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Goren A, Santos HC, Davis TW, Lowe RB, Monfette M, Meyer MN, Chabris CF. Comparison of Clinical Decision Support Tools to Improve Pediatric Lipid Screening. J Pediatr 2024; 269:113973. [PMID: 38401785 DOI: 10.1016/j.jpeds.2024.113973] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/24/2023] [Revised: 02/12/2024] [Accepted: 02/16/2024] [Indexed: 02/26/2024]
Abstract
OBJECTIVE To test whether different clinical decision support tools increase clinician orders and patient completions relative to standard practice and each other. STUDY DESIGN A pragmatic, patient-randomized clinical trial in the electronic health record was conducted between October 2019 and April 2020 at Geisinger Health System in Pennsylvania, with 4 arms: care gap-a passive listing recommending screening; alert-a panel promoting and enabling lipid screen orders; both; and a standard practice-no guideline-based notification-control arm. Data were analyzed for 13 346 9- to 11-year-old patients seen within Geisinger primary care, cardiology, urgent care, or nutrition clinics, or who had an endocrinology visit. Principal outcomes were lipid screening orders by clinicians and completions by patients within 1 week of orders. RESULTS Active (care gap and/or alert) vs control arm patients were significantly more likely (P < .05) to have lipid screening tests ordered and completed, with ORs ranging from 1.67 (95% CI 1.28-2.19) to 5.73 (95% CI 4.46-7.36) for orders and 1.54 (95% CI 1.04-2.27) to 2.90 (95% CI 2.02-4.15) for completions. Alerts, with or without care gaps listed, outperformed care gaps alone on orders, with odds ratios ranging from 2.92 (95% CI 2.32-3.66) to 3.43 (95% CI 2.73-4.29). CONCLUSIONS Electronic alerts can increase lipid screening orders and completions, suggesting clinical decision support can improve guideline-concordant screening. The study also highlights electronic record-based patient randomization as a way to determine relative effectiveness of support tools. TRIAL REGISTRATION ClinicalTrials.gov Identifier: NCT04118348.
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Affiliation(s)
- Amir Goren
- Behavioral Insights Team, Steele Institute for Health Innovation, Geisinger Health System, Danville, PA.
| | - Henri C Santos
- Behavioral Insights Team, Steele Institute for Health Innovation, Geisinger Health System, Danville, PA
| | - Thomas W Davis
- Department of Internal Medicine, Geisinger Health System, Danville, PA
| | - Robert B Lowe
- Department of Internal Medicine, Geisinger Health System, Danville, PA
| | - Mariya Monfette
- Clinical Informatics, Steele Institute for Health Innovation, Geisinger Health System, Danville, PA
| | - Michelle N Meyer
- Behavioral Insights Team, Steele Institute for Health Innovation, Geisinger Health System, Danville, PA; Department of Bioethics and Decision Sciences, Geisinger College of Health Sciences, Geisinger Health System, Danville, PA
| | - Christopher F Chabris
- Behavioral Insights Team, Steele Institute for Health Innovation, Geisinger Health System, Danville, PA; Department of Bioethics and Decision Sciences, Geisinger College of Health Sciences, Geisinger Health System, Danville, PA
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Walsh CG, Ripperger MA, Novak L, Reale C, Anders S, Spann A, Kolli J, Robinson K, Chen Q, Isaacs D, Acosta LMY, Phibbs F, Fielstein E, Wilimitis D, Musacchio Schafer K, Hilton R, Albert D, Shelton J, Stroh J, Stead WW, Johnson KB. Randomized Controlled Comparative Effectiveness Trial of Risk Model-Guided Clinical Decision Support for Suicide Screening. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2024:2024.03.14.24304318. [PMID: 38562678 PMCID: PMC10984050 DOI: 10.1101/2024.03.14.24304318] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 04/04/2024]
Abstract
Suicide prevention requires risk identification, appropriate intervention, and follow-up. Traditional risk identification relies on patient self-reporting, support network reporting, or face-to-face screening with validated instruments or history and physical exam. In the last decade, statistical risk models have been studied and more recently deployed to augment clinical judgment. Models have generally been found to be low precision or problematic at scale due to low incidence. Few have been tested in clinical practice, and none have been tested in clinical trials to our knowledge. Methods We report the results of a pragmatic randomized controlled trial (RCT) in three outpatient adult Neurology clinic settings. This two-arm trial compared the effectiveness of Interruptive and Non-Interruptive Clinical Decision Support (CDS) to prompt further screening of suicidal ideation for those predicted to be high risk using a real-time, validated statistical risk model of suicide attempt risk, with the decision to screen as the primary end point. Secondary outcomes included rates of suicidal ideation and attempts in both arms. Manual chart review of every trial encounter was used to determine if suicide risk assessment was subsequently documented. Results From August 16, 2022, through February 16, 2023, our study randomized 596 patient encounters across 561 patients for providers to receive either Interruptive or Non-Interruptive CDS in a 1:1 ratio. Adjusting for provider cluster effects, Interruptive CDS led to significantly higher numbers of decisions to screen (42%=121/289 encounters) compared to Non-Interruptive CDS (4%=12/307) (odds ratio=17.7, p-value <0.001). Secondarily, no documented episodes of suicidal ideation or attempts occurred in either arm. While the proportion of documented assessments among those noting the decision to screen was higher for providers in the Non-Interruptive arm (92%=11/12) than in the Interruptive arm (52%=63/121), the interruptive CDS was associated with more frequent documentation of suicide risk assessment (63/289 encounters compared to 11/307, p-value<0.001). Conclusions In this pragmatic RCT of real-time predictive CDS to guide suicide risk assessment, Interruptive CDS led to higher numbers of decisions to screen and documented suicide risk assessments. Well-powered large-scale trials randomizing this type of CDS compared to standard of care are indicated to measure effectiveness in reducing suicidal self-harm. ClinicalTrials.gov Identifier: NCT05312437.
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Charoensri S, Bashaw L, Dehmlow C, Ellies T, Wyckoff J, Turcu AF. Evaluation of a Best-Practice Advisory for Primary Aldosteronism Screening. JAMA Intern Med 2024; 184:174-182. [PMID: 38190155 PMCID: PMC10775078 DOI: 10.1001/jamainternmed.2023.7389] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/14/2023] [Accepted: 11/10/2023] [Indexed: 01/09/2024]
Abstract
Importance Primary aldosteronism (PA) is a common cause of secondary hypertension and an independent risk factor for cardiovascular morbidity and mortality. Fewer than 2% to 4% of patients at risk are evaluated for PA. Objective To develop and evaluate an electronic health record best-practice advisory (BPA) that assists with PA screening. Design, Setting, and Participants This prospective quality improvement study was conducted at academic center outpatient clinics. Data analysis was performed between February and June 2023 and included adults with hypertension and at least 1 of the following: 4 or more current antihypertensive medications; hypokalemia; age younger than 35 years; or adrenal nodule(s). Patients previously tested for PA were excluded. Exposure A noninterruptive BPA was developed to trigger for PA screening candidates seen in outpatient setting by clinicians who treat hypertension. The BPA included an order set for PA screening and a link to results interpretation guidance. Main Outcomes and Measures (1) The number of PA screening candidates identified by the BPA between October 1, 2021, and December 31, 2022; (2) the rates of PA screening; and (3) the BPA use patterns, stratified by physician specialty were assessed. Results Over 15 months, the BPA identified 14 603 unique candidates (mean [SD] age, 65.5 [16.9] years; 7300 women [49.9%]; 371 [2.5%] Asian, 2383 [16.3%] Black, and 11 225 [76.9%] White individuals) for PA screening, including 7028 (48.1%) with treatment-resistant hypertension, 6351 (43.5%) with hypokalemia, 1537 (10.5%) younger than 35 years, and 445 (3.1%) with adrenal nodule(s). In total, 2040 patients (14.0%) received orders for PA screening. Of these, 1439 patients (70.5%) completed the recommended screening within the system, and 250 (17.4%) had positive screening results. Most screening orders were placed by internists (40.0%) and family medicine physicians (28.1%). Family practitioners (80.3%) and internists (68.9%) placed most orders via the embedded order set, while specialists placed most orders (83.0%-95.4%) outside the BPA. Patients who received screening were younger and included more women and Black patients than those not screened. The likelihood of screening was higher among patients with obesity and dyslipidemia and lower in those with chronic kidney disease and established cardiovascular complications. Conclusions and Relevance The study results suggest that noninterruptive BPAs are potentially promising PA screening-assistance tools, particularly among primary care physicians. Combined with artificial intelligence algorithms that optimize the detection yield, refined BPAs may contribute to personalized hypertension care.
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Affiliation(s)
- Suranut Charoensri
- Division of Metabolism, Endocrinology, and Diabetes, Department of Internal Medicine, University of Michigan, Ann Arbor
- Division of Endocrinology and Metabolism, Department of Medicine, Faculty of Medicine, Khon Kaen University, Khon Kaen, Thailand
| | - Linda Bashaw
- Department of Internal Medicine, University of Michigan, Ann Arbor
| | - Cheryl Dehmlow
- Health Information and Technology Systems, University of Michigan, Ann Arbor
| | - Tammy Ellies
- Department of Internal Medicine, University of Michigan, Ann Arbor
| | - Jennifer Wyckoff
- Division of Metabolism, Endocrinology, and Diabetes, Department of Internal Medicine, University of Michigan, Ann Arbor
| | - Adina F. Turcu
- Division of Metabolism, Endocrinology, and Diabetes, Department of Internal Medicine, University of Michigan, Ann Arbor
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Sangillo E, Jube-Desai N, El-Metwally D, Hughes Driscoll C. Impact of a Clinical Decision Support Alert on Informed Consent Documentation in the Neonatal Intensive Care Unit. Pediatr Qual Saf 2024; 9:e713. [PMID: 38322296 PMCID: PMC10843373 DOI: 10.1097/pq9.0000000000000713] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/21/2023] [Accepted: 12/12/2023] [Indexed: 02/08/2024] Open
Abstract
Background Informed consent is necessary to preserve patient autonomy and shared decision-making, yet compliant consent documentation is suboptimal in the intensive care unit (ICU). We aimed to increase compliance with bundled consent documentation, which provides consent for a predefined set of common procedures in the neonatal ICU from 0% to 50% over 1 year. Methods We used the Plan-Do-Study-Act model for quality improvement. Interventions included education and performance awareness, delineation of the preferred consenting process, consent form revision, overlay tool creation, and clinical decision support (CDS) alert use within the electronic health record. Monthly audits categorized consent forms as missing, present but noncompliant, or compliant. We analyzed consent compliance on a run chart using standard run chart interpretation rules and obtained feedback on the CDS as a countermeasure. Results We conducted 564 audits over 37 months. Overall, median consent compliance increased from 0% to 86.6%. Upon initiating the CDS alert, we observed the highest monthly compliance of 93.3%, followed by a decrease to 33.3% with an inadvertent discontinuation of the CDS. Compliance subsequently increased to 73.3% after the restoration of the alert. We created a consultant opt-out selection to address negative feedback associated with CDS. There were no missing consent forms within the last 7 months of monitoring. Conclusions A multi-faceted approach led to sustained improvement in bundled consent documentation compliance in our neonatal intensive care unit, with the direct contribution of the CDS observed. A CDS intervention directed at the informed consenting process may similarly benefit other ICUs.
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Affiliation(s)
- Emily Sangillo
- From the Department of Pediatrics, University of Maryland School of Medicine, Baltimore, Md
| | - Neena Jube-Desai
- From the Department of Pediatrics, University of Maryland School of Medicine, Baltimore, Md
| | - Dina El-Metwally
- From the Department of Pediatrics, University of Maryland School of Medicine, Baltimore, Md
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Howell BL, Skelton JA, Jayaprakash MS, Lewis KH. Staff Knowledge, Attitudes, and Beliefs About Child Sugar-Sweetened Beverage Intake and Acceptability of a Pediatric Clinic-Based Beverage Screener. Comput Inform Nurs 2023; 41:402-409. [PMID: 36076342 DOI: 10.1097/cin.0000000000000950] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/25/2022]
Abstract
Beverages are the leading source of sugar in children's diets and a modifiable risk factor for adverse health conditions. Electronic health record-based screeners could facilitate health systems' efforts to reduce child consumption of sugary beverages. Before implementing a sugar-sweetened beverage screener in the electronic health record within academic healthcare system, 228 pediatric and family medicine clinic staff completed an online educational training to familiarize them with the screener and its rationale. Pretraining and posttraining surveys were used to examine the association between staff knowledge of sugar-sweetened beverages and the acceptability of the screening workflow. Respondents displayed high levels of pretraining knowledge about health consequences of added sugar intake, but lower levels of pediatric beverage guideline knowledge. Knowledge improved from pretraining to posttraining surveys, with high acceptability of the screening process. Staff compliance with sugar-sweetened beverage screening was examined using electronic health record data. During the 6 months after screener implementation, 47% of eligible pediatric patients were screened, with some variation in compliance by age group and practice type. This study demonstrated that engaging nursing and frontline staff to screen pediatric patients for behavioral determinants of health is feasible. Ongoing outreach and refreshers may improve sustainability.
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Affiliation(s)
- Bethany L Howell
- Author Affiliations: Patient Education and Nursing Clinical Advancement, Clinical Education, Atrium Health Wake Forest Baptist Medical Center (Ms Howell); Department of Pediatrics, Department of Epidemiology and Prevention, Wake Forest School of Medicine (Dr Skelton), Winston-Salem; General Internal Medicine, Duke Primary Care, Duke University, Raleigh (Dr Jayaprakash); and Department of Epidemiology and Prevention, Division of Public Health Sciences, Wake Forest School of Medicine, Winston-Salem (Dr Lewis), NC
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Abstract
OBJECTIVE Human factors and ergonomics (HF/E) frameworks and methods are becoming embedded in the health informatics community. There is now broad recognition that health informatics tools must account for the diverse needs, characteristics, and abilities of end users, as well as their context of use. The objective of this review is to synthesize the current nature and scope of HF/E integration into the health informatics community. METHODS Because the focus of this synthesis is on understanding the current integration of the HF/E and health informatics research communities, we manually reviewed all manuscripts published in primary HF/E and health informatics journals during 2020. RESULTS HF/E-focused health informatics studies included in this synthesis focused heavily on EHR customizations, specifically clinical decision support customizations and customized data displays, and on mobile health innovations. While HF/E methods aimed to jointly improve end user safety, performance, and satisfaction, most HF/E-focused health informatics studies measured only end user satisfaction. CONCLUSION HF/E-focused health informatics researchers need to identify and communicate methodological standards specific to health informatics, to better synthesize findings across resource intensive HF/E-focused health informatics studies. Important gaps in the HF/E design and evaluation process should be addressed in future work, including support for technology development platforms and training programs so that health informatics designers are as diverse as end users.
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Campbell NL, Holden RJ, Tang Q, Boustani MA, Teal E, Hillstrom J, Tu W, Clark DO, Callahan CM. Multicomponent behavioral intervention to reduce exposure to anticholinergics in primary care older adults. J Am Geriatr Soc 2021; 69:1490-1499. [PMID: 33772749 DOI: 10.1111/jgs.17121] [Citation(s) in RCA: 12] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/02/2020] [Revised: 02/10/2021] [Accepted: 02/13/2021] [Indexed: 11/30/2022]
Abstract
OBJECTIVE To test the impact of a multicomponent behavioral intervention to reduce the use of high-risk anticholinergic medications in primary care older adults. DESIGN Cluster-randomized controlled trial. SETTING AND PARTICIPANTS Ten primary care clinics within Eskenazi Health in Indianapolis. INTERVENTION The multicomponent intervention included provider- and patient-focused components. The provider-focused component was computerized decision support alerting of the presence of a high-risk anticholinergic and offering dose- and indication-specific alternatives. The patient-focused component was a story-based video providing education and modeling an interaction with a healthcare provider resulting in a medication change. Alerts within the medical record triggered staff to play the video for a patient. Our design intended for parallel, independent priming of both providers and patients immediately before an outpatient face-to-face interaction. MEASUREMENT Medication orders were extracted from the electronic medical record system to evaluate the prescribing behavior and population prevalence of anticholinergic users. The intervention was introduced April 1, 2019, through March 31, 2020, and a preintervention observational period of April 1, 2018, through March 31, 2019, facilitated difference in difference comparisons. RESULTS A total of 552 older adults had visits at primary care sites during the study period, with mean age of 72.1 (SD 6.4) years and 45.3% African American. Of the 259 provider-focused alerts, only three (1.2%) led to a medication change. Of the 276 staff alerts, 4.7% were confirmed to activate the patient-focused intervention. The intervention resulted in no significant differences in either the number of discontinue orders for anticholinergics (intervention: two additional orders; control: five fewer orders, p = 0.7334) or proportion of the population using anticholinergics following the intervention (preintervention: 6.2% and postintervention: 5.1%, p = 0.6326). CONCLUSION This multicomponent intervention did not reduce the use of high-risk anticholinergics in older adults receiving primary care. Improving nudges or a policy-focused component may be necessary to reduce use of high-risk medications.
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Affiliation(s)
- Noll L Campbell
- Department of Pharmacy Practice, Purdue University College of Pharmacy, West Lafayette, Indiana, USA.,Center for Aging Research, Regenstrief Institute, Inc., Indianapolis, Indiana, USA.,Sandra Eskenazi Center for Brain Care Innovation, Eskenazi Health, Indianapolis, Indiana, USA.,Department of Medicine, Indiana University School of Medicine, Indianapolis, Indiana, USA.,Center for Health Innovation and Implementation Science, Indiana University School of Medicine, Indianapolis, Indiana, USA
| | - Richard J Holden
- Center for Aging Research, Regenstrief Institute, Inc., Indianapolis, Indiana, USA.,Sandra Eskenazi Center for Brain Care Innovation, Eskenazi Health, Indianapolis, Indiana, USA.,Department of Medicine, Indiana University School of Medicine, Indianapolis, Indiana, USA.,Center for Health Innovation and Implementation Science, Indiana University School of Medicine, Indianapolis, Indiana, USA
| | - Qing Tang
- Department of Biostatistics and Health Data Science, Indiana University School of Medicine, Indianapolis, Indiana, USA
| | - Malaz A Boustani
- Center for Aging Research, Regenstrief Institute, Inc., Indianapolis, Indiana, USA.,Sandra Eskenazi Center for Brain Care Innovation, Eskenazi Health, Indianapolis, Indiana, USA.,Department of Medicine, Indiana University School of Medicine, Indianapolis, Indiana, USA.,Center for Health Innovation and Implementation Science, Indiana University School of Medicine, Indianapolis, Indiana, USA
| | - Evgenia Teal
- Data Core, Regenstrief Institute, Inc., Indianapolis, Indiana, USA
| | - Jennifer Hillstrom
- Sandra Eskenazi Center for Brain Care Innovation, Eskenazi Health, Indianapolis, Indiana, USA
| | - Wanzhu Tu
- Center for Aging Research, Regenstrief Institute, Inc., Indianapolis, Indiana, USA.,Department of Biostatistics and Health Data Science, Indiana University School of Medicine, Indianapolis, Indiana, USA
| | - Daniel O Clark
- Center for Aging Research, Regenstrief Institute, Inc., Indianapolis, Indiana, USA.,Sandra Eskenazi Center for Brain Care Innovation, Eskenazi Health, Indianapolis, Indiana, USA.,Department of Medicine, Indiana University School of Medicine, Indianapolis, Indiana, USA
| | - Christopher M Callahan
- Center for Aging Research, Regenstrief Institute, Inc., Indianapolis, Indiana, USA.,Sandra Eskenazi Center for Brain Care Innovation, Eskenazi Health, Indianapolis, Indiana, USA.,Department of Medicine, Indiana University School of Medicine, Indianapolis, Indiana, USA
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