Digital Health Information for the Consumer
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Paul Huntington. Peter Williams. This unique book draws on research that constituted the first major nationwide evaluation of the use and impact of key digital health information platforms which were provided to thousands of health consumers in the UK. The authors offer the first comprehensive and detailed comparison of usage and impact of the three major ICT platforms delivering health information - the This unique book draws on research that constituted the first major nationwide evaluation of the use and impact of key digital health information platforms which were provided to thousands of health consumers in the UK.
The authors offer the first comprehensive and detailed comparison of usage and impact of the three major ICT platforms delivering health information - the internet, touch-screen kiosks and digital interactive television. It provides an extensive reference source on how health consumers behave when online, whether this differs according to digital platform or type of user, how users perceive digital health services and what health benefits these services deliver.
The book will be invaluable reading for all those interested in digital health information - students, academics, health policy-makers and information managers. Get A Copy. Published April 22nd by Routledge first published January 1st More Details Other Editions 6. Friend Reviews. To see what your friends thought of this book, please sign up. To ask other readers questions about Digital Health Information for the Consumer , please sign up.
Be the first to ask a question about Digital Health Information for the Consumer. Lists with This Book. This book is not yet featured on Listopia. Note: Consumers were asked in an open-ended format about willingness to pay for various genetic tests. Because of the attention direct-to-consumer tests have received and the gap for incorporating genetic tests in clinical settings, we wanted to gauge consumer receptivity to various condition-based tests depending on the following attributes: 1 The use case clinical, wellness, or lifestyle 2 Level of actionability i.
People were least willing to pay for a test that provides insight on slow metabolism, likely because the genetic test would not reveal anything previously unknown. As a final note, we found no difference in willingness to pay whether we asked the question in the affirmative a test that confirms you will get a disease or the negative a test that confirms you will not get a disease. Consumers have a high willingness to share their health records and genetic data, especially with physicians and family members, suggesting that trust plays an enormous role. Consumers were almost as likely to share health data with insurance companies as with family members, but trust for insurers dropped significantly when sharing genetic data.
This may stem from concerns about genetic data being used against consumers when obtaining insurance. Although the Genetic Information Nondiscrimination Act GINA specifically forbids health insurers and employers from using genetic data to deny coverage or increase premiums, the act does not cover long-term care insurance or life insurance. Consumer confusion is not helped by state laws that provide varying degrees of protection. Of the technology companies we included in our survey, consumers had the most trust in Google, despite other companies like IBM and Apple having a stronger presence in the genomics field.
However, consumers were still hesitant to share their genetic data—even when offered benefits like lower insurance premiums, improved clinical trial outcomes, and cash. In fact, there was a negative association with receiving money for sharing genetic data. However, as consumers become increasingly responsible for managing their own health for further reading on this trend, see our Digital Health Consumer Adoption report and genetic data, it may become more acceptable for them to also receive compensation in return.
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For now, the best approach for genomics companies continues to be providing consumers with valuable and actionable use cases in return for sample and data submission. Interoperability and APIs are the key. As explored previously, consumers derive value from three categories of genetic tests: clinical, wellness, and lifestyle.
Despite great interest in genomics, many consumers fail to see a clear value proposition for why they should take a genetic test. The question is: in what ways can the industry increase the number of useful tests available or increase their value to consumers? After speaking with more than thirty firms, we identified three potential ways to incentivize consumer buy-in. First, companies such as 23andMe break down the primary barrier to mass consumer appeal by creating affordable, easily accessible, and enjoyable products that encourage even the most hesitant consumers to buy, due to limited downside.
Similarly, companies offering products that generate value long after the genome is initially sequenced i. A third approach is one in which physicians and health systems drive data collection. We spoke to several innovative health systems including Intermountain Healthcare and found that many providers are recommending that broader patient populations i.
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Intermountain is working closely with Syapse, which makes a product that simplifies the integration of genetic tests into clinical workflow. In addition to simply generating more data, the industry needs to improve at every point along the genomics cycle by better digesting, comprehending, and reporting on the value of that data.
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Historically, progression through the genomics cycle was limited by the high cost of sequencing. But advances in life science technology have pushed sequencing costs down and advances in computing power and storage e. Amazon Web Services have made processing and storage attainable for most labs. Although surely some of this can be solved by algorithms, the process requires highly specialized bioinformaticians to undertake a nuanced method for testing each hypothesis they investigate.
Now, assuming that the first two requirements—more and better data and interpretation of that data—are satisfied, what remains? Note: GINA is the Genetic Information Nondiscrimination Act of intended to forbid the use of genetic information in health insurance and employment decisions.
Digital Health Information for the Consumer: Evidence and Policy Implications
Two of the last remaining hurdles for genomics adoption stem from unclear regulation and limited reimbursement options. Regulations determining which tests are sold and how information can be used are constantly evolving. To date, the only act to specifically dictate post-test information usage has been GINA, which states that genetic information cannot be used for discrimination in health insurance and employment.
Beyond the fact that regulation is constantly evolving, it is also important to note that a number of parties are involved, further complicating the process. Currently, the FDA regulates laboratory developed test kits for whether the test is accurate and reliable analytical validity , whether it provides medically meaningful results clinical validity , and whether it provides health information that will be clinically helpful to the consumer clinical utility Some states have additional regulations that companies must abide by to sell or develop products in their state e.
New York. Due to heavy and constantly evolving regulations for clinical genetic tests, and relatively limited regulations for wellness and lifestyle tests, many early-stage consumer-focused companies choose to enter the market with non-clinical genetic products.
When a genetic test operates within a closed healthcare loop e. As a result, it is possible to accumulate evidence on the efficacy and cost-effectiveness of tests, which can be used in future care decisions and reimbursement guidelines.
Evidence and Impact on Human Health and the Healthcare System
Many companies are entering the market with tests focused on wellness and lifestyle to avoid FDA scrutiny; yet, these tests do not integrate with the broader healthcare system. As a result, they miss out on the opportunity for a potential feedback loop and rely on consumers for payment, traditionally a challenging channel. It remains to be seen whether genetics tests that offer wellness and lifestyle use cases will undergo scrutiny to be offered as clinical tests i.
Because healthcare systems stand to benefit from understanding which genetic tests drive clinical value, they are especially well positioned to drive demand for clinical tests. Companies that can overcome regulatory, reimbursement, and data hurdles will ultimately provide tremendous value to patients and see big gains. Consumers want and will have access to their genetic data. It remains to be seen whether physicians and experts will continue to serve as intermediaries in making sense of the genome, or whether we will reach a point in which consumers can be stewards of their own data.
For now, it is clear that health systems are well positioned to move the needle in genomics, as they collect data and increasingly rely on evidence to drive clinical decisions. Informatics tools will become more standardized and the FDA will help push that along. Testing will become a commodity. And interpretation of genetic variants will also become a commodity as free public data sources proliferate.
This report would not have been possible without the help of a number of industry partners and startup entrepreneurs who have graciously shared their expertise. We did not consider reimbursement to constitute a customer relationship for the purpose of this report. However, only partnerships that were announced in the last year were included. We found no difference in willingness to pay across the two.
Share this post. Special Topics. Authored by Lauren Devos. Teresa Wang.