Dana Mukamel
· Professor of MedicineUniversity of California, Irvine · Population Health & Disease Prevention
Active 2005–2022
About
Dana B. Mukamel, Ph.D., is a Distinguished Professor at the Department of Medicine and Director of the iTEQC Research Program at the University of California, Irvine. She also holds appointments in Public Health and Nursing. Her research focuses on issues related to quality of care in acute and long-term care settings, including methodological issues in measuring quality and empirical studies that provide insights into policy, market, and provider factors contributing to high-quality care. She has developed methods to measure quality in nursing homes and community-based long-term care programs based on risk-adjusted health outcomes, such as functional decline and pressure ulcers. Her work examines the role of competition, regulation, report cards, and other factors in the provision of quality care. Dr. Mukamel's extensive research program is funded by federal agencies, PCORI, and private foundations, and she has recently expanded her work to include the development of decision aids utilizing big data and preference elicitation techniques to improve decision-making for patients, providers, and policymakers. She serves on several CMS task forces advising on risk-adjusted quality measures, report cards, and pay-for-performance programs. Additionally, she has served on editorial boards of prominent journals and on numerous national advisory and review boards for organizations such as CMS, NIH, AHRQ, VA, and MedPAC.
Research topics
- Internal medicine
- Medicine
- Intensive care medicine
- Emergency medicine
- Nursing
Selected publications
Nephrology Dialysis Transplantation · 2022
- Medicine
- Intensive care medicine
- Internal medicine
Abstract BACKGROUND AND AIMS Within the Veterans Health Administration, the largest integrated healthcare system in the USA, 1.1 million Veterans (16.4%) have been identified as having chronic kidney disease (CKD). Annual spending on US Veterans with non-dialysis dependent CKD is estimated at $19 billion/year, and each year ∼10% of US Veterans with advanced CKD progress to end-stage renal disease (ESRD) requiring renal replacement therapy in the form of dialysis or kidney transplantation. While dialysis has been the dominant treatment paradigm in this population, with ∼22 000 enrolled Veterans receiving dialysis from VA-based dialysis facilities or from VA-contracted community providers, this treatment approach may not offer survival benefit nor improved quality of life in certain subgroups (elderly, multi-morbid). We sought to examine the clinical characteristics of a contemporary cohort of US Veterans with advanced CKD treated with conservative non-dialytic management versus dialysis. METHOD In a national cohort of US Veterans receiving care from the VA healthcare system, we identified patients with advanced CKD, identified as those with ≥ 2 eGFR measurements < 25 mL/min/1.73 m2 separated by ≥ 90 days over the period of 1 October 2010–30 September 2019. Used linked United States Renal Data System and Medicare data, patients were categorized according to (1) receipt of conservative management (CM), defined as those who did not receive dialysis within 2 years of the index eGFR (first eGFR < 25 mL/min/1.73 m2) and (2) receipt of dialysis within 2 years of the index eGFR. We then examined the clinical characteristics and outcome trajectory of those treated with CM versus dialysis, with follow-up through 30 September 2021. RESULTS Among 106 089 advanced CKD patients who met eligibility criteria, 24.6% (N = 26 113) and 75.4% (N = 79 956) were treated with dialysis versus CM, respectively (index eGFR distribution shown in Fig. 1, left panel). In the overall cohort, the mean ± SD age was 73 ± 12 years and 97.4% were men, with a younger age distribution seen in those receiving dialysis versus CM, yet a similar sex distribution across the two treatment groups (Table 1). Across racial groups, there was a greater tendency for Black, Asian, Pacific Islander and Native American Veterans to undergo dialysis versus CM as compared with Veterans of White race. A greater proportion of deaths were observed among Veterans treated with dialysis versus CM (73.2% versus 70.3%, respectively; available follow-up time to censoring or death is shown in Fig. 1, right panel). CONCLUSION In a nationally representative CKD cohort, we observed differences in socio-demographics, including racial background, among patients who were treated with CM versus dialysis. Additionally, death was more frequently observed in those who underwent dialysis versus CM. Further studies are needed to examine the comparative effectiveness of CM versus dialysis transition on CKD outcomes.
Nephrology Dialysis Transplantation · 2022
- Medicine
- Internal medicine
- Emergency medicine
Abstract BACKGROUND AND AIMS While dialysis has been the prevailing treatment paradigm in advanced CKD patients progressing to ESRD, this treatment approach may lead to a decline in physical function, loss of independence, and greater healthcare utilization among certain subgroups. We sought to compare the impact of dialysis versus conservative dialysis-free management on hospitalization lengths of stay (LOS) in advanced CKD patients. METHOD We examined a national cohort of advanced CKD patients (≥2 eGFRs <25 mL/min/1.73 m2 separated by ≥90 days) treated with conservative management (CM) versus dialysis over 1 January 2007—30 June 2020 from the OptumLabs® Data Warehouse (OLDW), which contains de-identified administrative claims, including medical and pharmacy claims and enrollment records for commercial and Medicare Advantage enrollees, as well as electronic health record data. In primary analyses, patients were categorized according to receipt of CM, defined as those who did not receive dialysis within 2-years of the index eGFR (1st eGFR <25 mL/min/1.73 m2), versus receipt of dialysis. In secondary analyses, we examined finer gradations of the timing of dialysis, defined as late versus early transition (eGFRs <15 versus ≥15 mL/min/1.73 m2 respectively, at the time of dialysis initiation). We compared LOS among patients treated with CM versus dialysis who were hospitalized within 2 years of their index eGFR using linear mixed effects models that separately considered a fixed age of the cohort (65-years old), with varying times of hospitalization from the index eGFR date, as well as a fixed time of hospitalization from the index eGFR date (12 months) with varying age. RESULTS Among 169 479 advanced CKD patients who were hospitalized within 2-years of their index eGFR, there were a total of 620 168 hospitalizations over this time period. In primary analyses that considered a fixed age of the cohort, dialysis patients experienced longer average LOS versus those treated with CM, with differences attenuating over time (∆ of + 1.5-days for hospitalizations 1-month from the index eGFR; Fig. 1A, upper panel). In secondary analyses, differences in average LOS were even greater for those treated with early dialysis versus CM (∆ of + 2-days for hospitalizations 1-month from the index eGFR, Fig. A, lower panel). In primary analyses that considered a fixed time of hospitalization from the index eGFR, dialysis patients >20-years old had longer average LOS versus those treated with CM, with differences increasing with older age (∆ of + 1.25-days for hospitalizations for patients 70-years old; Fig. 1B, upper panel). In secondary analyses, differences in average LOS were even greater for those treated with early dialysis versus CM (∆ of + 1.87-days for patients 70-years old, Fig. 1B, lower panel). CONCLUSION In a nationally representative CKD cohort, compared with dialysis, those treated with CM as an alternative patient-centered treatment strategy had shorter LOS across varying time points and age groups. Further studies are needed to examine the comparative effectiveness of CM versus dialysis transition on CKD outcomes.
Journal of Medical Internet Research · 2021 · 1058 citations
- Computer Science
- Psychology
- Applied psychology
BACKGROUND: Digital mental health interventions (DMHIs), which deliver mental health support via technologies such as mobile apps, can increase access to mental health support, and many studies have demonstrated their effectiveness in improving symptoms. However, user engagement varies, with regard to a user's uptake and sustained interactions with these interventions. OBJECTIVE: This systematic review aims to identify common barriers and facilitators that influence user engagement with DMHIs. METHODS: A systematic search was conducted in the SCOPUS, PubMed, PsycINFO, Web of Science, and Cochrane Library databases. Empirical studies that report qualitative and/or quantitative data were included. RESULTS: A total of 208 articles met the inclusion criteria. The included articles used a variety of methodologies, including interviews, surveys, focus groups, workshops, field studies, and analysis of user reviews. Factors extracted for coding were related to the end user, the program or content offered by the intervention, and the technology and implementation environment. Common barriers included severe mental health issues that hampered engagement, technical issues, and a lack of personalization. Common facilitators were social connectedness facilitated by the intervention, increased insight into health, and a feeling of being in control of one's own health. CONCLUSIONS: Although previous research suggests that DMHIs can be useful in supporting mental health, contextual factors are important determinants of whether users actually engage with these interventions. The factors identified in this review can provide guidance when evaluating DMHIs to help explain and understand user engagement and can inform the design and development of new digital interventions.
Understanding Mental Health App Use Among Community College Students: Web-Based Survey Study
Journal of Medical Internet Research · 2021 · 64 citations
- Psychology
- Medicine
- Psychiatry
BACKGROUND: Mental health concerns are a significant issue among community college students, who often have less access to resources than traditional university college students. Mobile apps have the potential to increase access to mental health care, but there has been little research investigating factors associated with mental health app use within the community college population. OBJECTIVE: This study aimed to understand facilitators of and barriers to mental health app use among community college students. METHODS: A web-based survey was administered to a randomly selected sample of 500 community college students from April 16 to June 30, 2020. Structural equation modeling was used to test the relationships between the use of mental health apps, perceived stress, perceived need to seek help for mental health concerns, perceived stigma, past use of professional mental health services, privacy concerns, and social influence of other people in using mental health apps. RESULTS: Of the 500 participants, 106 (21.2%) reported use of mental health apps. Perceived stress, perceived need to seek help, past use of professional services, and social influence were positively associated with mental health app use. Furthermore, the effect of stress was mediated by a perceived need to seek help. Privacy concerns were negatively associated with mental health app use. Stigma, age, and gender did not have a statistically significant effect. CONCLUSIONS: These findings can inform development of new digital interventions and appropriate outreach strategies to engage community college students in using mental health apps.
Journal of Medical Internet Research · 2021 · 108 citations
- Medicine
- Psychiatry
- Psychology
BACKGROUND: Accompanying the rising rates of reported mental distress during the COVID-19 pandemic has been a reported increase in the use of digital technologies to manage health generally, and mental health more specifically. OBJECTIVE: The objective of this study was to systematically examine whether there was a COVID-19 pandemic-related increase in the self-reported use of digital mental health tools and other technologies to manage mental health. METHODS: We analyzed results from a survey of 5907 individuals in the United States using Amazon Mechanical Turk (MTurk); the survey was administered during 4 week-long periods in 2020 and survey respondents were from all 50 states and Washington DC. The first set of analyses employed two different logistic regression models to estimate the likelihood of having symptoms indicative of clinical depression and anxiety, respectively, as a function of the rate of COVID-19 cases per 10 people and survey time point. The second set employed seven different logistic regression models to estimate the likelihood of using seven different types of digital mental health tools and other technologies to manage one's mental health, as a function of symptoms indicative of clinical depression and anxiety, rate of COVID-19 cases per 10 people, and survey time point. These models also examined potential interactions between symptoms of clinical depression and anxiety, respectively, and rate of COVID-19 cases. All models controlled for respondent sociodemographic characteristics and state fixed effects. RESULTS: Higher COVID-19 case rates were associated with a significantly greater likelihood of reporting symptoms of depression (odds ratio [OR] 2.06, 95% CI 1.27-3.35), but not anxiety (OR 1.21, 95% CI 0.77-1.88). Survey time point, a proxy for time, was associated with a greater likelihood of reporting clinically meaningful symptoms of depression and anxiety (OR 1.19, 95% CI 1.12-1.27 and OR 1.12, 95% CI 1.05-1.19, respectively). Reported symptoms of depression and anxiety were associated with a greater likelihood of using each type of technology. Higher COVID-19 case rates were associated with a significantly greater likelihood of using mental health forums, websites, or apps (OR 2.70, 95% CI 1.49-4.88), and other health forums, websites, or apps (OR 2.60, 95% CI 1.55-4.34). Time was associated with increased odds of reported use of mental health forums, websites, or apps (OR 1.20, 95% CI 1.11-1.30), phone-based or text-based crisis lines (OR 1.20, 95% CI 1.10-1.31), and online, computer, or console gaming/video gaming (OR 1.12, 95% CI 1.05-1.19). Interactions between COVID-19 case rate and mental health symptoms were not significantly associated with any of the technology types. CONCLUSIONS: Findings suggested increased use of digital mental health tools and other technologies over time during the early stages of the COVID-19 pandemic. As such, additional effort is urgently needed to consider the quality of these products, either by ensuring users have access to evidence-based and evidence-informed technologies and/or by providing them with the skills to make informed decisions around their potential efficacy.
Recent grants
NIH · $951k · 2012
Frequent coauthors
- 4 shared
Ran Schwarzkopf
NYU Langone Health
- 4 shared
Heather Ladd
University of California, Irvine
- 3 shared
Nimrod Snir
Tel Aviv University
- 2 shared
M. Rhona Limcangco
Social and Scientific Systems (United States)
- 2 shared
Jenny Ho
University of California, Irvine
- 2 shared
Brenda R. Wamsley
- 2 shared
Alejandra García Novoa
Complexo Hospitalario Universitario A Coruña
- 2 shared
Amy S. You
University of California, Los Angeles
Awards & honors
- 2022 - School of Medicine Lifetime Research Achievement Awar…
- 2015 - Lifetime Achievement Award, American Public Health As…
- 1997 - James G. Zimmer New Investigator Award for Excellence…
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