Electronic Health Records and Clinical Decision Support

Knowledge in Medicine – Defining the Problem

In this age, we aspire to practice evidence-based medicine , which has been described as an approach that applies “the best available   evidence gained from the scientific method to medical decision   making.” (Sackett DL, Rosenberg WM, Gray JA et al) Instead, we   are more likely to practice     memory-based medicine meaning that “Current medical practice relies heavily on the unaided mind to recall   a great amount of detailed knowledge.”(Crane RM)   Our failure to practice evidence based medicine is endemic   throughout medical care, as documented by McGlynn et. al. who   found that barely 55% of patients get recommended care, and that   this could be seen in the management of multiple conditions (Figures   1 & 2). Furthermore, the average time from the discovery of   medicine to reach patients is 17 years – because of the slow   adoption of practice changes.(Balas EA, Boren SA)  ….

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The feasibility of using natural language processing to extract clinical information from breast pathology reports

The feasibility of using natural language processing to extract clinical information from breast pathology reports

Julliette M. Buckley, Suzanne B. Coopey, John Sharko, Fernanda Polubriaginof, Brian Drohan, Ahmet K. Belli, Elizabeth M. H. Kim, Judy E. Garber1, Barbara L. Smith, Michele A. Gadd, Michelle C. Specht, Constance A. Roche, Thomas M. Gudewicz2, Kevin S. Hughes

Departments of Surgical Oncology and 2Surgical Pathology, Massachusetts General Hospital, 1Department of Surgical Oncology, Dana Farber Cancer Institute, Boston, Massachusetts, USA E-mail: *Kevin S. Hughes – kshughes@partners.org *Corresponding author

Received: 20 December 11 Accepted: 22 May 12 Published: 30 June 12

This article may be cited as: Buckley JM, Coopey SB, Sharko J, Polubriaginof F, Drohan B, Belli AK, et al. The feasibility of using natural language processing to extract clinical information from breast pathology reports. J Pathol Inform 2012;3:23.

Abstract Objective: The opportunity to integrate clinical decision support systems into clinical practice is limited due to the lack of structured, machine readable data in the current format of the electronic health record. Natural language processing has been designed to convert free text into machine readable data. The aim of the current study was to ascertain the feasibility of using natural language processing to extract clinical information from >76,000 breast pathology reports. Approach and Procedure: Breast pathology reports from three institutions were analyzed using natural language processing software (Clearforest, Waltham, MA) to extract information on a variety of pathologic diagnoses of interest. Data tables were created from the extracted information according to date of surgery, side of surgery, and medical record number. The variety of ways in which each diagnosis could be represented was recorded, as a means of demonstrating the complexity of machine interpretation of free text. Results: There was widespread variation in how pathologists reported common pathologic diagnoses. We report, for example, 124 ways of saying invasive ductal carcinoma and 95 ways of saying invasive lobular carcinoma. There were >4000 ways of saying invasive ductal carcinoma was not present. Natural language processor sensitivity and specificity were 99.1% and 96.5% when compared to expert human coders. Conclusion: We have demonstrated how a large body of free text medical information such as seen in breast pathology reports, can be converted to a machine readable format using natural language processing, and described the inherent complexities of the task.

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Modular EHR

Electronic Health Records and the Management of Women at High Risk of Hereditary Breast and Ovarian Cancer

Brian Drohan, MS,* Elissa M. Ozanne, PhD,and Kevin S. Hughes, MD

*Department of Computer Science, University of Massachusetts Lowell, Massachusetts; Institute for Technology Assessment, Massachusetts General Hospital, Harvard Medical School, Massachusetts; and Avon Breast Evaluation Center, Massachusetts General Hospital, Newton-Wellesley Hospital, Harvard Medical School, Massachusetts

Abstract: Currently, management strategies exist that can decrease the morbidity and mortality associated with having a BRCA1 or BRCA2 mutation. Unfortunately, the task of identifying these patients at high risk is a daunting challenge. This problem is intensified because Electronic Health Records (EHRs) today lack the functionality needed to identify these women and to manage those women once they have been identified. Numerous niche software programs have been developed to fill this gap. Unfortunately, these extremely valuable niche programs are prevented from being interoperable with the EHRs, on the premise that each EHR vendor will build their own programs. Effectively, in our efforts to adopt EHRs, we have lost sight of the fact that they can only have a major impact on quality of care if they contain structured data and if they interact with robust Clinical Decision Support (CDS) tools. We are at a cross roads in the development of the health care Information Technology infrastructure. We can choose a path where each EHR vendor develops each CDS module independently. Alternatively, we can choose a path where experts in each field develop external niche software modules that are interoperable with any EHR vendor. We believe that the modular approach to development of niche software programs that are interoperable with current EHRs will markedly increase the speed at which useful and functional EHRs that improve quality of care become a reality. Thus, in order to realize the benefits of CDS, we suggest vendors develop means to become interoperable with external modular niche programs.

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to download slides for the Genetic Alliance Webinar, June 6, 2012 regarding the EHR and family history (Hughes and Lin)

Family History Module ASHG

Submitted to the 2012 American Society of Human Genetics Annual Meeting


Title:  The Pregnancy and Health Profile Pilot Project:  Evaluating the impact of integrating a novel family history and genetic screening tool on patients, providers, and clinical practice.



Emily Edelman, MS, CGC

Bruce Lin, MPH

Teresa Doksum, PhD

Brian Drohan, PhD

Kevin Hughes, MD

Siobhan Dolan, MD, MPH

Vaughn Edelson, BS

James O’Leary, BS

Lisa Vasquez, MPA

Sara Copeland, MD

Joan Scott, MS, CGC

Effective patient-entered and EHR-compatible collection tools are needed to support translation of family health history (FH) into prenatal care. However, there are limited data about the impact of computerized tools on patient and provider acceptance and outcomes. “The Pregnancy and Health Profile,” (PHP) is a free prenatal genetic screening and risk assessment software for primary prenatal providers that collects FH during intake and provides point-of-care CDS for providers and education for patients. Our objective was to evaluate patient and provider outcomes of PHP in clinical practice. The study population included diverse prenatal providers and patients at 4 sites in IN, ME, NC, and NY. Evaluation included provider pre and post knowledge and usability surveys, pre and post chart audits to assess FH risk assessment, and patient satisfaction surveys. Quantitative survey results were entered into a SPSS database and analyzed using descriptive statistics, Fisher’s exact test, and paired t-tests. Qualitative thematic analysis was used for responses to open-ended questions. 513/618 (83%) patients of diverse age and education levels provided feedback; 81% were white, 11% black, and 9% Latina. Patients felt PHP was easy to use (96%) and understand (98%). Ninety-six percent were not worried about the confidentiality of entering FH into PHP. Twenty of 65 providers (10 OBs and 6 family medicine physicians, 2 nurse midwives, 1 nurse, and 1 dietician educator) provided feedback. Providers felt the data collection and patient education aspects of PHP were useful (60%; 67%); there was mixed feedback on the usefulness of the CDS report. Provider confidence in identifying and managing genetic risks improved after using PHP in practice (p<0.05). In 2 of 3 sites with performance measure data, PHP improved documentation of a 3-generation FH (p<0.001). PHP improved documentation of race and ancestry for patient and/or father of the baby in all 3 sites (p<0.001). This study is one of the first to report on the integration of FH into primary prenatal practice. These data demonstrate that PHP is acceptable to patients and providers for providing FH and that PHP collects FH equal to or better than standard practice. Our results can inform future strategies that use point-of-care tools or online portals to improve patient participation around FH and provider management of genetic risks. Additional research is needed to validate patient-entered data in the prenatal setting.


The Electronic Medical Record (EHR), Health Information Technology, Breast Center Administration, Breast Center Organization, Development of a Risk Assessment Clinic
Roche CA, Lucas MR, Hughes KS: Development of a Risk Assessment Clinic. In: Vogel V (ed.) Management of Women at High Risk for Breast Cancer. Blackwell Science, Inc. 1999. p.166-182.
Levine A, Hughes KS: Cost-Effectiveness of the Identification of Women at High Risk for the Development of Breast and Ovarian Cancer. In: Vogel V (ed.) Management of Women at High Risk for Breast Cancer. Blackwell Science, Inc. 1999 p. 262-276.
Shuster TD, Girshovich L, Whitney TM, Hughes KS: Multidisciplinary care for the breast cancer patient. Surgical Clin NA, 2000;80(2): 505-33.
Hughes KS, Barbarisi L, Rossi RL, Walsh J., deCrescinzo N: Using continuous quality improvement (CQI) to improve the care of patients with breast disease. Adm Radiol J. 1997:16(6-7): 19-27
HughesKS, El-Tamer, Mahmoud, Hughes, Sherwood,Drohan, Brian, Sharko, John,Lawrence, Christine, Loberg, Andrea, Grinstein, George Chapter 79 The Potential of the Electronic Health Record in theBreastCenter. In: Breast Surgery: Office Management and Surgical Technique. Eds: Scott-Conner CEH, Dirbas FM. Springer (In Press)
Drohan B, Ozanne EM,HughesKS. Electronic health records and the management of women at high risk of hereditary breast and ovarian cancer. Breast Journal 2009 Sep-Oct;15 Suppl 1:S46-55.
Hughes,KS, Hughes, S, Mahmoud, ET. The Potential of the Electronic Health Record in theBreastCenter. In: Breast Surgery.New York,New York: Springer Science + Business Media; 2010.
Kawamoto K, Del Fiol G, Strasberg HR, Hulse N, Curtis C, Cimino JJ, Rocha BH, Maviglia S, Fry E, Scherpbier HJ, Huser V, Redington PK, Vawdrey DK, Dufour JC, Price M, Weber JH, White T, Hughes KS, McClay JC, Wood C, Eckert K, Bolte S, Shields D, Tattam PR, Scott P, Liu Z, McIntyre AK. Multi-National, Multi-Institutional Analysis of Clinical Decision Support Data Needs to Inform Development of the HL7 Virtual Medical Record Standard. AMIA Annu Symp Proc. 2010 Nov 13;2010:377-81.
Buyske J, Mackarem G, Ulmer BC, Hughes KS: Breast Cancer in the Nineties. Association of periOperative Registered Nurses Journal 1996;64 (1): 64-72.

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