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Geographic Variation in Health IT and Health Care Outcomes: A Snapshot Before the Meaningful Use Incentive Program Began
While variation across markets in health care use and costs is well-documented, variation across markets in health IT adoption is not as well documented. Similarly, while the relationship between use and costs and various market-level health care and population factors has been measured, the potential correlation between the level of health IT use in a market and the level of health care use and costs has not been studied. Most studies have analyzed the characteristics associated with, and the impact of, higher levels of hospital and physician adoption of health IT at the individual provider level. In this study, we present a cross-sectional and longitudinal market-level analysis of the levels of health IT adoption and use among physicians and hospitals in relation to various measures of health care use and costs throughout the early implementation of the HITECH and MU programs, spanning the years 2007 through 2012.
Data and Methods
We construct measures of the use and adoption of health IT and important outcomes at the level of the hospital referral region (HRR), our definition of a market. Our physician health IT measure is based on data from the annual SK&A survey of physicians. The index is the percentage of physicians in the HRR working in a medical office that reported adopting an EHR and using it for e-prescribing.
For our hospital health IT measure, we use data from the annual IT Supplement of the American Hospital Association (AHA) Annual Survey of Hospitals. Our hospital health IT index is the percentage of hospital admissions taking place in a hospital that was “Meaningful Use (MU) ready”—that is, whether it had implemented eight core IT applications included in Stage 1 MU criteria that are reported in the AHA IT Supplement.
We regress the outcomes of interest on the physician and hospital health IT indices, controlling for other market factors. Outcomes include inpatient costs, covered inpatient stays per 1,000 beneficiaries, outpatient costs, imaging costs, lab test costs, and 30-day acute readmission rates.
Key Findings
There is considerable variation across HRRs in both the physician and hospital health IT indices. Furthermore, the two indices are not highly correlated with each other. That is, markets that are in the top quintile for one measure are often not in the top quintile for the other. There do appear to be correlations between the level of physician adoption and use and various outcome measures. For example, we find small but statistically significant negative linear relationships between the percentage of physicians using EHRs and inpatient costs, imaging costs, and lab test costs.
Conclusions
The findings of this descriptive analysis suggest that greater levels of physician health IT are associated with decreasing costs for a number of services, including inpatient stays, imaging services, and lab tests. Our analysis of trends comparing these different types of markets shed light on whether markets with greater physician health IT penetration have less room for improvement in efficiency, and whether greater gains will accrue in markets with lower health IT levels at baseline.