Healthcare Analytics
An introduction and brief overview of the different analytic tools that are currently used in healthcare delivery and how these tools can be optimized and engineered for the future of healthcare.
Oliver |
Target audience: Students who graduated with biology degree and plans to pivot to other fields.
As biology students, we all have experience conducting molecular or cellular biological experiments that take several hours just to wait for the reaction to happen. The time-consuming, tedious, and highly repetitive experiment protocols confine us in the laboratory for too long. You might agree with me on the argument but also want to ask: if I’m tired of wet-lab experiments, why not choose to become a bioinformatician? Especially when we are in an era of explosion of genomic data, the future of bioinformatics is promising. However, what if we are not interested in DNA sequence and protein structure simulation? What are other possible paths we can pivot to as a biology student who is interested in data science? There are several different answers to the above question, and I believe clinical informatics is definitely one of them. Clinical informatics is concerning the use of health information technologies and valuable data to improve our healthcare system to provide patients with higher quality, more cost-efficient, more accessible, and more personalized care. As the advance in our knowledge of healthcare and the recognition of the pitfalls of the current healthcare system, we are moving from fee-for-service health delivering model to value-based healthcare, where we care more about quality than quantity and emphasize on whether the proposed interventions, treatments, or delivery models have actually improved patients’ outcome. Before we dive into the possible solutions, we must first identify what are the problems our healthcare system is facing right now. The challenges faced by the healthcare system can be categorized into four big categories: cost, quality, accessibility, and satisfaction. It’s astonishing to know the percentage of GDP that the U.S has invested in the healthcare system, nearly 20 percent every year. Even with this amount of investment in healthcare, many may argue that the quality of care consumers receiving does not seem to be proportional to what we invest. The low quality of care can result from medical errors including prescribe allergic medications, neglect the adverse drug effect caused by drug-drug interaction, etc. The challenge of accessibility can be viewed from the equity point of view that how can government propose the insurance plan like Medicaid and Medicare that can cover most of the citizens in the U.S. On the other hand, accessibility is also concerning how can technologies help to provide healthcare to citizens who live in the rural area and cannot receive routine care as convenient as others. Finally, the last big issue face by the healthcare system is how to improve satisfaction not only for consumers but also for all the actors in the health delivery process. One of the frameworks that can guide us to address the above challenges is the STEEEP framework where STEEEP stands for safety, timely, efficient, effective, equitable, and patient-centered care. By keeping the challenges facing by the healthcare system and STEEEP framework in mind, we can identify what are we trying to address and how. Now we know the challenges and framework that can guide us for proposing the solution, it’s important to know what some of the effort other have tried and fixed and what new problems are emerging in clinical informatics. Although the 2008 HITECH act has successfully incentivized the transition of paper-based records to the electronic health records, the initial of letting patients access their data, improving communication between healthcare givers and between providers and consumers, and minimizing the medical errors are far from fulfilling. Another topic must discuss in clinical informatics is clinical decision support system that aims at assisting the decision support process for either healthcare givers or consumers by displaying the information or proposing the recommendations at the right time to the right person. Even though the data, electronic health record, and health information technologies, clinical decision support system, attract a lot of hype, the lack of consideration of human factor engineering and social-technical analysis results in the clinical decision support system that proposes information and recommendation in the wrong time to the wrong person through the wrong approach. Furthermore, the lack of data standard and framework to guide the health information exchange also hinder the meaningful aggregation of data that can be shared with patients or serve as valuable input for analytics tools for secondary usage. Data standards in health information exchange, data quality, completeness, and provenance issue in healthcare data analysis and prediction, and human-computer interaction between healthcare givers and health information technologies are the emerging issues that need to be solved by us. Except for EHRs and clinical decision support, researchers have also proposed new health delivery model: patient center medical home, that aims to provide coordinated, continuous, and patient-centered care; however, we are far from fully realizing its potential because of the same new challenges faced by EHRs and CDSS. Clinical informatics not only focuses on the technical and research topics but also how to manage change when incorporating a new health delivery model and concerning data privacy, confidentiality, and security issue. |
Dakota |
In recent years, healthcare has become an increasingly hot topic in the US. With more and more attention given to it every year, it has become increasingly apparent to the general public that the healthcare system which the US currently operates is ineffective, exorbitantly expensive, and outlandishly complicated. Over the past several months in this course, I have learned through articles, both academic and otherwise, that the US healthcare system is the most administratively complex and costly healthcare system in the world. This is something that I believe many Americans are aware of, at least in some capacity. However, it seems to be a general line of thinking that because we have such a robust administrative component to healthcare and because we put so much money into it that it must be the best healthcare system in the world. With medical errors being estimated as the third leading cause of death in this country, it then becomes complicated. How could our medical system be the most expensive and complicated one in the world yet still be so ineffective? It has become apparent to me that our healthcare system is not just flawed, it is fundamentally broken beyond repair.
To “fix” our healthcare system is going to require a complete overhaul on the governmental level which is going to require activism and voting of the right people. However, there are still things that we can do today in order to improve the state of healthcare. In 2008, the signing of the HITECH act marked a massive and abrupt transition towards the digitization of healthcare delivery. The speed with which this transition took place has caused many problems in the switch to electronic healthcare but this exposure is necessary for us to understand what went wrong and how to fix it. The future of healthcare lies in the digital world. With nearly every hospital in the country now operating with electronic health records (rather than paper records), there are massive amounts of health data being captured every day into online platforms. With some clever computer engineering, some data analytics specialists, and some convincing of the right people in the government, these electronic platforms have the potential to communicate easily and effectively with one another in order to make your routine health visits more effective, less costly, and less time-consuming. Far-off medical fantasies such as the medical androids in Star Wars with completely computerized medical providers are quickly becoming a more likely reality for us. With softwares that can double-check physician diagnoses, prognoses, and even surgical procedures, there is the very immediate potential for us to see massive reductions in medical errors in our lifetime. And these are only the primary benefits. If done correctly, these digital health platforms have the potential to aggregate mass amount of health data in order to start to recognize new patterns that humans have never noticed before and to that end, the state of individual prognosis, rare disorders, and even public health have nothing to lose and everything to gain. Indeed, we already have all the technology we need in order to fundamentally revolutionize the way healthcare is delivered in the US. In order to see these changes happen, however, it is going to require the continued and fervent support of your voice in order to give these tools a chance to make a difference. |