the two information sources with regard to the completeness, degree of overlap, and nature of discrepancies. Among patients with medications data from both SureScripts and the Suburban ED medication history, we counted individual medication matches by patient. After excluding all SureScripts medications which may have run out (based on dispensing data), more than 30% of the individual medications from SureScripts were not captured in the Suburban EDs medications history. On the other hand, 62% of the medications in the ED medications history were not included in the SureScripts data set. We also analyzed overlaps and gaps if we extended the time window to include medications prescribed within 3 months of the ED encounter: 50% of the SureScripts medications were not reported by the patients and 50% of the patient-reported medications were not in the SureScripts database. Neither source is complete, but SureScripts adds a lot of information to the medication histories collected by Suburban Hospital ED personnel. We have further work and analyses to do regarding the differences identified. Emergency Department providers are now getting the hardy copy summary of the SureScripts data, as needed for routine care and disaster preparedness.
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