These days, we hear a lot of talk about “digital healthcare”. We ought to understand more about what is wrong with our health, thanks to the data that we are accumulating, thanks to electronic health records, fitness apps, gadgets and home genome testing kits. It’s not enough to have a lot data. We must be aware of the data we have, know what it means and take action based on this understanding. The challenges in the United States are more severe because of the fragmented health care system, but they also exist around the world.
This is a very common scenario
June, 67 years old, presents to the emergency room with abdominal pain and bleeding in her rectal area. The tests reveal that the colon cancer is inoperable and has probably been growing for many years. She enters hospice after several unsuccessful and difficult chemotherapy courses. She dies a few weeks later.
Colon cancer can be largely cured and is often preventable, if caught early and precancerous growths are removed. If June had been screened, she might still be alive today. What happened? She had colonoscopies at 50 and 60 on time, but assumed she was safe until 70. No one noticed the radiologist’s note that a few minor irregularities meant she needed to come back at age 63. The radiologist was not responsible for making sure June took action on the findings, which were hidden in her EHR’s “Test Results”. She missed it. She missed it. The entire health care system missed this.
Too many Junes have been lost. The U.S. healthcare system is full of these small mistakes with huge consequences, which cost Americans millions of dollars and years of health life. It’s not surprising that these failures happened when clinicians were relying on paper folders, multipart forms and landline telephones to perform and track their tasks. Since computers, smartphones and the internet are available, they can (theoretically) be used to remind patients to have early colonoscopies.
But digital tools do not use themselves. We must tell them what to. In June’s situation, a combination of systems could have detected and analyzed the data, sent it to her and to her doctor, tracked their responses, made it easy for her “click here” for scheduling her procedure when she turned 63 and followed up with recommendations for testing and treatment. Although “alert exhaustion” is a real danger that must be avoided by clinicians and staff, they will appreciate reminders that are designed to help avoid missed or delayed diagnoses and regrets.
The National Committee for Quality Assurance (NCQA) has been using data since the 1990s to measure and improve healthcare quality. Originally focused on accrediting healthcare plans and now evaluating provider performance, the NCQA’s primary challenge was gathering enough data to draw meaningful conclusions. However, the current challenge is sorting through the vast amount of information to extract valuable insights and ultimately enhance the allocation of healthcare resources.
This article will explain how to close the digital loop between information and action.
Measuring quality: Basic principles
Three questions are at the heart of measuring health care quality.
- Do we do the right thing to manage health care and health?
- Do we get the results we want?
- What needs to be changed?
The outcome of healthcare cannot be easily determined due to the complex nature of individuals and various factors at play. Multiple elements, including the performance and attentiveness of caregivers, the initial health and motivation of the patient, and external circumstances such as income, location, and access to support, influence the outcome of care episodes. Factors like income, environment, and access to transportation and food also contribute to the overall outcome.
Measuring healthcare quality is challenging, but the United States has a mixed reputation in terms of care quality. The country is known for providing excellent care, but also for having high costs. The measurement of quality is underdeveloped due to limited provider incentives and a lack of consumer demand.
The primary reason that quality measurement is limited is because it relies on insurance claims to measure.
Claim Data: A Foundation that is Incomplete for Measuring Quality
In the healthcare industry, claims data has been the primary source for measuring quality of care since the 1990s. However, claims data has limitations as it is often outdated, lacks clinical details, and may not capture vital patient health information unless it financially benefits the provider. Each claim provides only a partial snapshot and cannot capture the dynamic nature of health over time. Therefore, it is important to reflect on results and strive for improvement in future care.
The Era of Digital Measures
The reliance on claims data for measuring healthcare quality is diminishing with the adoption of electronic health records (EHRs) and the availability of additional data sources such as fitness trackers, smartphones, genomics, and population-level data.
The Office of the National Coordinator for Health Information Technology (ONCHTIT) has led efforts to leverage EHR information and promote the integration of diverse data for a more comprehensive understanding of health status and healthcare effectiveness. Both CMS and commercial payers are actively promoting the use of digital data for quality measurement, and organizations are preparing for this new era by developing digital measures and assessing healthcare performance.
Learn from others
The United States can learn from other developed nations, like Denmark, that effectively utilize digital data to improve healthcare. Denmark has a comprehensive electronic health record system and a digital health strategy focused on timely information, patient partnership, prevention, and equity.
The European Union is also working towards creating a single market for digital health. Other countries facing similar healthcare challenges can find value and inspiration in the United States’ efforts to promote digital measures of value and address issues of access, affordability, and quality of care.
A To Do List for Digital Measures
There are four main imperatives that we see to get the United States to where it needs be:
Reduce the cost and improve the timeliness of data collection
It may seem like there are two goals, but digital methods achieve both. In some cases, traditional measures can be rendered irrelevant by using data (such insurance claims), which is often a year behind the actual care.
When designed correctly, electronic health records (EHRs) and wearable devices will generate data that can be used to manage care more efficiently. Once data collection is no longer a separate process from providing care, we can move straight to the analysis and results.
Extend the range of data that can be used
In addition to electronic health records and wearable health monitors, combining patient feedback and environmental information such as air and water quality, crime rates, access to green spaces, transportation, and availability of social services and grocery stores can provide a comprehensive understanding of healthcare outcomes.
The National Committee for Quality Assurance (NCQA) is exploring how to incorporate patients’ social circumstances, such as homelessness, poverty, or isolation, when evaluating quality of care. By analyzing more data about patients and accounting for differences in care requirements based on economic situations, patient self-management abilities, and quality of social support, more accurate measures can be developed.
Use artificial intelligence, mobile devices and electronic health records to guide and provide feedback in real-time.
Electronic health records have evolved from being just a record of a patient’s medical condition and care received, to offering real-time assistance: alerts, notifications, computer-based guidelines on managing chronic diseases, and logic which (tactfully critiques) a doctor’s orders for testing and medication by comparing them with standard practice and checking any inconsistencies. An intelligent EHR could have prompted June to schedule her follow-up colonoscopy at age 63.
Our systems of measuring care quality will become more sophisticated as we incorporate intelligence more tailored to the individual needs and preferences of patients. An intelligent EHR and practice management software will notice that June prefers to have her medical appointments scheduled on Tuesdays. With her consent, it would schedule the procedure the next Tuesday available.
Integrated health systems like the Intermountain Healthcare in Salt Lake City or Geisinger in Pennsylvania have developed digital tools for improving care. Both have the dual advantage of advanced IT capabilities as well as the financial incentive to focus more on improving the health of their patients than on simply delivering services. They and other organizations have used their electronic health records in order to give real-time feedback to patients and clinicians. These systems are able to provide more personalized feedback to patients by reducing costs and expanding the types of data they collect.
Create a digital platform for ongoing production processes that gather, analyze, and report quality measures.
Digital measures are not an overnight project, but rather a constant transformation. This foundation is built on the following:
To improve the standardization and efficiency of quality measures in healthcare, it is necessary to establish a rigorous yet flexible process that ensures consensus on definitions and ranges for various conditions. Replacing paper-based descriptions with software-based measures that can be integrated into clinical systems is crucial.
Collaboration among payers, regulators, and providers is essential for developing and maintaining measures that adapt to evolving illnesses and treatments. Automation through the use of the Fast Health Interoperability Resources (FHIR) standard API will enhance data extraction from electronic health records, improving accuracy and enabling CMS to mandate FHIR-enabled systems for providers in the near future.
Automating auditing and cleaning of data, including medical credentialing services. A large amount of data, but not all of it, in EHRs and clinical systems is entered manually, which can lead to mistakes, omissions, and inconsistent entry methods. Digital measures, supported by reliable medical credentialing services, ensure the accuracy and integrity of the data, making it invaluable for improving outcomes in healthcare.
Every stakeholder in the health care system has a role to play, including creating infrastructure for digital information.
- The community of quality measurement needs to expand and intensify its efforts in order to identify which new data elements will be most useful for identifying the best practices and explaining differences in outcomes.
- Hospitals and insurance companies both have legacy computer systems which struggle to exchange data. To meet the needs of digital measurements, they need a combination of upgrades, standards or workarounds.
- The primary payment for physicians and hospitals is based on volume of care, not quality. This reduces the motivation to change their approach to healthcare delivery. Payment models that are based on value and effectiveness must be adopted by both payers and providers.
- Employers and governments pay the majority of the cost of health care. They have an important role to play by using their influence (contracts and the ability to move provider and health plan businesses elsewhere) to insist that health plans and providers accelerate the adoption of digital measures of quality. Employers and governments can also use their talent to help the industry better understand how the measures will be used to enhance the health-care benefits they offer. Their staff should also participate in forums to define health data standards, as well as the appropriate use of data.
- Patients need these insights to be readily available in a form they can easily interpret and evaluate when making decisions about their health or health care.
Digital Measures and Their Impact
Leveraging the vast amount of healthcare data for measurement and management purposes would bring significant benefits. Providers could enhance their performance by accurately assessing and addressing patient needs, including screenings and managing chronic illnesses.
Patients and their families would have access to digital tools to make informed decisions and find the best possible care. Insurance companies and employers could optimize health benefits in real-time based on current data, improving outcomes and directing resources more effectively. Healthcare has the potential to become a data-driven powerhouse, akin to retailing and financial services, with the ultimate goal of saving lives and promoting overall health.