![Tina Sadarangani headshot](/sites/default/files/styles/full_width_fallback_refreshed/public/2019-10/Sadarangani_T_26.jpg?itok=_2Ghvhwg)
Tina Sadarangani
ANP-C GNP-BC PhD RN
Assistant Professor
tina.sadarangani@nyu.edu
1 212 992 7183
433 FIRST AVENUE
NEW YORK, NY 10010
United States
Tina Sadarangani's additional information
-
-
Tina Sadarangani is an NIH-funded Principal Investigator and board certified primary care nurse practitioner. She is cross-appointed as an assistant professor in the NYU School of Medicine Department of Population Health. Her program of research is underscored by a profound commitment to advancing the health of minoritized older adults by leveraging the strengths of community-based adult day health care centers to target health disparities. In the last three years, she has expanded her program of research to focus, specifically, on identifying and addressing the healthcare needs of cognitively impaired older immigrants, by using the adult day health center as a platform for the delivery of culturally and linguistically congruent care. Her on-going collaborations with the California Association of Adult Day Services, as well as other community-based organizations, have demonstrated that integrating adult day centers into the healthcare continuum contributes to reductions in avoidable healthcare utilization.
Sadarangani’s latest work focuses on improving communication between adult day centers and primary care providers using low-cost mobile technology. She recently received a K23 Career Development Award from the National Institute on Aging (NIA) as well as an R21 from NIA. She previously received a Career Development Award from the NIA IMPACT Collaboratory, and currently serves as an Adjunct Professor and member of the Collaboratory’s Patient and Caregiver Relevant Outcomes (PCRO) core. She holds prior degrees from Georgetown University (Anthropology), the University of Pennsylvania (MSN), and NYU Meyers (BSN, PhD).
-
-
PhD - New York UniversityMS - University of PennsylvaniaBSN - New York UniversityBA - Georgetown University
-
-
GerontologyImmigrantsHealth PolicyChronic diseaseUnderserved populationsVulnerable & marginalized populationsHealth Services Research
-
-
American Gerontological SocietyAmerican Heart AssociationNational Gerontological Nurses AssociationSigma Theta Tau Nursing Honor Society
-
-
Faculty Honors Awards
Provost’s Postdoctoral Fellowship Program, New York University (2019)Provost’s Postdoctoral Fellowship Program, New York University (2018)Provost’s Postdoctoral Fellowship Program, New York University (2017)Valedictorian, New York University (2017)Hermann Biggs Health Policy Scholar, Josiah Macy Jr. Foundation (2017)Hermann Biggs Health Policy Scholar, Josiah Macy Jr. Foundation (2016)Doctoral Audience Choice Winner, New York University (2016)Research Podium Presentation Award, Gerontology Advanced Practice Nurses Association (2016)Patricia G. Archbold Award, National Hartford Centers for Gerontological Nursing Excellence (2016)Hillman Alumni Network Innovation Fellowship, Hillman Alumni Network (2016)Patricia G. Archbold Award, National Hartford Centers for Gerontological Nursing Excellence (2015)Patricia G. Archbold Award, National Hartford Centers for Gerontological Nursing Excellence (2014)Spirit of Hillman Award, Hillman Alumni Network (2014)Phi Beta Kappa, Georgetown UniversitySumma Cum Laude, Georgetown University -
-
Publications
Optimizing the primary care management of chronic pain through telecare
AbstractTierce-Hazard, S., & Sadarangani, T. (2014). Journal of Clinical Outcomes Management, 21(11), 493-495.AbstractObjective. To evaluate the effectiveness of a collaborative telecare intervention on chronic pain management. Design. Randomized clinical trial. Settings and participants. Participants were recruited over a 2-year period from 5 primary care clinics within a single Veterans Affairs medical center. Patients aged 18 to 65 years were eligible if they had chronic (≥3 months) musculoskeletal pain of at least moderate intensity (Brief Pain Inventory [BPI] score ≥5). Patients were excluded if they had a pending disability claim or a diagnosis of bipolar disorder, schizophrenia, moderately severe cognitive impairment, active suicidal ideation, current illicit drug use or a terminal illness or received primary care outside of the VA. Participants were randomized to either the telephone-delivered collaborative care management intervention group or usual care. Usual care was defined as continuing to receive care from their primary care provider for management of chronic, musculoskeletal pain. Intervention. The telecare intervention comprised automated symptom monitoring (ASM) and optimized analgesic management through an algorithm-guided stepped care approach delivered by a nurse case manager. ASM was delivered either by an interactive voice-recorded telephone call (51%) or by internet (49%), set according to patient preference. Intervention calls occurred at 1 and 3 months. Additional contact with participants from the intervention group was generated in response to ASM trend reports. Main outcome measures. The primary outcome was the BPI total score. The BPI scale ranges from 0 to 10, with higher scores indicating worsening pain. A 1-point change is considered clinically important. Secondary pain outcomes included BPI interference and severity, global pain improvement, treatment satisfaction, and use of opioids and other analgesics. Patients were interviewed at 1, 3, 6, and 12 months. Main results. A total of 250 participants were enrolled, 124 assigned to the intervention group and 126 assigned to usual care. The mean (SD) baseline BPI scores were 5.31 (1.81) for the intervention group and 5.12 (1.80) for usual care. Compared with usual care, the intervention group had a 1.02-point lower BPI score at 12 months (95% confidence interval [CI], -1.58 to -0.47) (P < 0.001). Patients in the intervention group were nearly twice as likely to report at least a 30% improvement in their pain score by 12 months (51.7% vs. 27.1%; relative risk [RR], 1.9 [95% CI, 1.4 to 2.7]), with a number needed to treat of 4.1 (95% CI, 3.0 to 6.4) for a 30% improvement. Patients in the intervention group were more likely to rate as good to excellent the medication prescribed for their pain (73.9% vs 50.9%; RR, 1.5 [95% CI, 1.2 to 1.8]). Patients in the usual care group were more likely to experience worsening of pain by 6 months compared with the intervention group. A greater number of analgesics were prescribed to patients in the intervention group; however, opioid use between groups did not differ at baseline or at any point during the trial period. For the secondary outcomes, the intervention group reported greater improvement in depression compared with the usual care group, and this difference was statistically significant (P < 0.001). They also reported fewer days of disability (P = 0.34). Conclusion. Telecare collaborative management was more effective in improving chronic pain outcomes than usual care. This was accomplished through the optimization of non-opioid analgesic therapy facilitated by a stepped care algorithm and automated symptom monitoring.Telehealth as an alternative to traditional, in-person diabetes self-management support
AbstractBurchard, A., & Sadarangani, T. (2014). Journal of Clinical Outcomes Management, 21(11), 495-496.AbstractObjective. To investigate the feasibility and effectiveness of administering diabetes self-management support (DSMS) via telephone or secure messaging. Design. Prospective, longitudinal quasi-experimental study. Setting and participants. Participants (n = 150) who had previously completed diabetes self-management education (DSME) received follow-up DSMS in 1 of 3 selfselected ways: a one-time in-person visit, 3 brief visits by telephone, or via secure messaging via the electronic health record. The (usual care) in-person group (n = 47) received 1 follow-up appointment at the patient's request with a certified diabetes educator (CDE) within 3 to 6 months of DSME completion. The telephone group (n = 44) was given follow-up phone appointments with a CDE, each lasting approximately 20 minutes, at 3, 6, and 9 months post-DSME. The secure message group (n = 59) received follow-up messages via the patient portal from a CDE at 3, 6, and 9 months post-DSME. At each interval, patients received 3 messages, an initial one followed by 2 structured replies. Motivational interviewing techniques were used in all 3 groups to identify barriers to achieving behavior goals and solutions. Main outcome measures. Behavior goal measures, feasibility measures, and physiologic measures at 9 months' post DSME. Behavior goal achievement was measured using a survey that asked patients to rate their achievement regarding the following AADE7 goals: healthy eating, being active, self-monitoring, taking medications, problem solving, reducing risks, and healthy coping. Goals are rated on a scale from 0 to 10, with a rating ≥ 7 considered successful completion. Feasibility to integrate this technology into a DSME platform was assessed by comparing the number of attempts to contact patients with the number of contacts achieved; also calculated was intervention completion, mean time spent with the CDE, and total cost of each visit. Physiologic measures included HbA1C and LDL levels collected through medical record review. Results. There were no statistically significant differences between groups with respect to any of the primary outcomes. Behavioral goals were achieved by 59% of the in-person group, 73% of the telephone group, and 77% of the secure message group . Mean goal achievement for all 3 groups combined improved from 6.2 ± 2.4 to 7.2 ± 1.8 (P < 0.05). Overall, 70.3% ± 0.46% achieved behavioral goals, with no difference among groups. In terms of feasibility, at 3 months the contact success rate was 39%, 46%, and 29% in the in-person, telephone, and secure message groups, respectively. At 6 months, the contact success rate was 47% in the phone group versus 32% in the secure message group. At 9 months, the contact success rate was 35% in the phone group versus 21% in the secure message group. Sixty-two participants (41%) completed the intervention per protocol: 51% of in-person patients, 47% of phone patients, and 28% of secure message patients (P < 0.02). Visits lasted and cost, on average, 60 minutes and $50.00, 45.3 minutes and $37.75, and 17.8 minutes (P < 0.05) and $14.83 for the in-person, telephone, and secure message groups, respectively. There was no difference in HbA1c among groups. Overall, HbA1c decreased by -0.88% ± 1.63 (P < 0.05) from baseline to 9 months. Change in LDL was not significant, and neither were there statistical differences among groups. Conclusion. Diabetes follow-up care delivered via telephone and secure messaging is feasible. Using either of these methods results in similar outcomes compared with the traditional in-person visit, while requiring less staff time. -