On the Annotation of Health Care Pathways to Allow the Application of Care-Plans That Generate Data for Multiple Purposes.

Objectives: Procedural interoperability in health care requires information support and monitoring of a common work practice. Our aim was to devise an information model for a complete annotation of actions in clinical pathways that allow use of multiple plans concomitantly as several partial processes underlie any composite clinical process. Materials and Methods: The development of the information model was based on the integration of a defined protocol for clinical interoperability in the care of patients with chronic obstructive pulmonary disease and an observational study protocol for cohort characterization at the group level. In the clinical process patient reported outcome measures were included. Results: The clinical protocol and the observation study protocol were developed on the clinical level and a single plan definition was developed by merging of the protocols. The information model and a common data model that had been developed for care pathways was successfully implemented and data for the medical records and the observational study could be extracted independently. The interprofessional process support improved the communication between the stakeholders (health care professionals, clinical scientists and providers). Discussion: We successfully merged the processes and had a functionally successful pilot demonstrating a seamless appearance for the health care professionals, while at the same time it was possible to generate data that could serve quality registries and clinical research. The adopted data model was initially tested and hereby published to the public domain. Conclusion: The use of a patient centered information model and data annotation focused on the care pathway simplifies the annotation of data for different purposes and supports sharing of knowledge along the patient care path.

Utilization of BPM+ Health for the Representation of Clinical Knowledge: A Framework for the Expression and Assessment of Clinical Practice Guidelines (CPG) Utilizing Existing and Emerging Object Management Group (OMG) Standards.

Clinical Practice Guidelines (CPG), meant to express best practices in healthcare, are commonly presented as narrative documents communicating care processes, decision making, and clinical case knowledge. However, these narratives in and of themselves lack the specificity and conciseness in their use of language to unambiguously express quality clinical recommendations. This impacts the confidence of clinicians, uptake, and implementation of the guidance. As important as the quality of the clinical knowledge articulated, is the quality of the language(s) and methods used to express the recommendations. In this paper, we propose the BPM+ family of modeling languages as a potential solution to this challenge. We present a formalized process and framework for translating CPGs into a standardized BPM+ model. Further, we discuss the features and characteristics of modeling languages that underpin the quality in expressing clinical recommendations. Using an existing CPG, we defined a systematic series of steps to deconstruct the CPG into knowledge constituents, assign CPG knowledge constituents to BPM+ elements, and re-assemble the parts into a clear, precise, and executable model. Limitations of both the CPG and the current BPM+ languages are discussed.

Harmonization of the ICHOM Quality Measures to Enable Health Outcomes Measurement in Multimorbid Patients.

Objectives: To update the sets of patient-centric outcomes measures ("standard-sets") developed by the not-for-profit organization ICHOM to become more readily applicable in patients with multimorbidity and to facilitate their implementation in health information systems. To that end we set out to (i) harmonize measures previously defined separately for different conditions, (ii) create clinical information models from the measures, and (iii) restructure the annotation to make the sets machine-readable. Materials and Methods: First, we harmonized the semantic meaning of individual measures across all the 28 standard-sets published to date, in a harmonized measure repository. Second, measures corresponding to four conditions (Breast cancer, Cataracts, Inflammatory bowel disease and Heart failure) were expressed as logical models and mapped to reference terminologies in a pilot study. Results: The harmonization of semantic meaning resulted in a consolidation of measures used across the standard-sets by 15%, from 3,178 to 2,712. These were all converted into a machine-readable format. 61% of the measures in the 4 pilot sets were bound to existing concepts in either SNOMED CT or LOINC. Discussion: The harmonization of ICHOM measures across conditions is expected to increase the applicability of ICHOM standard-sets to multi-morbid patients, as well as facilitate their implementation in health information systems. Conclusion: Harmonizing the ICHOM measures and making them machine-readable is expected to expedite the global adoption of systematic and interoperable outcomes measurement. In turn, we hope that the improved transparency on health outcomes that follows will let health systems across the globe learn from each other to the ultimate benefit of patients.

An Efficient, Clinically-Natural Electronic Medical Record System that Produces Computable Data.

Current commercially-available electronic medical record systems produce mainly text-based information focused on financial and regulatory performance. We combined an existing method for organizing complex computer systems-which we label activity-based design-with a proven approach for integrating clinical decision support into front-line care delivery-Care Process Models. The clinical decision support approach increased the structure of textual clinical documentation, to the point where established methods for converting text into computable data (natural language processing) worked efficiently. In a simple trial involving radiology reports for examinations performed to rule out pneumonia, more than 98 percent of all documentation generated was captured as computable data. Use cases across a broad range of other physician, nursing, and physical therapy clinical applications subjectively show similar effects. The resulting system is clinically natural, puts clinicians in direct, rapid control of clinical content without information technology intermediaries, and can generate complete clinical documentation. It supports embedded secondary functions such as the generation of granular activity-based costing data, and embedded generation of clinical coding (e.g., CPT, ICD-10 or SNOMED). Most important, widely-available computable data has the potential to greatly improve care delivery management and outcomes.

Organizational ethics in managed behavioral health care: perspectives from executives and leaders.

Managed behavioral health care (MBHC) is frequently criticized on ethical grounds for the way it undermines classical ideals of professionalism in mental health and addiction treatment. There is an implied assumption that practitioners who are executives and leaders in MBHC companies have moved away from clinical ethics to the adoption of business and financial models. This qualitative study explores perceptions of organizational ethical issues from the point of view of leaders working in MBHC settings and how their perspectives contribute to our current schemas for analyzing the ethical complexities of MBHC. Twenty-seven participants from across the United States were interviewed using an interview guide that relied on open-ended questions and probes. Inquiry findings present four major themes and describe participant material in a way that enhances sensitivity and understanding to organizational ethics in MBHC and behavioral health services and research.

Integrating the nursing management minimum data set into the logical observation identifier names and codes system.

This poster describes the process used to integrate the Nursing Management Minimum Data Set (NMMDS), an instrument to measure the nursing context of care, into the Logical Observation Identifier Names and Codes (LOINC) system to facilitate contextualization of quality measures. Integration of the first three of 18 elements resulted in 48 new codes including five panels. The LOINC Clinical Committee has approved the presented mapping for their next release.

Physician use of electronic medical records: issues and successes with direct data entry and physician productivity.

At Intermountain Health Care, we evaluated whether physicians in an ambulatory setting will voluntarily choose to enter data directly into an electronic health record (EHR). In this paper we describe the benefits of an EHR, as they exist in the current IHC application and the ways in which we have sought to minimize obstacles to physician data entry. Currently, of 472 IHC employed physicians, 321 (68%) routinely enter some data directly into the EHR without coercion. Twenty-five percent (80/321) of the physicians use voice recognition for some data entry. Twelve of our 95 ambulatory clinics have voluntarily adopted measures to eliminate paper charts. Of the 212 physicians who entered data in 2004, sixty-nine physicians (22%) increased their level of data entry, while 12 (6%) decreased. We conclude that physicians will voluntarily adopt an EHR system, and will continue and even increase use after implementation barriers are addressed.