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Nudging Health Care Providers' Adoption of Clinical Decision Support: Protocol for the User-Centered Development of a Behavioral Economics-Inspired Electronic Health Record Tool

Richardson, Safiya; Dauber-Decker, Katherine; Solomon, Jeffrey; Khan, Sundas; Barnaby, Douglas; Chelico, John; Qiu, Michael; Liu, Yan; Mann, Devin; Pekmezaris, Renee; McGinn, Thomas; Diefenbach, Michael
BACKGROUND:The improvements in care resulting from clinical decision support (CDS) have been significantly limited by consistently low health care provider adoption. Health care provider attitudes toward CDS, specifically psychological and behavioral barriers, are not typically addressed during any stage of CDS development, although they represent an important barrier to adoption. Emerging evidence has shown the surprising power of using insights from the field of behavioral economics to address psychological and behavioral barriers. Nudges are formal applications of behavioral economics, defined as positive reinforcement and indirect suggestions that have a nonforced effect on decision-making. OBJECTIVE:Our goal is to employ a user-centered design process to develop a CDS tool-the pulmonary embolism (PE) risk calculator-for PE risk stratification in the emergency department that incorporates a behavior theory-informed nudge to address identified behavioral barriers to use. METHODS:All study activities took place at a large academic health system in the New York City metropolitan area. Our study used a user-centered and behavior theory-based approach to achieve the following two aims: (1) use mixed methods to identify health care provider barriers to the use of an active CDS tool for PE risk stratification and (2) develop a new CDS tool-the PE risk calculator-that addresses behavioral barriers to health care providers' adoption of CDS by incorporating nudges into the user interface. These aims were guided by the revised Observational Research Behavioral Information Technology model. A total of 50 clinicians who used the original version of the tool were surveyed with a quantitative instrument that we developed based on a behavior theory framework-the Capability-Opportunity-Motivation-Behavior framework. A semistructured interview guide was developed based on the survey responses. Inductive methods were used to analyze interview session notes and audio recordings from 12 interviews. Revised versions of the tool were developed that incorporated nudges. RESULTS:Functional prototypes were developed by using Axure PRO (Axure Software Solutions) software and usability tested with end users in an iterative agile process (n=10). The tool was redesigned to address 4 identified major barriers to tool use; we included 2 nudges and a default. The 6-month pilot trial for the tool was launched on October 1, 2021. CONCLUSIONS:Clinicians highlighted several important psychological and behavioral barriers to CDS use. Addressing these barriers, along with conducting traditional usability testing, facilitated the development of a tool with greater potential to transform clinical care. The tool will be tested in a prospective pilot trial. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID)/UNASSIGNED:DERR1-10.2196/42653.
PMCID:9892982
PMID: 36652293
ISSN: 1929-0748
CID: 5430822

How Should Clinicians' Performance Be Assessed When Health Care Organizations Implement Behavioral Architecture That Generates Negative Consequences?

Richardson, Safiya
Behavioral interventions have been shown to have powerful effects on human behavior both outside of and within the context of health care. As organizations increasingly adopt behavioral architecture, care must be taken to consider its potential negative consequences. An evidenced-based approach is best, whereby interventions that might have a significant deleterious effect on patients' health outcomes are first tested and rigorously evaluated before being systematically rolled out. In the case of clinical decision support, brief and thorough instructions should be provided for use. Physician performance when using these systems is best measured relatively, in the context of peers with similar training. Responsibility for errors must be shared with clinical team members and system designers.
PMCID:7605411
PMID: 33009771
ISSN: 2376-6980
CID: 4996202

A framework for digital health equity

Richardson, Safiya; Lawrence, Katharine; Schoenthaler, Antoinette M; Mann, Devin
We present a comprehensive Framework for Digital Health Equity, detailing key digital determinants of health (DDoH), to support the work of digital health tool creators in industry, health systems operations, and academia. The rapid digitization of healthcare may widen health disparities if solutions are not developed with these determinants in mind. Our framework builds on the leading health disparities framework, incorporating a digital environment domain. We examine DDoHs at the individual, interpersonal, community, and societal levels, discuss the importance of a root cause, multi-level approach, and offer a pragmatic case study that applies our framework.
PMCID:9387425
PMID: 35982146
ISSN: 2398-6352
CID: 5300232

Higher Imaging Yield When Clinical Decision Support Is Used

Richardson, Safiya; Cohen, Stuart; Khan, Sundas; Zhang, Meng; Qiu, Guang; Oppenheim, Michael I; McGinn, Thomas
OBJECTIVE:Increased utilization of CT pulmonary angiography (CTPA) for the evaluation of pulmonary embolism has been associated with decreasing diagnostic yields and rising concerns about the harms of unnecessary testing. The objective of this study was to determine whether clinical decision support (CDS) use would be associated with increased imaging yields after controlling for selection bias. METHODS:We performed a retrospective cohort study in the emergency departments of two tertiary care hospitals of all CTPAs performed between August 2015 and September 2018. Providers ordering a CTPA are routed to an optional CDS tool, which allows them to use Wells' Criteria for pulmonary embolism. After propensity score matching, CTPA yield was calculated for the CDS-use and CDS-dismissal groups and stratified by provider type. RESULTS:A total of 7,367 CTPAs were ordered during the study period. Of those, providers used the CDS tool in 2,568 (35%) cases and did not use the tool in 4,799 (65%) of cases. After propensity score matching, CTPA yield was 11.99% in the CDS-use group and 8.70% in the CDS-dismissal group (P < .001). Attending physicians, residents, and physician assistant CDS users demonstrated a 56.5% (P = .006), 38.7% (P = .01), and 16.7% (P = .03) increased yield compared with those who dismissed the tool, respectively. DISCUSSION/CONCLUSIONS:Diagnostic yield was 38% higher for CTPAs when the provider used the CDS tool, after controlling for selection bias. Yields were higher for every provider type. Further research is needed to discover successful strategies to increase provider use of these important tools.
PMCID:7136128
PMID: 31899178
ISSN: 1558-349x
CID: 4996172

Presenting Characteristics, Comorbidities, and Outcomes Among 5700 Patients Hospitalized With COVID-19 in the New York City Area

Richardson, Safiya; Hirsch, Jamie S; Narasimhan, Mangala; Crawford, James M; McGinn, Thomas; Davidson, Karina W; Barnaby, Douglas P; Becker, Lance B; Chelico, John D; Cohen, Stuart L; Cookingham, Jennifer; Coppa, Kevin; Diefenbach, Michael A; Dominello, Andrew J; Duer-Hefele, Joan; Falzon, Louise; Gitlin, Jordan; Hajizadeh, Negin; Harvin, Tiffany G; Hirschwerk, David A; Kim, Eun Ji; Kozel, Zachary M; Marrast, Lyndonna M; Mogavero, Jazmin N; Osorio, Gabrielle A; Qiu, Michael; Zanos, Theodoros P
Importance/UNASSIGNED:There is limited information describing the presenting characteristics and outcomes of US patients requiring hospitalization for coronavirus disease 2019 (COVID-19). Objective/UNASSIGNED:To describe the clinical characteristics and outcomes of patients with COVID-19 hospitalized in a US health care system. Design, Setting, and Participants/UNASSIGNED:Case series of patients with COVID-19 admitted to 12 hospitals in New York City, Long Island, and Westchester County, New York, within the Northwell Health system. The study included all sequentially hospitalized patients between March 1, 2020, and April 4, 2020, inclusive of these dates. Exposures/UNASSIGNED:Confirmed severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection by positive result on polymerase chain reaction testing of a nasopharyngeal sample among patients requiring admission. Main Outcomes and Measures/UNASSIGNED:Clinical outcomes during hospitalization, such as invasive mechanical ventilation, kidney replacement therapy, and death. Demographics, baseline comorbidities, presenting vital signs, and test results were also collected. Results/UNASSIGNED:A total of 5700 patients were included (median age, 63 years [interquartile range {IQR}, 52-75; range, 0-107 years]; 39.7% female). The most common comorbidities were hypertension (3026; 56.6%), obesity (1737; 41.7%), and diabetes (1808; 33.8%). At triage, 30.7% of patients were febrile, 17.3% had a respiratory rate greater than 24 breaths/minute, and 27.8% received supplemental oxygen. The rate of respiratory virus co-infection was 2.1%. Outcomes were assessed for 2634 patients who were discharged or had died at the study end point. During hospitalization, 373 patients (14.2%) (median age, 68 years [IQR, 56-78]; 33.5% female) were treated in the intensive care unit care, 320 (12.2%) received invasive mechanical ventilation, 81 (3.2%) were treated with kidney replacement therapy, and 553 (21%) died. Mortality for those requiring mechanical ventilation was 88.1%. The median postdischarge follow-up time was 4.4 days (IQR, 2.2-9.3). A total of 45 patients (2.2%) were readmitted during the study period. The median time to readmission was 3 days (IQR, 1.0-4.5) for readmitted patients. Among the 3066 patients who remained hospitalized at the final study follow-up date (median age, 65 years [IQR, 54-75]), the median follow-up at time of censoring was 4.5 days (IQR, 2.4-8.1). Conclusions and Relevance/UNASSIGNED:This case series provides characteristics and early outcomes of sequentially hospitalized patients with confirmed COVID-19 in the New York City area.
PMID: 32320003
ISSN: 1538-3598
CID: 4397182

Comparison of Chest Radiograph Impressions for Diagnosing Pneumonia: Accounting for Categories of Language Certainty

Makhnevich, Alexander; Sinvani, Liron; Feldhamer, Kenneth H; Zhang, Meng; Richardson, Safiya; McGinn, Thomas G; Cohen, Stuart L
OBJECTIVES/OBJECTIVE:Uncertain language in chest radiograph (CXR) reports for the diagnosis of pneumonia is prevalent. The purpose of this study is to validate an a priori stratification of CXR results for diagnosing pneumonia based on language of certainty. DESIGN/METHODS:Retrospective chart review. SETTING AND PARTICIPANTS/METHODS:CXR reports of 2,411 hospitalized patients ≥ 18 years, admitted to medicine, who received a CXR and noncontrast chest CT within 48 hours of emergency department registration at two large academic hospitals (tertiary and quaternary care) were reviewed. METHODS:test; a P value of .0031 was considered significant to account for multiple comparisons. RESULTS:CXR reports for the diagnosis of pneumonia revealed the following distribution: 61% negative, 32% uncertain, and 7% positive; CT reports were 55% negative, 22% uncertain, and 23% positive for the diagnosis of pneumonia. There were significant differences between CXR categories compared with CT categories for diagnosis of pneumonia (P < .001). Negative CXR results were not significantly different than the uncertain category with the most uncertain language (P = .030) but were significantly different from all other uncertain categories and positive results (each P < .001). Positive CXR results were not significantly different than the least uncertain category (most certain language) (P = .130) but were significantly different from all other categories (each P < .001). CONCLUSIONS AND IMPLICATIONS/CONCLUSIONS:Language used in CXR reports to diagnose pneumonia exists in categories of varying certainty and should be considered when evaluating patients for pneumonia.
PMID: 35792164
ISSN: 1558-349x
CID: 5280352

The effect of race coefficients on preemptive listing for kidney transplantation

Abate, Mersema; Jandovitz, Nicholas; Hirsch, Jamie S; Breslin, Nadine; Lau, Lawrence; Fahmy, Ahmed E; Jhaveri, Kenar D; Richardson, Safiya; Alsalmay, Yaser; Baez, Anthony; Mishra, Akash; Bolourani, Siavash; Miyara, Santiago J; Winnick, Aaron; Nair, Gayatri; Bhaskaran, Madhu C; Grodstein, Elliot; Kressel, Adam M; Teperman, Lewis W; Molmenti, Ernesto P; Nair, Vinay
BACKGROUND/UNASSIGNED:Race coefficients of estimated glomerular filtration rate (eGFR) formulas may be partially responsible for racial inequality in preemptive listing for kidney transplantation. METHODS/UNASSIGNED:We used the Scientific Registry of Transplant Recipients database to evaluate differences in racial distribution of preemptive listing before and after application of the Modification of Diet in Renal Disease (MDRD) and the Chronic Kidney Disease Epidemiology Collaboration (CKD-EPI) race coefficients to all preemptively listed non-Black kidney transplant candidates (eGFR modulation). Odds of preemptive listing were calculated by race, with Black as the reference before and after eGFR modulation. Variables known to influence preemptive listing were included in the model. RESULTS/UNASSIGNED:were removed. Compared with Black candidates, the adjusted odds of preemptive listing for White candidates decreased from 2.01 [95% confidence interval (95% CI) 1.78-2.26] before eGFR modulation to 1.18 (95% CI 1.0-1.39; P = 0.046) with the MDRD and 1.37 (95% CI 1.18-1.58) with the CKD-EPI equations after adjusting for race coefficients. CONCLUSIONS/UNASSIGNED:Removing race coefficients in GFR estimation formulas may result in a more equitable distribution of Black candidates listed earlier on a preemptive basis.
PMCID:9050544
PMID: 35498880
ISSN: 2048-8505
CID: 5394872

Automated Pulmonary Embolism Risk Assessment Using the Wells Criteria: Validation Study

Zhang, Nasen Jonathan; Rameau, Philippe; Julemis, Marsophia; Liu, Yan; Solomon, Jeffrey; Khan, Sundas; McGinn, Thomas; Richardson, Safiya
BACKGROUND:Computed tomography pulmonary angiography (CTPA) is frequently used in the emergency department (ED) for the diagnosis of pulmonary embolism (PE), while posing risk for contrast-induced nephropathy and radiation-induced malignancy. OBJECTIVE:We aimed to create an automated process to calculate the Wells score for pulmonary embolism for patients in the ED, which could potentially reduce unnecessary CTPA testing. METHODS:We designed an automated process using electronic health records data elements, including using a combinatorial keyword search method to query free-text fields, and calculated automated Wells scores for a sample of all adult ED encounters that resulted in a CTPA study for PE at 2 tertiary care hospitals in New York, over a 2-month period. To validate the automated process, the scores were compared to those derived from a 2-clinician chart review. RESULTS:A total of 202 ED encounters resulted in a completed CTPA to form the retrospective study cohort. Patients classified as "PE likely" by the automated process (126/202, 62%) had a PE prevalence of 15.9%, whereas those classified as "PE unlikely" (76/202, 38%; Wells score >4) had a PE prevalence of 7.9%. With respect to classification of the patient as "PE likely," the automated process achieved an accuracy of 92.1% when compared with the chart review, with sensitivity, specificity, positive predictive value, and negative predictive value of 93%, 90.5%, 94.4%, and 88.2%, respectively. CONCLUSIONS:This was a successful development and validation of an automated process using electronic health records data elements, including free-text fields, to classify risk for PE in ED visits.
PMCID:8922138
PMID: 35225812
ISSN: 2561-326x
CID: 5435692

Association of race/ethnicity with mortality in patients hospitalized with COVID-19

Richardson, Safiya; Martinez, Johanna; Hirsch, Jamie S; Cerise, Jane; Lesser, Martin; Roswell, Robert O; Davidson, Karina W
OBJECTIVE:To evaluate racial and ethnic differences in mortality among patients hospitalized with coronavirus disease 2019 (COVID-19) after adjusting for baseline characteristics and comorbidities. METHODS:This retrospective cohort study at 13 acute care facilities in the New York City metropolitan area included sequentially hospitalized patients between March 1, 2020, and April 27, 2020. Last day of follow up was July 31, 2020. Patient demographic information, including race/ethnicity and comorbidities, were collected. The primary outcome was in-hospital mortality. RESULTS:A total of 10 869 patients were included in the study (median age, 65 years [interquartile range (IQR) 54-77; range, 18-107 years]; 40.5% female). In adjusted time-to-event analysis, increased age, male sex, insurance type (Medicare and Self-Pay), unknown smoking status, and a higher score on the Charlson Comorbidity Index were significantly associated with higher in-hospital mortality. Adjusted risk of hospital mortality for Black, Asian, Hispanic, multiracial/other, and unknown race/ethnicity patients were similar to risk for White patients. CONCLUSIONS:In a large diverse cohort of patients hospitalized with COVID-19, patients from racial/ethnic minorities experienced similar mortality risk as White patients.
PMCID:9352026
PMID: 35925973
ISSN: 1932-6203
CID: 5430812

External validation of the IMPROVE-DD risk assessment model for venous thromboembolism among inpatients with COVID-19

Goldin, Mark; Lin, Stephanie K; Kohn, Nina; Qiu, Michael; Cohen, Stuart L; Barish, Matthew A; Gianos, Eugenia; Diaz, Anise; Richardson, Safiya; Giannis, Dimitrios; Chatterjee, Saurav; Coppa, Kevin; Hirsch, Jamie S; Ngu, Sam; Firoozan, Sheila; McGinn, Thomas; Spyropoulos, Alex C
There is a need to discriminate which COVID-19 inpatients are at higher risk for venous thromboembolism (VTE) to inform prophylaxis strategies. The IMPROVE-DD VTE risk assessment model (RAM) has previously demonstrated good discrimination in non-COVID populations. We aimed to externally validate the IMPROVE-DD VTE RAM in medical patients hospitalized with COVID-19. This retrospective cohort study evaluated the IMPROVE-DD VTE RAM in adult patients with COVID-19 admitted to one of thirteen Northwell Health hospitals in the New York metropolitan area between March 1, 2020 and April 27, 2020. VTE was defined as new-onset symptomatic deep venous thrombosis or pulmonary embolism. To assess the predictive value of the RAM, the receiver operating characteristic (ROC) curve was plotted and the area under the curve (AUC) was calculated. Sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) were calculated. Of 9407 patients who met study criteria, 274 patients developed VTE with a prevalence of 2.91%. The VTE rate was 0.41% for IMPROVE-DD score 0-1 (low risk), 1.21% for score 2-3 (moderate risk), and 5.30% for score ≥ 4 (high risk). Approximately 45.7% of patients were classified as high VTE risk, 33.3% moderate risk, and 21.0% low risk. Discrimination of low versus moderate-high VTE risk demonstrated sensitivity 0.971, specificity 0.215, PPV 0.036, and NPV 0.996. ROC AUC was 0.703. In this external validation study, the IMPROVE-DD VTE RAM demonstrated very good discrimination to identify hospitalized COVID-19 patients at low, moderate, and high VTE risk.
PMCID:8214061
PMID: 34146235
ISSN: 1573-742x
CID: 4917922