Table 5 Model Advantages and Disadvantages
From: Regional models of genetic services in the United States
Model | Advantages | Disadvantages |
|---|---|---|
Regional genetic service resource network | • Team approach • Familiar structure for current HRSA regional collaboratives and other centers; would permit HRSA to build on what has been learned, using existing or similar infrastructure • Looks at a wide range of issues/priorities • Region could focus on what is lacking most for the region within the context of the goals of HRSA • Training could be administered readily; fellowships could be supported as well; genetic counselor training could also be supported • Center could be used to facilitate relationships between states, genetics providers, nongenetics providers, consumers, other existing programs • Demonstrating national impact is achievable if common goals/objectives | • Current RCs still not widely known; use of this structure would require aggressive promotion of the system to improve access • Core outcomes could be defined, but if each region uses own methodology, based on regional needs, identifying common elements to measure outcomes could be difficult; some consistency with other HRSA programs also desirable • Lack of consistency in outcomes could affect funding in the long run • Demonstrating national impact difficult if regional activities highly variable • Work needs to be done within the health-care delivery system to impact access |
Regional clinical support centers | • May address workforce capacity • Promote efficiency • Most ability to get data for individual sites—clinical site data • For some payers, a national system may be OK • Other product development possible | • May not be needed in all regions • Limits services provided to other specialists and primary care providers • Education component for nongeneticists is not covered • Patient engagement component is left out • Health plans and structures vary so may not be able to provide national data on some access issues |
Regional genetics education and technical assistance centers | • Easier to do than some other suggested models • Much of the work could be done using online methodology • Would maximize impact of limited dollars • Potential for broad reach • Broad expertise exists in the field • Simpler system: billing/reimbursement is difficult but straight education is easier • Providers need just-in-time materials; webinars could be used | • Focusing on providers and public education means we could miss consumers; need to include consumers in education • Difficult to measure behavior change following an educational program; difficult to show clinical impact (improved access) • Disease-specific educational materials are more beneficial but can be difficult to develop • Need capacity to develop and distribute just-in-time materials at sites where needed • Would have to be driven by other national organizations (AAP) to get into training programs |
Regional patient engagement centers | • Addresses some high-need areas based on feedback from the survey: people aren’t getting information they want/need (low literacy, other languages) • Potential outcome measures are close to HRSA goals (getting patients to services) | • Difficult to address in stand-alone centers • Outcome measures may be difficult • Information-seeking individuals will be helped but may not reach entire population • If workforce capacity issue isn’t addressed, an influx of people could be entered into the system without appropriate workforce • Not addressing clinical/delivery systems; therefore doesn’t address underlying issues |
Public health model | • Enhanced data collection by state genetics coordinators • Increased access to individuals not getting services through coordination with Title V, Medicaid, and chronic disease programs • Many issues preventing access are at the state level • In a mixed model (combining elements of different models), some regions could support programs to provide information to state public health as needed by individual states • Easy access to other large public health programs (Medicaid, Title V) • Helps build relationships within state health departments and may provide access to other state budgets for specific programs (if genetics program budget isn’t available); once matured there should be a return on investment • Regional centers would have no control over states but NCC/RC system has built state NBS capacity, suggesting this is a feasible model • Structure within states can be a sustainable model | • Some states may be unwilling or unable to accept small amounts of money available through these grants • Some states may not wish to accommodate this position within their state structures • There needs to be a state champion for genetics beyond the coordinator • Success is dependent on genetics coordinator being high enough in the state structure to be effective • May have an issue filling 50 slots for coordinator with a trained genetic counselor (workforce issue); salary may not be as competitive as industry; may need to recruit professionals with other backgrounds • Coordinator requires time to develop relationships, work with other units in the department to create/fund programs to address clinical, educational needs |
Quality improvement model | • Validated method, evaluation built in, outcomes reportable • Could put almost any activity around access into a PDSA; in the absence of national baseline data, QI effort would address a specific problem, as opposed to all problems); development of metrics in genetics would be useful • Single national unified project would permit national data collection and outcomes assessment • Could permit coordination with MOC activities for providers • Many access problems could be addressed using QI methodology | • Higher cost • Would require a planning phase, lag likely in getting to data collection (identify methodology first, then start data collection) • Genetics professionals unfamiliar with QI and implementation science would require additional education. • Measurable outcomes from QI might not immediately promote access. • A single national QI focus may not be applicable to all regions. However, selection of regional QI projects would limit national data collection and outcomes assessment • Systemic issues related to genetic access seem too big for some QI approaches • Could end up with a number of pilot projects that might differ; local data easy to get, but national data difficult to collect |
Regional clinical support network | • Trackable outcomes as long as effectively communicated between center and clinics • Could enhance funding already in place if state does have contract funding • States could coordinate their support of genetic services with resource centers, so that funds could be equitably distributed • Takes advantage of mechanisms already in place in some states to contract out services | • Regional centers would focus on contracting and evaluating; less than 12 months to contract, complete the work, evaluate is a problem • A lot of contracts with very little money depending on the state; could enhance the maldistribution of dollars • Because clinical centers must apply for funds to meet their specific needs, funds may not be distributed to the communities efficiently or equitably |
Genetic service data centers | • Gets national, uniform baseline data • Allows measurement of impact of future programs • Data for policy development • National data set would be useful in informing the greater medical community • Could address health equity issues: drill down to different conditions, populations to identify regional and local needs • Reinforce formal relationships with state programs, can create data together so may not need to give money to state • Works well with meaningful use standards • Delays action steps until baseline data collected | • Does not improve access initially: no “action” steps until data are collected and analyzed to identify needed actions • Long-term results will be years from initiation of grant cycle; therefore more difficult to get buy-in from partners who would need to provide data • Would need to build in time to choose core data set (what to collect and from whom); also need time to define and create formal relationships with clinical programs and states • Would have to pay for data entry into a regional/national repository • This would be an all-consuming endeavor, and would obviate all other activities • States often don’t have data on non-NBS conditions; would require data from clinical sites and other sources |
Recommended hybrid model: regional genetic service support model | • Regions would focus on what is lacking most for the region within the context of the goals of HRSA as identified in this model (improved practice efficiency through technical assistance; nongenetics provider education using just-in-time point-of-care tools) • Center would be used to facilitate relationships between states, genetics providers, nongenetics providers, consumers, other existing programs; improved relationship would provide information on tailoring specific programs to the region • Demonstrating national impact is achievable since common goals/objectives are required • Should improve access to genetics services | • Core outcomes could be defined, but if each region uses own methodology, based on regional preferences, collection of comparable data may not be possible; some consistency with other HRSA programs also desirable • Lack of consistency in outcomes could affect funding in the long run • Demonstrating national impact difficult if regional activities highly variable • Work needs to be done within the health-care delivery system to impact access, requiring development of robust relationships with providers |
