Literature DB >> 24019974

Provider continuity prior to the diagnosis of advanced lung cancer and end-of-life care.

Gulshan Sharma1, Yue Wang, James E Graham, Yong-Fang Kuo, James S Goodwin.   

Abstract

BACKGROUND: Little is known about the effect of provider continuity prior to the diagnosis of advanced lung cancer and end-of-life care.
METHODS: Retrospective analysis of 69,247 Medicare beneficiaries aged 67 years or older diagnosed with Stage IIIB or IV lung cancer between January 1, 1993 and December 31, 2005 who died within two years of diagnosis. We examined visit patterns to a primary care physician (PCP) and/or any provider one year prior to the diagnosis of advanced lung cancer as measures of continuity of care. Outcome measures were hospitalization, ICU use and chemotherapy use during the last month of life, and hospice use during the last week of life.
RESULTS: Seeing a PCP or any provider in the year prior to the diagnosis of advanced lung cancer increased the likelihood of hospitalization, ICU care, chemotherapy and hospice use during the end of life. Patients with 1-3, 4-7 or >7 visits to their PCP in the year prior to the diagnosis of lung cancer had 1.0 (reference), 1.08 (95% CI; 1.04-1.13), and 1.14 (95% CI; 1.08-1.19) odds of hospitalization during the last month of life, respectively. Odds of hospice use during the last week of life were higher in patients with visits to multiple PCPs (OR 1.10: 95% CI; 1.06-1.15) compared to those whose visits were all to the same PCP.
CONCLUSION: Provider continuity in the year prior to the diagnosis of advanced lung cancer was not associated with lower use of aggressive care during end of life. Our study did not have information on patient preferences and result should be interpreted accordingly.

Entities:  

Mesh:

Year:  2013        PMID: 24019974      PMCID: PMC3760849          DOI: 10.1371/journal.pone.0074690

Source DB:  PubMed          Journal:  PLoS One        ISSN: 1932-6203            Impact factor:   3.240


Introduction

Outpatient provider continuity is central to the “medical home” concept of the Patient Protection and Affordable Care Act and is key to good medical care[1]. It is associated with improved patient satisfaction,[2] increased use of appropriate preventive health services[3]–[7], greater medication compliance, lower hospitalization rates,[8]–[12] less emergency department use[13] and fewer duplicate tests.[14] Moreover, continuity of care with a primary care physician (PCP) has shown substantial reductions in mortality among older adults.[15] Continuity is beneficial for cancer patients both prior to and after diagnosis. Pre-diagnosis continuity leads to diagnoses at earlier stages.[16] PCP continuity after cancer diagnosis increases the likelihood of receiving guideline concordant therapy,[17] decreases the likelihood of emergency room visits in the last six months of life,[18] and increases the likelihood of dying at home.[19] Patients visited by their PCP during their last hospitalization (outpatient to inpatient provider continuity) are less likely to receive Intensive Care Unit (ICU) care.[20] Studies of the effects of continuity on end-of-life care in cancer patients are primarily limited to patients already diagnosed with cancer. We were interested in whether the continuity established prior to this life- and care-altering event (diagnosis of advanced lung cancer) has enduring effects on the end-of-life medical care these patients received. Our hypothesis was that provider continuity prior to the diagnosis of advanced cancer is associated with lower hospitalization, less ICU use, less chemotherapy use and higher hospice use at the end of life. These measures are considered indicators of potentially appropriate care. We used a national sample of newly-diagnosed advanced lung cancer patients to examine the effect of provider continuity prior to the diagnosis of advanced lung cancer on end-of-life medical care.

Methods

Data Source

This is a retrospective study of advanced lung cancer patients identified from the linked Surveillance, Epidemiology and End Results (SEER)-Medicare database for the years 1993–2005. We included the 13 SEER registry geographic regions: the states of Connecticut, Hawaii, Utah, New Mexico, Iowa, California, Kentucky, Louisiana and New Jersey; rural Georgia; and the municipalities of Detroit, MI; Seattle, WA; and Atlanta, GA. For all incident cancers diagnosed in these areas, the SEER registries collect information on patient demographics, tumor characteristics, stage at diagnosis, date of diagnosis, therapy received within four months of diagnosis, and date and cause of death. Through a collaborative project between the National Cancer Institute and the Centers for Medicare and Medicaid Services (CMS), entitlement information and claims data from the Medicare program were linked to the SEER data for cancer patients aged 65 and older. Medicare eligibility could be identified for 93% of SEER patients aged 65 and older. Data from multiple files were used for this study: 1) the Patient Entitlement and Diagnosis File (SEER registry data and Medicare entitlement information); 2) Medicare Provider Analysis and Review file (MEDPAR, hospital inpatient and skilled nursing facility stays); 3) Outpatient Standard Analytic File (hospital outpatient services); 4) Physician/Supplier File (physician and other medical services); and 5) Hospice File.

Study Cohort

Eligible subjects selected from the Patient Entitlement and Diagnosis File included patients who were: 1) diagnosed with stage III B or stage IV lung cancer from 1993 – 2005 (N = 143,515), 2) 67 years or older at the time of diagnosis (N = 113,183), 3) enrolled in Medicare Parts A and B for at least two years prior to death (N = 76,434), and 4) died within two years of diagnosis and had continuous enrollment in Parts A and B until death (N = 69,427). To have completeness of information in the Medicare files of these patients, we excluded those enrolled in an HMO at any time from two years before date of diagnosis through date of death.

Measures

Patient characteristics

Patients' sociodemographic characteristics were obtained from the SEER data and included the following variables: age (67–74, 75–84, ≥85 years), gender (male, female), race/ethnicity (non-Hispanic white, Black, Hispanic, Other), diagnosis year and SEER geographic region. Socioeconomic status was based on whether the patient was eligible for state buy-in coverage provided by the Medicaid program for at least one month during the year of diagnosis. Comorbidity was measured with the Charlson comorbidity score (0, 1, 2, ≥3) using all Medicare claims from the year prior to diagnosis.[9] Survival time after diagnosis was measured in months (<1, 2–3, 4–6, 7–12, 13–18, 19–24). We also included the number of hospitalizations (0, 1, ≥2) in the 13–24 months before diagnosis as an independent variable.

Definition of study variables

HCFA Common Procedure Terminology (CPT) evaluation and management codes 99201 to 99205 (new patient) and 99221 to 99215 (established patient encounters) were used to establish outpatient visits. Individual providers were determined using the Unique Provider Identification Number (UPIN). We examined visits to PCPs and to any provider. PCPs included those in: family medicine, general practice, internal medicine and geriatrics. For female patients, OB/Gyn was included. Any provider was defined as a primary physician or an internal medicine specialist. To avoid overestimation of visits and continuity, we excluded visits that occurred one month prior to the diagnosis of lung cancer. Visits between months −2 to −13 constitute a year prior to diagnosis (herein referred to as the year prior to diagnosis). In some analyses we assessed visits in months −13 to −24 prior to diagnosis.

Provider continuity

We examined visit patterns for PCPs and for any provider separately as a measure of continuity. Visits to a PCP were defined as the total number of PCP visits in the year prior to diagnosis. (0, 1–3, 4–7, >7). Number of PCPs was defined as the number of unique PCPs seen in the year prior to diagnosis. Having more than one PCP was defined as seeing multiple PCPs. Visits to any provider was defined as the total number of visits to any physician in the year prior to diagnosis (0, 1–3, 4–7, >7). Number of any providers seen was defined as the number of unique providers seen in the year prior to diagnosis (unique UPINs). Seeing more than one physician was defined as having multiple providers. We assigned a PCP or a provider to a given patient with whom he/she had the majority of outpatient visits in the year prior to diagnosis of advanced lung cancer. We also used the time exposure method of continuity as defined by Wolinsky et al.[21] To calculate this measure, we expanded the pre-diagnosis period to two years and defined continuity (yes/no) as having visited the same physician twice within any eight months during that time.

Outcomes

Our outcome of interest was medical care during the end of life. We examined hospitalization, ICU use, and chemotherapy use during the last month of life, and hospice use during the last week of life. The first three were considered indicators of potentially aggressive (overtreatment) end of life care and hospice use as appropriate end of life care. The study was approved by the Institutional Review Board of the University of Texas Medical Branch, Galveston, TX. De-identified data provided by SEER-Medicare were analyzed and no prior informed consent was required. The manuscript was approved by SEER-Medicare for anonymity prior to submission for publication.

Statistical Analysis

The chi square test was used to compare end-of-life care by patient characteristics. Multivariate logistic regression analyses were used to assess whether different continuity measures affected end-of-life care (yes/no). Both patient characteristics (including age, gender, race, diagnosis year, geographic region, comorbidity, survival time, number of hospitalizations in the 13–24 months before diagnosis) and continuity measures (having a PCP, number of PCPs, total number of visits to PCP, total number of visits to assigned PCP, time exposure method of continuity) were added to the final model. All analyses were performed with SAS version 9.2 (SAS, Inc., Cary, NC). All reported p-values were two-sided and p<0.05 was considered statistically significant.

Results

Table 1 presents the baseline characteristics of the cohort and medical care measures (hospitalization during the last month of life, ICU use during the last month of life, chemotherapy use during the last month of life, and hospice use during the last week of life) in 69,427 patients diagnosed with advanced lung cancer who were followed for 24 months. Younger patients, males, non-whites and those with low socioeconomic status were more likely to be hospitalized and to receive ICU care during the last month of life. Hospice use was more common in females, non-Hispanic whites and those with higher socioeconomic status. Patients with lower comorbidity scores were less likely to be hospitalized or to receive ICU care.
Table 1

Baseline characteristics and percent of patients experiencing end of life care measures in Medicare patients with advanced lung cancer, 1993–2005.

End of life care measures,% yes
Characteristic3 NHospitalized1 ICU1 Chemotherapy1 Hospice2
All Subjects6942750.413.012.845.6
Age at Diagnosis (yrs)
66–743016953.514.516.644.5
75–843147849.212.511.346.6
> = 85778043.19.43.946.0
Gender
Male3771851.913.814.042.7
Female3170948.512.011.349.1
Race
Non-Hispanic White5845349.612.313.347.1
Black222754.516.39.039.0
Hispanic585452.717.212.242.4
Other289356.318.110.431.6
Low Socioeconomic Status
No5863850.112.413.647.1
Yes1078952.116.28.237.8
Charlson Comorbidity Score
03579548.611.613.346.9
11866351.613.613.246.3
2823751.915.311.843.2
≥3673254.616.310.140.3
Times hospitalized in the 13–24 months before diagnosis
05729750.012.713.245.9
1805451.213.811.245.2
>2407653.816.110.342.2
Survival time (months)
0–11544545.213.14.326.1
2–31905259.616.014.046.6
4–61337348.811.716.651.9
7–121330448.011.015.954.3
13–18575546.211.315.455.8
19–24249843.111.013.456.2
SEER site
Connecticut591650.39.512.938.5
Detroit830857.416.012.151.0
Hawaii114949.911.98.938.1
Iowa660445.66.211.052.0
New Mexico159443.011.710.250.8
Seattle520144.99.012.841.0
Utah125936.19.29.348.8
Atlanta256248.810.516.247.1
Rural Georgia23250.49.916.844.8
Kentucky524849.313.413.251.8
Louisiana403551.910.911.750.6
New Jersey744655.616.917.845.8
California1987350.215.812.141.5
Diagnosis Year
1993339451.48.97.328.3
1994344747.79.58.833.9
1995347250.09.78.533.8
1996344049.810.110.137.5
1997331150.811.411.341.4
1998339747.910.511.943.6
1999325749.311.613.145.7
2000721950.712.414.246.5
2001767550.814.014.947.0
2002773949.914.014.848.9
2003802351.415.414.549.9
2004779450.414.914.352.1
2005725951.715.912.254.1

1  =  use in last month of life.

2  =  use in last week of life. ICU, Intensive Care Unit; SEER, Surveillance, Epidemiology and End Results.

3  = All differences in the four measures of end of life care by characteristics were statistically significant with p<0.0001.

1  =  use in last month of life. 2  =  use in last week of life. ICU, Intensive Care Unit; SEER, Surveillance, Epidemiology and End Results. 3  = All differences in the four measures of end of life care by characteristics were statistically significant with p<0.0001. There was large variation in the receipt of aggressive end-of-life care and hospice care across SEER sites. Relative to other areas, hospitalization was more common in the Detroit metropolitan area; ICU use and chemotherapy use during the last month of life were more common in New Jersey; and hospice use was more common in Iowa. ICU use increased from 8.9% in 1993 to 15.9% in 2005 (p<0.0001). Similarly, hospice use increased from 28.3% in 1993 to 54.1% in 2005 (p<0.0001). Aggressive end-of-life care was more common in patients with shorter survival time. Patients who died within three months of diagnosis of advanced lung cancer were more likely to be hospitalized and receive ICU care during the last month of life. By contrast, hospice use was more common in those with longer survival time: 26.1% in those who survived < 1 month compared to 56.2% in those who survived > 18 months. Table 2 presents the bivariate analyses for several measures of provider continuity and end-of-life care. Seeing a PCP in the year prior to a diagnosis of advanced lung cancer increased the likelihood of hospitalization, ICU care during the last month of life, as well as hospice use during the last week of life. The association between end-of-life care and number of PCPs seen and number of outpatient visits to PCPs was inconsistent.
Table 2

Provider continuity in the year prior to diagnosis of advanced lung cancer and end-of-life care.

End of life care measures,% yes
Continuity MeasureNHospitalized1 ICU1 Chemotherapy1 Hospice2
All Subjects6942750.413.012.845.6
Saw a PCP
No2210647.312.311.141.4
Yes4732151.813.313.647.6
Number of PCPs seen
02210647.312.311.141.4
13328951.613.213.746.9
>11403252.413.713.349.3
Total number of visits to PCP
02210647.312.311.141.4
1–32019350.012.414.048.2
4–71722952.513.013.848.2
>7989954.315.912.345.2
Number of visits to an assigned PCP (N = 47321)
1–32332850.312.514.048.6
4–71644552.413.313.748.0
>7754855.016.312.243.5
Time exposure method continuity of PCP3
No2574547.812.211.542.2
Yes4368251.913.513.647.6
Saw any provider
No1330043.310.89.239.7
Yes5612752.113.513.647.0
Number of any provider seen
01330043.310.89.239.7
12188050.512.512.445.4
>13424753.114.214.548.0
Total number of visits to any provider
01330043.310.89.239.7
1–31722648.911.813.147.1
4–71872851.712.613.748.4
>72017355.015.914.045.7
Number of Visits to a assigned provider (N = 56127)
1–32532549.812.113.748.3
4–72087553.013.713.947.6
>7992755.916.712.842.7
Time exposure method continuity of any provider3
No1672744.410.910.240.8
Yes5270052.313.713.647.1

1  =  in last month of life.

2  =  in last week of life.

ICU, intensive care unit; PCP, primary care physician.

3 = Time exposure method of continuity is defined as having visited the same physician twice within any eight months over the two years prior to the diagnosis of lung cancer

1  =  in last month of life. 2  =  in last week of life. ICU, intensive care unit; PCP, primary care physician. 3 = Time exposure method of continuity is defined as having visited the same physician twice within any eight months over the two years prior to the diagnosis of lung cancer Table 3 shows the results of multivariable analyses of the association between provider continuity and end-of-life care measures. Seeing a PCP or any provider and having continuity with a PCP or any provider was associated with increased risk of hospitalization, ICU use and chemotherapy use during the last month of life, as well as hospice use during the last week of life. The odds of hospitalization and ICU use in the last month of life increased stepwise with an increase in number of visits. For example patients with 1–3, 4–7 or >7 visits to their PCP in the year prior to the diagnosis of lung cancer had 1.0 (reference), 1.08 (95% CI; 1.04–1.13), and 1.14 (95% CI; 1.08–1.19) odds of hospitalization during the last month of life, respectively. The results were similar for analyses limited to patients with an identifiable PCP. There was no clear association with hospice use during the last week of life, except for higher odds in patients with outpatient visits to multiple PCPs compared to those whose visits were all to the same PCP. Patients who made more visits (≥7) to their assigned PCP had 0.91 (0.86–0.96) lower odds of hospice use during the last week of life. There was no difference in end-of-life care measures using the time exposure method.
Table 3

Multivariable analyses of the associations between provider continuity measures and end-of-life care.

End of life care measures
Hospitalized1 OR (95% CI)ICU1 OR (95% CI)Chemotherapy1 OR (95% CI)Hospice2 OR (95% CI)
PCP
Saw a PCP
No 0.82 (0.79,0.84) 0.88 (0.84,0.93) 0.77 (0.73,0.81) 0.84 (0.82,0.87)
Yesrefrefrefref
Number of PCPs seen
0 0.82 (0.80,0.85) 0.89 (0.84,0.94) 0.77 (0.72,0.81) 0.87 (0.84,0.90)
1refrefrefref
> 11.04 (1.00,1.08)1.03 (0.97,1.10)1.00 (0.94,1.06) 1.10 (1.06,1.15)
Total visits to PCP
0 0.86 (0.83,0.89) 0.91 (0.85,0.96) 0.78 (0.73,0.82) 0.85 (0.81,0.88)
1–3refrefrefref
4–7 1.08 (1.04,1.13) 0.99 (0.93,1.06)1.03 (0.97,1.10)1.02 (0.97,1.06)
>7 1.14 (1.08,1.19) 1.15 (1.07,1.24) 1.01 (0.94,1.10)0.97 (0.92,1.02)
Number of visits to assigned PCP
1–3refrefrefref
4–7 1.07 (1.03,1.12) 1.01 (0.95,1.07)1.05 (0.99,1.11)1.00 (0.96,1.05)
>7 1.16 (1.09,1.22) 1.17 (1.08,1.26) 1.02 (0.94,1.12) 0.91 (0.86,0.96)
Time exposure method continuity of PCP3
No0.92 (0.83,1.02)0.93 (0.79,1.09)1.09 (0.94,1.26)0.94 (0.84,1.04)
Yesrefrefrefref
Any Provider
Saw any provider
No 0.68 (0.65,0.71) 0.77 (0.72,0.82) 0.61 (0.57,0.66) 0.8 (0.76,0.83)
Yesrefrefrefref
Number of any providers seen
0 0.72 (0.68,0.75) 0.81 (0.75,0.86) 0.67 (0.62,0.72) 0.83 (0.79,0.87)
1refrefrefref
> 1 1.1 (1.07,1.14) 1.09 (1.04,1.15) 1.18 (1.12,1.24) 1.09 (1.05,1.13)
Total visits to any provider
0 0.75 (0.71,0.78) 0.83 (0.77,0.89) 0.67 (0.62,0.72) 0.81 (0.77,0.85)
1–3refrefrefref
4–7 1.12 (1.07,1.17) 1.04 (0.98,1.11) 1.10 (1.04,1.18) 1.06 (1.02,1.11)
>7 1.26 (1.21,1.32) 1.24 (1.16,1.32) 1.23 (1.15,1.32) 1.01 (0.96,1.05)
Number of visits to assigned provider
1–3refrefrefref
4–7 1.13 (1.09,1.18) 1.08 (1.02,1.15) 1.1 (1.04,1.16) 1 (0.96,1.04)
>7 1.25 (1.19,1.31) 1.26 (1.17,1.35) 1.12 (1.04,1.2) 0.89 (0.84,0.93)
Time exposure method continuity of any provider3
No0.92 (0.83,1.02)0.88 (0.74,1.05)0.97 (0.84,1.14) 0.86 (0.77,0.96)
Yesrefrefrefref

ICU, intensive care unit; PCP, primary care physician; OR, odds ratio. CI, confidence interval. All models adjusted for age at diagnosis, gender, race, low socioeconomic status, SEER site, diagnosis year, survival time, Charlson comorbidity score and number of times hospitalized in the 13–24 months prior to diagnosis. Bolded values indicate p < 0.05.

3 = Time exposure method of continuity is defined as having visited the same physician twice within any eight months over the two years prior to the diagnosis of lung cancer

ICU, intensive care unit; PCP, primary care physician; OR, odds ratio. CI, confidence interval. All models adjusted for age at diagnosis, gender, race, low socioeconomic status, SEER site, diagnosis year, survival time, Charlson comorbidity score and number of times hospitalized in the 13–24 months prior to diagnosis. Bolded values indicate p < 0.05. 3 = Time exposure method of continuity is defined as having visited the same physician twice within any eight months over the two years prior to the diagnosis of lung cancer One potential confounder in analysis of pre-diagnosis continuity of care with post-diagnosis care is that earlier provider visits, precipitated by symptoms of the yet-undiagnosed cancer, may affect the estimation of true continuity of care. To address that possibility, we repeated all analyses using measures of provider visits generated in the period 13–24 months prior to the diagnosis of advanced lung cancer. Those analyses produced very similar results to those shown for the analysis using the 2–13 months prior to diagnosis.

Discussion

Prior studies on continuity and end-of-life care in patients with cancer have focused on patient-provider patterns following cancer diagnosis.[18]–[20]; [22]–[24] Continuity of care after diagnosis seems to matter. However, whether the continuity established prior to diagnosis of advanced lung cancer has an effect on end-of-life medical care is unknown. We examined associations between several measures of provider continuity prior to the diagnosis and medical care received during end of life. Provider continuity in the year prior to the diagnosis of advanced lung cancer was not substantially associated with less aggressive medical care during end-of-life care. However, survival time had a significant effect on end-of-life care. Patients with shorter survival were more likely to receive aggressive care whereas those with longer survival were likely to receive hospice care at the end of life. Long term survivors likely represent individuals with lung cancer sensitive to the standard initial chemotherapy and radiotherapy. These individuals are unlikely to benefit from additional treatment later in the course of their disease; thus, they are more likely to opt for hospice care. Moreover, longer survivors also had more time to cope with their terminal illness and perhaps are better prepared for end of life. Hospice care focuses on palliative care and symptom management rather than disease treatment. Our study showed both aggressive and palliative care increased over time, similar to prior reports [20]; [25]. Patients are choosing both types of care, rather than one or the other, regardless of provider continuity. These results are similar to a Kronman et al. study which showed no clear effect of PCP visits on hospice care.[26] A recent randomized control trial showed that patients with advanced lung cancer who received early palliative care consultation in addition to standard treatment were less likely to receive aggressive care during end of life and lived 2.6 months longer than those who received standard treatment alone [27]. The benefits seen in this study likely arise from better understanding of their disease process and more time to declare their end of life choices. Our findings are consistent with the study by Kronman et al. of decedent Medicare beneficiaries; compared to patients with no PCP visits during the 7–18 months prior to death, those with ≥9 PCP visits were hospitalized more frequently (0.9 versus 1.3 admissions), but they averaged 1.9 fewer days in the hospital during the last 6 months of life.[26] We did not examine the total number of days spent in the hospital, but whether patients had any hospital or ICU stay during the last month of life. Inherent to any continuity of care measure, whether based on visit pattern or indices, is the assumption that higher continuity of care leads to greater patient-physician trust. End-of-life decisions are often based on value, preferences and trust between patient and provider. A recent mixed method study of cancer patients showed that “experiencing continuity” involves receiving consistent time and attention, knowing future expectations, managing family consequences, coping between service contacts and believing that nothing has been overlooked.[28] Higher “experienced continuity” is associated with lower care needs. These aspects of continuity are not captured in claims data. Our study has several limitations. Information on patient preferences and appropriateness of clinical care is not available in claims data. These findings are limited to fee-for-service Medicare beneficiaries and are not generalizable to other populations. A patient's preferences change following diagnosis of a terminal illness and during the course of his or her disease. Moreover, a recently-diagnosed cancer patient tends to see several new providers in multiple care settings. Our study is limited to advanced lung cancer patients with generally poor survival and the results may not be applicable to patient diagnosed with other cancers. Lack of detailed information on patient's medical and social status in claims data may have added unmeasured confounding and potential explanation for lack of association between prior continuity and end of life care. In conclusion, our study showed no consistent association between provider continuity prior to diagnosis of advanced lung cancer and end of life care. Continuity did not substantially reduce potentially inappropriate or increase potentially appropriate care during end of life.
  26 in total

1.  A longitudinal examination of continuity of care and avoidable hospitalization: evidence from a universal coverage health care system.

Authors:  Shou-Hsia Cheng; Chi-Chen Chen; Yen-Fei Hou
Journal:  Arch Intern Med       Date:  2010-10-11

2.  Can primary care visits reduce hospital utilization among Medicare beneficiaries at the end of life?

Authors:  Andrea C Kronman; Arlene S Ash; Karen M Freund; Amresh Hanchate; Ezekiel J Emanuel
Journal:  J Gen Intern Med       Date:  2008-05-28       Impact factor: 5.128

3.  Continuity of care with a primary care physician and mortality in older adults.

Authors:  Fredric D Wolinsky; Suzanne E Bentler; Li Liu; John F Geweke; Elizabeth A Cook; Maksym Obrizan; Elizabeth A Chrischilles; Kara B Wright; Michael P Jones; Gary E Rosenthal; Robert L Ohsfeldt; Robert B Wallace
Journal:  J Gerontol A Biol Sci Med Sci       Date:  2009-12-08       Impact factor: 6.053

4.  The effect of continuity of care on emergency department use.

Authors:  J M Gill; A G Mainous; M Nsereko
Journal:  Arch Fam Med       Date:  2000-04

5.  Physician visits prior to treatment for clinically localized prostate cancer.

Authors:  Thomas L Jang; Justin E Bekelman; Yihai Liu; Peter B Bach; Ethan M Basch; Elena B Elkin; Michael J Zelefsky; Peter T Scardino; Colin B Begg; Deborah Schrag
Journal:  Arch Intern Med       Date:  2010-03-08

6.  Early palliative care for patients with metastatic non-small-cell lung cancer.

Authors:  Jennifer S Temel; Joseph A Greer; Alona Muzikansky; Emily R Gallagher; Sonal Admane; Vicki A Jackson; Constance M Dahlin; Craig D Blinderman; Juliet Jacobsen; William F Pirl; J Andrew Billings; Thomas J Lynch
Journal:  N Engl J Med       Date:  2010-08-19       Impact factor: 91.245

7.  Multiple measurement of serum lipids in the elderly.

Authors:  James S Goodwin; Adib Asrabadi; Bret Howrey; Sharon Giordano; Yong-Fang Kuo
Journal:  Med Care       Date:  2011-02       Impact factor: 2.983

8.  Family physician continuity of care and emergency department use in end-of-life cancer care.

Authors:  Frederick Burge; Beverley Lawson; Grace Johnston
Journal:  Med Care       Date:  2003-08       Impact factor: 2.983

9.  Continuity of care and intensive care unit use at the end of life.

Authors:  Gulshan Sharma; Jean Freeman; Dong Zhang; James S Goodwin
Journal:  Arch Intern Med       Date:  2009-01-12

10.  The patient-physician relationship, primary care attributes, and preventive services.

Authors:  Michael L Parchman; Sandra K Burge
Journal:  Fam Med       Date:  2004-01       Impact factor: 1.756

View more
  1 in total

1.  Primary care physician continuity, survival, and end-of-life care intensity.

Authors:  Peiyin Hung; Laura D Cramer; Craig E Pollack; Cary P Gross; Shi-Yi Wang
Journal:  Health Serv Res       Date:  2021-09-06       Impact factor: 3.734

  1 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.