Proposal2_iVoice

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Proposal2_iVoice

  1. 1. iVoiceSummaryThe goal of this proposed project is to set up, test, and evaluate an iVoice mobile app that will be used tocapture an individual patient’s perceptions of health improvement and quality of services. The data fromiVoicewill support quality improvement for mental health and substance use services in the city of PhiladelphiaBehavioral Health System. We are partnered with staff from the Quality Improvement Center for the City ofPhiladelphia Department of Behavioral Health to execute this project. iVoice survey data will be generated atthe point of mental health service. Currently, quality improvement does not factor in the patient’s perspective.Quality measures generated fromiVoice data includes measures of health behavior, quality of life, access, andquality of services. The iVoice data will be linked with data from the Aligning Forces program to create arobust profile of evidence to be used to evaluate quality of services and to support for pay-for-performancedecisions by the Philadelphia Quality Improvement Center team. To incentivize user participation we intend tocontribute points to an individuals’ account when they use iVoice. As points accumulate over time, patients’ canuse points to purchase a wide variety of consumer products. In addition, we propose to gamify the point systemby offering prizes for individuals or clinics based on the highest number of points, thereby encouragingparticipation. The purpose of creating patient data is to improve the health and the quality of care for thevulnerable population with mental and substance use conditions.The ProblemChronic illnesses are the leading cause of disability and death and, in the U.S., affect almost half the adultpopulation, or about 133 million Americans. A recent study places chronic care at 78% of total U.S. healthcarespending, and forecasts costs of over a trillion dollars per year by 2020.1 Among individuals with chronic illnesswho incur the highest costs are those with Serious Mental Illness (SMI) who have multiple layers of physicaland/or mental health problems that interfere with their capacity to socialize, plan, organize, and function in theirlife. People with serious mental illness (SMI), approximately 15 million Americans, are in the top 5% ofMedicaid beneficiaries for per capita costs and account for more than 50% of all Medicaid spending, withannual per person costs of $43,130 - $80,374. Despite this level of investment, services for the SMI have majorquality problems. These statistics speak volumes about the ineffectiveness of current health systems to care forsome of the most vulnerable of populations, and the need for innovative solutions to improve the quality andmanagement of their care.The goal of this project is to set up, test, and evaluate an iVoice mobile app that will be used to capture anindividual patient’s perceptions of health improvement and quality of services. The data from iVoice willsupport quality improvement for mental health and substance use services in the city of Philadelphia BehavioralHealth System. We are partnered with staff from the Quality Improvement Center for the City of PhiladelphiaDepartment of Behavioral Health to execute this project. iVoice survey data will be generated at the point ofmental health and substance use services. The generated data support public administrators to make evidencebased decisions that improve the quality and cost effectiveness of these services.Advances in mobile phone technology, and the adoption of these devices across all socio-economic strata, hascreated a powerful new potential to collect patient perceptions about their health and health experience forquality improvement. This platform includes native mobile apps and mobile web sites. Communication fromthe population to the care teams, public health practitioners, and care quality improvement organizations islimited and not systematically collected in health settings other than hospitals. The mobile technology platformis at an inflection point: the functionality is sufficiently reliable and sophisticated, and the device adoption iswidespread. There are mobile apps that have met with some recent success and motivating certain audiences.These include Eatery, Lift, RunKeeper, and Zamzee. These apps are popular with the “worried well”, generallypeople of higher SES and health status who are looking to improve their fitness. These are not the patients 1
  2. 2. associated with the bulk of the country’s health care expense: people suffering from serious diseases that are notbeing adequately managed, and often with comorbidities and complications.StrategyWe developed a prototype of iVoice and presented it to the City of Philadelphia Quality Improvement Team inthe Department of Behavioral Health. Cathy Bolton, PhD is the director of quality improvement. She has alarge team of research analysts and quality improvement specialists. Over the past 10 years, she has workedwith the Department of Behavioral Health to improve the quality of services. Currently, patient satisfactiondata comes for face-to-face surveys. Obviously, data collection is time consuming, expensive, and requirescleaning and manipulation to link it with claims data. Claims data, the primary data source for qualityimprovement, is limited to service utilization. A link with patient’s perception of health improvement andquality of services would be ideal. Mobile apps offer an opportunity to collect patient data at the point ofservice. Adding patient satisfaction data to the quality improvement assessment process provides andunprecedented opportunity. Additionally, linking with other government data sources to obtain contextualfactors provides a robust dataset for analysis and decision making about managing resources.Population: Currently there are 1.5 million people living in Philadelphia; 527,000 receive Medicaid services.Of these individuals, 224,654 have at least one administrative claim for a mental health diagnosis (ICD-9-CM295.xx to 316.xx); 76,187 are adults age 18 years and older and the remainder are children. The population thatwas treated for a serious mental illness includes 40,738 adult clients; 30% have an affective disorder; 6% have aschizophrenia diagnosis; 21% have a substance use disorder, and 43% have another functional disability.Approximately 68% of these adults have a major medical problem ranked in order of occurrence: diabetesmellitus, essential hypertension, lumbar pain, respiratory disorders and osteoarthritis and allied neurologicaldisorders. Thus, approximately 76,187 adults individuals could potentially useiVoice. Design and ImplementationSystems DiagramThe proposed system is mobile web site accessible with any smartphone, tablet, laptop, or desktop. Thespecifics of the system, including the data fields, end-user interfaces, and researcher dashboard interfaces,would be “co-designed” using rapid-prototyping approach with a sample of actual end-users giving iterativefeedback. 2
  3. 3. Sample Screen From Mobile Web App: Soliciting Patient Satisfaction Scores The technical implementation can be readily handled by Big Yellow Star Inc. during Phase 2 of this competition. We are accustomed to an agile approach to deployment of reliable mobile technology for health systems and public health informatics. We would use cloud infrastructure (multi-zone Amazon Web Services), scalable application architecture (Ruby on Rails and MongoDB) and mobile interface standards (HTML5 and jQuery). The main end-user interface is the mobile web app, which can include three types of layouts that share the same functionality: smartphone, tablet, and laptop/desktop. The second user interface is the interactive text messaging component. Although the exact use would need to be decided by the co-design process, an example scenario is that users set up text message “triggers” that solicit numeric data input. The users would receive these according their preferred schedule and then reply to them as they arrive. In this way the most routine data can be collected without the user even opening the mobile web app. And a third interface, added at a later phase, can be the automatic incorporation of data from wireless biometric sensors such as the Withings scale.Figure 1.0 provides a graph expressing the quality improvement loop from the collection of patient responsesusing iVoice to linking iVoice data with government and claims data to develop and evaluate quality indicatorsthen providing quality improvement reports to various stakeholders such as government officials, facilities, andproviders. Rationale for pay-for-performance decisions is most enhanced with the iVoice data, particularly foroutpatient services which have not been targeted with pay for performance incentives. Figure 1.0 demonstratesthe potential for the proposed data to identify and then support and evaluate quality improvement in particularareas. Dr. Bolton and her staff have used pay-for-performance for hospital services but the data for outpatientservices is lacking. Adding the robust proposed dataset provides evidence to support pay-for-performancedecisions because the linked data provides new quality measures that align with national quality measures. Theprocedures for data collection follows: 1. The secretary of the clinic assists patients to enter data onto an IPad that is securely attached to the check out desk. The usual patient flow is to check in for their appointment with the secretary; once service is completed, the patient checks out with the secretary to handling billing and future appointment. It is at this point, the secretary will instruct the patient to go to the IPad and answer questions about their visit. She will help the patient to sign on to a mobile website that will have the following frames: a. Login. The patient logs in with their Medicaid number. Typically, 80% of patients with serious mental health problems such as schizophrenia, mood or other mental status problems are covered by Medicaid. The secretary will provide the patient with their Medicaid number that the patient 3
  4. 4. enters onto the login page. If the patient has problems, the secretary will be trained to assist the patient. a. The next pages are a series of 5-10 questions about quality, health and services with likert scale answers. The questions were developed by the New York Care Coordination Program (NYCCP) and will be used because psychometric studies support reliability and validity. The measures also translate well with national quality indicators and are functionally relevant. The questions were developed using individuals with serious mental illness. We added a feature to the app that allows the Quality Director to periodically change the questions to get at access, quality and costs issues. We will use the same databases or tools for data collection. i. The Enrollee Satisfaction Survey allows patients to rate the services they receive. ii. Quality of life assessment. b. The data collected from the app includes the Medicaid number as the unique identifier that can link to other data such as Medicaid Claims where measures of cost and utilization of services can be obtained.2. Platforms for moving, storing, and archiving data are still to be determined and depend on privacy and security issues. The Quality Improvement team is familiar with the rigors of HIPAA laws of privacy and security and several attorneys’ work with their program on these challenges. 4
  5. 5. Data MeasuresQuality measures will be created from linking the Medicaid number of the patient and zip code. Quality Measures and Data SourcesMeasure Data SourcesHealth behaviors: tobacco use, diet and exercise, Behavioral Risk Factor Surveillancealcohol use, sexual activity National Center for Chronic Disease Prevention andHealth-related Quality of Life Health Promotion iVoiceHealth Conditions: HIV, diabetes, obesity. Behavioral Risk Factor SurveillanceMorbidity: poor or fair health, poor physical health iVoicedays, poor mental health days, injury, Sexually Medicaidtransmitted infectionsClinical Care: access, quality of services; utilization iVoiceof hospital, outpatient, emergency room, community Medicaid datasupport services and costs of care.Social and economic factors: education, employment, Behavioral Risk Factor Surveillanceincome, family support, safety (violent crime rate) FBI data on violent crime rates iVoicePhysical environment: air pollution, ozone days, U.S. Environmental Protection Agencyaccess to servicesAnalytic QuestionsAnalytic questions using the integrated data sets will focus on access, quality, and costs. Pay-for-performanceanalysis will use patient satisfaction, access, health improvement, and quality. Analysis of cost benefit willfactor patient health improvement and types and quantity of services. Longitudinal questions can be assessedbecause the patient is uniquely identified each time iVoiceis used. The County Health Rankings and Measurescan be used to assess population parameters and establish reasonable estimates for expected change. Hot spotsthat require targeted quality control can be identified from iVoicethen validated using the County Health data.Most important, exemplar places and providers of services can be identified and rewarded.Game/gamification design characteristic that drive engagement and experienceWe plan to use a point system for gamifying the design so that participants are engaged in the experience.Similar to point systems used by airlines or credit cards, the patient would accumulate points each time he/sheuses iVoice. Early implementation may be further incentivized by adding ways for individuals or even clinics tocompete for addition points and buying power. Decisions of the type of gamification incentives will bereviewed with consumers and other stakeholders to ensure that incentives are indeed attractive to the player. 5
  6. 6. Plan for adoption in the communityFigure 3.0 provides a graph of the steps we will take and the timeline for implementing and evaluating theperformance of the app and the data that is generated. The process is iterative until all stakeholders are satisfiedthat the app and data meet the goal of the project which is to create and implement an app that captures anindividual patient’s perceptions of health improvement and quality of services. 6
  7. 7. Task Start EndManage system platform, data storage, and data access for QI 5/7/2013 8/22/2014Build multidisciplinary team of Patients, Quality staff, and clinicians to providefeedback on feasibility and design 5/22/2013 7/7/2014Privacy and Security Issues 5/7/2013 6/25/2013Solve for Access to a unique person system: QR? 6/7/2013 7/26/2014Set up reward systems; 6/24/2013 8/25/2013Beta test 1.0 iVoice and point system among Quality Control Staff 6/24/2013 12/25/2013Correct issues identified in previous beta test 1.0 8/8/2013 11/9/2013Select one clinic and 5 patients for beta test 2.0 11/14/2013 12/17/2013Ensure web access 6/24/2013 3/25/2014Educate secretaries in their role assisting patients to use iVoice. 6/8/2013 6/11/2014Instruct patients in the use of iVoice, noting usability issues 1/26/2014 1/27/2014Correct bugs from beta test 2.0 2/2/2014 3/4/2014Continue to beta test until all bugs are worked out. Vary the clinics; 4/8/2014 5/8/2014Linking Data and create reports for QI. 5/9/2014 8/10/2014Test reward points 5/5/2014 5/5/2014Schedule full role out for all behavioral health clinics 1/8/2014 3/9/2014Beta test in medical clinics reiterating the process until bugs worked out 5/21/2014 5/21/2014Identify maintenance tasks 7/21/2014 8/22/2014 7

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