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Your ZIP code can signal a lot about your health — including how consistent you are in taking your pills.

STAT wanted to know: Where in America are people most likely to take their prescription drugs? And where are they least likely?


For a window into these broader patterns, we turned to a 2016 study from the Centers for Disease Control and Prevention, which looked at 18.5 million seniors taking medication for high blood pressure. The stakes here are high: When patients don’t take these drugs as directed, they’re at elevated risk of having a stroke or heart attack, being hospitalized, and dying early.

The government researchers examined when patients filled and refilled their prescriptions, defining non-adherent patients as those who had access to their medication for fewer than 80 percent of the days after their first fill. (The seniors were all covered by Medicare’s Part D program and the data collected were from 2014.)

Those findings can be drilled down to the county level. STAT only ranked counties that have at least 50,000 people, to ensure counties with small numbers of seniors didn’t skew the findings. A handful of white counties in the upper Midwest had sky-high rates of seniors taking their medications. But in several poor rural counties in the southwest, more than 40 percent of seniors don’t regularly refill their prescriptions.


Read on to see the list:

Where in the U.S. seniors do — and don't — take their blood pressure meds

When it comes to taking your blood pressure medicine, the country is divided. Hover over the map to see medication nonadherence by county. The dots represent the extremes in counties with at least 50,000 people.

56.2% RdYlGn 15.8%
Talia Bronshtein/STAT Source: Vital Signs: Disparities in Antihypertensive Medication Nonadherence Among Medicare Part D Beneficiaries — United States

America’s most adherent counties

  1. La Crosse County, Wis., 16.6 percent non-adherent
  1. Wood County, Wis., 16.6 percent
  1. Manitowoc County, Wis., 16.7 percent
  1. Olmsted County, Minn., 16.7 percent
  1. Otter Tail County, Minn., 16.7 percent

These upper Midwest counties have plenty of advantages that can make it easier for seniors to take their pills. Take as an example Olmsted County, Minn., which is surrounded by smaller counties with similarly good adherence.

Its residents are wealthier than most Americans, with a median household income of $68,000. That’s important, because although there are cheap generic blood pressure drugs available, patients who are financially comfortable tend to be in the habit of engaging with the health care system. Olmsted County also has plenty of rural space, but it’s densely populated enough that it’s never more than a short drive to the doctor’s office or the pharmacy.

And, crucially, Olmsted County is home to one of the world’s best-known hospitals, Mayo Clinic, which has five primary care clinics serving the county’s residents. Mayo is among the providers pushing a model of community care aimed in part at boosting medication adherence, according to Dr. Robert Stroebel, a primary care physician at Mayo. The tweaks can be simple but powerful, like making sure that everything is done consistently during an office visit and following up with calls or messages reminding at-risk patients to come back in.

“If we have a mechanism to identify those patients and engage with them, then we can hopefully readdress the issues that may be leading to their non-adherence,” Stroebel said.

America’s least adherent counties

  1. Apache County, Ariz., 45.1 percent non-adherent
  1. Maverick County, Texas,  41.8 percent
  1. Webb County, Texas, 41.7 percent
  1. McKinley County, N.M., 38.1 percent
  1. Columbus County, N.C., 38 percent

You don’t have to look far to find the challenges that make it hard for residents of these largely rural, minority-majority counties to take their pills consistently.

Consider Apache County, where seniors are nearly three times more likely than those in Olmsted County to be non-adherent to their blood pressure medications. Spanning parts of Navajo Nation and two other reservations, Apache County is three quarters American Indian — a population with high rates of high cholesterol and diabetes along with hypertension. Apache County residents live in poverty at a rate more than double that of the U.S. as a whole. And health resources are widely dispersed in a county that spreads just over 70,000 people over a landmass larger than the state of Massachusetts.

Dr. Daniel Derksen, a trained family practitioner who directs the University of Arizona’s Center for Rural Health, said that interventions to try to boost adherence won’t succeed if they don’t take these challenges into account.

After all, Derksen said, in Apache County, “it may not always be easy for individuals to access health care or get to a pharmacy — that could be an all-day endeavor across many miles of dirt roads.”

  • I would also encourage such efforts for adherence. But there are reasons to expect that adherence is only one of many issues going on that result in lesser outcomes due to the demographic, situation, condition, environment, access, chronic disease concentration, and other factors.

    Most studies involve populations quite different from those that are nonadherent – because they are excluded from study.

  • Notice that various studies of outcomes regarding physicians, health care plans, medical errors, insurance coverage, readmissions, MACRA, pay for performance, value based, male vs female physicians, Primary Care Medical Home, and other studies did not control for key areas such as adherence, health literacy, local resources, housing, environments, situations, and many of the factors more powerful that clinical interventions, especially digital clinical interventions or metrics.

    Studies using convenience data structured to specific findings apparently will continue – to fail to shed light on real solutions. Promotions of micromanagement continue to distract the US from the real problems – and efforts toward real solutions.

  • Those familiar with state health outcomes patterns layering out with the same band widths north to south can recognize this pattern. Child well being, health outcomes, education outcomes, and the factors that shape health literacy tend to layer out together. They correlate highly with each other and with disparities measurements at the county level. This alone should give pause to those who assume that incentives can improve health or education outcomes.

    The lowest physician concentration counties have higher concentrations of older, oldest, poorer, poorest, less healthy, veteran, disabled, diabetic, smoking, obese, Social Security, Medicare, Medicaid, and food stamp populations to go with higher concentrations of preventable deaths and mental illness. Apparently you can add adherence problems to this group.

    About 2621 lowest physician concentration counties with 40% of the population are increasing in numbers of counties, numbers of people, and complexity of care. The baseline is half enough primary care and major deficits of specialized care as all specialties other than family practice concentrate in counties with higher concentrations. There is little indication of any improvements in workforce or in the populations or the determinants. There is every indication of worsening situations, conditions, resources, and outcomes determinants by design.

    By 2040 closures of small and rural hospitals at 2 per month will increase this group past 2800 counties. Population growth has been highest in these counties since 1970. A majority of the US population will be left behind in these counties by 2040. Population growth in these counties is fueled by the housing crisis apparent across higher concentration counties in the US. The most vulnerable in finances and health are forced to migrate to lowest concentration counties with fewest health and support resources.

    The serious situation facing these counties is difficult to grasp. Stagnant revenue, higher costs of delivery, high turnover, highest turnover cost, lowest payments for services, greater losses in collections, rapid population growth, inmigration of complex populations low in resources, closures of small hospitals and practices, state cuts (child development, education, health, support services, public health), federal cuts (housing, environment, agriculture, interior, SNAP, disability), diversions of funds centrally (privatization, demonstration grants, block funding), and diversions of state jobs centrally will adversely impact health access, local workforce, team member function, and outcomes.

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