Description of the Sector Landscape
The Health Information Technology Sector has many components. We are looking specifically at EMRs, Informatics, Analytics and Devices. By analyzing the current state and trends, we can predict what each of these pieces of the Health IT will look like five years down the road.
EMR
In the past, health data that is collected during care was recorded on paper. EMRs offer immense opportunities to improve patient care at the point of delivery by using this data and changing typical workflow. Adoption, however, has been slow because of barriers including cost, lack of expertise or technical knowledge and problems with interoperability.
With recent legislation, however, there is a major shift with financial incentives for healthcare organization that are able to attain “Meaningful Use”. There has also been a trend to address complicated reimbursement issues using data entered into the EMR. Many EMR companies have also, in an effort to improve efficiency in healthcare delivery, are offering mobile services.
In the next five years, we will see significantly better adoption of EMRs. EMR companies will compete on how their product address associated issues such as efficiency and reimbursement. In addition, EMR companies will begin using cloud services. Patient data will have the capability of be entered on mobile device, either by the patient or a provider. The reimbursement cycle will be sped up as hospitals have more information and use that as power over insurance companies.
Informatics
Clinical data includes data collected throughout the drug development lifecycle, starting with the R&D. This includes data about clinical trial management, pharmacovigilance both before and after drug launch and data in the hospital information systems. Historically, this data has been in paper form. Paper-based data collection has multiple pitfalls including the fact that it is extremely hard to correlate and make sense of data. There are also challenges for the FDA in terms of validating data and finalizing approvals.
One of the major shifts in the digital era has been the electronic information systems. Data today is collected from multiple sources and stored in data bases across the world. There are enough infrastructures, not just to store the humongous amount of data, but also to normalize the data and gain insights. With redundant systems making this data fail-safe, cloud infrastructures have enabled real-time access to data by all stake holders.
While aggregating and normalizing data from conventional sources including biopharma, CROs, providers and insurers pose challenges currently, the future could be defined in terms of a shift in patient control of data. Given the sensitivity of the data, it is only fair that the patient has enough control on both access of the data and data entry itself. For example, in order to minimize human intervention, chip implants in humans (which is already history) could gain more momentum in terms of personal health data governance and monitoring.
Analytics
Currently analytics are used to realize cost savings for medical payers. Predictive models are implemented by insurance providers to identify fraud and to estimate future costs for more accurate planning and risk reductions. The digitization of historical, present and future medical data is creating the availability of “Big Data.” Less than 20% of medical delivery practices are currently able to conduct clinical decision support.
In the next 5 years analytics will be a capability to enable clinical decision support to reduce medical costs associated with time, errors, and inventory. Cloud computing, mobile technologies and government regulation imply more data will be available and accessible anytime anywhere. These trends suggest that analytics may enable personal preventative health opportunities.
Medical Devices
Major electro-medical equipment companies like GE, Siemens, and Philips have enjoyed healthy profit margins over the past 20 years. That environment is rapidly changing as Moore and Metcalf’s laws drive down the technical barriers to entry and drive up the importance of connectivity. Customer lock in will be hard to maintain, as the meaningful-use mandate forces interoperable standards for medical information.
Increasingly, medical device functionality is encapsulated into broad hardware platforms like the iPad and smartphones. To drive value, the big three are moving away from devices that capture patient information (where they see competition from companies like Apple and Nike) and towards security and analytics (where they now compete with IBM and Lockheed Martin). A linchpin for the industry will be how the FDA and CE change their requirements for consumer medical software. If these organizations were to restrict the medical apps market (currently only Apple reviews such programs), it could strengthen the position of the existing major device companies.
Conclusion
Overall, the industry will gain momentum in the next five years. Incentives for greater EMR adoption through the Affordable Care Act will spur adoption. Use of technology to increase privacy will improve informatics. Analytics will be used to drive decision-making, which has largely not been done in healthcare. All of these forces together will increase the influence of the healthcare information technology sector.
EMR
In the past, health data that is collected during care was recorded on paper. EMRs offer immense opportunities to improve patient care at the point of delivery by using this data and changing typical workflow. Adoption, however, has been slow because of barriers including cost, lack of expertise or technical knowledge and problems with interoperability.
With recent legislation, however, there is a major shift with financial incentives for healthcare organization that are able to attain “Meaningful Use”. There has also been a trend to address complicated reimbursement issues using data entered into the EMR. Many EMR companies have also, in an effort to improve efficiency in healthcare delivery, are offering mobile services.
In the next five years, we will see significantly better adoption of EMRs. EMR companies will compete on how their product address associated issues such as efficiency and reimbursement. In addition, EMR companies will begin using cloud services. Patient data will have the capability of be entered on mobile device, either by the patient or a provider. The reimbursement cycle will be sped up as hospitals have more information and use that as power over insurance companies.
Informatics
Clinical data includes data collected throughout the drug development lifecycle, starting with the R&D. This includes data about clinical trial management, pharmacovigilance both before and after drug launch and data in the hospital information systems. Historically, this data has been in paper form. Paper-based data collection has multiple pitfalls including the fact that it is extremely hard to correlate and make sense of data. There are also challenges for the FDA in terms of validating data and finalizing approvals.
One of the major shifts in the digital era has been the electronic information systems. Data today is collected from multiple sources and stored in data bases across the world. There are enough infrastructures, not just to store the humongous amount of data, but also to normalize the data and gain insights. With redundant systems making this data fail-safe, cloud infrastructures have enabled real-time access to data by all stake holders.
While aggregating and normalizing data from conventional sources including biopharma, CROs, providers and insurers pose challenges currently, the future could be defined in terms of a shift in patient control of data. Given the sensitivity of the data, it is only fair that the patient has enough control on both access of the data and data entry itself. For example, in order to minimize human intervention, chip implants in humans (which is already history) could gain more momentum in terms of personal health data governance and monitoring.
Analytics
Currently analytics are used to realize cost savings for medical payers. Predictive models are implemented by insurance providers to identify fraud and to estimate future costs for more accurate planning and risk reductions. The digitization of historical, present and future medical data is creating the availability of “Big Data.” Less than 20% of medical delivery practices are currently able to conduct clinical decision support.
In the next 5 years analytics will be a capability to enable clinical decision support to reduce medical costs associated with time, errors, and inventory. Cloud computing, mobile technologies and government regulation imply more data will be available and accessible anytime anywhere. These trends suggest that analytics may enable personal preventative health opportunities.
Medical Devices
Major electro-medical equipment companies like GE, Siemens, and Philips have enjoyed healthy profit margins over the past 20 years. That environment is rapidly changing as Moore and Metcalf’s laws drive down the technical barriers to entry and drive up the importance of connectivity. Customer lock in will be hard to maintain, as the meaningful-use mandate forces interoperable standards for medical information.
Increasingly, medical device functionality is encapsulated into broad hardware platforms like the iPad and smartphones. To drive value, the big three are moving away from devices that capture patient information (where they see competition from companies like Apple and Nike) and towards security and analytics (where they now compete with IBM and Lockheed Martin). A linchpin for the industry will be how the FDA and CE change their requirements for consumer medical software. If these organizations were to restrict the medical apps market (currently only Apple reviews such programs), it could strengthen the position of the existing major device companies.
Conclusion
Overall, the industry will gain momentum in the next five years. Incentives for greater EMR adoption through the Affordable Care Act will spur adoption. Use of technology to increase privacy will improve informatics. Analytics will be used to drive decision-making, which has largely not been done in healthcare. All of these forces together will increase the influence of the healthcare information technology sector.
Healthcare Industry value chain
Given the complexity of the healthcare industry, it is a bit complicated to devise a value chain based stack model for the industry. This in part stems from the fact that the information flow is across different layers and not linear. We try to visualize the industry in two perspectives. First, based on care and second, based on Information flow.
Care Stack:
As far as care is concerned, the first step in the process will be the discovery of drugs through biological / molecular research. This research is then taken forward by the Bio-pharma companies. Medical devices such as Diagnostic devices, Information recording devices (ECG), etc can also be seen in this layer of the stack. This is then passed on to the patients through the providers. The position of the payers could be a bit complicated since they cannot be visualized as the consumers of the service or care. However, they play a critical role in facilitating the care delivery to the patients. Thus, the stack can be visualized as below.
Information Stack:
Having tried to understand the industry from the care delivery perspective, we tried to map the information flow in the industry. The firms we have chosen fit into multiple layers on this stack. However, we would be concentrating on products specific to one or more layers in the stack.
Information Players in the Healthcare Industry
Here is one view of an industry map of the Healthcare industry. Because of the many linkages that exist, we see the potential for disruption coming from the players that best use Technology to create and capture value.
Our team will examine companies who are positioned to offer Software and Analytics capabilities. Specifically:
Allscripts (Katy Perkins)Athena Health (Nader Mousa)Microsoft (Wishwas Mohan)Verisk (Eli Mather)
Additionally non-profit institutions have a cause and effect relationship with potential disruptions. Therefore, we will also explore the analytics capabilities ofMassHealth.(Chris Glenn)
Do you agree with our view of the industry? Can you think of other companies that are positioned to enter or exit the industry? Do you think incumbency or capability will win out in the next 5 years?
Our team will examine companies who are positioned to offer Software and Analytics capabilities. Specifically:
Allscripts (Katy Perkins)Athena Health (Nader Mousa)Microsoft (Wishwas Mohan)Verisk (Eli Mather)
Additionally non-profit institutions have a cause and effect relationship with potential disruptions. Therefore, we will also explore the analytics capabilities ofMassHealth.(Chris Glenn)
Do you agree with our view of the industry? Can you think of other companies that are positioned to enter or exit the industry? Do you think incumbency or capability will win out in the next 5 years?