Difference between revisions of "Electronic medical records and diabetes quality of care: results from a sample of family medicine practices"
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Crosson JC, Ohman-Strickland PA, Hahn KA, DiCicco-Bloom B, Shaw E, Orzano AJ, Crabtree BF. Electronic medical records and diabetes quality of care: results from a sample of family medicine practices. Ann Fam Med. 2007 May-Jun;5(3):209-15. | Crosson JC, Ohman-Strickland PA, Hahn KA, DiCicco-Bloom B, Shaw E, Orzano AJ, Crabtree BF. Electronic medical records and diabetes quality of care: results from a sample of family medicine practices. Ann Fam Med. 2007 May-Jun;5(3):209-15. | ||
| − | '''Question''' It has been assumed that EMR use improves quality of care for chronic condtions. | + | '''Question''' It has been assumed that EMR use improves quality of care for chronic condtions. This study asks, is there a relationship between EMR use and the quality of care delivered for patients having diabetes? |
| − | '''Methods''' This was a secondary analysis of data from Using Learning Teams for Reflective Adaptation Study (ULTRA), a convenience cohort of 60 family medicine practices in Pennsylvania and New Jersey | + | '''Methods''' This was a secondary analysis of data from Using Learning Teams for Reflective Adaptation Study (ULTRA), a convenience cohort of 60 family medicine practices in Pennsylvania and New Jersey using quality improvement methods to increase chronic care guideline adherence. A total of 54 practices had data available, but 4 sites that recently adopted an EMR were excluded. Among 50 practices in the analysis, data was collected at baseline by provider/staff interview and retrospective chart review. For each practice, a random chart audit of 20 patients with ICD-9 codes for diabetes in the past year was conducted. Quality measures included process metrics (HgA1c, urine albumin, LDL, BP, smoking assessed), and treatment (Rx for HgA1c, BP, LDL) and patient outcomes (HgA1c<8, LDL<100, BP<130/85) benchmarks. |
| − | '''Results''' A total of 13 (26%) of practices | + | '''Results''' A total of 13 (26%) of practices used an EMR for 1 year or longer. Among all 50 practices, 50% had achieved benchmarks for processes of care, 46% for treatment, and 8.7% for patient outcomes. After adjusting for patient- and practice-level factors, as well as clustering of patients within practices, patients cared for by non-EMR practices were more likely to meet any benchmarks. For process of care, a total of 35% and 53.8% of patients in EMR and non-EMR practices achieved 3 out of 5 process metrics, respectively. A minority of practices (3/13 with EMR; 6/37 non-EMR) were using registries to track chronic care. |
| − | '''Conclusions''' Among a cohort of family medicine practices, the use of an EMR is not associated with ensuring a high level of quality | + | '''Conclusions''' Among a cohort of family medicine practices, the use of an EMR is not associated with ensuring a high level of quality care for patients with diabetes. |
| − | '''Commentary ''' While one might leap to the conclusion that having an EMR may lead to worse diabetes outcomes, it is important to recognize the limitations of the study. First, this was a cohort of practices who agreed to participate in a quality improvement project that involved organizational change. | + | '''Commentary ''' While one might leap to the conclusion that having an EMR may lead to worse diabetes outcomes, it is important to recognize the limitations of the study. First, this was a cohort of practices who agreed to participate in a quality improvement project that involved organizational change. This may bias the sample toward more activated practices, leading to smaller differences found. A comment about the external validity of the study would have been welcome, e.g. how many were first approached. Regardless, it is likely this cohort from 2 states represents the real world (only some used a registry), and the findings have value. A measurement concern exists, in that only 7 to 21 patients per practice were measured. Hofter et. al demonstrated that many provider profiling methods use an inadequate number of patients to measure diabetes outcomes with a reasonable level of certainty.(1) Given the finding that non-EMR practices were related to better outcomes, the study begs the questions: (a) were EMR practices different from non-EMR practices in ways other than those described, such as being less team-based or having greater support staff turnover? (b) what ARE relevant practice-level factors that predict better patient outcomes, and (c) are these factors related to use of clinical decision support? The study of practice behavior and its relationship to quality outcomes has identified many factors that are critical to performance but difficult to measure. (2) Finally, the authors rightly discuss the difference between providers just having an EMR vs. using the features of an EMR that, hopefully, will ultimately realize chronic care improvement. Further studies need to be conducted. |
1. Hofer TP, Hayward RA, Greenfield S, Wagner EH, Kaplan SH, Manning WG. The unreliability of individual physician "report cards" for assessing the costs and quality of care of a chronic disease. JAMA. 1999 Jun 9;281(22):2098-105. | 1. Hofer TP, Hayward RA, Greenfield S, Wagner EH, Kaplan SH, Manning WG. The unreliability of individual physician "report cards" for assessing the costs and quality of care of a chronic disease. JAMA. 1999 Jun 9;281(22):2098-105. | ||
Latest revision as of 17:54, 11 November 2011
Crosson JC, Ohman-Strickland PA, Hahn KA, DiCicco-Bloom B, Shaw E, Orzano AJ, Crabtree BF. Electronic medical records and diabetes quality of care: results from a sample of family medicine practices. Ann Fam Med. 2007 May-Jun;5(3):209-15.
Question It has been assumed that EMR use improves quality of care for chronic condtions. This study asks, is there a relationship between EMR use and the quality of care delivered for patients having diabetes?
Methods This was a secondary analysis of data from Using Learning Teams for Reflective Adaptation Study (ULTRA), a convenience cohort of 60 family medicine practices in Pennsylvania and New Jersey using quality improvement methods to increase chronic care guideline adherence. A total of 54 practices had data available, but 4 sites that recently adopted an EMR were excluded. Among 50 practices in the analysis, data was collected at baseline by provider/staff interview and retrospective chart review. For each practice, a random chart audit of 20 patients with ICD-9 codes for diabetes in the past year was conducted. Quality measures included process metrics (HgA1c, urine albumin, LDL, BP, smoking assessed), and treatment (Rx for HgA1c, BP, LDL) and patient outcomes (HgA1c<8, LDL<100, BP<130/85) benchmarks.
Results A total of 13 (26%) of practices used an EMR for 1 year or longer. Among all 50 practices, 50% had achieved benchmarks for processes of care, 46% for treatment, and 8.7% for patient outcomes. After adjusting for patient- and practice-level factors, as well as clustering of patients within practices, patients cared for by non-EMR practices were more likely to meet any benchmarks. For process of care, a total of 35% and 53.8% of patients in EMR and non-EMR practices achieved 3 out of 5 process metrics, respectively. A minority of practices (3/13 with EMR; 6/37 non-EMR) were using registries to track chronic care.
Conclusions Among a cohort of family medicine practices, the use of an EMR is not associated with ensuring a high level of quality care for patients with diabetes.
Commentary While one might leap to the conclusion that having an EMR may lead to worse diabetes outcomes, it is important to recognize the limitations of the study. First, this was a cohort of practices who agreed to participate in a quality improvement project that involved organizational change. This may bias the sample toward more activated practices, leading to smaller differences found. A comment about the external validity of the study would have been welcome, e.g. how many were first approached. Regardless, it is likely this cohort from 2 states represents the real world (only some used a registry), and the findings have value. A measurement concern exists, in that only 7 to 21 patients per practice were measured. Hofter et. al demonstrated that many provider profiling methods use an inadequate number of patients to measure diabetes outcomes with a reasonable level of certainty.(1) Given the finding that non-EMR practices were related to better outcomes, the study begs the questions: (a) were EMR practices different from non-EMR practices in ways other than those described, such as being less team-based or having greater support staff turnover? (b) what ARE relevant practice-level factors that predict better patient outcomes, and (c) are these factors related to use of clinical decision support? The study of practice behavior and its relationship to quality outcomes has identified many factors that are critical to performance but difficult to measure. (2) Finally, the authors rightly discuss the difference between providers just having an EMR vs. using the features of an EMR that, hopefully, will ultimately realize chronic care improvement. Further studies need to be conducted.
1. Hofer TP, Hayward RA, Greenfield S, Wagner EH, Kaplan SH, Manning WG. The unreliability of individual physician "report cards" for assessing the costs and quality of care of a chronic disease. JAMA. 1999 Jun 9;281(22):2098-105.
2. Stroebel CK, McDaniel RR Jr, Crabtree BF, Miller WL, Nutting PA, Stange KC. How complexity science can inform a reflective process for improvement in primary care practices. Jt Comm J Qual Patient Saf. 2005 Aug;31(8):438-46.
Susan Woods, MD, MPH Oregon Health & Sciences University
