IMPORTANCE: Understanding health conditions with the most spending and variation across locations and over time is important for identifying trends, highlighting inequalities, and developing strategies for lowering health spending. OBJECTIVE: To estimate US health care spending for each of 3110 US counties, across 4 payers (Medicare, Medicaid, private insurance, and out-of-pocket payments), and according to 148 health conditions, 38 age/sex groups, and 7 types of care from 2010 to 2019. DESIGN, SETTING, AND PARTICIPANTS: Observational analysis using more than 40 billion insurance claims and nearly 1 billion facility records. EXPOSURES: Ambulatory care, dental care, emergency department care, home health care, hospital inpatient care, nursing facility care, and purchase of prescribed retail pharmaceuticals. MAIN OUTCOMES AND MEASURES: Health care spending and utilization (eg, number of visits, admissions, or prescriptions) estimates from 2010 through 2019. RESULTS: Between 2010 and 2019, 76.6% of personal health care spending was captured by this study. More spending was on type 2 diabetes (43.9 billion [95% CI, 40 billion-47.2 billion]) than on any other health condition, followed by other musculoskeletal disorders, which includes joint pain and osteoporosis (08.6 billion [95% CI, 06.4 billion-10.3 billion]), oral disorders (3 billion [95% CI, 2.7 billion-3.3 billion]), and ischemic heart disease (0.7 billion [95% CI, 9 billion-2.4 billion]). Of total spending, 42.2% (95% CI, 42.2%-42.2%) was on ambulatory care, while 23.8% (95% CI, 23.8%-23.8%) was on hospital inpatient care and 13.7% (95% CI, 13.7%-13.7%) was on prescribed retail pharmaceuticals. At the county level, age-standardized spending per capita ranged from 410 (95% CI, 281-529) in Clark County, Idaho, to 3 332 (95% CI, 3 177-3 489) in Nassau County, New York. Across counties, the greatest variation was in age-standardized out-of-pocket spending, followed by private insurance spending. Cross-county variation was driven more by variation in utilization rates than variation in price and intensity of care, although both types of variation were substantial for all payers but Medicare. CONCLUSIONS AND RELEVANCE: Broad variation in health care spending was observed across US counties. Understanding this variation by health condition, sex, age, type of care, and payer is valuable for identifying outliers, highlighting inequalities, and assessing health care gaps.