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The American Journal of Managed Care September 2018
Food Insecurity, Healthcare Utilization, and High Cost: A Longitudinal Cohort Study
Seth A. Berkowitz, MD, MPH; Hilary K. Seligman, MD, MAS; James B. Meigs, MD, MPH; and Sanjay Basu, MD, PhD
Language Barriers and LDL-C/SBP Control Among Latinos With Diabetes
Alicia Fernandez, MD; E. Margaret Warton, MPH; Dean Schillinger, MD; Howard H. Moffet, MPH; Jenna Kruger, MPH; Nancy Adler, PhD; and Andrew J. Karter, PhD
Hepatitis C Care Cascade Among Persons Born 1945-1965: 3 Medical Centers
Joanne E. Brady, PhD; Claudia Vellozzi, MD, MPH; Susan Hariri, PhD; Danielle L. Kruger, BA; David R. Nerenz, PhD; Kimberly Ann Brown, MD; Alex D. Federman, MD, MPH; Katherine Krauskopf, MD, MPH; Natalie Kil, MPH; Omar I. Massoud, MD; Jenni M. Wise, RN, MSN; Toni Ann Seay, MPH, MA; Bryce D. Smith, PhD; Anthony K. Yartel, MPH; and David B. Rein, PhD
“Precision Health” for High-Need, High-Cost Patients
Dhruv Khullar, MD, MPP, and Rainu Kaushal, MD, MPH
From the Editorial Board: A. Mark Fendrick, MD
A. Mark Fendrick, MD
Health Literacy, Preventive Health Screening, and Medication Adherence Behaviors of Older African Americans at a PCMH
Anil N.F. Aranha, PhD, and Pragnesh J. Patel, MD
Early Experiences With the Acute Community Care Program in Eastern Massachusetts
Lisa I. Iezzoni, MD, MSc; Amy J. Wint, MSc; W. Scott Cluett III; Toyin Ajayi, MD, MPhil; Matthew Goudreau, BS; Bonnie B. Blanchfield, CPA, SM, ScD; Joseph Palmisano, MA, MPH; and Yorghos Tripodis, PhD
Currently Reading
Economic Evaluation of Patient-Centered Care Among Long-Term Cancer Survivors
JaeJin An, BPharm, PhD, and Adrian Lau, PharmD
High-Touch Care Leads to Better Outcomes and Lower Costs in a Senior Population
Reyan Ghany, MD; Leonardo Tamariz, MD, MPH; Gordon Chen, MD; Elissa Dawkins, MS; Alina Ghany, MD; Emancia Forbes, RDCS; Thiago Tajiri, MBA; and Ana Palacio, MD, MPH
Adjusting Medicare Advantage Star Ratings for Socioeconomic Status and Disability
Melony E. Sorbero, PhD, MS, MPH; Susan M. Paddock, PhD; Cheryl L. Damberg, PhD; Ann Haas, MS, MPH; Mallika Kommareddi, MPH; Anagha Tolpadi, MS; Megan Mathews, MA; and Marc N. Elliott, PhD

Economic Evaluation of Patient-Centered Care Among Long-Term Cancer Survivors

JaeJin An, BPharm, PhD, and Adrian Lau, PharmD
Providing patient-centered comprehensive care to long-term cancer survivors may lead to reduced total healthcare expenditures.
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Patient Perceptions of PCMH Characteristics

Self-reported patient data were used to determine whether or not cancer survivors perceived their medical care as patient-centered comprehensive care. The definition of patient-centered comprehensive care was adopted from previously published studies by using a set of questions about a patient’s interactions with their usual source of care (USC), which focused on whether the patient received “comprehensive care,” “accessible care,” and care with a “whole-person orientation,” all 3 of which are hallmark attributes of a PCMH model.22-26 Cancer survivors who responded positively for all 3 hallmark attributes of a PCMH model at baseline (year 1) were categorized as the patient-centered care (PCC) group. Cancer survivors who did not respond positively to any of the PCMH characteristics or responded positively to only 1 or 2 characteristics were subsequently categorized as the non-PCC group. The list of questions is in the eAppendix (available at

Economic Outcomes

Total healthcare utilization and total healthcare expenditures were measured in the PCC group and the non-PCC group at baseline and at follow-up (year 2). Total healthcare utilization included hospitalizations, emergency department (ED) visits, office visits, primary care provider (PCP; specialties of family medicine and internal medicine) visits, and oncologist visits. Total healthcare expenditures included spending on hospitalizations, office visits, ED visits, and prescriptions in 2014 US$.

Statistical Analyses

Descriptive statistics were used to summarize baseline characteristics in the PCC and non-PCC groups, with the baseline characteristics including age, age group, years since cancer diagnosis, gender, race/ethnicity, baseline survey year, region, marital status, education level, insurance type, perceived health, cancer type, comorbidities, and Elixhauser comorbidity score.27 Differences between the PCC group and the non-PCC group were compared using Student’s t test for continuous variables and χ2 test for categorical variables. Moreover, an inverse probability propensity score (PS) method was used to balance these baseline characteristics between the PCC group and the non-PCC group.28 Baseline characteristics with P <.25 (region, marital status, education level, insurance type, perceived health, comorbidity of hypertension, rheumatoid arthritis, depression, chronic pulmonary disease, and unknown skin cancer), as well as age, sex, baseline healthcare expenditures, and ED visits, were added to predict the PS. Generalized linear models with log-rank and gamma distribution were used to test the statistical significance of the total healthcare costs between the 2 groups. Recycled prediction methods were used to estimate the mean expenditures of each group after applying the PS model. Logistic regressions, with a response of 0 indicating no and 1 indicating yes, were used in conjunction with negative binomial models in the determination of the total healthcare utilization analysis. A priori subgroup analyses were conducted to examine whether the economic effects of PCC were consistent across the 2 subgroups of survivors either younger than 65 years or 65 years and older. Additionally, a secondary analysis was performed to investigate the association between each of the 3 PCMH model hallmark attributes and its potential impact on economic outcomes. A P value of <.05 was accepted for statistical significance. All statistical analyses were performed using SAS, version 9.4 (SAS Institute; Cary, North Carolina), and STATA, version 12 (STATA; College Station, Texas).


A total of 4288 adult patients were identified as long-term cancer survivors. At baseline, 1883 (43.9%) were categorized into the PCC group, while the remaining 2405 cancer survivors (56.1%) were categorized into the non-PCC group (Table 1 [part A and part B]). For each of the characteristics associated with the 3 hallmark attributes of a PCC (comprehensive care, whole-person orientation, and accessible care), a low of 79% to a high of 99% positive response rate was observed, depending on the characteristic (eAppendix). These positive responses allowed for the differentiation of the PCC group from the non-PCC group.

Overall, the mean (SD) age of a long-term cancer survivor was 65.2 (13.8) years, and the mean (SD) years since cancer diagnosis were 10.1 (10.0). Approximately 75.6% identified themselves as white and 57.4% were female. In general, cancer survivors in the PCC group were more likely to have private insurance, perceive their health as excellent, and have comorbid hypertension, and less likely to have comorbidities of depression and chronic pulmonary disease, compared with cancer survivors in the non-PCC group.

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