Assessing social and behavioral data in electronic health records: Availability, Accuracy, and Applicability

Problem statement: There is an increased appreciation of the importance of social and behavioral determinants of health (SBDH) on health outcomes, but no standards for collecting this information in various clinical data sources. The increased use of electronic health records (EHRs) provides a unique opportunity to understand SBDH and its impact on health. This dissertation aims to understand perspectives of, and assess trends in SBDH data collection, and compare rates of SBDH ICD10 code documentation in an EHR and insurance claims. Method: A qualitative study was undertaken to understand the facilitators and barriers to accessing SBDH information in an EHR. Using data from 2017, a cross-sectional retrospective data analysis was performed in an EHR’s social history table. Logistic regressions were used to calculate odds ratios to identify factors associated with completion rates. The documentation of behavior related ICD10 codes within a linked EHR, and insurance claims was compared with information in the social history section of the EHR. Results: Providers and researchers felt that SBDH data captured in the EHR was inconsistent and unreliable. Health systems should prioritize capturing some SBDH in a consistent manner, but it is unclear which variables to select. Individuals who are black, female, and between the ages of 30-65 are more likely to have their behavior documented in the social history section. With the move to ICD10, a wider range of SBDH information can be coded in a patient’s EHR and claims record. At this study site, the overlap of codes across these two data systems is limited and thus a fuller picture of the patient’s situation can be obtained by merging both sources. Conclusion: It appears that SBDH data collection is not consistent at this site. To improve this, clearer guidelines on how to capture SBDH risk factors are needed. Since there is no widely accepted “gold standard”, information in the EHR and insurance claims vary, which makes it more challenging to effectively understand SBDH factors in order to assess and enhance health outcomes. Improving data collection and data reliability will allow providers and researchers alike to utilize digital data for both patient care and population health

A State-wide Health IT Infrastructure for Population Health: Building a Community-wide Electronic Platform for Maryland’s All-Payer Global Budget

Maryland Department of Health (MDH) has been preparing for alignment of its population health initiatives with Maryland’s unique All-Payer hospital global budget program. In order to operationalize population health initiatives, it is required to identify a starter set of measures addressing community level health interventions and to collect interoperable data for those measures. The broad adoption of electronic health records (EHRs) with ongoing data collection on almost all patients in the state, combined with hospital participation in health information exchange (HIE) initiatives, provides an unprecedented opportunity for near real-time assessment of the health of the communities. MDH’s EHR-based monitoring complements, and perhaps replaces, ad-hoc assessments based on limited surveys, billing, and other administrative data. This article explores the potential expansion of health IT capacity as a method to improve population health across Maryland.First, we propose a progression plan for four selected community-wide population health measures: body mass index, blood pressure, smoking status, and falls-related injuries. We then present an assessment of the current and near real-time availability of digital data in Maryland including the geographic granularity on which each measure can be assessed statewide. Finally, we provide general recommendations to improve interoperable data collection for selected measures over time via the Maryland HIE. This paper is intended to serve as a high- level guiding framework for communities across the US that are undergoing healthcare transformation toward integrated models of care using universal interoperable EHRs

A State-wide Health IT Infrastructure for Population Health: Building a Community-wide Electronic Platform for Maryland’s All-Payer Global Budget

Maryland Department of Health (MDH) has been preparing for alignment of its population health initiatives with Maryland’s unique All-Payer hospital global budget program. In order to operationalize population health initiatives, it is required to identify a starter set of measures addressing community level health interventions and to collect interoperable data for those measures. The broad adoption of electronic health records (EHRs) with ongoing data collection on almost all patients in the state, combined with hospital participation in health information exchange (HIE) initiatives, provides an unprecedented opportunity for near real-time assessment of the health of the communities. MDH’s EHR-based monitoring complements, and perhaps replaces, ad-hoc assessments based on limited surveys, billing, and other administrative data. This article explores the potential expansion of health IT capacity as a method to improve population health across Maryland.First, we propose a progression plan for four selected community-wide population health measures: body mass index, blood pressure, smoking status, and falls-related injuries. We then present an assessment of the current and near real-time availability of digital data in Maryland including the geographic granularity on which each measure can be assessed statewide. Finally, we provide general recommendations to improve interoperable data collection for selected measures over time via the Maryland HIE. This paper is intended to serve as a high- level guiding framework for communities across the US that are undergoing healthcare transformation toward integrated models of care using universal interoperable EHRs