Small Communities Case Study

Small Communities Case Study

by | Sep 9, 2020 | Health and Wellness, Health Plans

How Analytics Can Impact and Improve the Health of Small Communities (+ Case Study)

Authored by Ayesha Rajan, Research Analyst at Altheia Predictive Health

Introduction 

Community health information can be very revealing; there is a lot to learn from the data of a specified community whether that specification be location, race, gender, occupation, age, or income bracket. However, these are relatively large communities and while that data is incredibly important, small community analytics can be even more targeted and actionable due to the ability to better communicate information to smaller groups. 

Discussion 

The biggest struggle in studying small communities is validity – many statisticians have argued that small community studies do not meet the benchmarks of a sample size to be referenced in other studies and this is a valid concern. However, if you don’t approach smaller studies as ones to be distributed, they can be especially impactful for their communities. Below, we’ve attached a case study from Cerner to demonstrate the importance of small community studies:

 

 

Cerner Case Study

 

Every year, approximately 735,000 Americans have a heart attack. There’s great interest in improving this number — and one of the ways we can contribute to that goal is by quickly identifying symptoms of and treating heart attacks. Troponin tests are commonly used in the emergency department (ED) to identify if a patient is experiencing a heart attack. In an ideal setting, the turnaround for a troponin test is about 35 minutes; most hospitals have a protocol setting of 60 minutes or less.

We recognized an opportunity for improvement with some of our clients around their troponin test rates. We pulled data on individual clients and compared it to industry wide data, and found that while some of our clients had fantastic numbers, others hadn’t had a focus group around this topic and there was room for improvement. If a hospital’s median turnaround time for a troponin test is 45 minutes, for example, that still means that approximately half their tests are taking longer than that.

Though there is currently no troponin test standard mandated by the Centers for Medicaid and Medicare Services (CMS), the turnaround time clearly impacts patient care. Think of it this way: The 25-minute difference in test results is akin to an ambulance arriving to pick up an individual with heart attack symptoms and then simply waiting in the driveway for over half an hour. 

Conclusion 

The study of the health of small communities can seem a little slow but actually has the potential to be extremely interesting! Small community studies can identify several localized issues ranging from issues in infrastructure to specified malnutrition to minor disease networks. Here at Altheia Predictive Health, we are specifically trying to make the research and benefits of big data accessible to small communities through our app. If you know a small company or organization that could benefit from our research, please send them our way!

 

The Most Personalized and Precise Form of Healthcare: a Discussion of the Genome

The Most Personalized and Precise Form of Healthcare: a Discussion of the Genome

by | Sep 3, 2020 | Analytics, Health and Wellness, Technology

The Most Personalized and Precise Form of Healthcare: a Discussion of the Genome

Authored by Ayesha Rajan, Research Analyst at Altheia Predictive Health

Introduction 

Our genomes are essentially a personalized index or library of everything we are – they are the combination of genes and DNA that hold all of our genetic information. The field of genomics is relatively new with most studies citing its roots in the 1980’s. In fact, The Human Genome Project only began development in 1990 and was declared complete in 2003. Though new, the field of genomics, like many other fields of study touched by technology, has evolved rapidly. For context, processing a human genome would have cost $20-25 million in 2006 compared to a cost of well below $1,000 today and its market has seen growth from $1 billion to $4.5 billion in the last 8 years alone. Furthermore, the first time a human genome was sequenced took 3 years of processing power while today a human genome can be processed in less than 3 days. The increased accessibility to genomic information is an incredibly important development in terms of preventative care and can be a life-saving step for many people.

Discussion

The Precision Medicine Initiative “is an emerging approach for disease treatment and prevention that takes into account individual variability in genes, environment, and lifestyle for each person [whose] approach will allow doctors and researchers to predict more accurately which treatment and prevention strategies for a particular disease will work in which groups of people.” This is where genomics finds its highest level of applicability and importance. Genomics and the power that we now have in machine learning can provide incredible insights into which genes are relevant to certain diseases. With that insight, patients can adjust their lifestyle to their risk factor and have a much better understanding of where they stand in terms of their health. Doctor’s also have a much clearer idea of what tests may need to be run a lot earlier in a patient’s life and what tests may never need to be run unless an event occurs prompting questions outside of the norm. Overall, genomics can save a lot of time and money for both providers and patients alike.

One of the struggles with sequencing an  individual’s entire genomic profile is the sheer processing and holding power needed to execute algorithms on an entire sequence – massive database space is necessary to perform these types of analytics. However, one consideration that can be factored into account to make genomics even more accessible is isolated sequencing. For example, if someone already knows their family has a high risk of a certain disease, they may choose to only sequence parts of their DNA, such as the BRCA1 and BRCA2 genes sequenced for those individuals with a higher risk of breast cancer. This methodology can be applied to any genetically passed disease. However, the ultimate hope and goal for many is that genome sequencing becomes accessible enough so anyone can sequence their entire genome. This could then be utilized by healthcare providers who can provide a much more personalized approach to a patient’s diagnosis and care plans with that information. 

Conclusion 

In comparison to many other fields of study, genomics is very new, however, that hasn’t stopped it from catching up (and even outrunning and outshining) many other fields in terms of accessibility. When we look at communities, whether that be by location, ethnicity, age or gender, we get a much clearer picture of how the health of a population is influenced. As accessibility to the technology used to support genomics increases for patients, we can expect that picture to get even clearer and to see an even more personalized approach to healthcare.

 

Improving the ROI of EHRs Through Analytics

Improving the ROI of EHRs Through Analytics

by | Aug 31, 2020 | Analytics

Improving the ROI of EHRs Through Analytics

Authored by Ayesha Rajan, Research Analyst at Altheia Predictive Health

Introduction 

As with any business feature, business owners and analysts must consider whether or not the cost associated with a feature is worth the return on investment. Electronic Health Records, though an integral part of the healthcare system, are a good example of a staple that does not often justify its cost. EHRs, of course, are extremely beneficial within healthcare, however, their high implementation and maintenance costs (think billions of dollars) means that they are not necessarily worth the investment unless steps are taken to optimize their use. Due to the fact that EHRs are ingrained into our healthcare system, the question isn’t whether or not they are worth the investment but how we can make them worth the investment? 

Discussion 

The first and most documented issues with EHRs is their accessibility and readability which limits their usability as well. Additionally, “EHR reports tend to run on a predetermined schedule, limiting how the data within the EHR can be used to evaluate key performance indicators, populations studies, or long-term trends” which further limits their ability to be improved upon. Many investors and market researchers say that the next step in EHR improvement is to invest heavily in programs and softwares that are able to translate the data from EHRs to other softwares so that it can be used across different contexts. This development will allow the power of analytics to significantly improve the return on investment for EHRs by providing insight and direction in terms of  bed management, case management, ED, workforce management, scheduling, and OR management systems [such that] staff can see the upstream and downstream effects of a single operational decision.” This is important because the time it takes to “translate” EHR data means that time has passed since data was collected and, in healthcare, real-time insights and decisions can be critical. Once the issue with readability and context application is solved, EHRs can be used to support predictive analytics endeavors by providing on-demand trend analysis and suggested steps to be verified by physicians. Such insight can cut costs for hospitals by tracking patient flow, for providers by creating demographic reports and for patients by reducing the number of tests needed for diagnosis. 

Conclusion 

The newest development in this space is a Google study’s use of deidentified EHRs to make patient health predictions. Though this project is still in the proof of concept phase, their prediction models have outperformed standard hospital models in every test thus far. This is a promising development in the optimization of EHR use that could encourage further research from smaller companies and at the university level, as well as inspire further investments towards the effort of getting the most out of Electronic Health Records. 

 

 

TeleTracking Technologies

by | Aug 21, 2020 | Health and Wellness, Technology

Concerns Regarding the Trump Administrations Contract with TeleTracking Technologies

Authored by Ayesha Rajan, Research Analyst at Altheia Predictive Health

 

Introduction

A few weeks ago, when the Trump Administration took Covid-19 reporting responsibilities away from the CDC, there were several questions about how data would be processed and whether or not the public could trust the accuracy of new data. Not long after that development, the Trump Administration awarded a company called TeleTracking Technologies a multi-million dollar contract to collect and report on Covid-19 data. However, inconsistencies in reporting and a lack of transparency in collection methods has raised a lot of questions regarding teletracking as a process and TeleTracking Technologies as a company. 

Discussion

One of the biggest causes for concern of TeleTracking Technologies is that they have refused to answer questions regarding Coronavirus data from United States senators due to a nondisclosure agreement with the Trump Administration. This is heavily concerning because it limits the scope of power of other branches of government outside of the executive branch. Lawyers for the company refuse to disclose how TeleTracking Technologies collects and shares its information; in our last article, we heard from physicians and hospital administrators who are extremely concerned that the process in which Covid-19 data will be skewed towards supporting the Trump Administration’s political goals and, given President Trump’s close ties to the founder and CEO of TeleTracking Technologies, this notion does not seem outside of the realm of possibility. This move has been highly criticized by researchers and academics who cannot accurately conduct their own research without transparent data collection and reporting practices.

Finally, a huge concern is that these policy and process changes are coming abruptly and at an awful time. Carrie Kroll, with the Texas Hospital Association, says that “Up until the switch, we were reporting about 70 elements and we’re now at 129… clearly we’re in the middle of a pandemic… this isn’t the type of stuff you try to do in the middle of a pandemic.” Hospitals have been reporting to the CDC with standard practice for over 15 years which means that these changes are a painfully challenging process to push onto hospitals while the Covid-19 Pandemic continues to plague the United States. 

Conclusion 

The transfer of Covid-19 data reporting responsibilities from the CDC to TeleTracking Technologies is ultimately an irresponsible move on the part of the Trump Administration who have put physicians and patients at a disadvantage by pursuing a path that limits the transparency of data to the general public. However, it is our new reality and if we cannot rely on our government to provide reliable data then we can hope that efforts from private companies, such as IBM, can provide researchers and physicians with trustworthy data.

 

 

Can Technology Boost Efficiency in Healthcare? Plus, A Look at Companies Leading the Way

Can Technology Boost Efficiency in Healthcare? Plus, A Look at Companies Leading the Way

by | Aug 13, 2020 | Health Plans, Technology

Can Technology Boost Efficiency in Healthcare? Plus, a Look at the Companies Leading the Way

Authored by Ayesha Rajan, Research Analyst at Altheia Predictive Health

 

Introduction

It is currently estimated that anywhere between 20% and 50% of the U.S. healthcare system costs are due to inefficiency. The troubling part of this statistic is that money could be going in several other places such as investments into healthcare startups or preventative care plans. These excess costs directly affect consumers who, in the field of healthcare, are also patients. However, we now live in a time of increased technological capabilities and, paired with the power of analytics, it can help us decrease redundant care, improve transitions of care and advance provider-provider and provider-patient communication in order to decrease cost waste in the healthcare industry.

Discussion

One of the biggest cost concerns in the healthcare field is communication – paper, phone calls and faxes are all big contributors to inaccuracies and miscommunications. Albert Santalo, the founder of CareCloud, believes technology can bridge a huge gap here. CareCloud is a cloud-based electronic health record provider that hopes to cut the costs of inefficiency by creating a platform that allows for cross communication between providers, billing and consumers. Another big concern in cutting costs in healthcare is the timely entry of data. Hill-Rom Holdings is another company making great strides in the field of healthcare with their smart hospital beds. Their beds ensure that vital signs are entered and time stamped immediately, rather than up to hours later when providers get a chance to enter data into their system. This technology saves money in healthcare by providing physicians with the ability to make accurate and timely decisions regarding a patient’s care plan. Eventually, analytics can further support the goal of accurate decisions further by applying machine learning techniques to the smart bed. 

Another use for analytics in healthcare is to improve the timeliness of when a patient is transferred from the ICU. The current system for transferring ICU patients is reactionary and subject to error but applying analytics to this process can not only reduce costs but can also prevent deaths. This is because opening up ICU beds can make space for those who need it more and because some patients may receive better, more specialized care in another unit.

Conclusion

When it can be estimated that up to half of an industry’s costs are due to waste and inefficiency, it is clear that something should change; when that industry is the healthcare industry, it is clear that something needs to change. There should be no room in healthcare for waste or inefficiency because this is an industry that deals with people’s livelihoods and well-being. Thankfully, the rise of analytics and technology helps create cost-solutions that prevent waste and inefficiency and can improve the lives of patients across the nation.