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Article: Efficacy of the Canadian CT Head Rule in Patients Presenting to the Emergency Department with Minor Head Injury.

Reddy, Ashok / Poonthottathil, Fawaz / Jonnakuti, Rani / Thomas, Roney

Indian journal of critical care medicine : peer-reviewed, official publication of Indian Society of Critical Care Medicine

2024 Volume 28, Issue 2, Page(s) 148–151

Abstract: Introduction: Approximately, one in three computed tomography (CT) scans performed for head injury may be avoidable. We evaluate the efficacy of the Canadian CT head rule (CCHR) on head CT imaging in minor head injury (MHI) and its association of ... ...

Abstract	Introduction: Approximately, one in three computed tomography (CT) scans performed for head injury may be avoidable. We evaluate the efficacy of the Canadian CT head rule (CCHR) on head CT imaging in minor head injury (MHI) and its association of Glasgow Coma Scale (GCS) and structural abnormality. Materials and methods: We conducted a prospective cross-sectional study from May 2018 to October 2019 in the Department of Emergency Medicine, Pushpagiri Institute of Medical Sciences and Research Centre, Thiruvalla, Kerala. The CCHR is applied to patients with MHIs (GCS 13-15) after initial stabilization and it is ascertained, if they require a non-contrast CT head and imaging is done. For those who do not require CT head as per the CCHR are excluded from this study. After imaging the patients who have a positive finding on CT head are admitted and followed up if they underwent any neurosurgical intervention, those with no findings in CT head are discharged from the hospital. A total of 203 patients were included during study period. Results: A total of 203 patients were included in study with mean age of 49.5 years. Approximately, 70% (142) were male. Sensitivity of CCHR for predicting positive CT finding in the present study sample was 68% and specificity was 42.5%. Conclusion: Canadian CT head rule is a useful tool in the Emergency Department for predicting the requirement of CT in patients with MHI. Canadian CT head rule can reduce the number of CT scans ordered following MHI in ED, thus improving the healthcare costs. How to cite this article: Reddy A, Poonthottathil F, Jonnakuti R, Thomas R. Efficacy of the Canadian CT Head Rule in Patients Presenting to the Emergency Department with Minor Head Injury. Indian J Crit Care Med 2024;28(2):148-151.
Language	English
Publishing date	2024-02-05
Publishing country	India
Document type	Journal Article
ZDB-ID	2121263-6
ISSN	1998-359X ; 0972-5229
ISSN (online)	1998-359X
ISSN	0972-5229
DOI	10.5005/jp-journals-10071-24620
Database	MEDical Literature Analysis and Retrieval System OnLINE

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Article ; Online: Ethics and Terminology for Opting In and Out-In Reply.

Marcotte, Leah M / Nelson, Karin M / Reddy, Ashok

JAMA internal medicine

2024 Volume 184, Issue 4, Page(s) 452–453

Language	English
Publishing date	2024-02-19
Publishing country	United States
Document type	Journal Article
ZDB-ID	2699338-7
ISSN	2168-6114 ; 2168-6106
ISSN (online)	2168-6114
ISSN	2168-6106
DOI	10.1001/jamainternmed.2023.7063
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Article ; Online: Identifying Patterns of Primary Care In-Person and Telemedicine Use in the Veterans Health Administration: A Latent Class Analysis.

Staloff, Jonathan / Gunnink, Eric / Rojas, Jorge / Wong, Edwin S / Nelson, Karin / Reddy, Ashok

Journal of general internal medicine

2024

Abstract: Background: The Veterans Health Administration increased synchronous telemedicine (video and telephone visits) in primary care in response to the COVID-19 pandemic.: Objective: Our objective was to determine veteran use patterns of in-person and ... ...

Abstract	Background: The Veterans Health Administration increased synchronous telemedicine (video and telephone visits) in primary care in response to the COVID-19 pandemic. Objective: Our objective was to determine veteran use patterns of in-person and telemedicine primary care when all modalities were available. Design: A retrospective cohort analysis. We performed a latent class analysis of primary care visits over a 1-year period to identify veteran subgroup (i.e., class) membership based on amount of primary care use and modality used. Then, we used multinomial logistic regression with a categorical outcome to identify patient characteristics associated with class identification. Participants: A random national sample consisting of 564,580 primary care empaneled veterans in June 2021. Main measures: Latent class membership. Key results: We identified three latent classes: those with few primary care visits that were predominantly telephone-based (45%), intermediate number of visits of all modalities (50%), and many visits of all modalities (5%). In an adjusted model, characteristics associated with the "few" visits class, compared to the intermediate class, were older age, male sex, White race, further driving distance to primary care, higher Gagne, optimal internet speed, and unmarried status (OR 1.002, 1.52, 1.13, 1.004, 1.04, 1.05, 1.06, respectively; p < .05). Characteristics associated with membership in the "many" visits class, compared to the intermediate class, were Hispanic race, higher JEN Frailty Index and Gagne (OR 1.12, 1.11, 1.02, respectively; p < .05), and higher comorbidity by Care Assessment Need score quartile (Q2 1.73, Q3 2.80, Q4 4.12; p < 0.05). Conclusions: Veterans accessing primary care in-person or via telemedicine do so primarily in three ways: (1) few visits, predominantly telephone; (2) intermediate visits, all modalities, (3) many visits, all modalities. We found no groups of veterans receiving a majority of primary care through video.
Language	English
Publishing date	2024-04-15
Publishing country	United States
Document type	Journal Article
ZDB-ID	639008-0
ISSN	1525-1497 ; 0884-8734
ISSN (online)	1525-1497
ISSN	0884-8734
DOI	10.1007/s11606-024-08751-5
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Article ; Online: Primary Care Spending in the Veterans Health Administration in 2014 and 2018.

Reddy, Ashok / Nelson, Karin M / Wong, Edwin S

JAMA network open

2021 Volume 4, Issue 7, Page(s) e2117533

MeSH term(s)	Health Expenditures/trends ; Humans ; Primary Health Care/economics ; Quality Improvement ; United States ; United States Department of Veterans Affairs/economics
Language	English
Publishing date	2021-07-01
Publishing country	United States
Document type	Journal Article ; Observational Study ; Research Support, U.S. Gov't, Non-P.H.S.
ISSN	2574-3805
ISSN (online)	2574-3805
DOI	10.1001/jamanetworkopen.2021.17533
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Article ; Online: Factors Associated With Use of the Preventive Health Inventory in US Veterans.

Wheat, Chelle L / Wong, Edwin S / Gray, Kristen E / Stockdale, Susan E / Nelson, Karin M / Reddy, Ashok

JAMA network open

2024 Volume 7, Issue 3, Page(s) e242717

Abstract: Importance: The COVID-19 pandemic caused significant declines in the quality of preventive and chronic disease care. The Veterans Health Administration (VHA) used the Preventive Health Inventory (PHI), a multicomponent care management intervention, to ... ...

Abstract	Importance: The COVID-19 pandemic caused significant declines in the quality of preventive and chronic disease care. The Veterans Health Administration (VHA) used the Preventive Health Inventory (PHI), a multicomponent care management intervention, to catch up on care disrupted by the pandemic. Objective: To identify key factors associated with PHI use. Design, setting, and participants: This cohort study of veterans receiving primary care used administrative data from national VHA primary care clinics for February 1, 2021, through February 1, 2022. Exposure: Patient PHI receipt. Main outcomes and measures: The main outcomes were patient, practitioner, and clinic factors associated with PHI receipt. Binomial generalized linear models with fixed effects for clinic were used to analyze factors associated with receipt of PHI. Least absolute shrinkage and selection operator procedures were used for variable selection. Results: A total of 4 358 038 veterans (mean [SD] age, 63.7 [16.0] years; 90% male; 76% non-Hispanic White) formed the study cohort, of whom 389 757 (9%) received the PHI. Veterans who received the PHI had higher mean Care Assessment Need (CAN) scores, which indicate the likelihood of hospitalization or death within 1 year (mean [SD], 51.9 [28.6] vs 47.2 [28.6]; standardized mean difference [SMD], -0.16). They were also more likely to live in urban areas (77% vs 64%; SMD, 0.28) and have a shorter drive distance to primary care (mean [SD], 13.2 [12.4] vs 15.7 [14.6] miles; SMD, 0.19). The mean outpatient use was higher among PHI recipients compared with non-PHI recipients (mean [SD], 18.4 [27.8] vs 15.1 [24.1] visits; SMD, -0.13). In addition, veterans with primary care practitioners with higher caseloads were more likely to receive the PHI (mean [SD], 778 [231] vs 744 [249] patients; SMD, -0.14), and they were more likely to be seen at larger clinics (mean [SD], 9670 [6876] vs 8786 [6892] patients; SMD, -0.13). Prior outpatient use and CAN score were associated with PHI receipt in the final model. Conclusions and relevance: In this cohort study of the VHA's PHI, patients with higher CAN scores and more outpatient use in the previous year were more likely to receive the PHI. This study identifies potential intervention points to improve care coordination for veterans.
MeSH term(s)	Humans ; Male ; Middle Aged ; Female ; Cohort Studies ; Pandemics ; Veterans ; Outpatients ; Preventive Health Services
Language	English
Publishing date	2024-03-04
Publishing country	United States
Document type	Journal Article
ISSN	2574-3805
ISSN (online)	2574-3805
DOI	10.1001/jamanetworkopen.2024.2717
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Article ; Online: Intensive care management for high-risk veterans in a patient-centered medical home - do some veterans benefit more than others?

Swankoski, Kaylyn E / Reddy, Ashok / Grembowski, David / Chang, Evelyn T / Wong, Edwin S

Healthcare (Amsterdam, Netherlands)

2023 Volume 11, Issue 2, Page(s) 100677

Abstract: Background: Primary care intensive management programs utilize interdisciplinary care teams to comprehensively meet the complex care needs of patients at high risk for hospitalization. The mixed evidence on the effectiveness of these programs focuses on ...

Abstract	Background: Primary care intensive management programs utilize interdisciplinary care teams to comprehensively meet the complex care needs of patients at high risk for hospitalization. The mixed evidence on the effectiveness of these programs focuses on average treatment effects that may mask heterogeneous treatment effects (HTEs) among subgroups of patients. We test for HTEs by patients' demographic, economic, and social characteristics. Methods: Retrospective analysis of a VA randomized quality improvement trial. 3995 primary care patients at high risk for hospitalization were randomized to primary care intensive management (n = 1761) or usual primary care (n = 1731). We estimated HTEs on ED and hospital utilization one year after randomization using model-based recursive partitioning and a pre-versus post-with control group framework. Splitting variables included administratively collected demographic characteristics, travel distance, copay exemption, risk score for future hospitalizations, history of hospital discharge against medical advice, homelessness, and multiple residence ZIP codes. Results: There were no average or heterogeneous treatment effects of intensive management one year after enrollment. The recursive partitioning algorithm identified variation in effects by risk score, homelessness, and whether the patient had multiple residences in a year. Within each distinct subgroup, the effect of intensive management was not statistically significant. Conclusions: Primary care intensive management did not affect acute care use of high-risk patients on average or differentially for patients defined by various demographic, economic, and social characteristics. Implications: Reducing acute care use for high-risk patients is complex, and more work is required to identify patients positioned to benefit from intensive management programs.
MeSH term(s)	Humans ; Veterans ; Retrospective Studies ; Patient-Centered Care ; Critical Care ; Risk Factors ; Hospitalization
Language	English
Publishing date	2023-02-08
Publishing country	Netherlands
Document type	Randomized Controlled Trial ; Journal Article
ZDB-ID	2724773-9
ISSN	2213-0772 ; 2213-0764 ; 2213-0772
ISSN (online)	2213-0772 ; 2213-0764
ISSN	2213-0772
DOI	10.1016/j.hjdsi.2023.100677
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Article ; Online: Bridging to value with codes that promote care management.

Hwang, Catherine S / Reddy, Ashok / Liao, Joshua M

The American journal of managed care

2020 Volume 26, Issue 11, Page(s) e344–e346

Abstract: Transitional care management (TCM) and chronic care management (CCM) fee-for-service billing codes can serve as bridges to help organizations build care management capabilities and effectively transition from volume- to value-based care. TCM codes ... ...

Abstract	Transitional care management (TCM) and chronic care management (CCM) fee-for-service billing codes can serve as bridges to help organizations build care management capabilities and effectively transition from volume- to value-based care. TCM codes encourage providers to build capabilities for managing hospital discharge transitions. CCM codes encourage physician and nonphysician staff to build capabilities for longitudinally managing patients with multiple chronic conditions. Implementation challenges include achieving return on investment in health information technology and securing stakeholder commitment and engagement. Nonetheless, policy makers have reinforced their commitment to these codes, offering an encouraging signal for organizations seeking more gradual ways to build competencies and bridge toward value-based payment and care delivery.
MeSH term(s)	Delivery of Health Care ; Fee-for-Service Plans ; Humans ; Multiple Chronic Conditions ; Patient Discharge ; Transitional Care
Language	English
Publishing date	2020-11-01
Publishing country	United States
Document type	Journal Article
ZDB-ID	2035781-3
ISSN	1936-2692 ; 1088-0224 ; 1096-1860
ISSN (online)	1936-2692
ISSN	1088-0224 ; 1096-1860
DOI	10.37765/ajmc.2020.88528
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Article ; Online: Does machine learning improve prediction of VA primary care reliance?

Wong, Edwin S / Schuttner, Linnaea / Reddy, Ashok

The American journal of managed care

2020 Volume 26, Issue 1, Page(s) 40–44

Abstract: Objectives: The Veterans Affairs (VA) Health Care System is among the largest integrated health systems in the United States. Many VA enrollees are dual users of Medicare, and little research has examined methods to most accurately predict which ... ...

Abstract	Objectives: The Veterans Affairs (VA) Health Care System is among the largest integrated health systems in the United States. Many VA enrollees are dual users of Medicare, and little research has examined methods to most accurately predict which veterans will be mostly reliant on VA services in the future. This study examined whether machine learning methods can better predict future reliance on VA primary care compared with traditional statistical methods. Study design: Observational study of 83,143 VA patients dually enrolled in fee-for-service Medicare using VA and Medicare administrative databases and the 2012 Survey of Healthcare Experiences of Patients. Methods: The primary outcome was a dichotomous measure denoting whether patients obtained more than 50% of all primary care visits (VA + Medicare) from VA. We compared the performance of 6 candidate models-logistic regression, elastic net regression, decision trees, random forest, gradient boosting machine, and neural network-in predicting 2013 reliance as a function of 61 patient characteristics observed in 2012. We measured performance using the cross-validated area under the receiver operating characteristic (AUROC) metric. Results: Overall, 72.9% and 74.5% of veterans were mostly VA reliant in 2012 and 2013, respectively. All models had similar average AUROCs, ranging from 0.873 to 0.892. The best-performing model used gradient boosting machine, which exhibited modestly higher AUROC and similar variance compared with standard logistic regression. Conclusions: The modest gains in performance from the best-performing model, gradient boosting machine, are unlikely to outweigh inherent drawbacks, including computational complexity and limited interpretability compared with traditional logistic regression.
MeSH term(s)	Aged ; Aged, 80 and over ; Female ; Forecasting/methods ; Humans ; Logistic Models ; Machine Learning ; Male ; Medicare ; Middle Aged ; Patient Acceptance of Health Care/statistics & numerical data ; Primary Health Care/statistics & numerical data ; United States ; United States Department of Veterans Affairs ; Veterans Health Services/trends
Language	English
Publishing date	2020-01-16
Publishing country	United States
Document type	Journal Article ; Observational Study ; Research Support, U.S. Gov't, Non-P.H.S.
ZDB-ID	2035781-3
ISSN	1936-2692 ; 1088-0224 ; 1096-1860
ISSN (online)	1936-2692
ISSN	1088-0224 ; 1096-1860
DOI	10.37765/ajmc.2020.42144
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Article ; Online: Nationwide Use of Telehealth Among Commercially Insured Individuals 2007-2017.

Marcotte, Leah M / Reddy, Ashok / Zhou, Lingmei / Liao, Joshua M

Journal of general internal medicine

2021 Volume 37, Issue 5, Page(s) 1318–1320

MeSH term(s)	Humans ; Insurance, Health ; Medicare ; Telemedicine ; United States
Language	English
Publishing date	2021-05-04
Publishing country	United States
Document type	Journal Article
ZDB-ID	639008-0
ISSN	1525-1497 ; 0884-8734
ISSN (online)	1525-1497
ISSN	0884-8734
DOI	10.1007/s11606-021-06816-3
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Article ; Online: From hazy dusk till dawn.

Bansal, Rolika / Majji, Ajit B / Reddy, Ashok G / Honavar, Santosh G

Indian journal of ophthalmology

2021 Volume 69, Issue 7, Page(s) 1657

MeSH term(s)	Circadian Rhythm ; Humans
Language	English
Publishing date	2021-06-11
Publishing country	India
Document type	Journal Article
ZDB-ID	187392-1
ISSN	1998-3689 ; 0301-4738
ISSN (online)	1998-3689
ISSN	0301-4738
DOI	10.4103/ijo.IJO_1424_21
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