Computed Tomography Head and Chest per 1000 Medicare Enrollees

$79 / year

This dataset contains Computed Tomography of head and chest per 1,000 Medicare enrollees. Data is for 2012 at the HRR (Hospital Referral Regions) level. Rates are adjusted for age, sex, and race.

Complexity

This dataset is one of the surveys carried out by Dartmouth Atlas under the umbrella “Effective Care”. Effective care refers to services that are of proven value and have no significant tradeoffs — that is, the benefits of the services so far outweigh the risks that all patients with specific medical needs should receive them. These services, such as beta-blockers for heart attack patients, are backed by well-articulated medical theory and strong evidence of efficacy, determined by clinical trials or valid cohort studies. Failure to provide effective care can lead to serious consequences; for example, amputation of a leg is an infrequent but devastating complication of peripheral vascular disease and diabetes.

The claims-based analyses of effective care focus on either the entire fee-for-service Medicare population eligible for both Part A and B and between the ages of 65 and 99 or a subset of that population at risk for a specific procedure or service. For example, the analysis of amputations examines the entire Medicare population, while the analyses of testing among diabetics are restricted to Medicare beneficiaries between the ages of 65 and 75 with a diagnosis of diabetes. When appropriate, statistical adjustments are carried out to account for differences in age, race and sex.

Evidence-based decisions, performance assessment, and explicit efforts to improve quality, reduce errors, and involve patients in care decisions are often components of high quality health care. Such care requires providers, health systems, and others to work together to improve health outcomes and patient satisfaction while containing costs.

Despite efforts towards higher quality care, an estimated 30% of patients did not receive recommended preventive care or treatment in 2009. Poor care coordination within and among facilities can lead to poor health outcomes and readmissions; about 20% of discharged elderly patients return to the hospital within 30 days. Hospital acquired infections killed about 100,000 Americans in 2007, and between 44,000 and 98,000 Americans are estimated to die from medical errors each year.

Quality varies widely by state, race, ethnicity, and income. Blacks, Hispanics, American Indians and those with low incomes often get lower quality care than non-Hispanic whites and those with high incomes. One study found that women and minorities get lower quality care than their counterparts even when insurance status, income, and condition are accounted for.

Even with the highest per capita health care spending in the world, the US has shorter lifespans and higher infant mortality rates than other wealthy nations. Several studies estimate that at least 30% of US health expenditures are on practices and procedures that do not improve health. Preventable hospitalizations cost $26 billion in 2009, and in 2008, medical errors cost nearly $20 billion.

Adopting and implementing initiatives to improve the quality of health care in all settings can help us all get the care we need when we need it, leading to longer, healthier lives, and healthier, more productive communities.

Date Created

2012

Last Modified

2012

Version

2012

Update Frequency

Annual

Temporal Coverage

2012

Spatial Coverage

United States

Source

John Snow Labs => The Dartmouth Institute for Health Policy and Clinical Practice

Source License URL

John Snow Labs Standard License

Source License Requirements

N/A

Source Citation

N/A

Keywords

Computed Tomography Data, CT Head and Chest, CT Chest Data, CMT for Medicare Enrollees, Dartmouth Atlas Surveys, Evidence-Based Decisions CMT, Claims-Based Analyses CMT

Other Titles

Computed Tomography Data per 1000 Medicare Enrollees for Chest 2012, Computed Tomography Data per 1000 Medicare Enrollees for Head 2012, Computed Tomography Chest for Medicare Enrollees 2012, Computed Tomography Head for Medicare Enrollees 2012

Name Description Type Constraints
Survey_YearYear for which the survey data was conducteddaterequired : 1
Event_AbbreviationAbbreviation of the event of which the data was collected. "CT_C" stands for "Computed Tomography of Chest" and "CT_H" stands for "Computed Tomography of Head"stringrequired : 1
Event_StratificationStratification of the event, "All" in this casestringrequired : 1
Location_IDID assigned to the data locationintegerrequired : 1 level : Nominal
State_AbbreviationState Abbreviation as well as name of the location.stringrequired : 1
DenominatorNumber of Medicare fee-for-service enrolleesintegerrequired : 1 level : Nominal
Observed_IndividualsNumber of individuals observed during the surveyintegerrequired : 1 level : Ratio
Observed_EventsNumber of events observed during the surveyintegerrequired : 1 level : Ratio
Expected_EventsNumber of events expected during the surveynumberrequired : 1 level : Ratio
Observed_Expected_Event_RatioRatio of observed events to expected eventsnumberrequired : 1 level : Ratio
Crude_RateA measure of overall frequency which has not been adjusted for significant factors which might have influenced the rate. (age, sex and race in this case)numberrequired : 1 level : Ratio
Adjusted_RateRates are adjusted for age, sex and race using the indirect method, using the U.S. Medicare population as the standard.numberrequired : 1 level : Ratio
Standard_ErrorThe standard error (SE) is a measure of the amount the statistic may be expected to differ by chance from the true value of the statistic. The larger the SE, the less sure you can be that if you took a different sample and computed the statistic again, that it would be close to the statistic you computed from the first sample.numberlevel : Ratio
Lower_Confidence_Interval95% confidence interval lower limitnumberlevel : Ratio
Upper_Confidence_Interval95% confidence interval upper limit.numberlevel : Ratio
Population_UnitPopulation Unit taken for the survey analysisintegerlevel : Ratio
Location_TypeType of location. "HRR" in this case. "HRR" or "Hospital Referral Regions" represents regional health care markets for tertiary medical care that generally requires the services of a major referral center.stringrequired : 1
Suppression_LimitSuppression limit of the eventintegerrequired : 1 level : Ratio
Precision_LimitPrecision limit of the eventintegerrequired : 1 level : Ratio
Survey_YearEvent_AbbreviationEvent_StratificationLocation_IDState_AbbreviationDenominatorObserved_IndividualsObserved_EventsExpected_EventsObserved_Expected_Event_RatioCrude_RateAdjusted_RateStandard_ErrorLower_Confidence_IntervalUpper_Confidence_IntervalPopulation_UnitLocation_TypeSuppression_LimitPrecision_Limit
2012CT_HALL999National276520512992433434653643465361157.187157.187hrr1126
2012CT_CALL999National27652051232294732488103248813.0671117.489117.4891000hrr1126
2012CT_CALL62CA- NAPA35180212627564084.6890.67578.3479.1121.47976.21382.1211000hrr1126
2012CT_HALL341OR- BEND28436179723883852.3650.6283.97896.7411.73392.938100.71000hrr1126
2012CT_CALL31CA- CHICO46232303439665427.440.73185.78585.6841.33683.05888.3931000hrr1126
2012CT_CALL73CA- REDDING53026324242836180.9740.69380.77281.231.21878.83383.71000hrr1126
2012CT_CALL325OH- AKRON48753418657475745.171117.88117.7181.524114.713120.8011000hrr1126
2012CT_CALL43CA- FRESNO82055541174939593.3390.78191.31791.6861.0489.63493.7861000hrr1126
2012CT_CALL256MN- ST PAUL52408358549626201.4460.894.6893.9061.30991.32996.5561000hrr1126
2012CT_CALL280NV- RENO81860575375999489.7860.80192.82993.8521.05791.76695.9871000hrr1126