AVISO IMPORTANTE


A partir del día 14 de junio de 2015, domingo, este blog dejará de ser actualizado como se ha venido haciendo hasta la fecha. La primera idea fue la de cerrar el blog, pero el deseo que que cuanto aquí se ha publicado pueda seguir siendo útil en el futuro, nos hace que mantengamos abierto el blog. Si tuviera alguna duda o quisiera hacer algún comentario, no tema hacerlo: seguiremos publicando cuantos comentarios se hagan y seguiremos contestando a las dudas que puedan surgir.
Gracias y hasta siempre.
Andrés Guerrero Serrano
-Homeópata-

viernes, 7 de noviembre de 2014

Effects of Integrative Medicine on Pain and Anxiety Among Oncology Inpatients

(Extraído de jncimono.oxfordjournals.org)

  1. Jill R. Johnson,
  2. Daniel J. Crespin,
  3. Kristen H. Griffin,
  4. Michael D. Finch and
  5. Jeffery A. Dusek

+Author Affiliations

  1. Affiliations of authors: Integrative Health Research Center, Penny George Institute for Health and Healing, Allina Health, Minneapolis, MN (JRJ, KHG, JAD); Division of Health Policy and Management, University of Minnesota School of Public Health, Minneapolis, MN (DJC); Medical Industry Leadership Institute, Carlson School of Management, University of Minnesota, Minneapolis, MN (MDF).
  1. Correspondence to: Jill R. Johnson, PhD, MPH, Penny George Institute for Health and Healing, 800 East 28th Street, MR 33540, Minneapolis, MN 55407-3799 (e-mail:Jill.Johnson3@allina.com)

Next Section

Abstract

Background Few studies have investigated the effectiveness of integrative medicine (IM) therapies on pain and anxiety among oncology inpatients.

Methods Retrospective data obtained from electronic medical records identified patients with an oncology International Classification of Diseases-9 code who were admitted to a large Midwestern hospital between July 1, 2009 and December 31, 2012. Outcomes were change in patient-reported pain and anxiety, rated before and after individual IM treatment sessions, using a numeric scale (0–10).

Results Of 10948 hospital admissions over the study period, 1833 (17%) included IM therapy. Older patients had reduced odds of receiving any IM therapy (odds ratio [OR]: 0.97, 95% confidence interval [95% CI] = 0.96 to 0.98) and females had 63% (OR: 1.63, 95% CI = 1.38 to 1.92) higher odds of receiving any IM therapy compared with males. Moderate (OR: 1.97, 95% CI = 1.61 to 2.41), major (OR: 3.54, 95% CI = 2.88 to 4.35), and extreme (OR: 5.96, 95% CI = 4.71 to 7.56) illness severity were significantly associated with higher odds of receiving IM therapy compared with admissions of minor illness severity. After receiving IM therapy, patients averaged a 46.9% (95% CI = 45.1% to 48.6%, P <.001) reduction in pain and a 56.1% (95% CI = 54.3% to 58.0%, P <.001) reduction in anxiety. Bodywork and traditional Chinese Medicine therapies were most effective for reducing pain, while no significant differences among therapies for reducing anxiety were observed.

Conclusions IM services to oncology inpatients resulted in substantial decreases in pain and anxiety. Observational studies using electronic medical records provide unique information about real-world utilization of IM. Future studies are warranted and should explore potential synergy of opioid analgesics and IM therapy for pain control.

Pain is a common, often debilitating symptom of cancer and a side effect of cancer treatment, affecting more than 50% of cancer patients (1,2). Consequentially, pain management plays a central role in cancer treatment (1). In addition to pain, ~13%–79% of oncology patients suffer from anxiety symptoms (3), although the relationship between pain and anxiety is complex and not yet well understood (4). Undertreatment of cancer-related pain is a major challenge for health-care providers, with nearly one in two patients with cancer pain being undertreated (5). At the same time, however, overuse of opioid analgesics in cancer treatment can lead to opioid tolerance or dependence and side effects such as nausea and constipation (6). Despite ongoing improvements in cancer care (7), pain management is an area with room for improvement.

Complementary and alternative medicine therapies have been used among cancer patients for decades, and the growing use of these therapies across the prevention and treatment spectrum is well documented (8,9). Prevalence of complementary and alternative medicine use among adult cancer patients in the United States has been estimated at 40.5% (10). The establishment of integrative oncology programs at major cancer centers (11) underscores the increasing acceptance of integrative approaches across both outpatient and inpatient populations.

The evidence base for integrative oncology among inpatients is comprised predominantly of small randomized controlled trials conducted over the past three decades, in which pain reduction has been reported (12–20). A larger, 2004 observational study of massage therapy showed reductions in pain and other symptoms, but this study was comprised of both oncology inpatients and outpatients (21). In 2010, Dusek et al. (22) reported a 55.8% average reduction in pain with integrative medicine (IM) use across 1837 inpatients based on a retrospective medical record review, but results for oncology patients were not separately analyzed. In the current study, we evaluate the effectiveness of various integrative medicine therapies for pain and anxiety, focusing specifically on a large, inpatient oncology population. To our knowledge, this study is the first in which multiple IM therapies are studied among oncology inpatients to treat pain and anxiety.

Previous SectionNext Section

Materials and methods

Study Design and Setting

This retrospective, observational study of oncology inpatients was conducted at Abbott Northwestern Hospital, a 630-bed teaching and specialty hospital in Minneapolis, MN. The Penny George Institute for Health and Healing at Abbott Northwestern offers hospitalized patients, through physician and nurse referrals, a wide array of integrative health services for pain relief, anxiety reduction, and healing at no charge (23).

Study Population

All oncology inpatients aged 18 years or older at Abbott Northwestern Hospital, who were admitted between July 1, 2009 and December 31, 2012, were included in the study population. We excluded patients who were seen as outpatients, in the emergency room, and who were in the hospital solely for observation. Electronic medical record (EMR) data were obtained on all eligible inpatients and oncology patients were retrospectively identified using EMR (Epic, Verona, WI). All patients whose data were obtained had provided written permission upon admission to Abbott Northwestern Hospital for their medical records to be used for general research purposes.

The study population included patients with primary malignant neoplasms identified using International Classification of Diseases, 9th Revision, Clinical Modification diagnosis codes (140.0–209.79). Any hospital admission that had at least one of these International Classification of Diseases-9 codes as a primary or secondary diagnosis was eligible for the study.

We created nonmutually exclusive indicators pertaining to primary malignancy site: female breast (174–174.9); bronchus, lung, and trachea (162.0, 162.2–162.5, 162.8–162.9, 209.21); colorectal (153–154, 209.10, 209.17); hematopoietic and lymph (200.0–208.92); and prostate (185). Patients of all other primary malignancies were grouped into an “other” cancer site category. Inpatients with benign neoplasms (210–229), carcinomas in situ (230–234), and neoplasms of uncertain behavior (235–238) or unspecified nature (239) were excluded.

The study was approved by the Institutional Review Board of Allina Health with a waiver of informed consent.

Measurements
Demographic and Hospital Admission Characteristics.

Data extracted from the EMR included patients’ ages at time of hospital admission, sex, race, marital status, and health insurance status. Our data included the All Patient Refined Diagnostic Related Groups (24) severity of illness measures calculated from patients’ diagnoses codes. The measure includes four categories of severity: 1) minor, 2) moderate, 3) major, and 4) extreme. Data pertaining to each IM session were routinely documented within the EMR.

IM Therapies.

IM practitioners used their clinical judgment to provide therapies, within their scope of practice, they deemed necessary and therapeutic for each patient, after consulting with the patient. Many patients received IM therapy multiple times throughout a hospital admission. We use the term “session” to define each unique administration of IM therapy, distinguished by time of procedure, within a hospital admission. For the present analysis, IM therapies were placed into one of three broad categories: bodywork, which included craniosacral therapy, medical massage, and reflexology; mind-body and energy therapies (MBE), which was divided into separate mind-body and energy subcategories; and traditional Chinese medicine, which included acupressure, acupuncture, and Korean hand therapy. Also, patients could receive therapy from more than one category during each session, which we define as combination therapies. We coded the presence or absence of each of these IM therapies at each session such that bodywork, MBE, traditional Chinese medicine, and any combination of these therapies were mutually exclusive.

Pain and Anxiety Scores.

For patients who received IM services, practitioners collected patients’ self-reported pain and anxiety scores directly before and after each IM session. Practitioners use standard procedures to request patients to indicate the level of pain they were currently experiencing on an 11-point numeric rating scale where 0 was defined as “no pain” and 10 was defined as “worst pain imaginable.” Similarly, practitioners recorded anxiety scores using the same methodology, where 0 was “no anxiety” and 10 was “worst anxiety imaginable.” The primary endpoints were change in pain and anxiety scores, calculated by subtracting the prescore from the postscore.

Analytic Dataset

We identified 11078 oncology-related hospital admissions in the EMR. We removed 20 hospital admissions due to missing demographic data (six admissions) or inability to determine severity of illness (14 admissions). Additionally, we excluded 110 hospital admissions because we were unable to classify their health insurance status as commercial, Medicare, or Medicaid (only nine of these 110 admissions received IM therapy), resulting in 10948 oncology admissions from 7727 unique patients. Of the 10948 admissions, 1833 (17%) had 4517 IM therapy sessions (an average of 2.46 per admission). In many cases, practitioners were unable to collect pre- or post-pain and anxiety scores or the patient reported no pain or anxiety. Only patients who reported both pre- and post-pain or pre- and post-anxiety scores were included in the subsequent analyses.

Because we observed IM therapy at the hospital admission level, but pain and anxiety scores were assessed at the IM session level, we randomly selected one session from each remaining hospital admission to keep the level of analysis consistent between the selection and score change equations (see below). Thus, we dropped all hospital admissions with only missing scores or only pre-pain or -anxiety scores equal to zero. This method produced a sample of 9998 hospital admissions for the pain model, of which 883 (9%) had IM therapy, and 9771 admissions for the anxiety model, of which 656 (7%) had IM therapy.

Statistical Analysis
IM Therapy Utilization.

Logistic regression was used to predict the probability of receiving any IM therapy during a hospital admission as a function of patient demographics, cancer site, severity, and health insurance status, and we present the odds ratios (ORs) for each covariate. A P value of less than .05 was used to signify statistically significant differences. To correct for serial correlation among patients with multiple hospital admissions, we clustered standard errors by patient. The goodness-of-fit of our model was tested using a Hosmer–Lemeshow test (25) as well as calculating the percent of admissions correctly classified by the model.

Pain and Anxiety.

To determine if IM therapies were associated with reductions in pain and anxiety, we first conducted paired t tests using the null hypothesis that the pre- and post-pain or anxiety scores were equal.

Second, multivariate regression was used to estimate reductions in pain and anxiety during IM sessions. Because patients receiving IM therapy may systematically differ from the general sample of oncology patients, an ordinary least squares model could produce bias parameters when generalizing results. To address this bias, we used a Heckman selection model (26) to account for selection into the sample of IM therapy recipients.

To correctly identify the parameters that affect pain and anxiety, at least one variable in the selection-equation (ie, utilization of IM therapy) should be specified which predicts IM therapy use, but does not affect changes in pain or anxiety. We expected marital status and health insurance status to fit this criterion. Therefore, our model predicted selection into the sample of IM sessions using all patient demographic, cancer site, severity variables (the same set of covariates as our logistic regression predicting IM therapy use). Changes in pain and anxiety scores were estimated using cancer site, age, sex, race, severity, and the inverse Mills ratio calculated from the selection-equation to control for selection. Additionally, we estimated a second model, which included IM therapy categories, to determine if differential effects between the categories existed. As above, to correct for serial correlation among patients with multiple observations, we clustered standard errors by patient.

We conducted all analyses in Stata Version 13 (StataCorp LP, College Station, TX).

Previous SectionNext Section

Results

Descriptive Statistics

Of the 10948 hospital admissions over the study period, 1833 (17%) included IM therapy (Table 1). The mean age of inpatients utilizing IM therapies (59.0 years) was nearly 6 years younger than inpatients not utilizing IM therapies (64.9 years). Women accounted for the majority of both IM and non-IM hospital admissions; however, admissions with IM services had a higher proportion of female patients, 64%, than non-IM admissions, 56%. The distributions of cancer sites were similar across IM and non-IM hospital admissions, although IM hospital admissions were comprised of patients with statistically significant higher illness severity. A total of 4517 IM therapy sessions were administered for an average of 2.46 sessions per hospital admission (Table 2). Bodywork comprised 54.8% compared with 13.0% for MBE, 9.7% for traditional Chinese medicine, and 22.6% for combination therapies.

View this table:

Table 1.

Abbott Northwestern oncology inpatient characteristics (n = 10948)*

View this table:

Table 2.

Distribution of integrative medicine (IM) sessions by treatment type and cancer site*

IM Therapy Utilization Analysis

Similar to our descriptive statistics, older patients had reduced odds of receiving any IM therapy in our logistic regression model (Table 3). Females had 63% (OR: 1.63, 95% confidence interval [CI] = 1.38 to 1.92, P<.001) higher odds of receiving any IM therapy during a hospital admission compared with males. We found that moderate (OR: 1.97, 95% CI = 1.61 to 2.41, P <.001), major (OR: 3.54, 95% CI = 2.88 to 4.35, P<.001), and extreme (OR: 5.96, 95% CI = 4.71 to 7.56, P <.001) illness severity were all significantly associated with higher odds of receiving IM therapy compared with patients with hospital admissions of minor illness severity.

View this table:

Table 3.

Odds ratio (OR) for integrative medicine (IM) use among oncology inpatients*

The P value from a Hosmer–Lemeshow test was .54, indicating a good fit. The model correctly classified 83% of hospital admissions as receiving IM or not receiving IM. Although this result was driven by the model’s under-prediction of IM hospital admissions and the large proportion of non-IM hospital admissions, we found a significant difference (P <.001) in the predicted probability of receiving IM therapy between IM hospitals admissions (P = .23) and non-IM hospital admissions (P = .16).

Pain and Anxiety Analysis

Sessions with IM therapy had, on average, a 46.9% (95% CI = 45.1 to 48.6%, P value <.001) decrease in pain score (Table 4). Anxiety scores decreased by an average of 56.1% (95% CI = 54.3% to 58.0%, P <.001) after the administration of IM therapies (Table 4).

View this table:

Table 4.

Pre- to postintegrative medicine (IM) therapy percent decrease in pain and anxiety scores by cancer site and therapy type*

For a male with mean age (63.9), mean inverse Mills ratio (1.91), and the modal value of all categorical variables (ie, white, “other” cancer, and moderate severity), our model predicts that IM therapy is associated with a 2.00 (95% CI = 1.71 to 2.30, P <.001) point reduction in pain (base model;Table 5). This result represents a 42.9% (95% CI = 36.7% to 29.4%, P<.001) decrease in pain for a male with the mean pain prescore (4.66). For a female with the same admission attributes, IM therapy was associated with a 39.9% (95% CI = 34.3%–45.5%, P <.001) reduction in pain.

View this table:

Table 5.

Predicted change in pain and anxiety scores*

When IM therapy categories were included in the regression analysis, we found bodywork therapy was 18.2 percentage points (95% CI = 11.4% to 25.3%, P <.001) more effective than MBE therapy and 6.9 percentage points (95% CI = 1.5% to 25.3%, P = .012) more effective than combination therapy at the mean pre-pain score. Additionally, we found traditional Chinese medicine was 14.3 percentage points (95% CI = 1.0% to 27.6%, P= .033) and combination therapy was 11.3 percentage points (95% CI = 3.8% to 18.9%, P = .003) more effective than MBE. The inverse Mills ratio had an insignificant effect on pain, suggesting that selection bias was not present.

We predicted a 1.63 (95% CI = 0.92 to 2.33, P <.001) point decrease (Table 5) or a 30.1% (95% CI = 17.3% to 43.7%, P <.001) reduction in anxiety score for a male with mean age (63.9), mean inverse Mills ratio (2.08), and the modal value of all categorical variables with the mean anxiety prescore (5.33). For females, IM therapy was associated with a 57.4% (95% CI = 48.8% to 66.0%, P <.001) reduction in anxiety. We found no significant difference by IM therapy type. The coefficient of the inverse Mills ratio was significant and suggests that a patient who selected into IM therapy received, on average, a greater reduction in anxiety from IM therapy than the expected anxiety reduction for a patient drawn at random from the full population of oncology patients.

Previous SectionNext Section

Discussion

This retrospective study using standardly collected EMR data is one of the first to comprehensively assess the effects of IM therapies on pain and anxiety among oncology inpatients. Older patients had reduced odds of receiving any IM therapy and females had higher odds of receiving any IM therapy compared with males. Moderate, major, and extreme illness severity were all significantly associated with higher odds of receiving IM therapy compared with hospital admissions of minor illness severity. Overall, IM sessions resulted in an average 46.9% reduction in pain and an average 56.1% reduction in anxiety.

Few observational effectiveness studies of IM for cancer inpatients have been reported, yet real-world data is important for better understanding the effectiveness of integrative therapies for cancer inpatients (27,28). Our results are generally consistent with previous studies involving oncology inpatients, including significantly reduced pain (12–21) and anxiety (19,29); however, the observational design of this study distinguishes it from previous studies [excepting Cassileth and Vickers (21)]. Cancer populations are diverse in many ways, including comorbidities and complex treatment regimens (28). Comparative effectiveness research is appropriate for integrative oncology due to the inclusiveness, wide-ranging outcomes, and decision-making potential of this research approach (28). Furthermore, effectiveness research has been emphasized as beneficial for conducting economic evaluations of complementary and alternative medicine (30). Pain management is a costly part of oncology care; cost analysis of IM, particularly for inpatients, is an area in need of more targeted research.

An important strength of this study over prior investigations is its focus on a large inpatient oncology population. Inpatient complementary and alternative medicine research in oncology populations has mostly involved small sample sizes (12–20,29), with the exception of Cassileth and Vickers’ analysis of 961 cancer inpatients receiving massage therapy (21). An additional strength of this study is our use of a Heckman selection model to adjust for any nonrandom selection of whether patients received IM therapy. As a result of this adjustment, our results are generalizable to oncology patients at Abbott Northwestern Hospital. However, these results may not necessarily generalize to other hospital settings. Finally, the large amount of data extracted from EMRs allowed us to perform a comprehensive analysis including multiple cancer sites, IM therapies, and outcome measures. To date, previous investigations had been far more limited in scope.

Some limitations are present in this study. First, we did not investigate the effect opioid analgesics may have had on self-reported pain and anxiety scores. It is possible that our findings overestimate the beneficial effects of IM on pain and anxiety. Future research should include patient use of opioid analgesics and account for time of use in relation to integrative therapies. Second, the EMR data extract from which this analysis was performed did not include specific information on cancer or cancer treatment, which may directly affect pain and anxiety levels. Analyses which account for parameters such as cancer stage, presence of metastases, and treatment type(s) should be considered. Third, our results reflect short-term changes in pain and anxiety; a fuller understanding on the long-term effects of IM on pain and anxiety awaits further research. Finally, since these are self-reported pain and anxiety scores collected by IM practitioners, the potential exists for bias in these scores.

In conclusion, this study provided a unique opportunity to describe and investigate the effectiveness of delivering IM therapy to oncology inpatients. Our results provide evidence that IM therapies substantially reduce both short-term pain and anxiety among oncology inpatients. Observational studies using EMR provide unique information about real-world utilization of IM. Additional investigations into the cost effectiveness of IM therapy for oncology inpatients must be considered.

Previous SectionNext Section

Funding

National Center for Complementary & Alternative Medicine of the National Institutes of Health (grant number R01 AT006518 to JAD); George Family Foundation; the Abbott Northwestern Hospital Foundation; the American Massage Therapy Association.

Previous SectionNext Section

Notes

The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health.

  • © The Author 2014. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

Previous Section

References

  1. 1.
    1. Kumar SP
    . Cancer pain: a critical review of mechanism-based classification and physical therapy management in palliative care. Indian J Palliat Care.2011;17(2):116–126.

    CrossRefMedlineGoogle Scholar

  2. 2.
    1. van den Beuken-van Everdingen MH,
    2. de Rijke JM,
    3. Kessels AG,
    4. Schouten HC,
    5. van Kleef M,
    6. Patijn J
    . Prevalence of pain in patients with cancer: a systematic review of the past 40 years. Ann Oncol. 2007;18(9):1437–1449.

    Abstract/FREE Full Text

  3. 3.
    1. Solano JP,
    2. Gomes B,
    3. Higginson IJ
    . A comparison of symptom prevalence in far advanced cancer, AIDS, heart disease, chronic obstructive pulmonary disease and renal disease. J Pain Symptom Manage. 2006;31(1):58–69.

    CrossRefMedlineWeb of ScienceGoogle Scholar

  4. 4.
    1. Kolva E,
    2. Rosenfeld B,
    3. Pessin H,
    4. Breitbart W,
    5. Brescia R
    . Anxiety in terminally ill cancer patients. J Pain Symptom Manage. 2011;42(5):691–701.

    CrossRefMedlineWeb of ScienceGoogle Scholar

  5. 5.
    1. Deandrea S,
    2. Montanari M,
    3. Moja L,
    4. Apolone G
    . Prevalence of undertreatment in cancer pain. A review of published literature. Ann Oncol. 2008;19(12):1985–1991.

    Abstract/FREE Full Text

  6. 6.
    1. Cady J
    . Understanding opioid tolerance in cancer pain. Oncol Nurs Forum.2001;28(10):1561–8; quiz 1569.

    MedlineGoogle Scholar

  7. 7.
    1. Shih YC,
    2. Ganz PA,
    3. Aberle D,
    4. et al.
    Delivering high-quality and affordable care throughout the cancer care continuum. J Clin Oncol. 2013;31(32):4151–4157.

    Abstract/FREE Full Text

  8. 8.
    1. Barnes P,
    2. Bloom B,
    3. Nahin R
    . Complementary and Alternative Medicine Use Among Adults and Children: United States, 2007. Hyattsville, MD: National Center for Health Statistics; 2008.

    Google Scholar

  9. 9.
    1. Eisenberg DM,
    2. Davis RB,
    3. Ettner SL,
    4. et al.
    Trends in alternative medicine use in the United States, 1990-1997: results of a follow-up national survey. JAMA.1998;280(18):1569–1575.

    CrossRefMedlineWeb of ScienceGoogle Scholar

  10. 10.
    1. Saydah SH,
    2. Eberhardt MS
    . Use of complementary and alternative medicine among adults with chronic diseases: United States 2002. J Altern Complement Med.2006;12(8):805–812.

    CrossRefMedlineWeb of ScienceGoogle Scholar

  11. 11.
    1. Seely DM,
    2. Weeks LC,
    3. Young S
    . A systematic review of integrative oncology programs. Curr Oncol. 2012;19(6):e436–e461.

    MedlineGoogle Scholar

  12. 12.
    1. Weinrich SP,
    2. Weinrich MC
    . The effect of massage on pain in cancer patients.Appl Nurs Res. 1990;3(4):140–145.

    CrossRefMedlineGoogle Scholar

  13. 13.
    1. Syrjala KL,
    2. Donaldson GW,
    3. Davis MW,
    4. Kippes ME,
    5. Carr JE
    . Relaxation and imagery and cognitive-behavioral training reduce pain during cancer treatment: a controlled clinical trial. Pain. 1995;63(2):189–198.

    CrossRefMedlineWeb of ScienceGoogle Scholar

  14. 14.
    1. Grealish L,
    2. Lomasney A,
    3. Whiteman B
    . Foot massage. A nursing intervention to modify the distressing symptoms of pain and nausea in patients hospitalized with cancer. Cancer Nurs. 2000;23(3):237–243.

    CrossRefMedlineWeb of ScienceGoogle Scholar

  15. 15.
    1. Smith MC,
    2. Kemp J,
    3. Hemphill L,
    4. Vojir CP
    . Outcomes of therapeutic massage for hospitalized cancer patients. J Nurs Scholarsh. 2002;34(3):257–262.

    CrossRefMedlineWeb of ScienceGoogle Scholar

  16. 16.
    1. Olson K,
    2. Hanson J,
    3. Michaud M
    . A phase II trial of Reiki for the management of pain in advanced cancer patients. J Pain Symptom Manage. 2003;26(5):990–997.

    CrossRefMedlineWeb of ScienceGoogle Scholar

  17. 17.
    1. Mehling WE,
    2. Jacobs B,
    3. Acree M,
    4. et al.
    Symptom management with massage and acupuncture in postoperative cancer patients: a randomized controlled trial. J Pain Symptom Manage. 2007;33(3):258–266.

    CrossRefMedlineWeb of ScienceGoogle Scholar

  18. 18.
    1. Currin J,
    2. Meister EA
    . A hospital-based intervention using massage to reduce distress among oncology patients. Cancer Nurs. 2008;31(3):214–221.

    CrossRefMedlineWeb of ScienceGoogle Scholar

  19. 19.
    1. Jane SW,
    2. Wilkie DJ,
    3. Gallucci BB,
    4. Beaton RD,
    5. Huang HY
    . Effects of a full-body massage on pain intensity, anxiety, and physiological relaxation in Taiwanese patients with metastatic bone pain: a pilot study. J Pain Symptom Manage.2009;37(4):754–763.

    CrossRefMedlineWeb of ScienceGoogle Scholar

  20. 20.
    1. Kligler B,
    2. Homel P,
    3. Harrison LB,
    4. et al.
    Impact of the Urban Zen Initiative on patients’ experience of admission to an inpatient oncology floor: a mixed-methods analysis. J Altern Complement Med. 2011;17(8):729–734.

    CrossRefMedlineGoogle Scholar

  21. 21.
    1. Cassileth BR,
    2. Vickers AJ
    . Massage therapy for symptom control: outcome study at a major cancer center. J Pain Symptom Manage. 2004;28(3):244–249.

    CrossRefMedlineWeb of ScienceGoogle Scholar

  22. 22.
    1. Dusek JA,
    2. Finch M,
    3. Plotnikoff G,
    4. Knutson L
    ; Penny George Institute for Health and Healing Inpatient Care Team. The impact of integrative medicine on pain management in a tertiary care hospital. J Patient Saf. 2010;6(1):48–51.

    CrossRefMedlineGoogle Scholar

  23. 23.
    1. Knutson L,
    2. Johnson PJ,
    3. Sidebottom A,
    4. Fyfe-Johnson A
    . Development of a hospital-based integrative healthcare program. J Nurs Adm. 2013;43(2):101–107.

    CrossRefMedlineGoogle Scholar

  24. 24.

    All Patient Refined Diagnosis Related Groups Vol. 20.0. Wallingford, CT: 3M Health Information Systems; 2003.

  25. 25.
    1. Hosmer D,
    2. Lemeshow S
    . Applied Logistic Regression. New York, NY: Wiley;2000.

    Google Scholar

  26. 26.
    1. Heckman J
    . Sample selection bias as a specification error. Econometrica.1979;47(1):153–161.

    CrossRefWeb of ScienceGoogle Scholar

  27. 27.
    1. Black N
    . Why we need observational studies to evaluate the effectiveness of health care. BMJ. 1996;312(7040):1215–1218.

    FREE Full Text

  28. 28.
    1. Cramer H,
    2. Cohen L,
    3. Dobos G,
    4. Witt CM
    . Integrative oncology: best of both worlds-theoretical, practical, and research issues. Evid Based Complement Alternat Med. 2013;2013:383142. doi:10.1155/2013/383142.

    MedlineGoogle Scholar

  29. 29.
    1. Ahles TA,
    2. Tope DM,
    3. Pinkson B,
    4. et al.
    Massage therapy for patients undergoing autologous bone marrow transplantation. J Pain Symptom Manage.1999;18(3):157–163.

    CrossRefMedlineWeb of ScienceGoogle Scholar

  30. 30.
    1. Coulter ID,
    2. Herman PM,
    3. Nataraj S
    . Economic analysis of complementary, alternative, and integrative medicine: considerations raised by an expert panel. BMC Complement Altern Med. 2013;13:191.

    CrossRefMedlineGoogle Scholar

No hay comentarios:

Publicar un comentario