Skip to main content

Main menu

  • Home
  • Current Issue
  • Content
    • Current Issue
    • Early Access
    • Multimedia
    • Podcast
    • Collections
    • Past Issues
    • Articles by Subject
    • Articles by Type
    • Supplements
    • Plain Language Summaries
    • Calls for Papers
  • Info for
    • Authors
    • Reviewers
    • Job Seekers
    • Media
  • About
    • Annals of Family Medicine
    • Editorial Staff & Boards
    • Sponsoring Organizations
    • Copyrights & Permissions
    • Announcements
  • Engage
    • Engage
    • e-Letters (Comments)
    • Subscribe
    • Podcast
    • E-mail Alerts
    • Journal Club
    • RSS
    • Annals Forum (Archive)
  • Contact
    • Contact Us
  • Careers

User menu

  • My alerts

Search

  • Advanced search
Annals of Family Medicine
  • My alerts
Annals of Family Medicine

Advanced Search

  • Home
  • Current Issue
  • Content
    • Current Issue
    • Early Access
    • Multimedia
    • Podcast
    • Collections
    • Past Issues
    • Articles by Subject
    • Articles by Type
    • Supplements
    • Plain Language Summaries
    • Calls for Papers
  • Info for
    • Authors
    • Reviewers
    • Job Seekers
    • Media
  • About
    • Annals of Family Medicine
    • Editorial Staff & Boards
    • Sponsoring Organizations
    • Copyrights & Permissions
    • Announcements
  • Engage
    • Engage
    • e-Letters (Comments)
    • Subscribe
    • Podcast
    • E-mail Alerts
    • Journal Club
    • RSS
    • Annals Forum (Archive)
  • Contact
    • Contact Us
  • Careers
  • Follow annalsfm on Twitter
  • Visit annalsfm on Facebook
Research ArticleOriginal ResearchA

Changes in Office Visit Use Associated With Electronic Messaging and Telephone Encounters Among Patients With Diabetes in the PCMH

David T. Liss, Robert J. Reid, David Grembowski, Carolyn M. Rutter, Tyler R. Ross and Paul A. Fishman
The Annals of Family Medicine July 2014, 12 (4) 338-343; DOI: https://doi.org/10.1370/afm.1642
David T. Liss
1Division of General Internal Medicine and Geriatrics, Northwestern University Fein-berg School of Medicine, Chicago, Illinois
2Group Health Research Institute, Seattle, Washington
PhD
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
  • For correspondence: david.liss@northwestern.edu
Robert J. Reid
2Group Health Research Institute, Seattle, Washington
3Department of Health Services, University of Washington School of Public Health, Seattle, Washington
MD, PhD
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
David Grembowski
2Group Health Research Institute, Seattle, Washington
3Department of Health Services, University of Washington School of Public Health, Seattle, Washington
PhD
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Carolyn M. Rutter
2Group Health Research Institute, Seattle, Washington
3Department of Health Services, University of Washington School of Public Health, Seattle, Washington
4Department of Biostatistics, University of Washington School of Public Health, Seattle, Washington
PhD
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Tyler R. Ross
2Group Health Research Institute, Seattle, Washington
MA
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Paul A. Fishman
2Group Health Research Institute, Seattle, Washington
3Department of Health Services, University of Washington School of Public Health, Seattle, Washington
PhD
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
  • Article
  • Figures & Data
  • eLetters
  • Info & Metrics
  • PDF
Loading

Abstract

PURPOSE Telephone- and Internet-based communication are increasingly common in primary care, yet there is uncertainty about how these forms of communication affect demand for in-person office visits. We assessed whether use of copay-free secure messaging and telephone encounters was associated with office visit use in a population with diabetes.

METHODS We used an interrupted time series design with a patient-quarter unit of analysis. Secondary data from 2008–2011 spanned 3 periods before, during, and after a patient-centered medical home (PCMH) redesign in an integrated health care delivery system. We used linear regression models to estimate proportional changes in the use of primary care office visits associated with proportional increases in secure messaging and telephone encounters.

RESULTS The study included 18,486 adults with diabetes. The mean quarterly number of primary care contacts increased by 28% between the pre-PCMH baseline and the postimplementation periods, largely driven by increased secure messaging; quarterly office visit use declined by 8%. In adjusted regression analysis, 10% increases in secure message threads and telephone encounters were associated with increases of 1.25% (95% CI, 1.21%–1.29%) and 2.74% (95% CI, 2.70%–2.77%) in office visits, respectively. In an interaction model, proportional increases in secure messaging and telephone encounters remained associated with increased office visit use for all study periods and patient subpopulations (P <.001).

CONCLUSIONS Before and after a medical home redesign, proportional increases in secure messaging and telephone encounters were associated with additional primary care office visits for individuals with diabetes. Our findings provide evidence on how new forms of patient-clinician communication may affect demand for office visits.

  • primary care
  • electronic mail
  • telephone
  • communication
  • office visits
  • family practice
  • health services needs and demand
  • practice redesign
  • utilization
  • practice-based research

INTRODUCTION

Telephone- and Internet-based communication between patients and clinicians is associated with increased access to care,1,2 reduced hospitalizations in the chronically ill,3 and improved control of type 2 diabetes and hypertension in care management interventions.4,5 Besides offering potential clinical benefits, these care modalities do not require patients to incur the time, effort, or cost of traveling to clinicians’ offices,1,2 and the asynchronous nature of electronic messaging allows patients and clinicians to initiate communication at any time.6

For these and other reasons, leaders in American medicine7–10 have recommended that the locus of primary care and chronic care delivery expand beyond traditional office visits to include alternative modes of communication. There is considerable uncertainty, however, about how use of these new care modalities affects demand for traditional office visits.6 Although one early study found that telephone encounters were a substitute for follow-up visits at a Veterans Health Administration clinic,11 a Scottish trial found that telephone encounters for acute issues delayed—but did not preclude the need for—subsequent clinic visits.12 Findings on secure electronic messaging have also varied. While Zhou and colleagues13 found that office visit use decreased after introduction of an online portal at Kaiser Permanente Northwest (secure messaging was one of several portal tools), Palen and colleagues14 found that portal users at Kaiser Permanente Colorado had more office visits than propensity-matched controls during the year after portal registration.

We contribute to the evidence base in this area by examining how patients’ use of primary care office visits is associated with use of secure electronic messaging and telephone encounters in a large health care system that featured these care modalities in a patient-centered medical home (PCMH) redesign.15 Our primary objective in this natural experiment was to assess changes in office visit use associated with secure messaging threads and telephone encounters in a population with chronic illness. Our secondary objective was to investigate whether PCMH implementation or selected patient characteristics modify associations under study.

METHODS

Study Setting

We investigated the impact of secure messaging and telephone encounters on patients’ use of primary care office visits at Group Health, an integrated health plan and care delivery system in the Pacific Northwest. Since launching a secure online patient portal in 2000, Group Health added portal tools and engaged in multiple initiatives that encouraged copay-free secure electronic messaging and telephone encounters (secure electronic messaging began in 2002).16–18 Group Health further emphasized these care modalities during a 2007–2008 PCMH prototype redesign at a clinic,19 where chronically ill patients had 86% more secure message threads and 10% more telephone encounters than patients at other Group Health clinics.20

After the prototype redesign, Group Health implemented a systemwide PCMH redesign.19,21 Group Health staggered the beginning of the redesign across its 26 clinics from January to April 2009; PCMH implementation at each clinic lasted 1 year, followed by the postimplementation period. Secure messaging and telephone encounters were incorporated within overlapping PCMH redesign efforts to improve access, continuity, and follow-up.15,22

Study Design and Population

We used an interrupted time series design23 with a patient-quarter unit of analysis. We included data from January 2008 to December 2011, which encompassed 3 study periods: pre-PCMH baseline (4 quarters), PCMH implementation (4 quarters), and postimplementation (8 quarters). Group Health’s institutional review board approved all study protocols.

The study population included adults aged 18 to 75 years who received care at Group Health’s 26 clinics and had preexisting diabetes mellitus, based on a previously implemented case definition incorporating diagnostic, pharmacy, and laboratory data (Supplemental Appendix).20 We required continuous enrollment at Group Health during the baseline year and the first 2 quarters of PCMH implementation. We excluded patients with preexisting dementia. Individuals were censored from analysis after death, disenrollment from Group Health, or aging out of the 18 to 75 age range.

Measures

Using previously documented methods,21 we extracted automated data on health service use. Monthly primary care use data were rolled up to quarterly counts of office visits, secure message threads (a “thread” includes an original message between a patient and care team, and all messages in subsequent replies24), telephone encounters, and total primary care contacts (sum of office visits, secure message threads, and telephone encounters). We defined time-varying morbidity burden using resource utilization band (RUB) variables from Johns Hopkins Adjusted Clinical Groups (ACG) System case mix software.25 The Supplemental Appendix presents additional information on data collection and measurement.

Analysis

We computed descriptive statistics for patient characteristics and primary care use. We then estimated 2 multivariable linear regression models, with log-transformed independent and dependent variables,26,27 which estimated the proportional change in office visits associated with a proportional increase in each independent variable. Patients’ log-transformed quarterly office visit count was the dependent variable in both regression models. Before performing log transformation, we added a constant of 1 to quarterly counts of each primary care modality, which ensured transformation of uniformly positive data but did not interfere with desirable statistical properties of the log-normal distribution.28

Our first regression model (adjusted model) contained 2 key independent variables—log-transformed quarterly counts of secure message threads and telephone encounters—and adjusted for covariates. The second regression model (interaction model) adjusted for covariates and investigated potential effect modification through covariate-by-log-count interactions for study period and selected patient characteristics (age, sex, morbidity, insurance type, plan generosity, and primary care physician behaviors).

We estimated regression models using generalized estimating equations (GEE) with an autoregressive-1 (AR1) working correlation matrix for these longitudinal data, with robust “sandwich” covariance estimates that were robust to misspecification of within-cluster correlation.29 We fit a linear model to log-transformed visits with a normal error structure. Analyses were conducted using Stata, version 12.0 (StataCorp). Further details on regression model specification are presented in the Supplementary Appendix.

RESULTS

The study population consisted of 18,486 adults with diabetes who were aged 18 to 75 years on the first day of PCMH implementation (Table 1). As would be expected in a diabetic population, 70% were aged 55 years and older, and 34% had high or very high morbidity.

View this table:
  • View inline
  • View popup
Table 1

Patient Characteristics at PCMH Baseline and Primary Care Contacts During the Pre-PCMH Baseline Year

In the population overall, use of secure messaging and telephone encounters steadily increased over the study period, while use of office visits declined slightly (Figure 1). The mean quarterly number of office visits declined from 0.93 (SD = 0.93) visits during baseline to 0.90 (SD 0.97) visits during PCMH implementation and 0.86 (SD 0.89) visits during postimplementation (8% total decrease). Largely driven by increased secure messaging, the mean quarterly number of primary care contacts increased from 3.46 (SD 3.48) contacts to 3.95 (SD 4.33) and 4.44 (SD 4.68) contacts, respectively (28% total increase).

Figure 1
  • Download figure
  • Open in new tab
  • Download powerpoint
Figure 1

Quarterly numbers of primary care contacts between care teams and patients with diabetes during baseline, PCMH implementation, and postimplementation periods.

PCMH = patient-centered medical home.

In regression analysis, increased use of either secure messaging or telephone encounters was associated with increased office visit use (Table 2). The adjusted model yielded estimates that a 10% increase in secure message threads was associated with a 1.25% increase in office visits (95% CI, 1.21%–1.29%), and that a 10% increase in telephone encounters was associated with a 2.74% increase in office visits (95% CI, 2.70%–2.77%).

View this table:
  • View inline
  • View popup
Table 2

Changes in Office Visits Associated With Proportional Increases in Secure Message Threads and Telephone Encounters

Interaction model results demonstrated some variation across study periods and patient subpopulations, but not to an extent that changed inference (Table 2). The association between log-transformed office visits and telephone encounters decreased over time; using the implementation period as the referent, it was highest during pre-PCMH baseline (P = .01) and decreased further during postimplementation (P <.001). In addition, characteristics such as morbidity and insurance type were associated with statistically significant modifications of main effects. Despite observed interaction effects, linear combinations of coefficients for all study periods and for patient subpopulations in the interaction model were positive at P <.001.

DISCUSSION

In an adult patient population with diabetes, proportional increases in telephone encounters and, to a lesser extent, secure message threads, were associated with proportional increases in primary care office visits. In an interaction model, results varied modestly across selected patient characteristics, and the positive association between log-transformed numbers of office visits and telephone encounters attenuated over time. Although unadjusted office visit use declined by 8% in the study population, patient-level regression analyses demonstrated that a proportional increase in patients’ telephone encounters or secure messaging was associated with additional office visits for all study periods and patient subpopulations.

It is not surprising that we observed positive associations between alternative care modalities and office visits in this setting. During its PCMH redesign, Group Health placed no constraints—financial or otherwise—on secure messaging or telephone use. Primary care clinicians may have selectively used secure messages and telephone encounters to curtail demand for office visits, but these communication modes probably stimulated some demand by reducing access barriers and allowing patients to address previously unmet needs. Although secure messaging and telephone encounters may facilitate patients’ self-management of diabetes,1,2 they cannot fully substitute for clinical tasks such as in-person foot and eye examinations30 and physical examinations.1 Our observational results, like recent findings from Palen and colleagues,14 do not support the hypothesis that, in general, chronically ill patients will use new forms of copay-free communication as an alternative to in-person visits.

This study has several limitations. We did not conduct content analyses of individual primary care contacts, and we did not identify whether a patient or clinician initiated each contact. We could not control for behaviors of nonphysician clinicians, such as medical assistants and nurses, and observed associations cannot be interpreted as causal effects. The study population was limited to individuals with diabetes who were universally insured and of relatively high socioeconomic status, limiting generalizability. Secure electronic messaging and telephone encounters had been conducted at Group Health for several years, facilitating high adoption rates that may be unique to this setting. Group Health’s salary-based clinician reimbursement and capitation-based financing probably affected observed care delivery and patterns of use. In addition, although we adjusted for multiple demographic and clinical characteristics, we could not explicitly adjust for patients’ propensity to seek medical advice and treatment.

Our findings point to several opportunities for further exploration. Pragmatic trials should assess whether telephone and secure messaging encounters can reduce or delay use of emergency and inpatient services. As primary care is increasingly delivered by clinician teams that communicate with patients outside traditional office visit settings, new definitions of primary care use—and accompanying new payment models—are needed to encapsulate and reward patient-centered care delivery.

In conclusion, we found that use of secure electronic messaging and use of telephone encounters were associated with additional primary care office visits among individuals with diabetes in a PCMH redesign. Our findings provide evidence on how new forms of patient-clinician communication may affect demand for office visits.

Acknowledgments

Clarissa Hsu, PhD, DeAnn Cromp, MPH, Kelly Ehrlich, MS, and Eric Johnson, MA, assisted with analysis planning and manuscript preparation. Dean Roehl, MD, and Deborah Brown, RN, shared information about protocols in the medical home redesign and clinician experiences at Group Health. James Ralston, MD, provided helpful feedback on an early draft. We thank Claire Trescott, MD, and Michael Erikson, MSW, for their leadership during the medical home redesign at Group Health.

Footnotes

  • Conflicts of interest: Drs Fishman, Rutter, and Reid and Mr Ross are employees and Dr Liss is a former employee of Group Health Cooperative. Dr Reid is an employee and shareholder of Group Health Physicians, the medical group affiliated with Group Health Cooperative.

  • Funding support: Funding was provided by the National Center for Advancing Translational Sciences (TL1 RR025016), the Agency for Healthcare Research and Quality (R18 HS019129), and Group Health Cooperative.

  • Previous presentation: Preliminary findings were presented at the Clinical and Translational Sciences Predoctoral Programs Meeting in Rochester, Minnesota, May 8, 2012.

  • Supplementary materials: Available at http://www.AnnFamMed.org/content/12/4/338/suppl/DC1/

  • Received for publication July 17, 2013.
  • Revision received December 18, 2013.
  • Accepted for publication January 29, 2014.
  • © 2014 Annals of Family Medicine, Inc.

References

  1. ↵
    1. Car J,
    2. Sheikh A
    . Email consultations in health care: 1—scope and effectiveness. BMJ. 2004;329(7463):435–438.
    OpenUrlFREE Full Text
  2. ↵
    1. Car J,
    2. Sheikh A
    . Telephone consultations. BMJ. 2003;326(7396): 966–969.
    OpenUrlFREE Full Text
  3. ↵
    1. Brown RS,
    2. Peikes D,
    3. Peterson G,
    4. Schore J,
    5. Razafindrakoto CM
    . Six features of Medicare coordinated care demonstration programs that cut hospital admissions of high-risk patients. Health Aff (Millwood). 2012;31(6):1156–1166.
    OpenUrlAbstract/FREE Full Text
  4. ↵
    1. Green BB,
    2. Cook AJ,
    3. Ralston JD,
    4. et al
    . Effectiveness of home blood pressure monitoring, Web communication, and pharmacist care on hypertension control: a randomized controlled trial. JAMA. 2008;299(24):2857–2867.
    OpenUrlCrossRefPubMed
  5. ↵
    1. Ralston JD,
    2. Hirsch IB,
    3. Hoath J,
    4. Mullen M,
    5. Cheadle A,
    6. Goldberg HI
    . Web-based collaborative care for type 2 diabetes: a pilot randomized trial. Diabetes Care. 2009;32(2):234–239.
    OpenUrlAbstract/FREE Full Text
  6. ↵
    1. McGeady D,
    2. Kujala J,
    3. Ilvonen K
    . The impact of patient-physician web messaging on healthcare service provision. Int J Med Inform. 2008;77(1):17–23.
    OpenUrlCrossRefPubMed
  7. ↵
    1. Margolius D,
    2. Bodenheimer T
    . Transforming primary care: from past practice to the practice of the future. Health Aff (Millwood). 2010;29(5):779–784.
    OpenUrlAbstract/FREE Full Text
  8. Committee on Quality of Health Care in America. Crossing the Quality Chasm: A New Health System for the Twenty-First Century. Washington, DC: Institute of Medicine; 2001.
    1. Bates DW,
    2. Wells S
    . Personal health records and health care utilization. JAMA. 2012;308(19):2034–2036.
    OpenUrlCrossRefPubMed
  9. ↵
    1. Wagner EH,
    2. Coleman K,
    3. Reid RJ,
    4. Phillips K,
    5. Abrams MK,
    6. Sugarman JR
    . The changes involved in patient-centered medical home transformation. Prim Care. 2012;39(2):241–259.
    OpenUrlCrossRefPubMed
  10. ↵
    1. Wasson J,
    2. Gaudette C,
    3. Whaley F,
    4. Sauvigne A,
    5. Baribeau P,
    6. Welch HG
    . Telephone care as a substitute for routine clinic follow-up. JAMA. 1992;267(13):1788–1793.
    OpenUrlCrossRefPubMed
  11. ↵
    1. McKinstry B,
    2. Walker J,
    3. Campbell C,
    4. Heaney D,
    5. Wyke S
    . Telephone consultations to manage requests for same-day appointments: a randomised controlled trial in two practices. Br J Gen Pract. 2002;52(477):306–310.
    OpenUrlAbstract/FREE Full Text
  12. ↵
    1. Zhou YY,
    2. Garrido T,
    3. Chin HL,
    4. Wiesenthal AM,
    5. Liang LL
    . Patient access to an electronic health record with secure messaging: impact on primary care utilization. Am J Manag Care. 2007;13(7):418–424.
    OpenUrlPubMed
  13. ↵
    1. Palen TE,
    2. Ross C,
    3. Powers JD,
    4. Xu S
    . Association of online patient access to clinicians and medical records with use of clinical services. JAMA. 2012;308(19):2012–2019.
    OpenUrlCrossRefPubMed
  14. ↵
    1. Hsu C,
    2. Coleman K,
    3. Ross TR,
    4. et al
    . Spreading a patient-centered medical home redesign: a case study. J Ambul Care Manage. 2012; 35(2):99–108.
    OpenUrlCrossRefPubMed
  15. ↵
    1. Ralston JD,
    2. Coleman K,
    3. Reid RJ,
    4. Handley MR,
    5. Larson EB
    . Patient experience should be part of meaningful-use criteria. Health Aff (Millwood). 2010;29(4):607–613.
    OpenUrlAbstract/FREE Full Text
    1. Ralston JD,
    2. Carrell D,
    3. Reid R,
    4. Anderson M,
    5. Moran M,
    6. Hereford J
    . Patient web services integrated with a shared medical record: patient use and satisfaction. J Am Med Inform Assoc. 2007;14(6):798–806.
    OpenUrlCrossRefPubMed
  16. ↵
    1. Ralston JD,
    2. Martin DP,
    3. Anderson ML,
    4. et al
    . Group Health Cooperative’s transformation toward patient-centered access. Med Care Res Rev. 2009;66(6):703–724.
    OpenUrlAbstract/FREE Full Text
  17. ↵
    1. Reid RJ,
    2. Coleman K,
    3. Johnson EA,
    4. et al
    . The Group Health medical home at year two: cost savings, higher patient satisfaction, and less burnout for providers. Health Aff (Millwood). 2010;29(5):835–843.
    OpenUrlAbstract/FREE Full Text
  18. ↵
    1. Liss DT,
    2. Fishman PA,
    3. Rutter CM,
    4. et al
    . Outcomes among chronically ill adults in a medical home prototype. Am J Manag Care. 2013;19(10):e348–e358.
    OpenUrlPubMed
  19. ↵
    1. Reid RJ,
    2. Fishman PA,
    3. Yu O,
    4. et al
    . Patient-centered medical home demonstration: a prospective, quasi-experimental, before and after evaluation. Am J Manag Care. 2009;15(9):e71–e87.
    OpenUrlPubMed
  20. ↵
    1. Reid RJ,
    2. Larson EB
    . Improvement happens: doctors talk about the medical home. An interview with Charles Mayer, MD, MPH and Eric Seaver, MD. J Gen Intern Med. 2012;27(7):871–875.
    OpenUrlCrossRefPubMed
  21. ↵
    1. Shadish WR,
    2. Cook TD,
    3. Campbell DT
    . Experimental and Quasi-Experimental Designs for Generalized Causal Inference. Boston, MA: Houghton Mifflin; 2002.
  22. ↵
    1. Carrell D,
    2. Ralston J
    . Messages, strands and threads: measuring use of electronic patient-provider messaging. AMIA Annu Symp Proc. 2005:913.
  23. ↵
    The Johns Hopkins ACG System: Technical Reference Guide, Version 10.0. Baltimore, MD: Johns Hopkins University; 2011.
  24. ↵
    1. McFadden D
    . Constant elasticity of substitution production functions. Rev Econ Stud. 1963;30(2):73–83.
    OpenUrlFREE Full Text
  25. ↵
    1. Gujarati DN
    . Essentials of Econometrics. 3rd ed. New York, NY: McGraw-Hill/Irwin; 2006.
  26. ↵
    1. Duan N
    . Smearing estimate: a nonparametric retransformation method. J Am Stat Assoc. 1983;78(383):605–610.
    OpenUrlCrossRef
  27. ↵
    1. Diggle P,
    2. Heagerty P,
    3. Liang K,
    4. Zeger S
    . Analysis of Longitudinal Data. 2nd ed. Norfolk, United Kingdom: Oxford University Press; 2002.
  28. ↵
    Executive summary: Standards of medical care in diabetes—2013. Diabetes Care. 2013;36(Suppl 1):S4–S10.
    OpenUrlFREE Full Text
PreviousNext
Back to top

In this issue

The Annals of Family Medicine: 12 (4)
The Annals of Family Medicine: 12 (4)
Vol. 12, Issue 4
July/August 2014
  • Table of Contents
  • Index by author
  • Back Matter (PDF)
  • Front Matter (PDF)
  • The Issue in Brief
Print
Download PDF
Article Alerts
Sign In to Email Alerts with your Email Address
Email Article

Thank you for your interest in spreading the word on Annals of Family Medicine.

NOTE: We only request your email address so that the person you are recommending the page to knows that you wanted them to see it, and that it is not junk mail. We do not capture any email address.

Enter multiple addresses on separate lines or separate them with commas.
Changes in Office Visit Use Associated With Electronic Messaging and Telephone Encounters Among Patients With Diabetes in the PCMH
(Your Name) has sent you a message from Annals of Family Medicine
(Your Name) thought you would like to see the Annals of Family Medicine web site.
CAPTCHA
This question is for testing whether or not you are a human visitor and to prevent automated spam submissions.
5 + 2 =
Solve this simple math problem and enter the result. E.g. for 1+3, enter 4.
Citation Tools
Changes in Office Visit Use Associated With Electronic Messaging and Telephone Encounters Among Patients With Diabetes in the PCMH
David T. Liss, Robert J. Reid, David Grembowski, Carolyn M. Rutter, Tyler R. Ross, Paul A. Fishman
The Annals of Family Medicine Jul 2014, 12 (4) 338-343; DOI: 10.1370/afm.1642

Citation Manager Formats

  • BibTeX
  • Bookends
  • EasyBib
  • EndNote (tagged)
  • EndNote 8 (xml)
  • Medlars
  • Mendeley
  • Papers
  • RefWorks Tagged
  • Ref Manager
  • RIS
  • Zotero
Get Permissions
Share
Changes in Office Visit Use Associated With Electronic Messaging and Telephone Encounters Among Patients With Diabetes in the PCMH
David T. Liss, Robert J. Reid, David Grembowski, Carolyn M. Rutter, Tyler R. Ross, Paul A. Fishman
The Annals of Family Medicine Jul 2014, 12 (4) 338-343; DOI: 10.1370/afm.1642
Twitter logo Facebook logo Mendeley logo
  • Tweet Widget
  • Facebook Like
  • Google Plus One

Jump to section

  • Article
    • Abstract
    • INTRODUCTION
    • METHODS
    • RESULTS
    • DISCUSSION
    • Acknowledgments
    • Footnotes
    • References
  • Figures & Data
  • eLetters
  • Info & Metrics
  • PDF

Related Articles

  • PubMed
  • Google Scholar

Cited By...

  • A Note on the Effects of Digital Primary Health Care on Utilization: Concepts, Evidence, and Descriptive Analysis of Non-Experimental Register Data from Sweden
  • Can Secure Patient-Provider Messaging Improve Diabetes Care?
  • Primary Care Practice Reengineering and Associations With Patient Portal Use, Service Utilization, and Disease Control Among Patients With Hypertension and/or Diabetes
  • Association between secure patient-clinician email and clinical services utilisation in a US integrated health system: a retrospective cohort study
  • In This Issue: Technical and Personal Systems, and Novel Risk Factors
  • Google Scholar

More in this TOC Section

  • Shared Decision Making Among Racially and/or Ethnically Diverse Populations in Primary Care: A Scoping Review of Barriers and Facilitators
  • Convenience or Continuity: When Are Patients Willing to Wait to See Their Own Doctor?
  • Feasibility and Acceptability of the “About Me” Care Card as a Tool for Engaging Older Adults in Conversations About Cognitive Impairment
Show more Original Research

Similar Articles

Subjects

  • Domains of illness & health:
    • Chronic illness
  • Methods:
    • Quantitative methods
  • Other research types:
    • Health policy
    • Health services
  • Core values of primary care:
    • Access

Keywords

  • primary care
  • electronic mail
  • telephone
  • communication
  • office visits
  • family practice
  • health services needs and demand
  • practice redesign
  • utilization
  • practice-based research

Content

  • Current Issue
  • Past Issues
  • Early Access
  • Plain-Language Summaries
  • Multimedia
  • Podcast
  • Articles by Type
  • Articles by Subject
  • Supplements
  • Calls for Papers

Info for

  • Authors
  • Reviewers
  • Job Seekers
  • Media

Engage

  • E-mail Alerts
  • e-Letters (Comments)
  • RSS
  • Journal Club
  • Submit a Manuscript
  • Subscribe
  • Family Medicine Careers

About

  • About Us
  • Editorial Board & Staff
  • Sponsoring Organizations
  • Copyrights & Permissions
  • Contact Us
  • eLetter/Comments Policy

© 2025 Annals of Family Medicine