Anupam Goel, MD, VP of Clinical Information, Advocate Health Care
Instead of focusing on patients and clinicians interacting during a healthcare encounter — or between healthcare encounters, I’m writing this post about patient-facing technology that could address population health challenges. In 1991, Robine and Ritchie proposed healthy life expectancy as a global indicator of changes in a population’s health. Multiple factors outside the healthcare system would play a role in healthy life expectancy: sex, age, socioeconomic group and disease burden. In 2002, Dr. Michael Hillman testified before the House Health Subcommittee of the Ways and Means committee and referred to Evans et al., who wrote a report to describe the multiple determinants of the health model, including inputs such as the social and physical environment, as well as genetic endowment that lead to an individual’s response. In quoting Fos et al. from Designing Health Care for Population: Applied Epidemiology in Health Care Administration, Dr. Hillman stated that population health includes these objectives:
- Reduction in volume of services utilized
- Shift of utilization to lower-cost settings
- Achievement of clinical improvement by focusing on the health status of the population
- Integration of healthcare services
- Organization of providers into networks
- Evaluation and documentation of quality
Dr. Hillman went on to state that patients, and the information with which they make decisions, are no longer solely dependent on their physicians. To accomplish the first three goals, mechanisms must be in place to assist patients in becoming active, empowered participants in their own healthcare decisions.
Goodarz et al. published an article in April 2009 ranking these 12 dietary, lifestyle and metabolic risk factors leading to preventable causes of death in the US:
- Tobacco smoking
- Overweight-obesity
- Physical inactivity
- High blood glucose
- High LDL cholesterol
- High dietary salt
- Low dietary omega-3 fatty acids
- High dietary trans fatty acids
- Alcohol use
- Low intake of fruits and vegetables
- Low dietary polyunsaturated fatty acids replaced with saturated fatty acids
The article includes additional analyses by sex and age subgroups. Each of these risk factors can be stratified into different levels based on exposure (e.g., levels of physical activity).
Thaker et al. published an assessment in 2006 ranking the leading causes of disability-associated life years in the United States (the source was dated 1996):
- Ischemic heart disease
- Cerebrovascular disease
- Motor vehicle crashes
- Depression
- Lung cancer
- Chronic lower respiratory disease
- Alcohol use
- HIV
- Diabetes mellitus
- Septicemia
Tobacco use, physical activity, and a healthy diet seem to play a role in both mortality and morbidity. Mental illness, alcohol use and unsafe sex have a role in Americans’ morbidity.
Role of patient-facing technology
Smartphones and their associated applications open up the possibility of delivering behavioral health tools to populations rather than waiting for someone to arrive at a healthcare setting. The American Heart Association has been promoting their “Life’s Simple 7:”
- Manage blood pressure
- Control cholesterol
- Reduce blood sugar
- Get active
- Eat better
- Lose weight
- Stop smoking
An analysis earlier this year found patients who achieved more of these lifestyle changes also had better brain health. The two most important behaviors for maintaining brain health appeared to be reducing blood sugar and quitting smoking. For most Americans, focusing on the “Simple 7” should reduce their risk of developing cardiovascular disease, pulmonary disease and obesity-related conditions.
As a physician, informaticist, and healthcare consumer, I would like to see smartphone apps developed or refined for the following behaviors. Please note, most healthcare apps have not been rigorously tested against best care without an app or even usual care:
Quitting smoking. Multiple apps dedicated to this exist today. There’s even an app to deliver a mild electrical shock to help reinforce the need to quit smoking.
Physical activity. Until the operating characteristics of mobile apps improve to detect physical activity, apps may serve as a place to track time and distance rather than precisely calculate calories burned.
Diet. There are many apps already in this space, but, to my knowledge, none that have been shown to help patients reduce caloric intake to lose weight or reduce a user’s percentage of body fat for more than a few weeks.
Medication adherence. Like the diet apps, many apps currently exist, but the evidence to support their use is thin.
Mental health. More apps here, but very little evidence to support making a formal recommendation.
Safer driving. The three features that might have the greatest impact would be:
- A breathalyzer to be validated before starting a car, and
- Disabling all texts to reduce the likelihood that a driver will take their eyes off of the road.
- Limit a car’s maximum speed to reduce the risk of high-speed accidents
Patient Expectations of Their Apps
The FDA has stated its interest in regulating apps that provide patients specific recommendations for behavioral change like smoking cessation. At least one website states that the FDA will only approve 20 apps a year, so the absence of the FDA stamp of approval may reflect bad luck instead of the FDA rejecting the app after a thorough analysis of the app’s capabilities.
Some considerations for patients and caregivers might include:
- Any patient-entered data is only shared with the app owners and other patients after obtaining explicit permission that can be changed at any time. In a recent JAMA research letter, less than 20 percent of diabetes-related apps had a privacy policy. Of those that did have a policy, different apps had different levels of data sharing that could be controlled by the patient.
- The app should be able to download patient-specific data into an Excel file or pdf for review with family members or other members of the healthcare team. If the patient decides to move to a different app, there should be some ability to transfer relevant information across apps. This last statement may depend on meaningful data standards that may not yet exist.
- The app should accommodate changing patient preferences. Patients’ lifestyles can change over time and their apps should allow for adjustments over time.
Ideally, patients would only use apps validated with double-blind, randomized controlled trials to help change a behavior or reach a personal goal. Since technology adoption usually outpaces testing or oversight, healthcare providers may be left providing more generic advice to patients and their caregivers about using health IT to drive behavior change.
If America is going to improve its healthcare delivery system without driving other parts of the economy into bankruptcy, engaging patients to manage their own health outside the healthcare system will be critical. Dr. Thomas Farley, current health commissioner of Philadelphia, worked with his predecessors in New York to demonstrate health improvements across communities using public health policies like restrictions on tobacco use. These interventions may even play a role in reducing health disparities. Health systems tasked with improving community health should consider deploying mobile health apps to help reinforce behaviors that may reduce morbidity and mortality through channels outside their offices and hospitals.
[This piece was originally published by Anupam Goel, VP of Clinical Information at Advocate Health Care, on his blog page. To view the original post, click here.]
riteshpatil732 says
Very informative post.Thank you for sharing