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Article ; Online: Comparing Stroke Risk Factors Among Sexual Minority Groups in Texas.

Krenek, Brittany / Tundealao, Samuel / Beauchamp, Jennifer E S / Savitz, Sean I / Tamí-Maury, Irene

International journal of behavioral medicine

2024

Abstract: Background: Knowledge gaps remain on stroke risk and disparities between sexual minority (SM) subgroups. In this study, stroke risk between SM subgroups, specifically gay/bisexual men and lesbian/bisexual women (G/BM and L/BW), was assessed.: Method: ...

Abstract	Background: Knowledge gaps remain on stroke risk and disparities between sexual minority (SM) subgroups. In this study, stroke risk between SM subgroups, specifically gay/bisexual men and lesbian/bisexual women (G/BM and L/BW), was assessed. Method: Data were collected in June 2022 using a bilingual (English and Spanish) cross-sectional paper-and-pen survey distributed among 183 SM individuals attending the 2022 Houston Pride Parade and Festival, as well as across Texas via phone call or online format. Relevant sociodemographic and stroke risk factors were compared between G/BM and L/BW using chi-square (or Fisher's exact, when appropriate) and two-sample t-tests. Sexual orientation was used to predict stroke risk using multiple binomial logistic regression, adjusting for other sociodemographic determinants. Results: While comparing the stroke risk factors between G/BW and L/BW, statistically significant differences were found in hypertension (p = 0.047), age (p < 0.001), smoking status (p = 0.043), cholesterol level (p < 0.001), and HIV (p = 0.038). G/BM were 2.79 times more likely to have a higher stroke risk compared to L/BW (aOR = 2.79; CI, 1.11-6.05, p = 0.032), after adjusting for other sociodemographic factors. Conclusion: This pilot study, conducted in Texas, adds to the existing scientific literature on stroke risk among the SM population and revealed that G/BM might have a higher stroke risk compared to L/BW. These findings can inform future research and intervention designs tailored to G/BM and L/BW communities and improve their overall health.
Language	English
Publishing date	2024-02-23
Publishing country	England
Document type	Journal Article
ZDB-ID	1187972-5
ISSN	1532-7558 ; 1070-5503
ISSN (online)	1532-7558
ISSN	1070-5503
DOI	10.1007/s12529-024-10267-5
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Article ; Online: Evaluation of the Predictive Value of Routinely Collected Health-Related Social Needs Measures.

Savitz, Samuel T / Inselman, Shealeigh / Nyman, Mark A / Lee, Minji

Population health management

2023 Volume 27, Issue 1, Page(s) 34–43

Abstract: The objective was to assess the value of routinely collected patient-reported health-related social needs (HRSNs) measures for predicting utilization and health outcomes. The authors identified Mayo Clinic patients with cancer, diabetes, or heart failure. ...

Abstract	The objective was to assess the value of routinely collected patient-reported health-related social needs (HRSNs) measures for predicting utilization and health outcomes. The authors identified Mayo Clinic patients with cancer, diabetes, or heart failure. The HRSN measures were collected as part of patient-reported screenings from June to December 2019 and outcomes (hospitalization, 30-day readmission, and death) were ascertained in 2020. For each outcome and disease combination, 4 models were used: gradient boosting machine (GBM), random forest (RF), generalized linear model (GLM), and elastic net (EN). Other predictors included clinical factors, demographics, and area-based HRSN measures-area deprivation index (ADI) and rurality. Predictive performance for models was evaluated with and without the routinely collected HRSN measures as change in area under the curve (AUC). Variable importance was also assessed. The differences in AUC were mixed. Significant improvements existed in 3 models of death for cancer (GBM: 0.0421, RF: 0.0496, EN: 0.0428), 3 models of hospitalization (GBM: 0.0372, RF: 0.0640, EN: 0.0441), and 1 of death (RF: 0.0754) for diabetes, and 1 model of readmissions (GBM: 0.1817), and 3 models of death (GBM: 0.0333, RF: 0.0519, GLM: 0.0489) for heart failure. Age, ADI, and the Charlson comorbidity index were the top 3 in variable importance and were consistently more important than routinely collected HRSN measures. The addition of routinely collected HRSN measures resulted in mixed improvement in the predictive performance of the models. These findings suggest that existing factors and the ADI are more important for prediction in these contexts. More work is needed to identify predictors that consistently improve model performance.
MeSH term(s)	Humans ; Machine Learning ; Hospitalization ; Diabetes Mellitus/epidemiology ; Diabetes Mellitus/therapy ; Neoplasms ; Heart Failure/epidemiology ; Heart Failure/therapy
Language	English
Publishing date	2023-10-30
Publishing country	United States
Document type	Journal Article
ZDB-ID	2454546-6
ISSN	1942-7905 ; 1942-7891
ISSN (online)	1942-7905
ISSN	1942-7891
DOI	10.1089/pop.2023.0129
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Article ; Online: Identifying appropriate comparison groups for health system interventions in the COVID-19 era.

Savitz, Samuel T / Scott, Jason L / Leo, Michael C / Keast, Erin M / Savitz, Lucy A

Learning health systems

2022 , Page(s) e10344

Abstract: Introduction: COVID-19 has created additional challenges for the analysis of non-randomized interventions in health system settings. Our objective is to evaluate these challenges and identify lessons learned from the analysis of a medically tailored ... ...

Abstract	Introduction: COVID-19 has created additional challenges for the analysis of non-randomized interventions in health system settings. Our objective is to evaluate these challenges and identify lessons learned from the analysis of a medically tailored meals (MTM) intervention at Kaiser Permanente Northwest (KPNW) that began in April 2020. Methods: We identified both a historical and concurrent comparison group. The historical comparison group included patients living in the same area as the MTM recipients prior to COVID-19. The concurrent comparison group included patients admitted to contracted non-KPNW hospitals or admitted to a KPNW facility and living outside the service area for the intervention but otherwise eligible. We used two alternative propensity score methods in response to the loss of sample size with exact matching to evaluate the intervention. Results: We identified 452 patients who received the intervention, 3873 patients in the historical comparison group, and 5333 in the concurrent comparison group. We were able to mostly achieve balance on observable characteristics for the intervention and the two comparison groups. Conclusions: Lessons learned included: (a) The use of two different comparison groups helped to triangulate results; (b) the meaning of utilization measures changed pre- and post-COVID-19; and (c) that balance on observable characteristics can be achieved, especially when the comparison groups are meaningfully larger than the intervention group. These findings may inform the design for future evaluations of interventions during COVID-19.
Language	English
Publishing date	2022-09-29
Publishing country	United States
Document type	Journal Article
ISSN	2379-6146
ISSN (online)	2379-6146
DOI	10.1002/lrh2.10344
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Article ; Online: Sudden Cardiac Death or Ventricular Arrythmia in Patients Taking Levetiracetam or Oxcarbazepine.

Cross, Madeline R / Savitz, Samuel T / Sangaralingham, Lindsey R / So, Elson L / Ackerman, Michael J / Noseworthy, Peter A

Neurology

2024 Volume 102, Issue 9, Page(s) e209177

Abstract: Background and objectives: Levetiracetam is a widely used antiseizure medication. Recent concerns have been raised regarding the potential prolongation of the QT interval by levetiracetam and increased risk of sudden cardiac death. This could have ... ...

Abstract	Background and objectives: Levetiracetam is a widely used antiseizure medication. Recent concerns have been raised regarding the potential prolongation of the QT interval by levetiracetam and increased risk of sudden cardiac death. This could have profound implications for patient safety and for prescribing practice. This study assessed the potential association of levetiracetam with cardiac outcomes related to QT interval prolongation. We compared outcomes of patients taking levetiracetam with those taking oxcarbazepine as a comparator medication that has not been associated with prolongation of the QT interval. Methods: The sample included patients who were newly prescribed levetiracetam or oxcarbazepine from January 31, 2010, to December 31, 2019, using administrative claims data from the OptumLabs Data Warehouse (OLDW). The analysis focused on a combined endpoint of sudden cardiac death or ventricular arrythmia, which are both linked to QT interval prolongation. We used a new user design and selected oxcarbazepine as an active comparator with levetiracetam to minimize bias. We used propensity score weighting to balance the levetiracetam and oxcarbazepine cohorts and then performed weighted Cox regressions to evaluate the association of levetiracetam with the combined endpoint. Results: We identified 104,655 enrollees taking levetiracetam and 39,596 enrollees taking oxcarbazepine. At baseline, enrollees taking levetiracetam were older, more likely to have diagnosed epilepsy, and more likely to have diagnosed comorbidities including hypertension, cerebrovascular disease, and coronary artery disease. In the main analysis, we found no significant difference between levetiracetam and oxcarbazepine in the rate of the combined endpoint for the Cox proportional hazards model (hazard ratio [HR] 0.79, 95% CI 0.42-1.47) or Cox regression with time-varying characteristics (HR 0.78, 95% CI 0.41-1.50). Discussion: When compared with oxcarbazepine, levetiracetam does not correlate with increased risk of ventricular arrythmia and sudden cardiac death. Our finding does not support the concern for cardiac risk to indicate restriction of levetiracetam use nor the requirement of cardiac monitoring when using it. Classification of evidence: This study provides Class II evidence that sudden cardiac death and ventricular arrythmia are not more frequent in patients older than 17 years newly prescribed levetiracetam, compared with those prescribed oxcarbazepine.
MeSH term(s)	Humans ; Levetiracetam/adverse effects ; Oxcarbazepine/adverse effects ; Anticonvulsants/adverse effects ; Death, Sudden, Cardiac/epidemiology ; Death, Sudden, Cardiac/etiology ; Arrhythmias, Cardiac/chemically induced
Chemical Substances	Levetiracetam (44YRR34555) ; Oxcarbazepine (VZI5B1W380) ; Anticonvulsants
Language	English
Publishing date	2024-04-01
Publishing country	United States
Document type	Journal Article
ZDB-ID	207147-2
ISSN	1526-632X ; 0028-3878
ISSN (online)	1526-632X
ISSN	0028-3878
DOI	10.1212/WNL.0000000000209177
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Article: Can delivery systems use cost-effectiveness analysis to reduce healthcare costs and improve value?

Savitz, Lucy A / Savitz, Samuel T

F1000Research

2016 Volume 5

Abstract: Understanding costs and ensuring that we demonstrate value in healthcare is a foundational presumption as we transform the way we deliver and pay for healthcare in the U.S. With a focus on population health and payment reforms underway, there is ... ...

Abstract	Understanding costs and ensuring that we demonstrate value in healthcare is a foundational presumption as we transform the way we deliver and pay for healthcare in the U.S. With a focus on population health and payment reforms underway, there is increased pressure to examine cost-effectiveness in healthcare delivery. Cost-effectiveness analysis (CEA) is a type of economic analysis comparing the costs and effects (i.e. health outcomes) of two or more treatment options. The result is expressed as a ratio where the denominator is the gain in health from a measure (e.g. years of life or quality-adjusted years of life) and the numerator is the incremental cost associated with that health gain. For higher cost interventions, the lower the ratio of costs to effects, the higher the value. While CEA is not new, the approach continues to be refined with enhanced statistical techniques and standardized methods. This article describes the CEA approach and also contrasts it to optional approaches, in order for readers to fully appreciate caveats and concerns. CEA as an economic evaluation tool can be easily misused owing to inappropriate assumptions, over reliance, and misapplication. Twelve issues to be considered in using CEA results to drive healthcare delivery decision-making are summarized. Appropriately recognizing both the strengths and the limitations of CEA is necessary for informed resource allocation in achieving the maximum value for healthcare services provided.
Language	English
Publishing date	2016
Publishing country	England
Document type	Review ; Journal Article
ZDB-ID	2699932-8
ISSN	2046-1402
ISSN	2046-1402
DOI	10.12688/f1000research.7531.1
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Article ; Online: Identifying appropriate comparison groups for health system interventions in the COVID‐19 era

Samuel T. Savitz / Jason L. Scott / Michael C. Leo / Erin M. Keast / Lucy A. Savitz

Learning Health Systems, Vol 7, Iss 2, Pp n/a-n/a (2023)

2023

Abstract: Abstract Introduction COVID‐19 has created additional challenges for the analysis of non‐randomized interventions in health system settings. Our objective is to evaluate these challenges and identify lessons learned from the analysis of a medically ... ...

Abstract	Abstract Introduction COVID‐19 has created additional challenges for the analysis of non‐randomized interventions in health system settings. Our objective is to evaluate these challenges and identify lessons learned from the analysis of a medically tailored meals (MTM) intervention at Kaiser Permanente Northwest (KPNW) that began in April 2020. Methods We identified both a historical and concurrent comparison group. The historical comparison group included patients living in the same area as the MTM recipients prior to COVID‐19. The concurrent comparison group included patients admitted to contracted non‐KPNW hospitals or admitted to a KPNW facility and living outside the service area for the intervention but otherwise eligible. We used two alternative propensity score methods in response to the loss of sample size with exact matching to evaluate the intervention. Results We identified 452 patients who received the intervention, 3873 patients in the historical comparison group, and 5333 in the concurrent comparison group. We were able to mostly achieve balance on observable characteristics for the intervention and the two comparison groups. Conclusions Lessons learned included: (a) The use of two different comparison groups helped to triangulate results; (b) the meaning of utilization measures changed pre‐ and post‐COVID‐19; and (c) that balance on observable characteristics can be achieved, especially when the comparison groups are meaningfully larger than the intervention group. These findings may inform the design for future evaluations of interventions during COVID‐19.
Keywords	comparison groups ; COVID‐19 ; observational studies ; program evaluation ; Medicine (General) ; R5-920 ; Public aspects of medicine ; RA1-1270
Subject code	796
Language	English
Publishing date	2023-04-01T00:00:00Z
Publisher	Wiley
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article ; Online: How much can we trust electronic health record data?

Savitz, Samuel T / Savitz, Lucy A / Fleming, Neil S / Shah, Nilay D / Go, Alan S

Healthcare (Amsterdam, Netherlands)

2020 Volume 8, Issue 3, Page(s) 100444

Abstract: Trust in EHR data is becoming increasingly important as a greater share of clinical and health services research use EHR data. We discuss reasons for distrust and acknowledge limitations. Researchers continue to use EHR data because of strengths ... ...

Abstract	Trust in EHR data is becoming increasingly important as a greater share of clinical and health services research use EHR data. We discuss reasons for distrust and acknowledge limitations. Researchers continue to use EHR data because of strengths including greater clinical detail than sources like administrative billing claims. Further, many limitations are addressable with existing methods including data quality checks and common data frameworks. We discuss how to build greater trust in the use of EHR data for research, including additional transparency and research priority areas that will both enhance existing strengths of the EHR and mitigate its limitations.
Language	English
Publishing date	2020-07-08
Publishing country	Netherlands
Document type	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.2020.100444
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Article ; Online: Association of Patient and System-Level Factors With Social Determinants of Health Screening.

Savitz, Samuel T / Nyman, Mark A / Kaduk, Anne / Loftus, Conor / Phelan, Sean / Barry, Barbara A

Medical care

2022 Volume 60, Issue 9, Page(s) 700–708

Abstract: Background: Health systems are increasingly recognizing the importance of collecting social determinants of health (SDoH) data. However, gaps remain in our understanding of facilitators or barriers to collection. To address these gaps, we evaluated a ... ...

Abstract	Background: Health systems are increasingly recognizing the importance of collecting social determinants of health (SDoH) data. However, gaps remain in our understanding of facilitators or barriers to collection. To address these gaps, we evaluated a real-world implementation of a SDoH screening tool. Methods: We conducted a retrospective analysis of the implementation of the SDoH screening tool at Mayo Clinic in 2019. The outcomes are: (1) completion of screening and (2) the modality used (MyChart: filled out on patient portal; WelcomeTablet: filled out by patient on a PC-tablet; EpicCare: data obtained directly by provider and entered in chart). We conducted logistic regression for completion and multinomial logistic regression for modality. The factors of interest included race and ethnicity, use of an interpreter, and whether the visit was for primary care. Results: Overall, 58.7% (293,668/499,931) of screenings were completed. Patients using interpreters and racial/ethnic minorities were less likely to complete the screening. Primary care visits were associated with an increase in completion compared with specialty care visits. Patients who used an interpreter, racial and ethnic minorities, and primary care visits were all associated with greater WelcomeTablet and lower MyChart use. Conclusion: Patient and system-level factors were associated with completion and modality. The lower completion and greater WelcomeTablet use among patients who use interpreters and racial and ethnic minorities points to the need to improve screening in these groups and that the availability of the WelcomeTablet may have prevented greater differences. The higher completion in primary care visits may mean more outreach is needed for specialists.
MeSH term(s)	Ethnicity ; Humans ; Mass Screening ; Retrospective Studies ; Social Determinants of Health
Language	English
Publishing date	2022-07-22
Publishing country	United States
Document type	Journal Article ; Research Support, Non-U.S. Gov't
ZDB-ID	411646-x
ISSN	1537-1948 ; 0025-7079
ISSN (online)	1537-1948
ISSN	0025-7079
DOI	10.1097/MLR.0000000000001754
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Article ; Online: Evaluation of safety and care outcomes after the introduction of a virtual registered nurse model.

Savitz, Samuel T / Frederick, Ryannon K / Sangaralingham, Lindsey R / Lampman, Michelle A / Anderson, Stephanie S / Habermann, Elizabeth B / Bell, Sarah J

Health services research

2023 Volume 58, Issue 5, Page(s) 999–1013

Abstract: Objective: To evaluate the impact of a virtual registered nurse (ViRN) model on safety and care outcomes. ViRN is a telemedicine intervention that enables an experienced virtual nurse to assist the in-person care team in providing care to patients.: ... ...

Abstract	Objective: To evaluate the impact of a virtual registered nurse (ViRN) model on safety and care outcomes. ViRN is a telemedicine intervention that enables an experienced virtual nurse to assist the in-person care team in providing care to patients. Data sources and study setting: Electronic health records data were utilized from the Mayo Clinic during the intervention (December 2020-November 2021) and historical periods (December 2018-November 2019). ViRN was implemented on general medical units at the Mayo Clinic Rochester. We used general medical units at the Mayo Clinic Arizona as the comparison group. Study design: This study used a difference-in-differences design to evaluate the impact of ViRN compared to usual care on transfer to the intensive care unit (ICU), inpatient mortality, and length of stay (LOS). We used logistic regression for transfer to the ICU and inpatient mortality and negative binomial regression for LOS. We controlled for demographics, patient interaction with the health system, clinical characteristics, and admission characteristics. We clustered standard errors to account for patients who have multiple admissions during the study period. Principal findings: There were no significant differences for transfer to the ICU (average marginal effect (AME) -0.08 percentage point [95% confidence interval (CI): -1.34, 1.18]), inpatient mortality (AME 0.43 percentage point [95% CI: -0.33, 1.18]), or LOS (AME -0.20 days [95% CI: -0.57, 0.17]). The findings were mostly consistent across the sensitivity analyses. Conclusions: Our results suggest that ViRN led to similar outcomes as usual care in general medical units. These findings support the potential to develop more advanced models of ViRN at the Mayo Clinic and the dissemination of the ViRN model to other systems. In the context of staffing shortages and other disruptions to the delivery of nursing care, it is critical to understand whether new models like ViRN provide nurse staffing alternatives without negatively affecting outcomes.
MeSH term(s)	Humans ; Intensive Care Units ; Telemedicine ; Nurses ; Hospital Mortality ; Length of Stay
Language	English
Publishing date	2023-07-31
Publishing country	United States
Document type	Journal Article ; Research Support, Non-U.S. Gov't
ZDB-ID	410435-3
ISSN	1475-6773 ; 0017-9124
ISSN (online)	1475-6773
ISSN	0017-9124
DOI	10.1111/1475-6773.14208
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Article ; Online: Co-Occurrence of Social Risk Factors and Associated Outcomes in Patients With Heart Failure.

Savitz, Samuel T / Chamberlain, Alanna M / Dunlay, Shannon / Manemann, Sheila M / Weston, Susan A / Kurani, Shaheen / Roger, Véronique L

Journal of the American Heart Association

2023 Volume 12, Issue 14, Page(s) e028734

Abstract: Background Among patients with heart failure (HF), social risk factors (SRFs) are associated with poor outcomes. However, less is known about how co-occurrence of SRFs affect all-cause health care utilization for patients with HF. The objective was to ... ...

Abstract	Background Among patients with heart failure (HF), social risk factors (SRFs) are associated with poor outcomes. However, less is known about how co-occurrence of SRFs affect all-cause health care utilization for patients with HF. The objective was to address this gap using a novel approach to classify co-occurrence of SRFs. Methods and Results This was a cohort study of residents living in an 11-county region of southeast Minnesota, aged ≥18 years with a first-ever diagnosis for HF between January 2013 and June 2017. SRFs, including education, health literacy, social isolation, and race and ethnicity, were obtained via surveys. Area-deprivation index and rural-urban commuting area codes were determined from patient addresses. Associations between SRFs and outcomes (emergency department visits and hospitalizations) were assessed using Andersen-Gill models. Latent class analysis was used to identify subgroups of SRFs; associations with outcomes were examined. A total of 3142 patients with HF (mean age, 73.4 years; 45% women) had SRF data available. The SRFs with the strongest association with hospitalizations were education, social isolation, and area-deprivation index. We identified 4 groups using latent class analysis, with group 3, characterized by more SRFs, at increased risk of emergency department visits (hazard ratio [HR], 1.33 [95% CI, 1.23-1.45]) and hospitalizations (HR, 1.42 [95% CI, 1.28-1.58]). Conclusions Low educational attainment, high social isolation, and high area-deprivation index had the strongest associations. We identified meaningful subgroups with respect to SRFs, and these subgroups were associated with outcomes. These findings suggest that it is possible to apply latent class analysis to better understand the co-occurrence of SRFs among patients with HF.
MeSH term(s)	Humans ; Female ; Adolescent ; Adult ; Aged ; Male ; Cohort Studies ; Heart Failure/diagnosis ; Heart Failure/epidemiology ; Heart Failure/therapy ; Risk Factors ; Social Isolation ; Minnesota/epidemiology ; Hospitalization
Language	English
Publishing date	2023-07-08
Publishing country	England
Document type	Journal Article ; Research Support, N.I.H., Extramural ; Research Support, Non-U.S. Gov't
ZDB-ID	2653953-6
ISSN	2047-9980 ; 2047-9980
ISSN (online)	2047-9980
ISSN	2047-9980
DOI	10.1161/JAHA.122.028734
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