The impact of electronic health record implementation and use on performance of the surgical care improvement project measures
This is a review for Thirukumaran, C. P., Dolan, J. G., Webster, P. R., Panzer, R. J., & Friedman, B. (2015). The Impact of Electronic Health Record Implementation and Use on Performance of the Surgical Care Improvement Project Measures. Health Services Research, 50(1), 273–289. doi:10.1111/1475-6773.12191.
One study that examined the impact of EHR use on the composite Surgical Care Improvement Project (SCIP)found a decline in the composite score when hospitals transitioned to comprehensive EHRs. Studies that examined individual process measures relevant to SCIP have shown mixed results. EHRs can also adversely impact quality of care. Research has demonstrated an unfavorable association between the use of Computerized Physician Order Entry and clinical. The disruption in the workflows associated with EHR deployment can provide an opportunity for errors to occur.
Thirukumaran et al.’s objective was to examine the impact of electronic health record (EHR) deployment on Surgical Care Improvement Project (SCIP) measures in a tertiary-care teaching hospital. These 10 evidence-based process measures and their composite measure aim to increase adherence to processes that reduce postoperative complications. Thirukumaran et al. (2015) hypothesized that EHR deployment may be associated with a short-term unintended decline (worsening) of the SCIP score, followed by an increased probability of achieving a higher (better) SCIP score.
One-group pre- and post-EHR logistic regression and difference-in-differences analyses. SCIP Core Measure dataset from the CMS Hospital Inpatient Quality Reporting Program (March 2010 to February 2012).
The main setting for the study was Strong Memorial Hospital (SMH), a 792-bed tertiary-care teaching hospital located in Rochester, New York. The hospital deployed an ONC-ATCB-certified EHR2 (ONC HIT 2012) across most of its inpatient areas on March 5, 2011. Highland Hospital (HH), a 261-bed teaching hospital located 1.3 miles from SMH, was selected by the researchers as the comparison hospital. EHRs were deployed at HH on June 11, 2011. Study Duration and Design For the main (short-term) analysis, the preEHR (before) phase extended from October 1, 2010, to March 4, 2011; and the post-EHR (after) phase extended from March 5, 2011, to June 10, 2011. Three sensitivity analyses were conducted using different long-term study periods. The study adopted two statistical methods for the main analysis and each of the sensitivity analyses: (1) one-group pretest-posttest design (prepost) for SMH patients and (2) difference-in-difference (DID) estimation with pre- and post-EHR samples from SMH, utilizing HH as the control group.
Statistical models were created for each SCIP measure. The dependent variable for each model was a dichotomous variable. The impact was quantified as the change in the relative odds of achieving success on a particular measure with EHR use. The composite measure represented episodes that had received appropriate care for all qualifying measures.
Statistically significant short-term declines in scores were observed for the composite, postoperative removal of urinary catheter and post–cardiac surgery glucose control measures, states Thirukumaran et al. A statistically insignificant improvement in scores for these measures was noted 3 months after EHR deployment.
The findings demonstrated a decline in SCIP scores in the months immediately following EHR deployment, according to Thirukumaren et al. For the composite measure, EHR use was associated with lesser likelihood of success in the first 2 months afterwards.
- First limitation Thirukumaran et al. cited, the choice of hospitals.
- Second, a concurrent abstraction process for the SCIP measures at SMH as compared to retrospective abstraction at HH.
- Third, it is difficult to tell from the data whether the fall in quality followed by the rebound that we observed is likely to be an effect directly linked to the EHR or is just random variation. Though, they give evidence to counter the randomness.
- Fourth, it is possible that changes in scores may be due to changes in documentation. 
According to Thirukumaran et al., the study identified statistically significant temporary reductions in surgical quality associated with EHR deployment. . Implementation strategies should be developed to preempt or minimize this initial decline While the use of EHRs has the potential to improve quality of care, their deployment may lead to a temporary reduction in quality. Incorporating this awareness in the design of the implementation process should reap rich benefits.
This article is a bit dated but confirms what another study already found to be true. Knowing that such a decrease in productivity is probable should motivate mitigating responses during the implementation period.
- Thirukumaran, C. P., Dolan, J. G., Webster, P. R., Panzer, R. J., & Friedman, B. (2015). The Impact of Electronic Health Record Implementation and Use on Performance of the Surgical Care Improvement Project Measures. Health Services Research, 50(1), 273–289. doi:10.1111/1475-6773.12191.http://onlinelibrary.wiley.com.ezproxyhost.library.tmc.edu/doi/10.1111/1475-6773.12191/full