Risk Stratification Application Jason McDaniel 2015

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Risk Stratification Application Jason McDaniel 2015 by Mind Map: Risk Stratification Application Jason McDaniel 2015

1. References

2. Need for innovation

2.1. Description

2.1.1. Risk Stratification is the process of extracting data from many sources to determine and assign a level of risk. A risk stratification application can extract or upload data from multiple sources to determine which patients are at a higher risk. By determining the risk of a patient disease can be prevented

2.2. Rationale

2.2.1. The future of health care is in the prevention of disease, both acute and chronic. There are currently applications that compile health care data to determine a patients risk, but there is no application that looks at non-health care data to assist in determining that risk. In reality, there are many sources of information that can assist in determining a patients risk. Sources such as grocery receipts, magazine subscriptions, occupation, and type of automobile can all aid in determining a patients risk.

2.2.1.1. "Traditional organizational infrastructures are effective for just that, traditional organizations created to function in the industrial age. As the transition from the Industrial Age to the age of technology and information availability accelerates, the process of work, relationships between workers and customers, and the speed at which all of this occurs requires a new emphasis for organizations." (Porter-O'Grady & Malloch, 2010, pg. 33)

2.3. Social Context

2.3.1. Health care entities are now focusing on the "triple aim" to make themselves successful. An advanced risk stratification model can make the "triple aim" a more likely outcome

2.3.1.1. Triple Aim

2.3.1.1.1. Improved patient experience

2.3.1.1.2. Improved health of patient population

2.3.1.1.3. Reduced per capita cost

2.3.1.1.4. "The Triple Aim, an approach to health delivery that targets quality, cost and population health, could have been just another piece of healthcare jargon. Instead, hospitals and health systems large and small have adopted it as framework for major provisions of the Patient Protection and Affordable Care Act." (Ready, 2015)

3. Major Stakeholders

3.1. Stakeholders

3.1.1. Chief Medical Informatics Officer and staff

3.1.1.1. Must assist in setting parameters and criteria that determines patient risk

3.1.1.2. Extract appropriate data from electronic healthcare applications into risk stratification application

3.1.1.3. Add icon to the EMR banner to alert providers to patients with a higher risk

3.1.2. Marketing

3.1.2.1. Develop surveys with appropriate questions to disseminate

3.1.2.2. Receive completed surveys and organize data

3.1.3. Medical Coders

3.1.3.1. Must ensure that the diagnosis and procedure codes are accurate

3.1.4. Labs

3.1.4.1. Patient's A1Cs, GFRs, and other labs must be extracted

3.1.5. Physicians

3.1.5.1. Must correctly diagnose patients and record a complete and accurate history

3.1.6. Nursing Staff

3.1.6.1. Accurate documentation of BMI and other vitals

3.1.7. Applications Team

3.1.7.1. Manage application

3.1.8. "Employees at successful innovative organizations have a shared definition of innovative thinking and use the same innovative thinking processes." (Weiss & Legrand, 2011, pg. 64)

3.2. DiSC & VAT

3.2.1. Characteristics of the Dominance style must be utilized by the Chief Medical Informatics Officer for the qualities of directness and the desire to achieve success.

3.2.2. Characteristics of both i and S styles will be demonstrated by the providers and nursing staff for their enthusiasm, encouragement and support for this innovation

3.2.3. Characteristics of the C style will be utilized by the medical coders and the application team for their accuracy, knowledge and attention to quality

4. Information

4.1. Questions and information that must be obtained

4.1.1. What amount of staffing will be needed to maintain application?

4.1.1.1. Staff to collect and enter surveys into application

4.1.1.2. IT/applications staff to maintain application

4.1.2. How much memory and bandwidth will be needed?

4.1.3. What will be the best questions to have on the patient survey?

4.1.3.1. Physician panel to determine questions

4.1.4. How will application interface with EMRs?

4.1.4.1. All Scripts

4.1.4.2. Epic

4.1.4.3. Cerner

4.1.4.4. Citrix

4.1.4.5. Others

4.1.5. Who are the key leaders needed to implement application?

4.1.5.1. CMIO

4.1.5.2. Finance Director

4.1.5.3. Medical Directors

4.1.5.4. "The more formal officially sanctioned leadership positions as described in bureaucratic or structured hierarchies often act counter to the requisites of informal leadership,..." (Porter-O'Grady & Malloch, 2010, pg. 4)

4.1.6. What numerical values do we assign based off of risk determinants?

4.1.6.1. Numbers (1-5, 1-10, etc.)

4.1.6.2. Letters (A-Z)

4.1.6.3. Symbols

4.1.7. What incentives can we offer patients to fill out survey accurately?

4.1.7.1. Free wellness exams

4.1.7.2. Gym Memberships

4.1.7.3. Healthy food vouchers

4.1.7.3.1. Whole foods

4.1.7.3.2. Weight Watchers

4.1.7.3.3. Fresh & Easy

4.1.7.4. Gift Certificates

5. Measurables

5.1. Evaluation

5.1.1. Metrics

5.1.1.1. Net Promoter Score (NPS)

5.1.1.2. Healthcare Effectiveness Data and Information Set (HEDIS)

5.1.1.2.1. "The Healthcare Effectiveness Data and Information Set (HEDIS) is a tool used by more than 90 percent of America's health plans to measure performance on important dimensions of care and service. Altogether, HEDIS consists of 81 measures across 5 domains of care. Because so many plans collect HEDIS data, and because the measures are so specifically defined, HEDIS makes it possible to compare the performance of health plans on an "apples-to-apples" basis." (NCQA)

5.1.1.3. Patient Satisfaction Scores

5.1.1.4. Disease prevalence

5.1.1.4.1. As a baseline for disease prevalence, ICD-9 and ICD-10 codes can be extracted from both electronic medical records and claims data to search for new occurrences in individual patients per year. The evaluation of this metric would be determined by a decrease in the amount of new diagnoses.

5.1.1.5. Cost per patient visit

5.1.1.5.1. "Takes into account all of the resources associated with providing a particular service and calculates how much it costs to provide that service at the smallest practical unit." (Kullgren & Sebella, 2004)

5.1.1.6. Readmission Rates

5.1.1.6.1. "Section 3025 of the Affordable Care Act added section 1886(q) to the Social Security Act establishing the Hospital Readmissions Reduction Program, which requires CMS to reduce payments to IPPS hospitals with excess readmissions, effective for discharges beginning on October 1, 2012." (CMS, 2015)

5.1.1.7. Mortality Rates

5.1.1.7.1. With the ability to more accurately predict the occurrence of disease, mortality rates will see a reduction

5.1.2. Adaptability

5.1.2.1. Healthcare is an extremely fluid field and priorities can change at any moment. It is necessary for the application to be manipulated if their are emergencies. If outbreaks, national disasters, terrorism or any other catastrophic event occur, the application can help to determine who is at the greatest risk

5.1.3. Baselines

5.1.3.1. Most baseline data can be extracted by interfacing with other healthcare applications. (EMR, claims, demographics, payers, CMS) This baseline data can then be used to determine the variable change in the future.

5.1.3.1.1. Extract 2015 chronic condition data as baseline

5.1.4. Risk Mitigation

5.1.4.1. The ability to effectively and efficiently identify risk.

5.1.4.1.1. "Risk is not good or bad. We define risk as the probability that something will happen, multiplied by the potential consequences. In all complex situations, some level of risk exists because we cannot eliminate all uncertainties and ambiguities. The key is to understand the nature and level of the risks attached to an innovative idea." (Weiss & Legrand, 2011, pg. 153)

6. Relationships

6.1. Organizational Impact

6.1.1. Executive Leadership

6.1.1.1. Approve and lead change

6.1.1.1.1. "Organizations where every decision must be rational and justified by reams of data can also have a negative impact on innovation. Innovation can be stalled indefinitely, as there is always more data, however biased or obsolete, to support the status quo than to support a brand new idea." (Weiss & Legrand, 2011, pg. 228)

6.1.1.1.2. "The leadership of innovation in complex adaptive systems requires a whole new leadership skill set in an emergent notion of leadership itself." (Porter-O'Grady & Malloch, 2010, pg. 29)

6.1.2. Marketing

6.1.2.1. Advertise and market surveys

6.1.3. Outreach Teams

6.1.3.1. Training and education

6.1.4. IT

6.1.4.1. Team to monitor and maintain application

6.1.5. Analytics

6.1.5.1. Assemble analytics team

6.1.5.2. Identify pertinent criteria to identify patient risk

6.2. Barriers

6.2.1. Financing

6.2.1.1. Similar software cost approximately $1000 per user.

6.2.1.1.1. Data extracted by a handful of users

6.2.1.1.2. Cost benefit analysis

6.2.2. Utilization

6.2.2.1. Must become every day process

6.2.3. Education

6.2.3.1. Super Users

6.2.3.2. Clinical staff

6.2.3.3. IT

6.2.4. Change Management

6.2.4.1. "Because change is inherently unsettling for people at all levels of an organization, when it is on the horizon, all eyes will turn to the CEO and the leadership team for strength, support, and direction. The leaders themselves must embrace the new approaches first, both to challenge and to motivate the rest of the institution." (Jones, 2004)

7. Timeline