Dataset Information

Meaningful use of electronic health record systems and process quality of care: evidence from a panel data analysis of U.S. acute-care hospitals.

ABSTRACT:

Objective

To estimate the incremental effects of transitions in electronic health record (EHR) system capabilities on hospital process quality.

Data source

Hospital Compare (process quality), Health Information and Management Systems Society Analytics (EHR use), and Inpatient Prospective Payment System (hospital characteristics) for 2006-2010.

Study setting

Hospital EHR systems were categorized into five levels (Level_0 to Level_4) based on use of eight clinical applications. Level_3 systems can meet 2011 EHR "meaningful use" objectives. Process quality was measured as composite scores on a 100-point scale for heart attack, heart failure, pneumonia, and surgical care infection prevention. Statistical analyses were conducted using fixed effects linear panel regression model for all hospitals, hospitals stratified on condition-specific baseline quality, and for large hospitals.

Principal findings

Among all hospitals, implementing Level_3 systems yielded an incremental 0.35-0.49 percentage point increase in quality (over Level_2) across three conditions. Hospitals in bottom quartile of baseline quality increased 1.16-1.61 percentage points across three conditions for reaching Level_3. However, transitioning to Level_4 yielded an incremental decrease of 0.90-1.0 points for three conditions among all hospitals and 0.65-1.78 for bottom quartile hospitals.

Conclusions

Hospitals transitioning to EHR systems capable of meeting 2011 meaningful use objectives improved process quality, and lower quality hospitals experienced even higher gains. However, hospitals that transitioned to more advanced systems saw quality declines.

SUBMITTER: Appari A

PROVIDER: S-EPMC3626353 | biostudies-literature | 2013 Apr

REPOSITORIES: biostudies-literature

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Publications

Meaningful use of electronic health record systems and process quality of care: evidence from a panel data analysis of U.S. acute-care hospitals.

Appari Ajit A Eric Johnson M M Anthony Denise L DL

Health services research 20120720 2 Pt 1

<h4>Objective</h4>To estimate the incremental effects of transitions in electronic health record (EHR) system capabilities on hospital process quality.<h4>Data source</h4>Hospital Compare (process quality), Health Information and Management Systems Society Analytics (EHR use), and Inpatient Prospective Payment System (hospital characteristics) for 2006-2010.<h4>Study setting</h4>Hospital EHR systems were categorized into five levels (Level_0 to Level_4) based on use of eight clinical application ...[more]

PMID: 22816527

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Project description:ObjectiveTo determine if recent growth in hospital and physician electronic health record (EHR) adoption and use is correlated with decreases in expenditures for elderly Medicare beneficiaries.Data sourcesAmerican Hospital Association (AHA) General Survey and Information Technology Supplement, Health Information Management Systems Society (HIMSS) Analytics survey, SK&A Information Services, and the Centers for Medicare & Medicaid Services (CMS) Chronic Conditions Data Warehouse Geographic Variation Database for 2010 through 2013.Study designFixed effects model comparing associations between hospital referral region (HRR) level measures of hospital and physician EHR penetration and annual Medicare expenditures for beneficiaries with one of four chronic conditions. Calculated hospital penetration rates as the percentage of Medicare discharges from hospitals that satisfied criteria analogous to Meaningful Use (MU) Stage 1 requirements and physician rates as the percentage of physicians using ambulatory care EHRs.Principal findingsAn increase in the hospital penetration rate was associated with a small but statistically significant decrease in total Medicare and Medicare Part A acute care expenditures per beneficiary. An increase in physician EHR penetration was also associated with a significant decrease in total Medicare and Medicare Part A acute care expenditures per beneficiary as well as a decrease in Medicare Part B expenditures per beneficiary. For the study population, we estimate approximately $3.8 billion in savings related to hospital and physician EHR adoption during 2010-2013. We also found that an increase in physician EHR penetration was associated with an increase in lab test expenses.ConclusionsHealth care markets that had steeper increases in EHR penetration during 2010-2013 also had steeper decreases in total Medicare and acute care expenditures per beneficiary. Markets with greater increases in physician EHR had greater declines in Medicare Part B expenditures per beneficiary.

Project description:BACKGROUND:The increased use of electronic medical records (EMRs) in Canadian primary health care practice has resulted in an expansion of the availability of EMR data. Potential users of these data need to understand their quality in relation to the uses to which they are applied. Herein, we propose a basic model for assessing primary health care EMR data quality, comprising a set of data quality measures within four domains. We describe the process of developing and testing this set of measures, share the results of applying these measures in three EMR-derived datasets, and discuss what this reveals about the measures and EMR data quality. The model is offered as a starting point from which data users can refine their own approach, based on their own needs. METHODS:Using an iterative process, measures of EMR data quality were created within four domains: comparability; completeness; correctness; and currency. We used a series of process steps to develop the measures. The measures were then operationalized, and tested within three datasets created from different EMR software products. RESULTS:A set of eleven final measures were created. We were not able to calculate results for several measures in one dataset because of the way the data were collected in that specific EMR. Overall, we found variability in the results of testing the measures (e.g. sensitivity values were highest for diabetes, and lowest for obesity), among datasets (e.g. recording of height), and by patient age and sex (e.g. recording of blood pressure, height and weight). CONCLUSIONS:This paper proposes a basic model for assessing primary health care EMR data quality. We developed and tested multiple measures of data quality, within four domains, in three different EMR-derived primary health care datasets. The results of testing these measures indicated that not all measures could be utilized in all datasets, and illustrated variability in data quality. This is one step forward in creating a standard set of measures of data quality. Nonetheless, each project has unique challenges, and therefore requires its own data quality assessment before proceeding.

Dataset Information

Meaningful use of electronic health record systems and process quality of care: evidence from a panel data analysis of U.S. acute-care hospitals.

Objective

Data source

Study setting

Principal findings

Conclusions

Publications

Meaningful use of electronic health record systems and process quality of care: evidence from a panel data analysis of U.S. acute-care hospitals.

Similar Datasets

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