Electronic Medical Record and Clinical Evaluation of Two Patient Cohorts at Risk of Hypophosphatasia: Family History is an Underutilized Tool to Diagnose Patients with Rare Disease (Preprint)

2021 ◽  
Author(s):  
Christina Peroutka ◽  
Natalie Beck ◽  
Ethan Gough ◽  
Mark Marzinke ◽  
Julie Hoover-Fong
Keyword(s):  
At Risk ◽  
Family History ◽  
Bone Density ◽  
Medical Record ◽  
Electronic Medical Record ◽  
Clinical Evaluation ◽  
Family Members ◽  
Similar Proportion ◽  
Low Bone Density ◽  
Genetic Medicine

BACKGROUND Family history (FH) is a powerful tool in screening and testing for chronic disease, oncologic conditions, and other genetic diagnoses, and is dependent upon observing patterns of features inherited across generations. Despite acceptance of FH as a fundamental part of a genetic medicine evaluation, there are limited data in other medical fields about its utility and benefit to patients. To date, there are no published data pertaining to the clinical utility of FH to diagnose individuals with hypophosphatasia (HPP), a rare genetic low bone density condition. OBJECTIVE To compare FH recorded in the electronic medical record (EMR) of patients at risk of HPP before a genetic medicine encounter to that learned during that clinical evaluation. METHODS We evaluated two patient populations at-risk of a rare metabolic condition-- hypophosphatasia (HPP)—for the quality and quantity of FH data in their medical records. Population 1 was derived from patients seeking evaluation for a low bone density diagnosis at the Johns Hopkins Greenberg Center for Skeletal Dysplasias (GCSD); population 2 was identified through a targeted electronic medical record (EMR) query of low serum alkaline phosphatase (AP) measurements obtained through the Johns Hopkins Clinical Laboratory. RESULTS In population 1 (n = 38), 27 (71%) were confirmed to have HPP. Of these, 14 (52%) presented with FH information in the EMR from 3 or more family members, and in 4 (15%) FH was suggestive of HPP. In population 2 (n=348), a similar proportion of subjects had 3 or more family members mentioned in the EMR (183 or 53%), but only 3 subjects (1%) included sufficient detail to determine that the family history was suggestive of HPP. Notably, once all patients in population 1 completed a medical genetics evaluation and HPP was confirmed, 20 (74%) had probable affected family members identified through obtaining and analyzing a pedigree. After cascade testing was offered to these family members, 17 patients (71%) from population 1 had at least one family member with HPP confirmed at a molecular level. CONCLUSIONS Based on these results, we propose that a full genetic medicine evaluation of those subjects from population 2 at highest risk of HPP would confirm HPP in many of them and identify similarly affected family members. We propose that taking a FH refines the diagnostic precision for patients with low bone density and identifies affected family members, and that HPP is likely more prevalent than previously thought. CLINICALTRIAL n/a

scholarly journals Electronic Medical Record and Clinical Evaluation of Two Patient Cohorts at Risk of Hypophosphatasia: Family History is an Underutilized Tool to Diagnose Patients with Rare Disease

2021 ◽  
Author(s):  
Christina Peroutka ◽  
Natalie M Beck ◽  
Ethan Gough ◽  
Mark Marzinke ◽  
Julie Hoover-Fong
Keyword(s):  
At Risk ◽  
Family History ◽  
Bone Density ◽  
Medical Record ◽  
Electronic Medical Record ◽  
Family Members ◽  
Similar Proportion ◽  
Low Bone Density ◽  
Populations At Risk ◽  
Genetic Medicine

Abstract Background: Family history (FH) is a powerful tool in screening and testing for chronic disease, oncologic conditions, and other genetic diagnoses, and is dependent upon observing patterns of features inherited across generations. Despite acceptance of FH as a fundamental part of a genetic medicine evaluation, there are limited data in other medical fields about its utility and benefit to patients. Methods: We evaluated two patient populations at-risk of a rare metabolic condition-- hypophosphatasia (HPP)—for the quality and quantity of FH data in their medical records. Population 1 was derived from patients seeking evaluation for a low bone density diagnosis at the Johns Hopkins Greenberg Center for Skeletal Dysplasias (GCSD); population 2 was identified through a targeted electronic medical record (EMR) query of low serum alkaline phosphatase (AP) measurements obtained through the Johns Hopkins Clinical Laboratory. Results: In population 1 (n = 38), 27 (71%) were confirmed to have HPP. Of these, 14 (52%) presented with FH information in the EMR from 3 or more family members, and in 4 (15%) FH was suggestive of HPP. In population 2 (n=348), a similar proportion of subjects had 3 or more family members mentioned in the EMR (183 or 53%), but only 3 subjects (1%) included sufficient detail to determine that the family history was suggestive of HPP. Notably, once all patients in population 1 completed a medical genetics evaluation and HPP was confirmed, 20 (74%) had probable affected family members identified through obtaining and analyzing a pedigree. After cascade testing was offered to these family members, 17 patients (71%) from population 1 had at least one family member with HPP confirmed at a molecular level. Conclusions: Based on these results, we propose that a full genetic medicine evaluation of those subjects from population 2 at highest risk of HPP would confirm HPP in many of them and identify similarly affected family members. We propose that taking a FH refines the diagnostic precision for patients with low bone density and identifies affected family members, and that HPP is likely more prevalent than previously thought.

2.16 Electronic Medical Record Identification of At-Risk Patients in a Child Psychiatry Fellow Outpatient Clinic

2017 ◽  
Vol 56 (10) ◽  
pp. S182
Author(s):  
Rebecca Reilly ◽  
Courtney Demuth ◽  
Katie Gallagher ◽  
Luann French ◽  
Oscar Gary Bukstein ◽  
...  
Keyword(s):  
At Risk ◽  
Medical Record ◽  
Electronic Medical Record ◽  
Child Psychiatry ◽  
Outpatient Clinic ◽  
Risk Patients

Using the electronic medical record to identify and follow survivors of pediatric malignancies.

2012 ◽  
Vol 30 (34_suppl) ◽  
pp. 302-302
Author(s):  
Elizabeth Bell ◽  
Robert Michael Cooper ◽  
Lisa Mueller
Keyword(s):  
At Risk ◽  
Cancer Treatment ◽  
Childhood Cancer ◽  
Medical Record ◽  
Electronic Medical Record ◽  
Late Effects ◽  
Kaiser Permanente ◽  
Pediatric Malignancies ◽  
Group 2 ◽  
Group 1

302 Background: There are currently more than 328,000 survivors of pediatric malignancies in the United States (NCI, The Childhood Cancer Survivor Study: An Overview, http://www.cancer.gov/cancertopics/coping/ccss . 6/6/2012). These survivors are at risk for significant late effects from their cancer treatments (Childhood Cancer Survivors Study (Oeffinger, et al, NEJM 2006)). The Kaiser Permanente health care system has good insurance retention of patients treated for pediatric malignancies. Kaiser also uses an electronic medical record, which improves our ability to identify survivors and follow them over time to identify and manage late effects of cancer treatment. The Children’s Oncology Group (COG) has released a summary of cancer treatment form and specific guidelines for follow-up based on patients’ treatment. Methods: In 2010, we queried the Kaiser Permanente Southern California Cancer Registry for all patients who were diagnosed with a malignancy under the age of 18 from 1980 to 2009. This was cross-referenced with list of current Kaiser members as of 2010. We created a database of the current members and their diagnosis, treatment center, age at diagnosis, date of diagnosis, current age, years of survivorship, and sex. We divided the patients into priority groups: (1) more than 5 years from diagnosis and over age 18, (2) more than 5 years from diagnosis and less than age 18, and (3) less than 5 years from diagnosis. We began to prepare summaries of cancer treatment for the groups using the COG form. Results: We identified 1,267 survivors of pediatric malignancies who were Kaiser members in 2010. 54% are still Kaiser members 10 years after diagnosis. There were 611 in Group 1, 293 in Group 2, and 363 in Group 3. We have prepared summaries of cancer treatment including late effects for 400 of the survivors, 360 from Group 1, and 40 from Group 2. Conclusions: The combination of an electronic medical record and insurance retention allows us to identify and track survivors of pediatric malignancies into adulthood. With completed summaries of cancer treatment we will be able to quickly identify at-risk populations for monitoring and potential interventions.

An Automated Model to Identify Heart Failure Patients at Risk for 30-Day Readmission or Death Using Electronic Medical Record Data

Medical Care ◽  
2010 ◽  
Vol 48 (11) ◽  
pp. 981-988 ◽  
Author(s):  
Ruben Amarasingham ◽  
Billy J. Moore ◽  
Ying P. Tabak ◽  
Mark H. Drazner ◽  
Christopher A. Clark ◽  
...  
Keyword(s):  
Heart Failure ◽  
At Risk ◽  
Medical Record ◽  
Electronic Medical Record ◽  
Medical Record Data ◽  
Heart Failure Patients ◽  
Electronic Medical Record Data ◽  
Record Data ◽  
Patients At Risk

scholarly journals FROM BRAIN DISEASE TO BRAIN HEALTH: PRIMARY PREVENTION OF ALZHEIMER’S DISEASE AND RELATED DISORDERS IN A HEALTH SYSTEM USING AN ELECTRONIC MEDICAL RECORD-BASED APPROACH

2017 ◽  
pp. 1-8
Author(s):  
A.M. Fosnacht ◽  
S. Patel ◽  
C. Yucus ◽  
A. Pham ◽  
E. Rasmussen ◽  
...  
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
At Risk ◽  
Primary Prevention ◽  
Health System ◽  
Medical Record ◽  
Electronic Medical Record ◽  
Brain Disease ◽  
Brain Health ◽  
Risk Patients

Background: Alzheimer’s disease and aging brain disorders are progressive, often fatal neurodegenerative diseases. Successful aging, modern lifestyles and behaviors have combined to result in an expected epidemic. Risks for these diseases include genetic, medical, and lifestyle factors; over 20 modifiable risks have been reported. Objectives: We aim to primarily prevent Alzheimer’s disease and related disorders through electronic medical record (EMR)-based screening, risk assessments, interventions, and surveillance. Design: We identified modifiable risks; developed human, systems and infrastructural resources; developed interventions; and targeted at-risk groups for the intervention. Setting: A Community Based Health System. Participants: In year one (June 2015 to May 2016), 133 at-risk patients received brain health services with the goal of delaying or preventing Alzheimer’s disease and related disorders. Measurements: We created mechanisms to identify patients at high risk of neurodegenerative disease; EMR-based structured clinical documentation support tools to evaluate risk factors and history; evidence-based interventions to modify risk; and the capacity for annual surveillance, pragmatic trials, and practice-based and genomic research using the EMR. Results: This paper describes our Center for Brain Health, our EMR tools, and our first year of healthy but at-risk patients. Conclusion: We are translating research into primary prevention of Alzheimer’s disease and related disorders in our health system and aim to shift the paradigm in Neurology from brain disease to brain health.

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