Evidence-based Synthesis Program Department of Veterans Affairs

Health Services Research & Development Service

July 2012

Prepared for:

Department of Veterans Affairs

Veterans Health Administration

Quality Enhancement Research Initiative

Health Services Research & Development Service

Washington, DC 20420

Prepared by:

Evidence-based Synthesis Program (ESP) Center 

Durham Veterans Affairs Healthcare System

Durham, NC

John W Williams Jr., M.D., M.H.Sc., Director

Shared Medical Appointments for 

Chronic Medical Conditions: 

A Systematic Review

Investigators:

Principal Investigator:

David Edelman, M.D.

Co-Investigators:

Jennifer R. McDuffie, Ph.D.

Eugene Oddone, M.D., M.H.Sc.

Jennifer M. Gierisch, Ph.D., M.P.H.

John W. Williams Jr., M.D., M.H.Sc.

Research Associate:

Avishek Nagi, M.S.

Medical Editor:

Liz Wing, M.A.
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Shared Medical Appointments for Chronic Medical Conditions Evidence-based Synthesis Program

PREFACE

Quality Enhancement Research Initiative’s (QUERI’s) Evidence-based Synthesis Program 

(ESP) was established to provide timely and accurate syntheses of targeted healthcare topics 

of particular importance to Veterans Affairs (VA) managers and policymakers, as they work to 

improve the health and healthcare of Veterans. The ESP disseminates these reports throughout 

VA.

QUERI provides funding for four ESP Centers and each Center has an active VA affiliation. The 

ESP Centers generate evidence syntheses on important clinical practice topics, and these reports 

help:

• develop clinical policies informed by evidence,

• guide the implementation of effective services to improve patient outcomes 

and to support VA clinical practice guidelines and performance measures, 

and 

• set the direction for future research to address gaps in clinical knowledge.

In 2009, the ESP Coordinating Center was created to expand the capacity of QUERI Central 

Office and the four ESP sites by developing and maintaining program processes. In addition, 

the Center established a Steering Committee comprised of QUERI field-based investigators, 

VA Patient Care Services, Office of Quality and Performance, and Veterans Integrated Service 

Networks (VISN) Clinical Management Officers. The Steering Committee provides program 

oversight, guides strategic planning, coordinates dissemination activities, and develops 

collaborations with VA leadership to identify new ESP topics of importance to Veterans and the 

VA healthcare system.

Comments on this evidence report are welcome and can be sent to Nicole Floyd, ESP 

Coordinating Center Program Manager, at nicole.floyd@va.gov.

Recommended citation: Edelman D, McDuffie JR, Oddone E, Gierisch JM, Nagi A, Williams 

JW Jr. Shared Medical Appointments for Chronic Medical Conditions: A Systematic Review. VAESP Project #09-010; 2012.

This report is based on research conducted by the Evidence-based Synthesis 

Program (ESP) Center located at the Durham VA Medical Center, Durham, NC, 

funded by the Department of Veterans Affairs, Veterans Health Administration, Office 

of Research and Development, Quality Enhancement Research Initiative. The findings 

and conclusions in this document are those of the author(s) who are responsible for 

its contents; the findings and conclusions do not necessarily represent the views of 

the Department of Veterans Affairs or the United States government. Therefore, no 

statement in this article should be construed as an official position of the Department 

of Veterans Affairs. No investigators have any affiliations or financial involvement (e.g., 

employment, consultancies, honoraria, stock ownership or options, expert testimony, 

grants or patents received or pending, or royalties) that con¬flict with material 

presented in the report.
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Shared Medical Appointments for Chronic Medical Conditions Evidence-based Synthesis Program

EXECUTIVE SUMMARY

BACKGROUND

The most successful health care systems offer ready access to high-quality primary care—an 

approach that is embedded in the fundamental design of Veterans Affairs (VA) health care and 

which is consistent with the Institute of Medicine’s definition of high-quality care. This definition 

emphasizes safe, effective, patient-centered, timely, efficient, and equitable health care. Group 

medical visits are a method to deliver health care that offers the promise of improving these 

aspects for patients with chronic conditions.

Group visits (or clinics) are a system redesign in which clinicians see multiple patients together 

in the same clinical setting. Shared medical appointments (SMAs) are a subset of such clinics and 

are defined by groups of patients meeting over time for comprehensive care for a defining chronic 

condition or health care state. SMAs usually involve both a person trained or skilled in delivering 

patient education or facilitating patient interaction and a practitioner with prescribing privileges. 

SMA sessions typically last 60 to 120 minutes, with time set aside for social integration, interactive 

education, and medication management, in an effort to achieve improved disease outcomes. 

SMAs have been scientifically tested in an array of primary care settings over the last 10 to 

15 years. However, there has been great variability among these studies in relation to setting; 

components included in the intervention; and measurement of clinical, cost, and utilization 

outcomes. For example, the patient group may stay constant, in an attempt to provide group 

bonding, or the patients may be allowed to choose sessions from a schedule at their convenience 

to promote attendance. Like patients, provider teams can be constant or vary over time. This 

uncertainty regarding the optimal design and impact of SMAs led the VA to commission this 

evidence synthesis report.

Our objective was to summarize the effects of SMA on staff, patient, and economic outcomes 

and to evaluate whether the impact varied by clinical condition or specific intervention 

components.

Key Question 1. For adults with chronic medical conditions, do shared medical appointments 

(SMAs) compared with usual care improve the following:

•	 Patient and staff experience?

•	 Treatment adherence?

•	 Quality measures such as (a) process of care measures utilized by VA, National Quality 

Forum, or National Committee for Quality Assurance and (b) biophysical markers 

(laboratory or physiological markers of health status such as HbA1c and blood pressure)?

•	 Symptom severity and functional status?

•	 Utilization of medical resources or health care costs?

Key Question 2. For adults with chronic medical conditions, do the effects of SMAs vary by 

patient characteristics such as specific chronic medical conditions and severity of disease?

Key Question 3. Is the intensity of the intervention or the components used by SMAs associated 

with intervention effects?
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Shared Medical Appointments for Chronic Medical Conditions Evidence-based Synthesis Program

METHODS

We searched MEDLINE® (via PubMed®), Embase®, CINAHL® , PsycINFO®, and Web of 

Science for peer-reviewed publications comparing shared medical appointments or group 

visits with usual care from January 1996 through April 2012. Our search strategy used the 

National Library of Medicine’s medical subject headings (MeSH) keyword nomenclature and 

text words for group visits, and validated search terms for both randomized controlled trials 

and relevant observational studies. We limited the search to articles published in the English 

language involving human subjects 18 years of age and older. We developed our search strategy 

in consultation with a master librarian. We supplemented the electronic searches with a manual 

search of citations from a set of key primary articles, review articles and systematic reviews. 

As a mechanism to assess the risk of publication bias, we searched www.clinicaltrials.gov for 

completed but unpublished studies. 

DATA SYNTHESIS

Using prespecified inclusion and exclusion criteria, we critically analyzed studies to compare 

their characteristics, methods, findings and quality. When meta-analysis was appropriate, we 

used random-effects models to synthesize the effects quantitatively, reporting by a weighted 

difference of the means when the same scale (e.g., blood pressure) was used and a standardized 

mean difference when the scales (e.g., health-related quality of life) differed across studies. 

Heterogeneity was examined among the studies using graphical displays and test statistics 

(Cochran’s Q and I2

). We explored heterogeneity in study effects by using subgroup analyses 

for categorical variables (e.g., study quality) and meta-regression analyses for continuous or 

discrete variables (e.g., baseline HbA1c, intervention robustness). Our subgroup and metaregression analyses should be considered hypothesis-generating because they consist of indirect 

comparisons and thus are subject to confounding. Outcomes not suitable to meta-analyses were 

described qualitatively

RATING THE BODY OF EVIDENCE

In addition to rating the quality of individual studies, we evaluated the overall strength of 

evidence (SOE) for each Key Question by assessing the following domains: risk of bias, 

consistency, directness, precision, strength of association (magnitude of effect), and publication 

bias. These domains were considered qualitatively, and a summary rating of high, moderate, low, 

or insufficient SOE was assigned after discussion by two reviewers.

PEER REVIEW

The draft version of the report was reviewed by technical experts and clinical leadership. 

A transcript of their comments is in an appendix of the full report and elucidates how each 

comment was considered in the final report.
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Shared Medical Appointments for Chronic Medical Conditions Evidence-based Synthesis Program

RESULTS

We identified 1104 unique citations from a combined search of MEDLINE (via PubMed, n=323), 

CINAHL (n=290), Embase (n=145), PsycINFO (n=157), the Web of Science (n=186) and by 

manual searching of included study bibliographies and review articles (n=2). After applying 

eligibility criteria, 25 articles (representing 19 unique studies) were included in the review. 

Of the 19 studies, 16 (13 trials) evaluated SMA interventions in patients with diabetes mellitus 

and 3 (2 trials) evaluated SMAs in older adults with high utilization of medical resources. 

SMAs were generally led by teams of 1 to 3 clinicians that usually included a physician and/

or a registered nurse. Typically, sessions involved fixed patient panels and included individual 

breakouts for medication management. Group size averaged 6 to 10 members; median visit 

length was 2 hours and visit frequency ranged from approximately every 3 weeks to every 3 

months. Followup ranged from 4 to 48 months. All studies compared SMAs with usual care 

or enhanced usual care; there were no direct comparisons between SMA and other qualityimprovement strategies. 

Our search of www.clinicaltrials.gov did not identify any completed but unpublished studies. We 

found four ongoing studies, three for patients with diabetes and one for those with heart failure.

Key Question 1. For adults with chronic medical conditions, do shared medical 

appointments (SMAs) compared with usual care improve the following:

•	 Patient and staff experience?

•	 Treatment adherence?

•	 Quality measures such as (a) process of care measures utilized by VA,

National Quality Forum, or National Committee for Quality Assurance 

and (b) biophysical markers (laboratory or physiological markers of

health status such as HbA1c and blood pressure)?

•	 Symptom severity and functional status?

•	 Utilization of medical resources or health care costs?

Of the 13 randomized trials that evaluated the effects of SMAs on outcomes for patients with 

diabetes, ten examined type 2 diabetes only, one examined type 1 only, and two examined 

a mixed patient population. Other chronic medical conditions were not represented. Studies 

enrolled patients with poor glucose control (thresholds varied from A1c .6.5% to >9%); a 

minority required elevated blood pressure or lipids. Only two trials described the effects on 

patient experience, and neither of those trials showed greater satisfaction among those in SMAs 

compared with usual care. All studies reported effects on average hemoglobin A1c at the end 

of the intervention. SMAs were associated with lower A1c than usual care at 4 to 48 months’ 

followup (mean difference=-0.55; 95% CI, -0.99 to -0.11). However, effects varied significantly 

across studies and this was not explained by study quality. Eight studies reported effects on 

either total or LDL cholesterol, showing small but statistically nonsignificant treatment effects 

that varied across studies. Five studies reported effects on systolic blood pressure, showing a 

consistent and statistically significant effect (mean difference=-5.2; CI, -7.40 to -3.05). Five 

studies reported large improvements in health-related quality of life (standardized mean 

difference=-0.84; CI, -1.64 to -0.03), but effects were greater when using a disease-specific 

measure. Three observational studies examined a more limited set of outcomes, with findings 
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Shared Medical Appointments for Chronic Medical Conditions Evidence-based Synthesis Program

generally consistent with those of the randomized trials.

The effects of SMAs on hospital admissions and emergency department visits were explored in 

five studies on patients with diabetes. In three of these, admission rates were lower with SMAs, 

but the result was statistically significant in only one study. Two studies found emergency 

department visits decreased significantly with SMAs. Four studies reported effects on total costs, 

but results were mixed. In one, total costs were significantly higher; in another, total costs were 

significantly lower; in a third, results did not differ significantly; and the fourth was conducted in 

Europe and so costs may not be applicable to the U.S. health system.

We identified two randomized trials and one observational study that evaluated the effects of 

SMAs on older adults with high health care service utilization rates. All studies reported positive 

effects on patient experience with SMAs compared with usual care. Both trials reported effects 

on overall health status and functional status, but there was no difference compared with usual 

care for either of these measures. Biophysical outcomes were not reported. All three studies 

showed fewer hospital admissions in the SMA groups, and both trials reported a statistically 

significant decrease in emergency department visits with SMAs compared with usual care. Total 

costs also were lower for the SMA group in each study but varied substantially across studies and 

did not reach statistical significance for any study.

Table ES-1 summarizes the strength of evidence (SOE) for KQ 1.

Table ES-1. Summary of the strength of evidence for KQ 1

Population

Number of

Studiesa 

(Subjects)

Domains Pertaining to SOE SOE

Risk of

Bias: Study 

Design/ 

Quality

Consistency Directness Precision Effect Estimate 

(95% CI)

Staff experience Insufficient

Diabetes 0 NA NA NA NA Not estimable

Older adults 1 (1236) Obs/Fair NA Direct Imprecise Not estimable

Patient experience Insufficient

Diabetes 2 (769) RCT/Fair Consistent Direct Imprecise No effect

Older adults 2 (444) RCT/Fair Inconsistent Direct Imprecise Small to large positive 

effect

Treatment adherence Insufficient

Diabetes 3 (536) RCT/Fair Some 

inconsistency Direct Imprecise Not estimable

Older adults 0 NA NA NA NA Not estimable

Biophysical

Diabetes:

A1c 13 (2921) RCT/Good Inconsistent Direct Some imprecision

MD = -0.55

(-0.99 to -0.11)

Moderate SOE
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Shared Medical Appointments for Chronic Medical Conditions Evidence-based Synthesis Program

Population

Number of

Studiesa 

(Subjects)

Domains Pertaining to SOE SOE

Risk of

Bias: Study 

Design/ 

Quality

Consistency Directness Precision Effect Estimate 

(95% CI)

Diabetes: 

Total 

Cholesterol

LDL 

Cholesterol

5 (1556)

5 (997)

RCT/Fair

RCT/Fair

Inconsistent

Inconsistent

Direct

Direct

Imprecise

Imprecise

MD = -4.9 (-17.8 to 7.9)

Low SOE

MD -6.6 (-16.1 to 2.8)

Low SOE

Diabetes: 

Blood 

pressure

5 (1125) RCT/Good Consistent Direct Some 

imprecision

MD = -5.2 

(-7.4 to -3.1)

Moderate SOE

Older adults 0 NA NA NA NA Not estimable

Health-related quality of life or functional status

Diabetes 5 (1561) RCT/Fair Inconsistent Direct Imprecise

SMD = -0.84 

(-1.6 to -0.03)

Low SOE

Older adults 2 (615) RCT/Fair Inconsistent Direct Imprecise Not estimable

Economic

Diabetes

5 (1339)

5 (1339)

4 (1125)

RCT/Good

RCT/Good

RCT/Fair

Inconsistent

Consistent

Inconsistent

Direct

Direct

Direct

Imprecise

Some 

imprecision

Imprecise

ED visits lower rates 

in 2 of 5 studies 

Insufficient SOE

Hospitalizations lower 

in 4 of 5 studies

Low SOE

Total costs range 

from lower to higher 

Insufficient SOE

Older adults

2 (615)

2 (615)

2 (615)

RCT/Fair

RCT/Fair

RCT/Fair

Consistent

Some 

inconsistency

Inconsistent

Direct

Direct

Direct

Imprecise

Imprecise

Imprecise

ED visits lower rates in 

2 of 2 studies

Low SOE

Hospitalizations lower 

in 1 of 2 studies

Insufficient SOE

Total costs lower 

but not statistically 

significant

Insufficient SOE

a

Studies(subjects) given are for randomized trials; observational studies were also considered in SOE ratings but are not listed 

separately in the table.

Abbreviations: CI=confidence interval; ED=emergency department; MD=mean difference; NA=not applicable; RCT=randomized 

controlled trial; RD=risk difference; RR=risk ratio; SMD=standardized mean difference; SOE=strength of evidence
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Shared Medical Appointments for Chronic Medical Conditions Evidence-based Synthesis Program

Key Question 2. For adults with chronic medical conditions, do the effects of 

SMAs vary by patient characteristics such as specific chronic medical conditions

and severity of disease?

No included studies explored the subgroups of patients that would benefit most from an SMA

intervention.

Key Question 3. Is the intensity of the intervention or the components used by

SMAs associated with intervention effects?

No included studies explored the specific components of an SMA intervention that were most 

potent. SMA interventions did, however, have certain common components. SMAs were led 

by teams of 1 to 3 clinicians that included a physician (n=15), clinical pharmacists (n=9; the 

prescribing clinician in 3 studies), and a registered nurse. The clinical team was multidisciplinary 

in most studies; pharmacists and licensed mental health professionals participated in almost 

half the studies. Sessions were designed for closed panels of patients in all but three studies, 

which used drop-in models. Group size was 6 to 10 members for most studies, with size ranging 

between 10 and 20 members in 4 studies and as large as 25 members in 1 study. The planned 

visit frequency ranged from monthly to approximately every 3 months. SMA visits were a 

median of 2 hours (range 1 to 3.5 hours). At least 16 of 19 studies offered individual breakouts 

with a physician or clinical pharmacist as part of the SMA design specified that medication 

changes could be made at group visits. Details of the SMA interventions are given in an appendix 

of the full report.

We devised an intervention robustness score to attempt to address KQ 3 quantitatively, but it 

was not associated with treatment effects. More than 70 percent of all studies were similar on 

six of the seven variables used in the robustness score: (1) whether the team was continuous, 

(2) whether the group was closed, (3) whether individual breakout sessions were conducted, (4) 

whether medication changes were made, (5) how long each session was, and (6) whether there 

was contact outside the session. It is possible that there are other more important variables that 

are not being measured with current approaches. The strength of evidence for both questions was 

judged to be insufficient.

RECOMMENDATIONS FOR FUTURE RESEARCH

We used a structured framework to identify gaps in evidence and classify why these gaps exist 

(Table ES-2).

Table ES-2. Evidence gaps and future research

Evidence Gap Reason Type of Studies to Consider

Patients

Absence of data for patients with 

conditions other than diabetes mellitus 

and high utilization

Insufficient information Single and multisite RCTs

Quasi-experimental studies

Interventions

Uncertain which elements of an SMA 

intervention are most effective and 

efficient

Insufficient information RCTs of head-to-head comparisons 

of different types of SMAs; 

Disaggregation trials
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Shared Medical Appointments for Chronic Medical Conditions Evidence-based Synthesis Program

Evidence Gap Reason Type of Studies to Consider

Outcomes

Uncertain effects on patient and staff 

satisfaction

Insufficient information Nonrandomized or cluster 

randomized, multisite implementation 

studies, qualitative studies

Uncertain effects on physiological 

variables other than HbA1c

Insufficient information Large scale RCTs

Nonrandomized, cluster controlled 

trials, controlled before-and-after 

studies, interrupted time series

Uncertain effects on health system costs 

with the exception of the elderly high 

utilizers of the health system

Insufficient information Costs analyses 

Uncertain whether there would be 

unintended consequences to other 

aspects of the health care system if 

SMAs were implemented

Insufficient information Multisite observational studies

Abbreviation: RCT=randomized controlled trial; SMA=shared medical appointment

CONCLUSION 

Our review shows that SMAs—typically using closed groups with individual breakouts and 

opportunity for medication management—improve intermediate clinical outcomes for type 2 

diabetes. A smaller literature shows positive effects on patient experience in older adults and 

the possibility of lower health care utilization. SMAs may be most effective for illnesses such 

as diabetes that have a phase in which the risk of complication is relatively high while the 

disease is simultaneously asymptomatic, and in which medication titration and self-management 

are important. Until further studies are done that allow for comparisons across conditions, 

the targeting of SMA interventions for chronic conditions other than diabetes will remain 

speculative. 

ABBREVIATIONS TABLE

CI confidence interval

ED emergency department

KQ key question

MD mean difference

MeSH medical subject headings

NA not applicable

NR not reported

RCT randomized controlled trial

RD risk difference

RR risk ratio

SMA shared medical appointment

SMD standardized mean difference

SOE strength of evidence

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