Electronic Medical Records and Diabetes Quality of Care: Results From a Sample of Family Medicine Practices

INTRODUCTION

Use of an electronic medical record (EMR) in ambulatory care settings has been widely recommended as a method for reducing errors, improving the quality of health care, and reducing costs.^1–10 One area where EMRs are expected to improve quality is in the management of care for patients with chronic illnesses, such as diabetes. For example, by facilitating the management of complex clinical information, EMRs have been shown to improve the coordination of tasks among members of the health care team,⁸ to lead to lower rates of missing clinical information,¹¹ and to support evidence-based clinical decision making.^12–15 Several recent systematic reviews of EMRs and clinical decision support systems have shown that systems developed in-house over many years lead health care institutions to improve adherence to clinical guidelines.^16–18 There is little evidence, however, on whether commercially developed multifunctional health information technology systems, such as EMRs, improve patient care in the primary care settings, where most chronic illness care is delivered.^18,19

Much of the current evidence addressing EMR effectiveness in primary care settings is derived from a few intervention studies and from case study reports. Some studies have documented improved diabetes-related patient outcomes after EMR adoption,^20,21 whereas others have shown improvements in the processes of diabetes care but not in patient outcomes.^22–24 In a previous case study we found that, with everyday use of an EMR in a primary care practice, clinical decision support functions may be disabled, resulting in EMR uses which differ substantially from those in institutions reporting efficacy of this technology.²⁵ Another comparative case study found that EMR implementation can have a temporarily negative impact on the quality of diabetes care and care outcomes. In this case, the EMR practice failed to exceed outcomes of a similar non-EMR practice 4 years after implementation.²⁶ To date, no studies have examined the effect of EMR use across a large number of primary care settings. Such studies are needed to assess the impact of widespread EMR implementation on quality of care in primary care settings.

We examined the relationship between EMR usage and diabetes care quality across a variety of primary care settings by analyzing baseline data collected in 50 family medicine practices participating in an organizational change intervention.

METHODS

RESULTS

Of the 50 practices, 13 (26%) had used an EMR for 1 year or more. Whereas larger practices were disproportionately represented among EMR-using practices, this pattern was not statistically significant. Although one commonly mentioned benefit of an EMR is the disease registry, only 9 (18%) practices (3 EMR and 6 non-EMR) reported that they used a registry to track the care of patients with diabetes, and this difference was not statistically significant. Furthermore, there were no significant differences between the 2 groups of practices in their use of various electronic or paper reminder systems, such as flow sheets, reminders to clinicians, patient recall systems, or internal chart auditing designed to improve practice adherence to clinical guidelines. Patients in practices that did not use an EMR were somewhat older than those in the practices that reported using an EMR (Table 2⇓). EMR and non-EMR practices did not differ significantly on any of the other patient-level or organizational-level variables. Across both groups, older patients were somewhat more likely to receive the selected treatments and to meet the targets, and male patients were more likely than female patients to meet all 3 treatment targets.

The 50 practices had between 7 and 21 charts of diabetic patients per practice audited, for a total of 927 patients. Across all 50 practices the care of 49.9% of patients met our criterion for processes of care, 46.2% met the criterion for treatment, and 40.3% met the criterion for achievement of 2 of the 3 intermediate outcomes targets; 8.7% met our criterion of simultaneous achievement of all 3 outcomes. Table 3⇓ displays the mean practice-level rates of guideline adherence for EMR and non-EMR practices. In all cases, the mean rates for non-EMR practices were higher. Hierarchical logistic regression analyses showed that, after controlling for potential practice- and patient-level confounders and for the clustering of patients within practices, patients with diabetes in practices that did not have an EMR were significantly more likely to have received care that met the guidelines for processes of care, treatment, and intermediate outcomes (Table 4⇓). For intermediate outcomes, the odds of patients in non-EMR using practices meeting all 3 targets was 2.68 times the odds of patients in EMR-using practices.

DISCUSSION

Diabetes care in the family medicine practices assessed here, regardless of whether they reported using an EMR, showed marked room for improvement, especially with regard to achievement of target values for intermediate outcomes. Contrary to the assumptions underlying suggestions from professional organizations, other researchers, and federal policy makers, we found that EMR usage was associated with poorer adherence to the diabetes quality of care measures examined here. Because we have data for the presence or absence of an EMR only, rather than on specific features of each EMR, our explanation for the quality differences between the 2 groups is somewhat speculative. Because commercially developed EMR systems vary by manufacturer in the features and levels of technological support available to users, our findings are likely to represent an accurate picture of the systemwide health effects of EMR implementation on quality of diabetes care in primary care practices.³³ Thus the study findings from our sample may be more representative of the overall effects of EMR implementation than the findings of previous studies evaluating the impact of particular EMR systems or features.

The main limitations of this study derive from the cross-sectional nature of the observations and that data were collected as a baseline for a practice improvement trial rather than to evaluate EMR effects on diabetes care quality. Specifically, our sample may not be representative; in fact, we found that in comparison with national data, a relatively high proportion of the practices participating in this study reported using an EMR.^34–37 Our findings are similar to the National Ambulatory Medical Care Survey data in that we found proportionately fewer solo practitioners reporting EMR use.³⁶ Moreover, our overall findings of quality of diabetes care are similar to those from a recent study of a nationally representative sample of patients, which documented a low proportion of recommended care provided to patients with chronic illnesses, such as diabetes.³⁸

There may be additional unaccounted-for selection biases that could explain the better performance of non-EMR practices. For example, we did not collect detailed information regarding possible variations in use of EMRs, the number of years each practice had been using an EMR, or the particular diabetes care-related EMR features used in each practice. Furthermore, medical records typically do not include information on patient-level demographic variables (such as insurance status, socioeconomic position, and literacy), which may affect the outcomes measured here. In addition, since several of the practices provided only a few patient charts for audit, they may have had unusually few patients with diabetes or particular difficulties providing lists of patients, which would potentially bias our results. Even so, excluding these practices from our analyses did not lead to substantially different results.

Finally, this study faces the same limitations of any study that relies on chart audit in that the thoroughness of chart documentation may vary considerably among clinicians, across practice sites, or even between paper and electronic records. Despite these limitations, the guidelines examined here include items likely to be included in most medical records (ie, physical examinations, laboratory testing orders, and laboratory testing results), and a recent study found that in terms of intermediate outcomes, such as those assessed here, electronic and paper charts do not differ in the information that they include.³⁹

Primary care practices are under increasing pressure to computerize their patient records and, as the recent United Kingdom experience has shown, documentation requirements of pay-for-performance programs are likely to increase this pressure.⁴⁰ Furthermore, the Medicare Management Performance Demonstration of the Centers for Medicare and Medicaid Services, set to begin payments to participating practices in summer 2007, includes a bonus for reporting data using a certified EMR.⁴¹ Although pay-for-performance systems also include incentives for increased quality of care and have been successful in the United Kingdom,⁴² practice leaders may react to these reporting pressures by implementing EMR systems without paying sufficient attention to the effects on the overall system of care delivery within their practices.²⁵ As has been found with computerized physician order entry and other technologically based safety procedures, implementation of health information technologies without sufficient attention to workflow redesign can create new quality problems and adversely affect patient health.^43–46 Our findings suggest that these sorts of unintended consequences may already be affecting the quality of diabetes care in our sample of US family medicine practices.

The findings presented here suggest that national policy makers and primary care practice owners should pay renewed attention to maintaining and improving quality in primary care settings during and after EMR implementation. EMR vendors should be encouraged to address existing recommendations to develop products that provide more than a means to enhance billing for clinician services. They should include, or make more easily usable, features that can support improved health care quality (such as developing a chronic illness registry capable of identifying patients for whom treatment intensification would be warranted or offering real-time clinical guidelines support).^47,48 More research on best uses of EMR technology and a high level of support for EMR implementation will be required if the federal goal of an electronic health record for every American by 2014 is to be met while preserving and enhancing the quality of care delivered. Policy makers should demand that evidence-based quality benchmarks be met as part of this support to ensure that EMR technology is used to enhance the quality of care. Finally, practice leaders should encourage a culture of improvement and quality within their practices and work to develop methods to improve diabetes care before implementation of an EMR. Simply having an EMR does not guarantee higher quality care.