Kelly Stolzmann

Biographic Data

ID4804129
NAMEKelly Stolzmann
GIVEN NAMESKelly
FAMILY NAMEStolzmann
SIGNATURESTOLZMANN K
AFFILIATIONSVA Boston Healthcare System
ORCID0000-0002-3491-9803
VERIFIEDYes
TOTAL WORKS10
TOTAL CITATIONS11
AUTHOR COUNT10
EDITOR COUNT0
FIRST PUBLICATION YEAR2010
LATEST PUBLICATION YEAR2024
H-INDEX2

  • Twelve-Month Sustainment of IPV Screening and Response Programs in Primary Care

    Open AccessKatherine M Iverson, Julianne E Brady et al.ARTICLEWomen s Health Issues2024

  • Patient and provider predictors of telemental health use prior to and during the Covid-19 pandemic within the Department of Veterans Affairs

    Open AccessSamantha L Connolly, Kelly Stolzmann et al.ARTICLEAmerican Psychologist2021Cited by: 2

    The current study examined patient and provider differences in use of phone, video, and in-person mental health (MH) services. Participants included patients who completed ≥ 1 MH appointment within the Department of Veterans Affairs (VA) from 10/1/17-7/10/20 and providers who completed ≥ 100 VA MH appointments from 10/1/17-7/10/20. Adjusted odds ratios (aORs) are reported of patients and providers: (a) completing ≥1 video MH appointment in the pr…

  • An Economic Analysis of the Implementation of Team-based Collaborative Care in Outpatient General Mental Health Clinics

    Christopher J Miller, Kevin N Griffith et al.ARTICLEMedical Care2020References: 34

    BACKGROUND: Collaborative Chronic Care Models represent an evidence-based way to structure care for chronic conditions, including mental health conditions. Few studies, however, have examined the cost implications of collaborative care for mental health. OBJECTIVE: We aimed to conduct an economic analysis of implementing collaborative care in 9 outpatient general mental health clinics. RESEARCH DESIGN: Analyses were derived from a stepped wedge h…

  • The Collaborative Chronic Care Model for Mental Health Conditions

    Mark S Bauer, Kendra Weaver et al.ARTICLEMedical Care2019References: 30

    BACKGROUND: Extensive evidence indicates that Collaborative Chronic Care Models (CCMs) improve outcome in chronic medical conditions and depression treated in primary care. Beginning with an evidence synthesis which indicated that CCMs are also effective for multiple mental health conditions, we describe a multistage process that translated this knowledge into evidence-based health system change in the US Department of Veterans Affairs (VA). EVID…

  • Patient Possession of Excess Medication Supply in the VA

    Amy Linsky, Syahputra A Gani et al.ARTICLEMedical Care2019References: 29

    Medication excess was high among VHA users, with nearly two-thirds of patients experiencing at least 1 duplicative medication. As systems such as mail-order pharmacies and 90-day supply are increasingly implemented to reduce costs and improve medication adherence, it is important to recognize the potential for systems-level inefficiencies and potentially inappropriate prescribing

  • Factor structure of the Q-LES-Q short form in an enrolled mental health clinic population

    Open AccessRachel P Riendeau, Jennifer L Sullivan et al.ARTICLEQuality of Life Research2018

    The English version of the Q-LES-Q-SF is a valid, reliable self-report instrument for assessing quality of life. Its factor structure can be best described as one strong psychosocial factor. Differences in underlying factor structure across studies may be due to limitations in using EFA on Likert scales, language, culture, locus of participant recruitment, disease burden, and mode of administration

  • Patient Perceptions of Deprescribing

    Amy M Linsky, Amy Linsky et al.ARTICLEMedical Care2017References: 27

    BACKGROUND: Although clinicians ultimately decide when to discontinue (deprescribe) medications, patients' perspectives may guide the process. OBJECTIVES: To develop a survey instrument that assesses patients' experience with and attitudes toward deprescribing. RESEARCH DESIGN: We developed a questionnaire with established and newly created items. We used exploratory factor analysis and confirmatory factor analysis (EFA and CFA) to assess the psy…

  • Response Rates, Nonresponse Bias, and Data Quality

    Mark Meterko, Joseph D Restuccia et al.ARTICLEPublic Opinion Quarterly2015Cited by: 9References: 8

    Survey response rate is regarded as a key data-quality indicator, yet response rate is not necessarily predictive of nonresponse bias. Our study objective was to use a high-response-rate survey to assess nonresponse bias across successive waves. This survey of healthcare leaders utilized a web-based, self-report format with an initial invitation and four nonrespondent follow-ups. Across five waves, comparisons were made for demographic and facili…

  • Psychiatric Diagnoses and Neurobehavioral Symptom Severity among OEF/OIF VA Patients with Deployment-Related Traumatic Brain Injury

    Open AccessKatherine M Iverson, Ann Hendricks et al.ARTICLEWomen s Health Issues2011

  • Accounting for Variation in Technical Quality and Patient Satisfaction

    Kelly Stolzmann, Kelly L Stolzmann et al.ARTICLEMedical Care2010References: 31

    BACKGROUND: The delivery of healthcare depends on individual providers, coordination within teams, and the structure of the work setting. We analyzed the amount of variation in technical quality and patient satisfaction accounted for at the patient, provider, team, and medical center level. METHODS: Data abstracted from Veterans Health Administration patient medical records for 2007 were used to calculate measures of technical quality based on ad…