Your organization is improving health outcomes and may even offer solutions that are transforming healthcare. You want trustworthy evidence to show that your programs are making a real difference. Two questions need to be answered:
The healthcare marketplace requires feedback loops for both internal and external stakeholders to validate these programs. Schooner Strategies is now offering through Trajectory® Healthcare LLC, a patented process to successfully answer these questions using advanced epidemiological and statistical verification methods.
The Trajectory evaluation model uses the science of epidemiology, the cornerstone of public health, to meet the medical needs of individual patients and targeted populations.
Epidemiology asks the same questions about a population that a medical doctor asks about an individual:
The last question: “Did it work?” is answered by another question: "Compared to what?"
Providers, epidemiologists and others often rely on professional knowledge and published evidence to predict expected health outcomes. Epidemiologists take the additional step of performing intensive quantitative analyses. Achieving excellence requires credible measurement of an equivalent comparison population.
Every disease has a "natural history." Things are different before getting sick than afterwards. The Trajectory evaluation model provides a unique approach that not only tracks the natural history of a disease but describes the trajectory of population-based conditions.
Trajectory creates and studies virtual epidemics™ as the basis of much of its analyses. A virtual epidemic starts each patient on the same “trajectory day” and maps their course over time, providing an innovative framework for analysis.
Trajectory constructs critical feedback loops that demonstrate the link between program interventions and outcomes. Multiple sources power this analysis, including medical and prescription claims, lab results and patient surveys. The Trajectory data analytic engine creates and customizes study designs that validate the impact of program interventions more accurately than other evaluation approaches or tools.
Trajectory evaluates the "cause and effect" of an intervention by controlling for the confounding variable of time.
Trajectory evaluates the "cause and effect" of an intervention by controlling for the confounding variable of time. This approach adds clarity and fidelity to the analysis that other approaches cannot replicate. A demo of the Trajectory data analytic engine, combined with our wrap-around consulting services, will show you the current value of your program and provide insights on how to support future growth and improvement.
Clients can access Trajectory’s secure online portal and subject matter experts who offer insightful and objective consulting services. We can help you share your results by drafting scientific publications, white papers, press releases and other communications. Trajectory is a total outcomes solution! Trajectory’s Return on Investment (ROI) Calculator can examine the financial and clinical efficacy of most medical interventions in almost real time. We can address "what if" scenarios to examine the ROI for sub-populations and help you identify new opportunities.
Schooner Strategies is now offering a breakthrough solution powered by Trajectory® Healthcare LLC using advanced epidemiological and statistical verification methods to demonstrate healthcare outcomes.
The Trajectory application uses a patented process to create and study “virtual epidemics” to examine a wide-variety of programs. We provide critical feedback loops that prove the value of digital health, population health and other interventions.
Contact us today to learn more how Schooner Strategies, powered by Trajectory® Healthcare, can support your business mission.
Use claims to compare defined population with age-gender matched data. Deep dive investigations can include:
Identify probability scores to help predict future high risk individuals in programs through:
Evaluate and verify the clinical and financial impact using retrospective and real time data, including “what if” scenarios:
We leverage the best of epidemiology science and statistical evaluation to provide critical feedback loops that demonstrate a link between programs and outcomes. Many information sources help power this analysis, including medical and RX claims, lab results and patient surveys. The Trajectory data analytic engine creates and customizes study designs that validate the impact of interventions more accurately than other evaluation approaches or tools.Click here to learn more
Telehealth is use of medical information exchanged from one site to another via electronic communications to improve a patient’s clinical health status.Click here to learn more
Digital health represents the convergence of digital technologies with care interventions to improve the efficacy and efficiency of the healthcare delivery system.Click here to learn more
Mr. Carneal has researched, written and published extensively on quality, health insurance, population health, information technology, and regulatory trends. He has brought to market over two dozen accreditation programs in healthcare and has an established track record supporting the policy, research and business development needs of his clients.
Dr. Wilson is an epidemiologist specializing in the design, evaluation, and science-based improvement of population health programs. He is the Founder of Trajectory ® Healthcare LLC, which uses “virtual” epidemics and other statistical verification methods to demonstrate outcomes Dr. Wilson is a thought leader in the comparative effectiveness field.
Trajectory can provide independent and verified proof that a telehealth program is improving clinical outcomes and reducing costs. In addition, Trajectory’s evidence and consulting expertise can help identify the improvements you need to make to achieve the outcomes you are targeting if your program is not fully optimized.
Telehealth (and telemedicine) is typically defined as the use of medical information exchanged from one site to another via electronic communications to improve a patient’s clinical health status. Telehealth includes a growing variety of applications and services using two-way video, email, smart phones, wireless tools, and other forms of telecommunication technology. Some payers and other stakeholders are skeptical that telehealth programs add value, while others believe they improve access and strengthen many types of clinical interactions.
The diverse array of telehealth services in the marketplace require a customized approach that is grounded on a solid, evidence-based foundation to assess outcomes. Trajectory leverages the National Quality Forum’s telehealth outcomes framework that was published in 2017 and ClearHealth Quality Institute’s new Telemedicine Outcomes Evaluation methodology to accomplish this goal.
Many self-funded plans use a variety of health interventions to coordinate care for chronically ill and complex populations. Telephonic case management has served as a cornerstone of many such population health programs. In this case study, a self-insured employer wanted an independent assessment of the return-on-investment (ROI) for its 3rd party care management program. The vendor, using a pre-post measurement technique, purported its program would achieve a 10:1 ROI. Although the plan found some cost savings after implementing the vendor program, the overall spending by “super users” continued to increase year-after-year. These results seemed at odds with the anticipated savings that should have been achieved if the vendor’s ROI claims were accurate. A study was undertaken to better understand why plan health care costs were still rising for a sub-set of the population.
Trajectory designed a retrospective study which created two comparable populations: The first included patients who received telephonic case management services who reached a high-cost threshold (“super users”) The second – identified in the same fashion from the prior year – was a similar group in terms of demographics and health conditions but did not receive telephonic case management services (the “referent group”).
While people who previously had been “super users” were much less likely to be “super users” after receiving a telephonic case management intervention, the ROI – now accurately measured by Trajectory –was less than the pre-post study result reported by the vendor. Specific findings for the group receiving telephonic case management (compared to the referent group) included: The average per person medical cost was $6,000 less annually; the cost of the case management program was approximately $3,000 per person. The actual ROI achieved for telephonic case management was 2:1 ($6,000 saved vs $3,000 spent), not the 10:1 claimed by the vendor. The company withdrew from the vendor program and brought case management in house, along with access to the Trajectory portal and consultation from the Trajectory team. Trajectory continued to provide secondary analyses, including risk scoring, reviews of individual patient factors (e.g., diagnoses, procedures, pharmacy utilization), and established feedback loops on medical trends and costs for “super-users.”
Trajectory determined the true ROI for a 3rd party case management program. These findings led to a replacement of the vendor product with an in-house care management program supported by Trajectory data analysis and consultation services which helped plan medical staff develop and implement customized care plans. These changes in strategy have continued to drive better clinical outcomes and cost savings.
The Trajectory evaluation model helps demonstrate to key stakeholders how a digital health solution such as a remote patient monitoring (RPM) program is making a difference. And if the program is not fully optimized, we can show the client - using Trajectory generated evidence and consulting expertise - how to make real time, evidence-based tweaks to improve the outcomes they are targeting.
Digital health represents the convergence of digital technologies with care interventions to improve the efficacy and efficiency of the healthcare delivery system. Its footprint is broad based and is constantly changing.
For example, RPM interventions have been gaining traction in recent years, including an uptick due to the reimbursement codes issued by CMS for several types of RPM services. The concept often includes some form of telecommunication or digital technology to collect medical and other forms of health data from individuals in one location and electronically transmit that information securely to health care providers in a different location for clinical assessment, disease monitoring and analysis for potential clinical intervention with the patients care team.
However, digital health applications like RPM devices can mean different things to different people. So, it is imperative that we study these new emerging care treatment trends to promote the best evidence-based pathways.
With digital health (like wearable monitoring devices), the evaluation solution should use comparative evaluation techniques. These can be of three (3) types, listed in order of evaluation power:
A remote patient monitoring (RPM) company contacted a Medicare Advantage Plan about using a wearable safety alert device to promote patient safety and reduce cost of emergency room visits and inpatient stays. In response, the Plan’s strategic management team asked if the RPM company could work with an independent 3rd party to evaluate the efficacy of the device in a population with congestive heart failure (CHF).
Trajectory designed a prospective study, with a randomized, risk-matched CHF population into two groups, one cohort that used the device and one that did not. The RPM company believed (hypothesized) the device would: a) bring peace of mind to the seniors and family members; b) increase the likelihood of re-enrollment into Medicare Advantage; and c) lower utilization costs, especially inpatient costs. The study was designed to last 9-12 months; the first 3 months were used to install the device on those selected to receive the device; the start date for each person was the date the device was installed, the start date for the reference was randomly selected from all the start dates of the intervention group. Each patient and their age-, sex-matched control were followed for 6 months (due to delayed claims run out the team needed the full 9 months to get data on everyone). After the study was completed a survey was generated for a random sample from each group. A report was generated month-by-month (after the 3-month lag) and published after 6 months of data was available and the survey was completed.
The survey found that the “peace of mind” hypothesis was a major factor among RPM users. The overall satisfaction with the health plan – as a marker of likelihood to re-enroll—was higher in the RPM users than the comparator group. The overall cost of care was lower in the wearable device population, but it was not statistically significant. The inpatient costs were lower in the wearable device population for the 1st three months (p<0.05) and still lower (but less so) for the entire 6 months (p=0.54).
Inpatient cost savings were superior in the RPM cohort but did appear to drop off after the first three months and then some more after the second three months (as did use of the RPM device). This provided an important feedback loop to both the RPM Company and the Medicare Advantage Plan. If the parties can make sure that the “safety alert” device continues to be used over time, it can continue to improve clinical outcomes and promote savings. But the ongoing success is tied to finding updated strategies to promote patient engagement after six months. This could include creating incentive programs for patients to continue actively wearing the device, among other options.
Healthcare organizations must move quickly to assess the clinical and financial efficacy of their programs and product solutions. Trajectory offers a rapid research study design that can make this happen!
Dr. Wilson has conducted rapid epidemiological studies since 1989 in the West Indies, Africa, and the United States. After initial planning and sign-offs, these studies were completed- including data collection, analysis, report writing and presentation – in just 2 to 6 weeks. One study used cluster random sampling to detect prevalence of diabetes, heart disease and hypertension in an island nation in the Caribbean; a second examined salt intake (via 24 hours urine sample), blood pressures and BMI in one country in Sub-Saharan Africa; a third looked at cardiovascular risk factors in a work place in a self-insured employer group. The third program morphed into virtually instant reporting based upon an iPad generated Health Risk assessment; with yearly reports on the relationship between “heart age,” cardiovascular risk factors, and cost of care.
Once a study is designed, metrics described, and data prepared in a structured format, a full report based on retrospective data can be analyzed and a report delivered very quickly. This is accomplished by software that has been developed based on over two decades of real-world experience in the health care space.
A nationally recognized accreditation agency partnered with a national health plan to assess how the age of the ultrasound machine could affect quality. To test the validity of this hypothesis, our researchers looked at regulations, peer-reviewed literature, expert opinion, and then completed an analysis by studying trends in claims database. The findings from a regulatory survey, literature review, and expert opinion supported the hypothesis that there was a correlation between the increasing age of an ultrasound machine and a decrease in quality of the ultrasound images.
Trajectory was engaged to conduct a study to analyze the impact of information both in the accreditation agency and the health plan’s databases. The study used claims data to look at the number of ultrasounds that were done twice on the same person over a short period of time based on the age of the ultrasound machine. The researchers used the frequency of repeat scans within a short period of time as the primary indicator of quality.
The Rapid Response study did find a correlation between the quality of the image and the age of the machine. While the analysis data did not indicate a clear cut-off point that results in a large increase of repeat scans, there was a trend suggesting machines older than nine years had the highest repeat rates, which was detected in both parts of the study.
Once this retrospective study was designed the results were completed within weeks. The overall findings of this research paper supported the premise that the age of ultrasound equipment can impact image quality. Based on the study results, the accreditation agency and health plan updated their imaging certification program to adjust for machine age. The findings also highlighted the need to track related variables that might impact quality, such as the upgrades to the transducer probe, frequency of usage, and other key factors.