Dataset Information

The population health record: concepts, definition, design, and implementation.

ABSTRACT: In 1997, the American Medical Informatics Association proposed a US information strategy that included a population health record (PopHR). Despite subsequent progress on the conceptualization, development, and implementation of electronic health records and personal health records, minimal progress has occurred on the PopHR. Adapting International Organization for Standarization electronic health records standards, we define the PopHR as a repository of statistics, measures, and indicators regarding the state of and influences on the health of a defined population, in computer processable form, stored and transmitted securely, and accessible by multiple authorized users. The PopHR is based upon an explicit population health framework and a standardized logical information model. PopHR purpose and uses, content and content sources, functionalities, business objectives, information architecture, and system architecture are described. Barriers to implementation and enabling factors and a three-stage implementation strategy are delineated.

SUBMITTER: Friedman DJ

PROVIDER: S-EPMC2995645 | biostudies-literature | 2010 Jul-Aug

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

The population health record: concepts, definition, design, and implementation.

Friedman Daniel J DJ Parrish R Gibson RG

Journal of the American Medical Informatics Association : JAMIA 20100701 4

In 1997, the American Medical Informatics Association proposed a US information strategy that included a population health record (PopHR). Despite subsequent progress on the conceptualization, development, and implementation of electronic health records and personal health records, minimal progress has occurred on the PopHR. Adapting International Organization for Standarization electronic health records standards, we define the PopHR as a repository of statistics, measures, and indicators regar ...[more]

PMID: 20595299

Similar Datasets

Project description:ObjectiveCommon data elements (CDEs) are standardized questions and answer choices that allow aggregation, analysis, and comparison of observations from multiple sources. Clinical CDEs are foundational for learning health care systems, a data-driven approach to health care focused on continuous improvement of outcomes. We aimed to create clinical CDEs for pediatric epilepsy.MethodsA multiple stakeholder group (clinicians, researchers, parents, caregivers, advocates, and electronic health record [EHR] vendors) developed clinical CDEs for routine care of children with epilepsy. Initial drafts drew from clinical epilepsy note templates, CDEs created for clinical research, items in existing registries, consensus documents and guidelines, quality metrics, and outcomes needed for demonstration projects. The CDEs were refined through discussion and field testing. We describe the development process, rationale for CDE selection, findings from piloting, and the CDEs themselves. We also describe early implementation, including experience with EHR systems and compatibility with the International League Against Epilepsy classification of seizure types.ResultsCommon data elements were drafted in August 2017 and finalized in January 2020. Prioritized outcomes included seizure control, seizure freedom, American Academy of Neurology quality measures, presence of common comorbidities, and quality of life. The CDEs were piloted at 224 visits at 10 centers. The final CDEs included 36 questions in nine sections (number of questions): diagnosis (1), seizure frequency (9), quality of life (2), epilepsy history (6), etiology (8), comorbidities (2), treatment (2), process measures (5), and longitudinal history notes (1). Seizures are categorized as generalized tonic-clonic (regardless of onset), motor, nonmotor, and epileptic spasms. Focality is collected as epilepsy type rather than seizure type. Seizure frequency is measured in nine levels (all used during piloting). The CDEs were implemented in three vendor systems. Early clinical adoption included 1294 encounters at one center.SignificanceWe created, piloted, refined, finalized, and implemented a novel set of clinical CDEs for pediatric epilepsy.

Project description:BackgroundThe translation of evidence-based practices and rapid uptake of innovations into global health practice is challenging. Design thinking is a consultative process involving multiple stakeholders and has been identified as a promising solution to create and apply implementation strategies in complex environments like health systems.MethodsWe conducted a process evaluation of a real-world example, namely an initiative to innovate hypertension screening, diagnosis and care in São Paulo, Brazil. The parameters of the evaluation were informed by a specification rubric and categorization system, recommended for the investigation of implementation strategies, and the double-diamond conceptual framework to describe and examine the strategic architecture and nature of the design thinking approach, with particular emphasis on identifying potential areas of "value-add" particular to the approach. The retrospective evaluation was performed by an independent partner who had not been involved in the setting up and implementation of the design thinking process.ResultsThe evaluation unveiled a dense catalogue of strategically driven, mostly theoretically based, activities involving all identified health system stakeholders including patients. Narrative reconstruction illuminated the systematic and coherent nature of this approach, with different resulting actions progressively accounting for all relevant layers of the health system to engineer a broad selection of specific implementation solutions. The relevance of the identified features and the mechanics used to promote more successful implementation practices was manifested in several distinct ways: design thinking offered a clear direction on which innovations really mattered and when, as well as several new dimensions for consideration in the development of an innovation mindset amongst stakeholders. It thereby promoted relationship quality in terms of familiarity and trust, and commitment to evidence-based enquiry and action. Design thinking was also able to navigate the territory between the need for intervention "fidelity" versus "adaptation" and provide the operational know-how to face familiar implementation hurdles. Lastly, it brought a new kind of skill set to the public health stakeholders that incorporated diplomacy, multidisciplinary approaches and management sciences-skills that are considered necessary but not yet widely taught as part of public health training.ConclusionsDesign thinking is a sound and viable tool to use as part of an implementation strategy for engaging with health system stakeholders and successfully translating evidence-based practices and new innovations into routine practice, thereby addressing an important knowledge-practice gap and, more broadly, contributing to the strategic repertoire available to implementation science.

Project description:BackgroundClinical prediction rules (CPRs) represent a method of determining individual patient risk to help providers make more accurate decisions at the point of care. Well-validated CPRs are underutilized but may decrease antibiotic overuse for acute respiratory infections. The integrated clinical prediction rules (iCPR) study builds on a previous single clinic study to integrate two CPRs into the electronic health record and assess their impact on practice. This article discusses study design and implementation of a multicenter cluster randomized control trial of the iCPR clinical decision support system, including the tool adaptation, usability testing, staff training, and implementation study to disseminate iCPR at multiple clinical sites across two health care systems.MethodsThe iCPR tool is based on two well-validated CPRs, one for strep pharyngitis and one for pneumonia. The iCPR tool uses the reason for visit to trigger a risk calculator. Provider completion of the risk calculator provides a risk score, which is linked to an order set. Order sets guide evidence-based care and include progress note documentation, tests, prescription medications, and patient instructions. The iCPR tool was refined based on interviews with providers, medical assistants, and clinic managers, and two rounds of usability testing. "Near live" usability testing with simulated patients was used to ensure that iCPR fit into providers' clinical workflows. Thirty-three Family Medicine and General Internal Medicine primary care clinics were recruited at two institutions. Clinics were randomized to academic detailing about strep pharyngitis and pneumonia diagnosis and treatment (control) or academic detailing plus use of the iCPR tool (intervention). The primary outcome is the difference in antibiotic prescribing rates between the intervention and control groups with secondary outcomes of difference in rapid strep and chest x-ray ordering. Use of the components of the iCPR will also be assessed.DiscussionThe iCPR study uses a strong user-centered design and builds on the previous initial study, to assess whether CPRs integrated in the electronic health record can change provider behavior and improve evidence-based care in a broad range of primary care clinics.Trial registrationClinicaltrials.gov ( NCT02534987 ).

Project description:BackgroundClinical prediction rules (CPRs) represent well-validated but underutilized evidence-based medicine tools at the point-of-care. To date, an inability to integrate these rules into an electronic health record (EHR) has been a major limitation and we are not aware of a study demonstrating the use of CPR's in an ambulatory EHR setting. The integrated clinical prediction rule (iCPR) trial integrates two CPR's in an EHR and assesses both the usability and the effect on evidence-based practice in the primary care setting.MethodsA multi-disciplinary design team was assembled to develop a prototype iCPR for validated streptococcal pharyngitis and bacterial pneumonia CPRs. The iCPR tool was built as an active Clinical Decision Support (CDS) tool that can be triggered by user action during typical workflow. Using the EHR CDS toolkit, the iCPR risk score calculator was linked to tailored ordered sets, documentation, and patient instructions. The team subsequently conducted two levels of 'real world' usability testing with eight providers per group. Usability data were used to refine and create a production tool. Participating primary care providers (n = 149) were randomized and intervention providers were trained in the use of the new iCPR tool. Rates of iCPR tool triggering in the intervention and control (simulated) groups are monitored and subsequent use of the various components of the iCPR tool among intervention encounters is also tracked. The primary outcome is the difference in antibiotic prescribing rates (strep and pneumonia iCPR's encounters) and chest x-rays (pneumonia iCPR only) between intervention and control providers.DiscussionUsing iterative usability testing and development paired with provider training, the iCPR CDS tool leverages user-centered design principles to overcome pervasive underutilization of EBM and support evidence-based practice at the point-of-care. The ongoing trial will determine if this collaborative process will lead to higher rates of utilization and EBM guided use of antibiotics and chest x-ray's in primary care.Trial registrationClinicalTrials.gov Identifier NCT01386047.

Dataset Information

The population health record: concepts, definition, design, and implementation.

Publications

The population health record: concepts, definition, design, and implementation.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets