Choosing A Frame Reframing in Action Essence of reframing is examining the same situation from multiple vantage points to develop holistic picture. Each Frame provides advantages, but also blind spots.
Until we can consistently send and receive accurate and useful patient data nationwide, we will fail to realize the documented benefits of well-executed health information exchanges: Among the remaining challenges to successful nationwide exchange is patient matching across organizational boundaries.
The inability to consistently and accurately match patient data creates a number of problems for physicians and other health care providers. In addition, providers may experience a number of clinical workflow inefficiencies that are costly.
Those include prolonged troubleshooting to find the correct patient record, a reversion to manual telephone and fax information exchange workflows, waiting for a duplicate lab test order, or a manual effort to fix a patient record match.
To address these critical patient matching and identity management issues, The Sequoia Project, in collaboration with the Care Connectivity Consortium CCChas developed a framework for future growth and improvement that will shed light on several key topics: Over time, it is the intent of The Sequoia Project that this document is periodically updated to capture and advance cross-organizational patient matching innovations.
Case Study Intermountain Health Care, a CCC member, is a sophisticated healthcare Organizational resource paper and payer, and has invested heavily in healthcare information technology. So when they started exchanging data with other organizations, they expected a reasonably high degree of success.
An analysis of common patient matching traits is presented, along with a list of rules developed during the study.
|Structural Frame||Meyer and Allen created this model for two reasons: Meyer and Allen's research indicated that there are three "mind sets" which can characterize an employee's commitment to the organization.|
These rules are further analyzed in terms of completeness and uniqueness. The result was significantly improved match rates for Intermountain and its partners, and patient matching improvement strategies that can be replicated across the industry.
We also provide a self-diagnostic tool, in the form of a questionnaire, to jump start a self-assessment of your own patient matching strategies. Patient Matching Maturity Model We believe that more precise definitions of the maturity model will give organizations the ability to adopt more advanced patient identity management in a methodical manner.
The levels currently being contemplated in our proposed maturity model, now open to public comment, include: Indicating ad hoc processes and outcomes, little to no management oversight or recognition; Level 1: Indicating adoption of basic defined processes with associated repeatable outcomes, and limited management involvement; Level 2: Indicating increasing maturation of processes, definitions of most key processes, data governance, algorithm use, active management involvement, accumulation of quality metrics; Level 3: Indicating advanced use of existing technologies with associated management controls and senior management awareness, use of quality metrics; and Level 4: Indicating innovation, on-going optimization, and senior management active involvement.
Assessments are based on the International Organization for Standardization ISO framework, which includes people, process, and technology, with the added dimension of governance.
Current traits associated with the various levels include patient identity management validation plans, community collaboration, use of standards, quality metrics, knowledge sharing, partner onboarding maturity, and more.
Each of these traits is defined and mapped to appropriate maturity levels.
Patient Matching Minimal Acceptable Principles This proposed framework illustrates a very low-level, and concrete, list of cross-organizational patient matching practices.
The target audience for this, the last section in this paper, are senior technical staff responsible for implementing clinical document care summary exchange. A number of specific rules are presented, such as the prohibition of using exact character-by-character matching, the corresponding responsibilities on both partners to an exchange of patient data, and similar practices.
Other principles include not relying on any specific identifier such as a social security numbernot making any assumptions about the life cycle of a patient identifier, using normalized traits, and more.Consumer Satisfaction and Service Quality Analysis of ACI Power Tiller Bangladesh is a South Asian country with the record of highest population density (% population growth per annum) where 77% people live in rural areas.
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