openEHR Based Contextual Problem List

The problem list is a key facet of the digital patient record that has historically been difficult to curate. This paper presents an implementation of a contextual problem list using openEHR. It describes the modelling approach, key model elements, and how these are assembled to underpin a Problem Oriented Medical Record. Finally, it discusses issues associated with how problem lists may be used.

Increasing the Density of Laboratory Measures for Machine Learning Applications

Background. The imputation of missingness is a key step in Electronic Health Records (EHR) mining, as it can significantly affect the conclusions derived from the downstream analysis in translational medicine. The missingness of laboratory values in EHR is not at random, yet imputation techniques tend to disregard this key distinction. Consequently, the development of an adaptive imputation strategy designed specifically for EHR is an important step in improving the data imbalance and enhancing the predictive power of modeling tools for healthcare applications. Method. We analyzed the laboratory measures derived from Geisinger’s EHR on patients in three distinct cohorts—patients tested for Clostridioides difficile (Cdiff) infection, patients with a diagnosis of inflammatory bowel disease (IBD), and patients with a diagnosis of hip or knee osteoarthritis (OA). We extracted Logical Observation Identifiers Names and Codes (LOINC) from which we excluded those with 75% or more missingness. The comorbidities, primary or secondary diagnosis, as well as active problem lists, were also extracted. The adaptive imputation strategy was designed based on a hybrid approach. The comorbidity patterns of patients were transformed into latent patterns and then clustered. Imputation was performed on a cluster of patients for each cohort independently to show the generalizability of the method. The results were compared with imputation applied to the complete dataset without incorporating the information from comorbidity patterns. Results. We analyzed a total of 67,445 patients (11,230 IBD patients, 10,000 OA patients, and 46,215 patients tested for C. difficile infection). We extracted 495 LOINC and 11,230 diagnosis codes for the IBD cohort, 8160 diagnosis codes for the Cdiff cohort, and 2042 diagnosis codes for the OA cohort based on the primary/secondary diagnosis and active problem list in the EHR. Overall, the most improvement from this strategy was observed when the laboratory measures had a higher level of missingness. The best root mean square error (RMSE) difference for each dataset was recorded as −35.5 for the Cdiff, −8.3 for the IBD, and −11.3 for the OA dataset. Conclusions. An adaptive imputation strategy designed specifically for EHR that uses complementary information from the clinical profile of the patient can be used to improve the imputation of missing laboratory values, especially when laboratory codes with high levels of missingness are included in the analysis.

Characterizing outpatient problem list completeness and duplications in the electronic health record

Objective The study sought to characterize rates of problem list completeness and duplications in common chronic diseases and to identify any relationships that they may have with respect to disease type, demographics, and disease severity. Materials and Methods We performed a retrospective analysis of electronic health record data from Partners HealthCare. We selected 8 common chronic diseases and identified patients with each of those diseases. We then analyzed each patient’s problem list for completeness and duplications and also collected information regarding demographics and disease severity. Rates of completeness and duplications were calculated for each disease and compared according to disease type, demographics, and disease severity. Results A total of 327 695 unique patients and 383 404 problem list entries were identified. Problem list completeness varied from 72.9% in hypertension to 93.5% in asthma, whereas problem list duplications varied from 4.8% in hypertension to 28.2% in diabetes. There was a variable relationship between demographic factors and rates of completeness and duplication. Rates of completeness were positively correlated with disease severity for most diseases. Rates of duplication were consistently positively correlated with disease severity. Conclusions Incompleteness and duplications are both important issues in problem lists. These issues vary widely across different diseases and can also be impacted by patient demographics and disease severity. Further studies are needed to investigate the effect of individual user behaviors and organizational policies on problem list utilization, which will aid the development of interventions that improve the utility of problem lists.

Problems with the problem list: challenges of transparency in an era of patient curation

In recent years, the OpenNotes movement and other changes in healthcare have driven institutions to make medical records increasingly transparent. As patients have begun to question and request changes to their Problem Lists, clinicians have come to face the ever more frequent challenge of discerning which changes to make and which to refuse. Now clinicians and patients together choose the list of problems that represent the patient’s current state of health and illness. As the physician’s role slides closer to consultant and the medical paternalism of the twentieth century falls further into the background of our technology-infused present, who holds the power of delineating a patient’s clinical identity? This paper examines the ethical and practical dimensions of this question and proposes a research agenda that aims to answer it. Such explorations are essential to ensuring that the physician remains relevant to patient’s notions of health, illness, intervention, and healing.

Abstract 240: Assessing the Lack of Appropriate Anticoagulation in Patients With Atrial Fibrillation - Implications for Cardiology Registry-Based Care

Intro: Anticoagulation is indicated for many patients with atrial fibrillation (AF) for prevention of cardioembolic stroke, although national proportions of eligible patients receiving anticoagulation remain suboptimal. Automated and semi-automated quality improvement techniques including registries and population health coordinators may help identify and increase eligible patients to receive anticoagulation. Methods: We queried our electronic health record to identify patients without anticoagulation but with atrial fibrillation (as identified as either paroxysmal atrial fibrillation, persistent atrial fibrillation, chronic atrial fibrillation, typical atrial flutter, atypical atrial flutter, or unspecified atrial flutter) either on the problem list or as billed administrative claims between September 2016 - September 2019 in MGH outpatient cardiology clinics. All patients were participating in MGH cardiology, with their primary care based either within MGH or outside of MGH. Then, we conducted detailed chart review to calculate thromboembolic risk with respective CHADS-VASC score and confirmed that the patient was not receiving anticoagulation. A typology was developed as charts were reviewed to categorize reasons for lacking anticoagulation. These categories were grouped into broader categories representing a (1) potential quality problem or (2) appropriate lack of anticoagulation. Results: Of 100 patients, 59 were deemed to have a potential quality problem and 41 were deemed to have appropriate lack of anticoagulation. Of the patients with a potential quality problem, 11 have a CHADS VASC score of 1, 18 have a CHADS VASC score of 2, 6 have a CHADS VASC score of 3, 10 have a CHADS VASC score of 4, and 8 have a CHADS of 5, and 6 have a CHADS VASC of 6 or above. Additionally, 3 patients have been lost to follow up, 12 patients had presented with current symptoms of AF within the last year, and 44 patients exhibited acute history of AF symptoms. 41 patients did not present concern for multiple reasons including: CHADS VASC=0, deceased, patients declined medication, followed by outside cardiologist, technology and medication discrepancies, inaccurate administrative data for AF, and prior major bleeding. Conclusions: We found that most un-anticoagulated AF patients identified by administrative claims and EHR problem lists are likely eligible for anticoagulation. Of those, most have a history of paroxysmal AF. As such, registry-based strategies based on queries of past AF may improve rates of anticoagulation in this population. Since automated queries still detect many patients with contraindications such as bleeding or inaccurate administrative data, manual review of administrative queries is likely to be important in quality efforts for AF.

Factors Influencing Problem List Use in Electronic Health Records—Application of the Unified Theory of Acceptance and Use of Technology

Background Problem-oriented electronic health record (EHR) systems can help physicians to track a patient's status and progress, and organize clinical documentation, which could help improving quality of clinical data and enable data reuse. The problem list is central in a problem-oriented medical record. However, current problem lists remain incomplete because of the lack of end-user training and inaccurate content of underlying terminologies. This leads to modifications of diagnosis code descriptions and use of free-text notes, limiting reuse of data. Objectives We aimed to investigate factors that influence acceptance and actual use of the problem list, and used these to propose recommendations, to increase the value of problem lists for (re)use. Methods Semistructured interviews were conducted with physicians, heads of medical departments, and data quality experts, who were invited through snowball sampling. The interviews were transcribed and coded. Comments were fitted in constructs of the validated framework unified theory of acceptance user technology (UTAUT), and were discussed in terms of facilitators and barriers. Results In total, 24 interviews were conducted. We found large variability in attitudes toward problem list use. Barriers included uncertainty about the responsibility for maintaining the problem list and little perceived benefits. Facilitators included the (re)design of policies, improved (peer-to-peer) training to increase motivation, and positive peer feedback and monitoring. Motivation is best increased through sharing benefits relevant in the care process, such as providing overview, timely generation of discharge or referral letters, and reuse of data. Furthermore, content of the underlying terminology should be improved and the problem list should be better presented in the EHR system. Conclusion To let physicians accept and use the problem list, policies and guidelines should be redesigned, and prioritized by supervising staff. Additionally, peer-to-peer training on the benefits of using the problem list is needed.

Electronic Health Record and Problem Lists in Leeds, United Kingdom: Variability of general practitioners’ views

Data sharing of Electronic Health Records from general practices to secondary care in Leeds occurs through the so-called Leeds Care Records, which collects a specific set of codes from primary care, known as ‘Active Problems’, and presents it to the user. Variability on its content is a known issue. To explore general practitioners’ views on their use of ‘Active Problems’ and on sharing data, so lessons could be learnt on how to homogenise and improve shared data. Assessing Leeds general practitioners’ views through two parallel processes (60 online surveys and 17 interviews). General practitioners feel they do not have the time nor the training required for keeping a shared approach to concise and current Problem Lists in electronic patient records. Action is needed to reduce current variability, and to improve the quality of shared information. Some types of codes currently present in Problem Lists have very little support among general practitioners who consider the focus should be on long-term conditions and probably adding current acute diagnoses and life expectancy items and not omitting sensitive information. There is a perceived need of training and time to update Problem Lists if their quality is to improve.

Two algorithms for the reorganisation of the problem list by organ system

ObjectiveLong problem lists can be challenging to use. Reorganisation of the problem list by organ system is a strategy for making long problem lists more manageable.MethodsIn a small-town primary care setting, we examined 4950 unique problem lists over 5 years (24 033 total problems and 2170 unique problems) from our electronic health record. All problems were mapped to the International Classification of Diseases, 10th Revision, Clinical Modification (ICD-10-CM) and SNOMED CT codes. We developed two different algorithms for reorganising the problem list by organ system based on either the ICD-10-CM or the SNOMED CT code.ResultsThe mean problem list length was 4.9±4.6 problems. The two reorganisation algorithms allocated problems to one of 15 different categories (12 aligning with organ systems). 26.2% of problems were assigned to a more general category of ‘signs and symptoms’ that did not correspond to a single organ system. The two algorithms were concordant in allocation by organ system for 90% of the unique problems. Since ICD-10-CM is a monohierarchic classification system, problems coded by ICD-10-CM were assigned to a single category. Since SNOMED CT is a polyhierarchical ontology, 19.4% of problems coded by SNOMED CT were assigned to multiple categories.ConclusionReorganisation of the problem list by organ system is feasible using algorithms based on either ICD-10-CM or SNOMED CT codes, and the two algorithms are highly concordant.

Complexity in pediatric primary care

BackgroundThe management of patients in primary care is often complicated by the presence of multiple chronic conditions and psychosocial issues that increase the complexity of the encounter and have important impacts on care. There is a paucity of literature on this subject in the pediatric population.ObjectivesThe aim of this study was to quantify the burden of chronic conditions in pediatric primary care.MethodsThe problem lists of 3995 randomly selected patients from a community pediatric clinic and an academic hospital-based pediatric clinic in the same metropolitan area were analyzed for the presence and number of any chronic condition.ResultsIn total, 53% of patients suffered from at least one chronic problem, 25% had two or more chronic conditions and 5.1% had four or more conditions. Compared with the community clinic, the academic clinic had significantly more children with catastrophic complex conditions (P<0.001). A regression analysis showed a significant positive correlation between the number of chronic medical conditions and mental health diagnoses.ConclusionsThe burden of chronic disease in the pediatric primary care setting may be significantly higher than has been previously suggested. To ensure optimal quality of care, health planners should take into account the high burden of chronic illness, psychosocial issues and multimorbidity among patients in the pediatric primary care setting, as well as the higher complexity profile of patients attending academic clinics.