Objective:Harmonized data quality (DQ) assessment terms, methods, and reporting practices can establish a common understanding of the strengths and limitations of electronic health record (EHR) data for operational analytics, quality improvement, and research. Existing published DQ terms were harmonized to a comprehensive unified terminology with definitions and examples and organized into a conceptual framework to support a common approach to defining whether EHR data is ‘fit’ for specific uses.Materials and Methods:DQ publications, informatics and analytics experts, managers of established DQ programs, and operational manuals from several mature EHR-based research networks were reviewed to identify potential DQ terms and categories. Two face-to-face stakeholder meetings were used to vet an initial set of DQ terms and definitions that were grouped into an overall conceptual framework. Feedback received from data producers and users was used to construct a draft set of harmonized DQ terms and categories. Multiple rounds of iterative refinement resulted in a set of terms and organizing framework consisting of DQ categories, subcategories, terms, definitions, and examples. The harmonized terminology and logical framework’s inclusiveness was evaluated against ten published DQ terminologies.Results:Existing DQ terms were harmonized and organized into a framework by defining three DQ categories: (1) Conformance (2) Completeness and (3) Plausibility and two DQ assessment contexts: (1) Verification and (2) Validation. Conformance and Plausibility categories were further divided into subcategories. Each category and subcategory was defined with respect to whether the data may be verified with organizational data, or validated against an accepted gold standard, depending on proposed context and uses. The coverage of the harmonized DQ terminology was validated by successfully aligning to multiple published DQ terminologies.Discussion:Existing DQ concepts, community input, and expert review informed the development of a distinct set of terms, organized into categories and subcategories. The resulting DQ terms successfully encompassed a wide range of disparate DQ terminologies. Operational definitions were developed to provide guidance for implementing DQ assessment procedures. The resulting structure is an inclusive DQ framework for standardizing DQ assessment and reporting. While our analysis focused on the DQ issues often found in EHR data, the new terminology may be applicable to a wide range of electronic health data such as administrative, research, and patient-reported data.Conclusion:A consistent, common DQ terminology, organized into a logical framework, is an initial step in enabling data owners and users, patients, and policy makers to evaluate and communicate data quality findings in a well-defined manner with a shared vocabulary. Future work will leverage the framework and terminology to develop reusable data quality assessment and reporting methods.

The provision of patient-centered care requires a health care environment that fosters engagement between patients and their health care team. One way to encourage patient-centered care is to incorporate patient-reported outcomes into clinical settings. Collecting these outcomes in routine care ensures that important information only the patient can provide is captured. This provides insights into patients' experiences of symptoms, quality of life, and functioning; values and preferences; and goals for health care. Previously embraced in the research realm, patient-reported outcomes have started to play a role in successful shared decision making, which can enhance the safe and effective delivery of health care. We examine the opportunities for using patient-reported outcomes to enhance care delivery and outcomes as health care information needs and technology platforms change. We highlight emerging practices in which patient-reported outcomes provide value to patients and clinicians and improve care delivery. Finally, we examine present and future challenges to maximizing the use of patient-reported outcomes in the clinic.

Background:Web-based collection of patient-reported outcome measures (PROMs) in clinical practice is expanding rapidly as electronic health records include web portals for patients to report standardized assessments of their symptoms. As the value of PROMs in patient care expands, a framework to guide the implementation planning, collection, and use of PROs to serve multiple goals and stakeholders is needed.Methods:We identified diverse clinical, quality, and research settings where PROMs have been successfully integrated into care and routinely collected and analyzed drivers of successful implementation. Findings are based on key informant interviews with 46 individuals representing 38 organizations, of whom 40 participated in a webinars series, and 25 attended an in-person workshop designed to enable broad stakeholder input, review and refinement of the proposed PROMs implementation model. Stakeholders identified differing uses of PROMs to support: 1) individual patient care decisions, 2) quality improvement initiatives, 3) payer mandates, and 4) population health and research.Results:The implementation framework and steps that are consistently identified by stakeholders as best practices to guide PROM capture and use are described. Of note, participants indicate that web-based informatics tools are necessary but not sufficient for PROM use, suggesting that successful PROM implementation requires integration into clinic operations and careful planning for user’s analytic needs. Each of the four identified uses may require implementation modifications at each step to assure optimal use.Conclusions:The proposed framework will guide future PROM implementation efforts across learning health care systems to assure that complete PROMs are captured at the correct time, and with associated risk factors, to generate meaningful information to serve diverse stakeholders.

This manuscript presents an initial description of doctoral level core competencies for health services research (HSR). The competencies were developed by a review of the literature, text analysis of institutional accreditation self-studies submitted to the Council on Education for Public Health, and a consensus conference of HSR educators from US educational institutions. The competencies are described in broad terms which reflect the unique expertise, interests, and preferred learning methods of academic HSR programs. This initial set of core competencies is published to generate further dialogue within and outside of the US about the most important learning objectives and methods for HSR training and to clarify the unique skills of HSR training program graduates.

Based on a national survey of 2,014 randomly selected public and private firms with three or more workers, this paper reports changes in employer-based health insurance from spring 2001 to spring 2002. The cost of health insurance rose 12.7 percent, the highest rate of growth since 1990. Employee contributions for health insurance rose in 2002, from $30 to $38 for single coverage and from $150 to $174 for family coverage. Deductibles and copayments rose also, and employers adopted formularies and three-tier cost-sharing formulas to control prescription drug expenses. PPO and HMO enrollment rose, while the percentage of small employers offering health benefits fell. Because increasing claims expenses rather than the underwriting cycle are the major driver of rising premiums, double-digit growth appears likely to continue.