AHRQ Innovations Exchange | Real-Time Decision and Documentation Support Increases Adherence to Recommended Care for Respiratory Infections, Diabetes, and Heart Disease

Real-Time Decision and Documentation Support Increases Adherence to Recommended Care for Respiratory Infections, Diabetes, and Heart Disease


Snapshot
Summary
Partners HealthCare System seeks to ensure appropriate care for patients with acute respiratory infections, coronary artery disease, and diabetes by providing real-time clinical decision and documentation support through the system’s electronic medical record. Pre- and post-implementation pilot studies show that the system has improved the appropriateness of antibiotic prescribing for acute respiratory infections and increased use of appropriate therapies and improved documentation for patients with coronary artery disease and diabetes. Results from a randomized controlled trial of the system have not yet been published.
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Developing Organizations
Partners Healthcare System

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Date First Implemented
2004



What They Did
Problem Addressed
Physicians frequently fail to adhere to recommended clinical care for patients with coronary artery disease (CAD), diabetes, and acute respiratory infections. Electronic health records (EHRs) with decision support functionality can help physicians follow guidelines, but this type of support is seldom easy to use or readily available at the point of care.
Failure to follow recommended care: Physicians frequently fail to provide recommended care for CAD, diabetes and prescribing antibiotics for acute respiratory infections. For example, acute respiratory infections account for approximately one-half of all antibiotic prescriptions written for adults, yet studies have found many of these prescriptions to be inappropriate, either because the infection is viral (rendering antibiotics ineffective) or the antibiotic is too strong for the bacteria being treated.1 Another study found that only one-third of primary care visits involving patients with diabetes resulted in the provision of five recommended services (foot examination, referral for an eye examination, blood glucose measurement, a lipid panel, and a urine microalbumin test).2
Unrealized potential of decision support: Although research suggests that one potential use of clinical decision support systems is to help clinicians identify opportunities to improve disease management, real-world use of these systems has resulted in minimal improvements in patient outcomes.3 Key factors in this underperformance include poor timing, little or no integration of decision support into existing workflow, lack of relevance to the patient’s condition or care needs, the failure to link decision support and clinical action (e.g., medication prescribing or test ordering), and lack of time savings or other efficiencies for physicians using such systems.3 Correcting these shortcomings—for example, by providing real-time decision support at the point of care and automatically documenting the provision of care in the patient’s record—could increase the use and effectiveness of these systems.
Description of the Innovative Activity
Partners HealthCare System uses a "Smart Form" within the EHR to provide real-time reminders to physicians about guideline-based care recommendations for patients with acute respiratory infections, CAD, and diabetes. For CAD and diabetes, the system identifies appropriate tests and medical treatment, whereas the acute respiratory infection Smart Form helps physicians prescribe antibiotics appropriately. In all cases, the system automatically documents care provided within the clinical notes section of the patient’s medical record. Key elements of the system are described below:
Point-of-care access: The physician accesses the Smart Form from the EHR’s “notes” section while conducting the patient visit, a time when the physician will likely be receptive to clinical suggestions.
Review of background information: Physicians review the left side of the form, which contains critical background information about the patient’s health, including allergies, medications, vital signs, and laboratory test results. Having all relevant information in one place facilitates the physician’s understanding of the patient’s health status.
Complete documentation: The physician interviews the patient about his or her symptoms and medical history and reviews the patient’s medication list, confirming its accuracy and deleting or adding medications as specified by the patient. During the physical exam, the physician documents all relevant observations and information by clicking pre-existing boxes, choosing statements from dropdown menus, and/or entering free text. All information becomes part of the patient’s record and is available to aid in current and future decision making.
Automatic recommendations on care needs: The system automatically generates recommended tests and treatments for the physician's consideration based on the available information and established guidelines, as outlined below:
For CAD and diabetes: The system presents a list of care options for the physician’s consideration. For example, if a patient with CAD has low-density lipoprotein levels that are above goal despite being on a statin, the system offers various options, including changing therapy (e.g., increasing dosage of the current drug, initiating fibrate therapy, and/or changing to a different statin), ordering laboratory tests (e.g., lipid panel, liver function), and/or referring the patient to another clinician (e.g., nutritionist, lipid specialist). The physician then checks desired actions on the list. Suggested actions cover glycemia therapy, cholesterol management, antiplatelet therapy, blood pressure management, diabetic foot examination, weight management, and cigarette smoking.
Acute respiratory infections: After physicians document patient symptoms using a checklist, the acute respiratory infection form presents possible diagnoses and treatment options appropriate for each. The physician selects the suspected diagnosis and is presented with testing options (e.g., a throat culture or a rapid strep test) and potential treatments, including prescription and/or over-the-counter medications appropriate for that diagnosis. For example, if the physician enters a diagnosis for which antibiotic therapy is appropriate (e.g., streptococcal pharyngitis), the physician sees a list of antibiotic options for that diagnosis. However, if the physician selects a diagnosis for which antibiotics are not indicated, such as the common cold or acute bronchitis, the physician sees a statement confirming the inappropriateness of antibiotic therapy along with a list of potential therapies to control symptoms.
Identifying and addressing gaps in care: The form identifies any omissions in recommended care (e.g, failure to conduct a comprehensive foot exam for a diabetes patient in the past 12 months) and prompts the physician to address them, either by providing the recommended care, prescribing appropriate treatment, and/or making a referral for testing or a consult. The physician also fills in key pieces of missing information (e.g., blood pressure, weight, or smoking status), which are flagged by the system for easy identification.
Patient review: The forms include a section for patients that summarizes health status, care that has been given, and remaining care needs. The patient and physician review this information together to decide on future care needs and options.
Patient education and materials: Physicians check off needed educational materials based on the patient's needs. The physician clicks one button to print all information needed by the patient, including laboratory order forms, new prescriptions, and educational materials.
References/Related Articles
Schnipper JL, Linder JA, Palchuk MB, et al. “Smart Forms” in an electronic medical record: documentation-based clinical decision support to improve disease management. J Am Med Inform Assoc 2008 Jul/Aug;15(4):513-23. [PubMed]

Linder JA, Schnipper JL, Volk LA, et al. Clinical decision support to improve antibiotic prescribing for acute respiratory infections: results of a pilot study. AMIA Annu Symp Proc 2007;468-72. [PubMed]

Schnipper JL, McColgan KE, Linder JA, et al. Improving management of chronic diseases with documentation-based clinical decision support: results of a pilot study. AMIA Annu Symp Proc 2008;1050. [PubMed]

Linder JA, Rose AF, Palchuk MB, et al. Decision support for acute problems: the role of the standardized patient in usability testing. J Biomed Inform 2006 Jan;39:648-55. [PubMed]
Contact the Innovator
Principal investigator:
Blackford Middleton, MD, MPH, MSc
Director, Clinical Informatics R&D
Director, Center for IT Leadership
Partners Healthcare
93 Worcester St., Box 81905
Wellesley, MA 02481
(781) 416-8528
E-mail: bmiddleton1@partners.org

Coronary artery disease/diabetes Smart Form:
Jeffrey L. Schnipper, MD, MPH
Director of Clinical Research, Brigham and Women’s Hospital Hospitalist Program
Associate Physician, Division of General Medicine, Brigham and Women’s Hospital
Assistant Professor of Medicine, Harvard Medical School
(617) 732-6201
E-mail: jschnipper@partners.org

Acute respiratory infections Smart Form:
Jeffrey A. Linder, MD, MPH
Associate Physician, Division of General Medicine, Brigham and Women’s Hospital
Assistant Professor of Medicine, Harvard Medical School
(617) 525-6654
E-mail: jlinder@partners.org

Did It Work?
Results
Pre- and post-implementation pilot studies show that the system improved the appropriateness of antibiotic prescribing for acute respiratory infections and increased use of recommended therapies and improved documentation for patients with CAD and diabetes. Results from a randomized controlled trial (RCT) of the acute respiratory infection form are pending publication, while results from an RCT of the CAD/diabetes form are currently being analyzed.
More appropriate antibiotic prescribing: A 4-week pilot study involving 10 primary care physicians and 26 patients with respiratory symptoms found that when clinicians used the Smart Form, they prescribed antibiotics to all patients who needed them according to the guidelines, compared to 90 percent of appropriate patients when not using the form. During the previous cold and flu season, these same physicians prescribed antibiotics to only 42 percent of these patients. Those using the Smart Form inappropriately prescribed antibiotics to patients who did not need them 15 percent of the time, below the 21 percent rate when not using the form. These same physicians had inappropriately prescribed antibiotics to 26 percent of these patients during the previous cold and flu season.1
Greater adherence to—and documentation of—recommended diabetes and CAD care: A pilot study involving 30 physicians and 1,940 patients with CAD and/or diabetes analyzed records in which a gap in care existed. Overall, clinicians addressed an average of 13.9 percent of care deficiencies per patient during the 6 weeks after they began using the Smart Form, well above the 8.6-percent rate during the 6 weeks before implementation; in addition, deficiencies were corrected within 1 month of the visit in which the Smart Form was used.4 Specific results are as follows:
More likely to change therapy for those with high blood glucose: Physicians changed or increased therapy for 16.9 percent of patients currently on diabetes medications who had a hemoglobin A1c level above 7 percent, compared to just 9.8 percent of such patients before implementation.
More appropriate beta-blocker use and documentation: Physicians documented beta-blocker use or a contraindication in 100 percent of cases after implementation, compared to none before implementation.
Better documentation of health status information: Among those patients without appropriate documentation in the previous 12 months, 93.3 percent had their most recent blood pressure reading documented properly in the EHR after implementation, compared to just 26.7 percent before. Similar improvements were seen for height and weight (9.4 percent after implementation, compared to 4.6 percent before) and smoking status (23.9 percent, 5.2 percent).
Evidence Rating (What is this?)
Moderate: The evidence consists of before-and-after comparisons of key outcomes measures, including rates of appropriate antibiotic prescribing, adjustments in diabetes therapy, prescribing of antiplatelet therapy and beta-blocker medications, and documentation of key metrics in the EHR.

How They Did It
Context of the Innovation
The Partners HealthCare System is an integrated system that includes Brigham and Women's Hospital, Massachusetts General Hospital, several community hospitals, and Partners Community HealthCare, a physician network of more than 4,000 clinicians who use Partners’ internally developed EHR. Approximately 20 percent of Partners’ patients have CAD and/or diabetes, and approximately 22,000 acute respiratory infection visits annually are made to primary care practices affiliated with Brigham and Women's Hospital and Massachusetts General Hospital; thus, these conditions are a resonable focus of care improvement efforts. Three physicians—Blackford Middleton, MD; Jeffrey Schnipper, MD; and Jeffrey Linder, MD—drove the development of the acute respiratory infection and CAD/diabetes Smart Forms, as they believed that adding point-of-care decision support functionality to the EHR could enhance its impact (and hence improve quality of care) by making it easy for physicians to use within their current workflow.

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AHRQ Innovations Exchange | Real-Time Decision and Documentation Support Increases Adherence to Recommended Care for Respiratory Infections, Diabetes, and Heart Disease