Editorial: An Essay On The Need To Expand And Integrate Nursing Practice Educational Horizons With Information Technology And Interdisciplinary Collaboration

Dr. Irina V. McKeehan Campbell
Editor in Charge, Population Informatics and Quality Informatics 

Campbell, I. (February, 2006). Editorial: An Essay on The Need To Expand And Integrate Nursing Practice Educational Horizons With Information Technology and Interdisciplinary Collaboration. Online Journal of Nursing Informatics (OJNI), 10 (1), [Online]. Available at http://ojni.org/10_1/irina.htm

Nursing is intrinsically affected, both clinically and intellectually, with health policy and data which systematically monitors community risk factors of chronic disease together with clinical factors and personal health practices. The clinical patient perspective and health delivery system perspectives intersect with Quality and Population Informatics. A current trend in the growth of Quality Informatics, ensuring patient safety with evidence-based practice and health policy, is the translation of research into practice with  multidisciplinary collaboration and exchange of health information, collected from disparate sources and at various levels of organization into a single data set.

Population Informatics promotes the Public Health Information Network (PHIN) and supports the eGov health information initiative to connect systems capable of supporting a broad range of public health functions: disease detection, surveillance, analysis, interpretation, alerting, and interventions. Population Informatics supplements and supports the PHIN by improving “the electronic exchange of health data and information between clinical healthcare and all levels of public health (federal, state, local) through national standards based approaches to information technology and health data (http://www.cdc.gov/phin/overview.html)”.  

Population Informatics makes available health information which is vital for policy interventions that propose to improve health outcomes a.) by increasing community participation in designing health interventions, b.) by increasing access to and delivery of high quality health care, and c.) by redefining consumer health status as embedded in the environmental and socioeconomic conditions prevalent in a community. Population Informatics integrates a Public Health Information Network (PHIN) with standard electronic exchange of health information across clinical settings, data sources, geopolitical levels, which is accessible and understood by consumers, providers, public health professionals, and government agencies. The availability of individual clinical and community health information will permit constructing and testing more rigorous causal models of variation in health outcomes and visually illustrating health disparities variation with mapping.

Linking clinical and population health data, with standard terminologies and codes, is essential for disease surveillance systems and evidence-based health policy. Private Health Informatics initiatives are marketing iHealthRecord Services as secure community and web-based personal health records (www.Medem.com), which can be integrated with electronic medical records and remain accessible by consumers and providers (physicians, insurance payors, HMOs). Consumers can "Create an iHealthRecord  By investing just a few minutes to create an iHealthRecord, you can feel confident that you'll have comprehensive health information for you and the ones you care for (your spouse, children, parents or other loved ones) whenever you may need it. The iHealthRecord is a no-cost, secure and confidential interactive record that allows you to store, update and share health information with your physician or in an emergency situation."  http://www.medem.com/pat/pat.cfm .  Such technological advances enable the empirical testing of cutting edge informatics paradigms, as well as the creation of interoperable health information systems from existing unmined data resources.

Carolyn Clancy, Director of AHRQ, has challenged the health care delivery system to provide Quality Informatics as “good quality care…patient-centered care…cost-effective care [and]  interoperability to get the right information, for the right person, at the right time and place.
(http://www.ahrq.gov/news/sp030705.htm). Quality Informatics connects patient safety directly to interoperability between HIT and EMR to monitor compliance and implementation of evidence-based guidelines. ( http://clinicalinformatics.stanford.edu/scci_seminars/05_13_05.html). CMS and the eHealth Initiative are currently engaged in supporting demonstration projects which include provider performance incentives for adopting IT and implementation of such quality processes derived from the manufacturing industry as Six Sigma. ( http://www.GovHealthIT.com ). The Medicare Modernization Act of 2003 calls for evidence-based research in Population Informatics to resolve the practice variations in 15% of Medicaid patients which account for 80% of Medicare costs (http://www.ahrq.gov/qual/errorsix.htm ).

The integration of Quality Informatics with Population Informatics parallels the development of quality of care improvement measures with the evaluation of the cost-effectiveness of evidence-based clinical interventions. Clinical outcomes may vary due to incomplete measurement of risk factors in existing secondary data sources, as well as empirical differences at interindividual levels, within and across population groups and health delivery systems. Interventions are often affected by misspecifying model risk factors, where population profiling is based on individual data. This has been demonstrated by the Harvard Public Health Disparities Geocoding Project (http://www.hsph.harvard.edu/thegeocodingproject ) with poverty indicators and the Dartmouth Atlas with small area analysis of Hospital Referral Regions ( http://www.dartmouthatlas.org/about.php ).

Population Informatics can address one critical problem in deriving evidence-based interventions for eliminating health disparities by linking disparate data sources for complete risk specification. Quality Informatics can address another critical problem with clinical data that do not contain standard codes linking outcomes with population health data. Use of standard codes, which deidentify individuals without losing information on macro risk factors, enable the interoperability of data essential for evidence-based interventions. Development of standard terminologies can reduce causal model specification errors by linking clinical with population health data to inform evidence-based policy.

The growth of Quality Informatics as a specialization has been due to the need for health cost containment and to the involvement of the Nursing Profession in daily assessments of quality of care at the point of care. The initiatives in implementing Electronic Health Records (EHR, PHR) and  Electronic Medical Records (EMR), with the community  based Continuity of Care Record (CCR)  and the Regional Health Information Organizations (RHIO) have provided the framework for the integration of Quality Informatics, primarily clinically oriented, with Population Informatics, primarily oriented for community interventions.
The role of nursing, as a profession integral to the continued development of patient safety and consumer health, needs to become more visible in these seminal fields. Both Quality Informatics and Population Informatics are at the cutting-edge for designing methodological innovations, such as the Personal Health Record and Continuity of Care Record. The PHR and CCR have already been implemented in a variety of tentative forms in England, Germany, and now, in the US, as well. Nurses also need to make continued contributions to the interface between health policy and environmental context with informatics. My own work in geopolitical health mapping continues to seek innovative methods in synthesizing the disparate areas of geocoding, Quality, and Population Informatics to understand the clinical and population determinants of variations in health outcomes.