Hotspotting Has Many Spots To Consider
Hotspotting is a technique that can be used to identify geographic places with lesser health outcomes. It has become quite popular. Is hot spotting just a method to identify populations left behind in health care design? Does it help? Will hotspots receive the resources to resolve hotspots?
It is easy to do hotspotting. Define your geographic area. Collect data about the area. Examine correlations between the data elements. Find the correlations with significant differences. It helps to find correlations that are dramatic or controversial - ones likely to get published and attract attention.
The recent Health Affairs article about diabetic amputations by zip code has increased interest in such studies. The authors appropriately listed limitations of the study, but there are many limitations. These limitations are very important to understand as numerous recent articles about health outcomes have had similar limitations.
Segregation and Hotspotting
Segregation is a word that has long taken on a racial tone, but segregation has become the rule rather than the exception across the geographic areas of the United States. Socioeconomic segregation is highly prevalent. In some cities only a short distance separates much higher from much lower income.
Places can be identified and categorized according to deficits. The places with deficits typically have more than a few deficits. Poverty, low literacy and education levels, poor health literacy, low property value, and limitations of health and other resources tend to be found in the same places. These can also be places that have ethnic minority populations. Segregation often involves lesser social determinants and associations with ethnic minorities - so is it the socioeconomic status or situation or the race/ethnicity or both?
Cancer studies have demonstrated lesser outcomes by race. But the data is skewed for many of these studies. The data that is specific to the individual is about disease (cancer), outcomes, race, and place (of care or residence). The researchers only have race and zip code or county location. They do not have the income or other characteristics specific to the individual with cancer - only race is specific. In analysis, race picks up the contributions of other place based variables such as income, education, and situation. This is because the researcher fills in the gaps in data with local income, or education level, etc.
Segregation results in places with multiple deficits. For example about 2624 counties with 40% of the population have numerous deficits across health and education and social resources. These are counties that also have lesser outcomes. In these counties behind by multiple designs, numerous conditions and situations are more likely - smoking, diabetes, obesity, transportation, access, and nutrition issues are more likely.
Also if the finding of the study is lesser outcome due to race, what can be done? You cannot change race. After all other possibilities are eliminated for health outcome differences, will the United States begin to address the very designs for distributions of education and income and government spending - designs that can result in improvements for those good at grants and government funding - and designs that can result in problems for populations that often have little clue about funding designed for them, or actually inaccessible to them.
Looking "upstream" toward root causes is less common and appears far too costly for improvement of any one disease or outcome - but when considering numerous outcomes or the global consideration, there are better choices.
Hotspotting Success, and Failure
You have just done your study and you found that diabetic amputations are much higher in certain zip code areas. So what?
Nutrition, exercise, health literacy, healthy food, fair to poor health status, and good health habits are all lower where care is needed and where outcomes are poor. Obesity, diabetes, smoking, poor housing conditions, rates of preventable hospitalization, infant mortality, and other markers of poor health are at higher levels. Complexity of care is higher where workforce is lower along with health spending - such is the American design.
Hotspotting makes it seem that poor health outcomes can be addressed simply, but there is no simple easy solution for decades of previous life experiences that have shaped diabetic amputations, plus the last years of various habits and situations, plus the final specific injury or lack of regular foot inspection, plus what happens before care is given, plus what happens in the days after care is given also shaped by decades prior to the event.
Hot spotting is relatively easy to do, but what can you do when you find that place or race or status is the reason? Looking "upstream" toward root causes is less common and appears far too costly for improvement of any one disease or outcome - but when considering numerous outcomes or the global consideration, there are better choices.
Hotspotting and Pay for Performance
At the heart of penalties for readmissions and lower pay for lower performance is hotspotting specific to a provider. If you "believe" that care is about providers with a few minutes of patient contact, this limited approach makes sense. If you understand that patient care outcomes are about the patient, life situations, and determinants before and after contact with a provider - well you can understand the shortcomings of penalty design. But wait, there is worse...
We have been in the health policy era of cost cutting for over 30 years now. The focus of US health policy is not care delivery. The focus is cutting cost. Because certain types of care "are more equal than others" this results in worsening of primary care and basic services. Cost cutting for the basics results in less basic care available and less access.
Now add hotspotting and health care designers that want to do good - except that they do not understand the situations facing the populations and providers where care outcomes are marginal.
Are Designers Aware of the Adverse Consequences of Their Innovative Designs?
What if you set up pay for performance or penalties for lower health outcomes? You just decided to send less spending to an area with lower income, lesser health spending, and lesser workforce.
If your design change results in the closure of a rural hospital, the entire county takes a hit in income, better paying jobs, even fewer clinicians, a local point of health care organization, and more.
The clinicians where health outcomes are lower are found in lower concentrations. Often the sites for care are overwhelmed with numbers of patients and their complexities. There are more barriers to care than just lower concentrations of clinicians - even for those on Medicare.
A major problem is lower income and less available spending. How does it help to have lowest reimbursement from Medicaid and Medicare? Low pay for Medicare sets up fewer providers accepting Medicare and lower local health spending - for further deteriorations. Areas where Medicare and Medicaid patients are more common have patients that are generally more complex.
Now designers want to penalize providers for poor outcomes. Why would you want to damage the providers, services, or facilities that remain and care for patients where care is most needed? Designers often think of rewards or value. Governments and insurance companies think of cost cutting and penalties. The end result is decline by design.
Much Better Awareness of Social Determinants, Situations, and Study Limitations
The beginning of health and health outcomes are about the birth to health care encounter experiences of the patient. Much is involved in what determines place of living - numerous social determinants act over decades of time. Numerous designs shape lesser outcomes - designs involving education, health, economics, and more.
If hotspotting helps to understand care limitations and need for more resources, it can help. If hotspotting is use to penalize care where needed - situations will be worse.
Better Research Needed, Including Top Level Research
As a journal editor I have rejected articles where proxy variables were used rather than data specific to the patients. Race or place variables tend to pick up the contributions of many different variables not included in the regression.
The Institutes of Medicine studies represent a top level of research, but the studies have involved flawed use of proxy variables that overemphasize provider or insurance problems, because these are the variables inserted.
The IOM has done effective coordination in the most important intervention areas - such as the recent Strategies for Scaling Effective Family-FocusedPreventive Interventions to Promote Children's Cognitive, Affective, andBehavioral Health - Workshop Summary
Failures from the start result in substantial costs in the end. On a daily bases we see alternatives rather than a focus on care where needed and care specific to the populations in need.
The steps taken identify the problem areas can involve bias
My research has often been quite different - not surprising since my research has a foundation in initial rural practice and decades of focus on health access. Traditional researchers have a very different pathway involving different training, support, and research approaches.
Very few researchers have the money or support to gain access to databases. Fewer have the time to be able to study more than a few databases. Researchers are often the only ones with certain data sets. They also have different sets of data on geographic areas. Researchers can compare their data and can pick and choose the geographic area, the data, and the methods used. Studies that get published usually need differences demonstrated - so authors must choose well to find problem areas.
Authors also need controls. Distributions of income, education, or other social determinants are often used. Unfortunately the distributions of such variables can be related to health outcomes.
Different approaches and measuring tools as well as different designs for payment and training are required to resolve health access woes.
Stimulated by
It is easy to do hotspotting. Define your geographic area. Collect data about the area. Examine correlations between the data elements. Find the correlations with significant differences. It helps to find correlations that are dramatic or controversial - ones likely to get published and attract attention.
The recent Health Affairs article about diabetic amputations by zip code has increased interest in such studies. The authors appropriately listed limitations of the study, but there are many limitations. These limitations are very important to understand as numerous recent articles about health outcomes have had similar limitations.
- Spurious relationships can result - especially when the data used is assumed (based on place, proxy variables) rather than using data specific to the individual patient
- Numerous studies are studies "of convenience" and have poor controls with insufficient numbers and types of variables studied - variables that may be more important in explaining the outcome
- Geographic locations often cannot "be fixed" or fixed easily
- Numerous sources of bias are possible and even likely in such studies
Segregation and Hotspotting
Segregation is a word that has long taken on a racial tone, but segregation has become the rule rather than the exception across the geographic areas of the United States. Socioeconomic segregation is highly prevalent. In some cities only a short distance separates much higher from much lower income.
Point for reflection: School district funding is substantially based on property values,
a design that clearly leads to advantages and disadvantages from the start of life.
Places can be identified and categorized according to deficits. The places with deficits typically have more than a few deficits. Poverty, low literacy and education levels, poor health literacy, low property value, and limitations of health and other resources tend to be found in the same places. These can also be places that have ethnic minority populations. Segregation often involves lesser social determinants and associations with ethnic minorities - so is it the socioeconomic status or situation or the race/ethnicity or both?
Cancer studies have demonstrated lesser outcomes by race. But the data is skewed for many of these studies. The data that is specific to the individual is about disease (cancer), outcomes, race, and place (of care or residence). The researchers only have race and zip code or county location. They do not have the income or other characteristics specific to the individual with cancer - only race is specific. In analysis, race picks up the contributions of other place based variables such as income, education, and situation. This is because the researcher fills in the gaps in data with local income, or education level, etc.
Segregation results in places with multiple deficits. For example about 2624 counties with 40% of the population have numerous deficits across health and education and social resources. These are counties that also have lesser outcomes. In these counties behind by multiple designs, numerous conditions and situations are more likely - smoking, diabetes, obesity, transportation, access, and nutrition issues are more likely.
Also if the finding of the study is lesser outcome due to race, what can be done? You cannot change race. After all other possibilities are eliminated for health outcome differences, will the United States begin to address the very designs for distributions of education and income and government spending - designs that can result in improvements for those good at grants and government funding - and designs that can result in problems for populations that often have little clue about funding designed for them, or actually inaccessible to them.
Looking "upstream" toward root causes is less common and appears far too costly for improvement of any one disease or outcome - but when considering numerous outcomes or the global consideration, there are better choices.
Hotspotting Success, and Failure
You have just done your study and you found that diabetic amputations are much higher in certain zip code areas. So what?
Nutrition, exercise, health literacy, healthy food, fair to poor health status, and good health habits are all lower where care is needed and where outcomes are poor. Obesity, diabetes, smoking, poor housing conditions, rates of preventable hospitalization, infant mortality, and other markers of poor health are at higher levels. Complexity of care is higher where workforce is lower along with health spending - such is the American design.
Hotspotting makes it seem that poor health outcomes can be addressed simply, but there is no simple easy solution for decades of previous life experiences that have shaped diabetic amputations, plus the last years of various habits and situations, plus the final specific injury or lack of regular foot inspection, plus what happens before care is given, plus what happens in the days after care is given also shaped by decades prior to the event.
Hot spotting is relatively easy to do, but what can you do when you find that place or race or status is the reason? Looking "upstream" toward root causes is less common and appears far too costly for improvement of any one disease or outcome - but when considering numerous outcomes or the global consideration, there are better choices.
Hotspotting and Pay for Performance
At the heart of penalties for readmissions and lower pay for lower performance is hotspotting specific to a provider. If you "believe" that care is about providers with a few minutes of patient contact, this limited approach makes sense. If you understand that patient care outcomes are about the patient, life situations, and determinants before and after contact with a provider - well you can understand the shortcomings of penalty design. But wait, there is worse...
We have been in the health policy era of cost cutting for over 30 years now. The focus of US health policy is not care delivery. The focus is cutting cost. Because certain types of care "are more equal than others" this results in worsening of primary care and basic services. Cost cutting for the basics results in less basic care available and less access.
Now add hotspotting and health care designers that want to do good - except that they do not understand the situations facing the populations and providers where care outcomes are marginal.
Are Designers Aware of the Adverse Consequences of Their Innovative Designs?
What if you set up pay for performance or penalties for lower health outcomes? You just decided to send less spending to an area with lower income, lesser health spending, and lesser workforce.
If your design change results in the closure of a rural hospital, the entire county takes a hit in income, better paying jobs, even fewer clinicians, a local point of health care organization, and more.
The clinicians where health outcomes are lower are found in lower concentrations. Often the sites for care are overwhelmed with numbers of patients and their complexities. There are more barriers to care than just lower concentrations of clinicians - even for those on Medicare.
A major problem is lower income and less available spending. How does it help to have lowest reimbursement from Medicaid and Medicare? Low pay for Medicare sets up fewer providers accepting Medicare and lower local health spending - for further deteriorations. Areas where Medicare and Medicaid patients are more common have patients that are generally more complex.
Why is the payment less in such locations?
Now designers want to penalize providers for poor outcomes. Why would you want to damage the providers, services, or facilities that remain and care for patients where care is most needed? Designers often think of rewards or value. Governments and insurance companies think of cost cutting and penalties. The end result is decline by design.
Much Better Awareness of Social Determinants, Situations, and Study Limitations
The beginning of health and health outcomes are about the birth to health care encounter experiences of the patient. Much is involved in what determines place of living - numerous social determinants act over decades of time. Numerous designs shape lesser outcomes - designs involving education, health, economics, and more.
If hotspotting helps to understand care limitations and need for more resources, it can help. If hotspotting is use to penalize care where needed - situations will be worse.
Better Research Needed, Including Top Level Research
As a journal editor I have rejected articles where proxy variables were used rather than data specific to the patients. Race or place variables tend to pick up the contributions of many different variables not included in the regression.
The Institutes of Medicine studies represent a top level of research, but the studies have involved flawed use of proxy variables that overemphasize provider or insurance problems, because these are the variables inserted.
- Iatrogenic Blame - Studies inserting physician variables without proper controls assign too much blame or too much credit for physician variables. Many variables conspire for adverse events in hospitals, but iatrogenic designs result in physician blame when controls are missing.
- Insurance Reform Can Fail - Studies used variables involving insurance deficits and not surprisingly indicated that lack of insurance was a problem for patient outcomes. Unfortunately the locations with insurance gaps also have other deficits. Insurance focus in reform has been the result of studies using lack of insurance as a variable. Not surprisingly lack of insurance emerges as associated with adverse outcomes. Adding insurance does not add workforce or improve access or address any number of other variables that contribute to poor outcomes.
The IOM has done effective coordination in the most important intervention areas - such as the recent Strategies for Scaling Effective Family-FocusedPreventive Interventions to Promote Children's Cognitive, Affective, andBehavioral Health - Workshop Summary
Failures from the start result in substantial costs in the end. On a daily bases we see alternatives rather than a focus on care where needed and care specific to the populations in need.
The steps taken identify the problem areas can involve bias
My research has often been quite different - not surprising since my research has a foundation in initial rural practice and decades of focus on health access. Traditional researchers have a very different pathway involving different training, support, and research approaches.
Very few researchers have the money or support to gain access to databases. Fewer have the time to be able to study more than a few databases. Researchers are often the only ones with certain data sets. They also have different sets of data on geographic areas. Researchers can compare their data and can pick and choose the geographic area, the data, and the methods used. Studies that get published usually need differences demonstrated - so authors must choose well to find problem areas.
Authors also need controls. Distributions of income, education, or other social determinants are often used. Unfortunately the distributions of such variables can be related to health outcomes.
Different approaches and measuring tools as well as different designs for payment and training are required to resolve health access woes.
Stimulated by
- The New England Journal / Commonwealth Foundation plea for costly care management
- Disappointment with regard to a health care researcher hero
- The Health Affairs Hotspotting Article Regarding Diabetic Amputations By Zip Code
- The Health Care Journalists' Read on Diabetic Amputations
- Successful Amputation Prevention in Native Reservations
- Local Focused Intervention Sufficient for Globally Improved Outcomes
Recent Works
Will Teaching CHC Sites Deliver on the Promise of Health Access?
How Bad Medicine is Sweeping The Country.
Preventing Rural Workforce By Design
Best of Basic Health Access
Retail Clinic Recoil
Global Fails Local But Local Focus Succeeds Globally
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Health Care Delivery Is No Laughing Matter - Political Cartoons are Nice, but...
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How Bad Medicine is Sweeping The Country.
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Best of Basic Health Access
Blogs indicate that primary care can be recovered and should be recovered.
Dr. Bowman is the North American Co-Editor of Rural and Remote Health. He was the founding chair of the Rural Medical Educators Group of the National Rural Health Association and the long term chair of the STFM Group on Rural Health.
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