Christine Bredfeldt

Neonatal Outcomes After Antenatal Influenza Immunization During the 2009 H1N1 Influenza Pandemic: Impact on Preterm Birth, Birth Weight, and Small for Gestational Age Birth

During the 2009 influenza A (H1N1) pandemic, infants of H1N1-vaccinated mothers had 38% lower odds of being born preterm, and were 45.0 g heavier, on average, than infants of unvaccinated mothers.

Managing protected health information in distributed research network environments: automated review to facilitate collaboration

BackgroundMulti-site health sciences research is becoming more common, as it enables investigation of rare outcomes and diseases and new healthcare innovations. Multi-site research usually involves the transfer of large amounts of research data between collaborators, which increases the potential for accidental disclosures of protected health information (PHI). Standard protocols for preventing release of PHI are extremely vulnerable to human error, particularly when the shared data sets are large.MethodsTo address this problem, we developed an automated program (SAS macro) to identify possible PHI in research data before it is transferred between research sites. The macro reviews all data in a designated directory to identify suspicious variable names and data patterns. The macro looks for variables that may contain personal identifiers such as medical record numbers and social security numbers. In addition, the macro identifies dates and numbers that may identify people who belong to small groups, who may be identifiable even in the absences of traditional identifiers.ResultsEvaluation of the macro on 100 sample research data sets indicated a recall of 0.98 and precision of 0.81.ConclusionsWhen implemented consistently, the macro has the potential to streamline the PHI review process and significantly reduce accidental PHI disclosures.

Patient reported outcomes for diabetic peripheral neuropathy

OBJECTIVE Multiple patient-reported outcomes (PROs) have been used to assess symptoms among patients with Diabetic Peripheral Neuropathy (DPN). However, there is little consistent application of measures in clinical or research settings. Our goal was to identify and compare patient reported outcome measures (PROs) specifically evaluated in neuropathy populations. METHODS Literature search, summary, and qualitative comparison of PROs validated in neuropathy populations. RESULTS We identified 12 studies of PROs evaluated in neuropathy populations that included DPN patients. Two assessed sleep quality, 5 assessed painful symptoms, and 5 assessed quality of life. The number of items per measure ranged from one to 97, and the number of domains ranged from one to 18. All had adequate internal consistency (Chronbachs Alpha>0.70). There was mild to moderate standardization of domains across measures and only a few instruments used common comparators. The spectrum of DPN symptoms addressed included: sensory symptoms, autonomic symptoms, and function, beliefs, role participation, sleep quality, and perceptions of illness. CONCLUSIONS There remains a need for a gold standard for DPN symptom assessment. Few existing instruments are adequately validated and the domains assessed are inconsistent. Current instrument selection should depend on the clinical and social context of the assessment.

CB4-03: An Eye on the Future: A Review of Data Virtualization Techniques to Improve Research Analytics

Background/Aims Integrating data across systems can be a daunting process. The traditional method of moving data to a common location, mapping fields with different formats and meanings, and performing data cleaning activities to ensure valid and reliable integration across systems can be both expensive and extremely time consuming. As the scope of needed research data increases, the traditional methodology may not be sustainable. Data Virtualization provides an alternative to traditional methods that may reduce the effort required to integrate data across disparate systems. Objective Our goal was to survey new methods in data integration, cloud computing, enterprise data management and virtual data management for opportunities to increase the efficiency of producing VDW and similar data sets. Methods Kaiser Permanente Information Technology (KPIT), in collaboration with the Mid-Atlantic Permanente Research Institute (MAPRI) reviewed methodologies in the burgeoning field of Data Virtualization. We identified potential strengths and weaknesses of new approaches to data integration. For each method, we evaluated its potential application for producing effective research data sets. Results Data Virtualization provides opportunities to reduce the amount of data movement required to integrate data sources on different platforms in order to produce research data sets. Additionally, Data Virtualization also includes methods for managing “fuzzy” matching used to match fields known to have poor reliability such as names, addresses and social security numbers. These methods could improve the efficiency of integrating state and federal data such as patient race, death, and tumors with internal electronic health record data. Discussion The emerging field of Data Virtualization has considerable potential for increasing the efficiency of producing research data sets. An important next step will be to develop a proof of concept project that will help us understand to benefits and drawbacks of these techniques.

Managing personal health information in distributed research network environments

BackgroundStudying rare outcomes, new interventions and diverse populations often requires collaborations across multiple health research partners. However, transferring healthcare research data from one institution to another can increase the risk of data privacy and security breaches.MethodsA working group of multi-site research programmers evaluated the need for tools to support data security and data privacy. The group determined that data privacy support tools should: 1) allow for a range of allowable Protected Health Information (PHI); 2) clearly identify what type of data should be protected under the Health Insurance Portability and Accountability Act (HIPAA); and 3) help analysts identify which protected health information data elements are allowable in a given project and how they should be protected during data transfer. Based on these requirements we developed two performance support tools to support data programmers and site analysts in exchanging research data.ResultsThe first tool, a workplan template, guides the lead programmer through effectively communicating the details of multi-site programming, including how to run the program, what output the program will create, and whether the output is expected to contain protected health information. The second performance support tool is a checklist that site analysts can use to ensure that multi-site program output conforms to expectations and does not contain protected health information beyond what is allowed under the multi-site research agreements.ConclusionsTogether the two tools create a formal multi-site programming workflow designed to reduce the chance of accidental PHI disclosure.

PS1-49: Methods for Integrating Patient-Reported Outcomes Into the Electronic Health Record

Background/Aims Patient-reported outcomes (PROs) provide valuable information to the clinician about the patient’s symptoms and how the patient is responding to treatment. In some cases, electronic or phone-based PROs can reduce the need for office visits. In order to be maximally useful, PROs need to be integrated with electronic health record (EHR) data so providers can evaluate the PRO in the context of a patient’s complete clinical record. In this work we identified methods for integrating PROs into the EHR. We focused primarily on PROs collected through electronic interfaces such as personal health records, email, external websites and standalone apps for smartphones and tablets. Methods We compared the benefits and drawbacks of different methods for integrating PROs into Epic Systems Corporations’ suite of EHR products. Available methods for automatic integration of PROs into the EHR includes the flowsheet and questionnaire extensions to Epic’s MyChart product and HL7 messaging from external applications such as websites or smartphone/tablet apps. Results The questionnaire and flowsheet methodologies within Epic’s MyChart product provide a technically simple way to collect PROs. However, these methods are relatively inflexible in terms of how you can present information to the patient. For example, neither method allows you to present images or drawings that can help patients better express concepts such as where symptoms occur in their body. In contrast, website and smartphone/tablet applications can provide much more flexible patient interface options, but the data can be harder to integrate into the EHR system. Regardless of how PROs are collected, integrating the information into the provider’s workflow remains a challenge. Discussion Multiple methodologies exist for collecting and integrating PROs into the Epic EHR. Major trade-offs include the flexibility of the patient interface and the ease of integrating the data back into the EHR.

PS2-51: Utilization Quality Assurance: Are We Better Yet?

Background The HMORN Virtual Data Warehouse (VDW) Utilization files are used in almost every VDW research project for a range of purposes including selecting study populations, building disease registries, measuring health status, and evaluating resource use and appropriateness of care. Utilization data, including encounter, diagnosis and procedure data, comes from multiple data sources including legacy data, electronic health records, and claims. Because the data come from many sources and require complicated processes of standardization, the VDW tables can be very complex to build, potentially leading to inconsistencies across sites. Our objective was to assess, document, and improve the overall quality, availability, and completeness of the VDW Utilization data. To understand whether our QA approach was effective, we compared the current data quality to quality assurance data collected in 2009. Methods The HMORN Utilization Work Group, together with KP CESR staff, developed quality assurance programs to build summary tables for participating sites. The Utilization Work Group then combined the summary tables from each site and graphically compared utilization rates, diagnosis capture, and other statistics across HMORN sites to provide a more complete picture of the variability across sites and identify potential outliers that may indicate data quality concerns. Results Overall, we found that VDW Utilization data quality has improved considerably since 2009, as demonstrated by the reduction in variability across sites. In particular, rates of hospitalization, inpatient days, and doctor’s office visits are considerably more consistent across time and sites. Residual differences likely reflect real-world variation in membership composition and standards of care. In addition, we identified areas with persistent variability that indicate a need for further exploration, such as rates of dialysis and out-of-office encounters. Finally, we also found between-site differences in the interpretation of the Utilization specification, such as the designation of principal and primary diagnoses. Conclusions Identification and resolution of data quality problems through frequent use of the data, cross-site quality checks, QA programs that produce traffic light (pass/warning/fail) reports, and sites sharing ETL (Extract, Transform, Load) code have considerably improved the data quality of the VDW utilization files.

PS1-17: H1N1 Flu and Pregnancy: The Kaiser Permanente Experience

Background/Aims It is known that seasonal influenza infection disproportionately impacts pregnancy. Based on preliminary information, the pandemic H1N1 virus that first surfaced in spring 2009 appears to cause disproportionate morbidity and mortality among pregnant women - possibly to an even greater degree than that seen from seasonal flu. While it is estimated that over 10% of the pandemic influenza-related deaths in the United States have been in pregnant women-there is little data on the total impact of H1N1 infection upon pregnant women and their developing infants. This study will present a population-based assessment of the impact of H1N1 flu upon pregnancy, maternal, and birth outcomes. Methods This is an open cohort study covering the seasonal (mid 2008–2009) and H1N1 (mid 2009–2010) influenza seasons, with follow-up for pregnancy and infant outcomes up to one month after delivery. All pregnant women in KPNC, KPSC, KPCO, KPMA and KPGA during this period (mid 2008–2010) will be categorized according to their infection status as defined via lab test and/ or ICD-9 code for influenza-like-illness. Descriptive and regression analyses will be conducted to examine neonatal and pregnancy outcomes. Results Due to time constraints in relation to availability of the most recent data within Kaiser Permanente, the final data extraction will not be completed until November 2010. Statistical analyses will be conducted on the following outcomes:: pregnancy (pre-eclampsia, eclampsia, premature labor, premature delivery, pregnancy-induced hypertension; maternal (hospitalization for respiratory-related conditions, other hospitalizations, death); infant (intra-uterine growth retardation; low birth weight, major congenital anomalies); vaccine use and effect (extent to which pregnant women received H1N1 and seasonal flu vaccine; impact of vaccination upon the risk for adverse pregnancy, maternal and infant outcomes); antiviral use and effect (extent to which pregnant women received antiviral medication for H1N1 or seasonal flu, and the impact of these therapeutics upon the risk for adverse pregnancy, maternal and infant outcomes). Conclusions This study will be both analytic and descriptive, showcase the abilities of CESR and inform the scientific and public health communities with a range of unique information related to H1N1 infection during pregnancy within the combined KP populations.Note: Final analyses and results will be presented at the HMORN Conference.

PS2-10: Economic Impact of Electronic Health Information Exchange

Background/Aims More than 40% of outpatient visits involve a transition in care. Effectively coordinating care across providers is critical to reducing healthcare costs and improving patient safety and quality of care. Electronic health information exchange (eHIE) facilitates coordination of care by enabling information transfer across providers and medical clinics. By increasing care coordination, eHIE is expected to reduce healthcare costs resulting from redundant lab tests and radiology studies. In this study, we examine the economic consequences of eHIE in the context of x-ray imaging for bone fractures. Methods We have previously demonstrated that eHIE is associated with a significant reduction in follow-up x-ray imaging for patients with bone fractures of the extremities. This retrospective cohort study of Kaiser Permanente Mid-Atlantic States (KPMAS) members compared the rate of duplicate x-rays in patients with a diagnosis of bone fractures from the Emergency Department (ED) or from outpatient care between 2006 and 2010. Here, we use the Medicare fee schedule to estimate costs for all imaging events, including x-rays, CT scans and MRIs, during the two month period following the initial fracture diagnosis. We estimate total cost by identifying all relevant radiology procedures during the two months following the index event and assigning costs based on published estimates for each procedure. Results The study included 5680 patients from KPMAS with bone fractures diagnoses. 38% of patients were initially seen in the ED, while 62% of patients were seen in outpatient care. The median cost of imaging procedures in the month after diagnosis was

PS2-54: Best Practices: Improving Quality and Reliability in Research Data Sets

30.60. Patients who received diagnosis and follow-up care at facilities that did not have active eHIE cost the healthcare system 1.7 times as much as patients who received diagnosis and follow-up care at institutions that electronically shared radiology data between facilities and providers. Conclusions eHIE reduces healthcare costs related to duplication of diagnostic tests, specifically imaging studies. Next steps will be to evaluate the impact of different eHIE access methods on its effectiveness.