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The American Journal of Managed Care April 2012
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Evaluation of Human Immunodeficiency Virus and Hepatitis C Telemedicine Clinics
Hemen N. Saifu, MPH; Steven M. Asch, MD, MPH; Matthew Bidwell Goetz, MD; Jason P. Smith, PharmD; Christopher J. Graber, MD, MPH; Dennis Schaberg, MD; and Benjamin C. Sun, MD, MPP
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John S. Hudson, RN, PhD; James A. Neff, PhD, MPH; Miguel A. Padilla, PhD; Qi Zhang, PhD; and Larry T. Mercer, EdD
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Hsien-Yen Chang, PhD; Jonathan P. Weiner, DrPH; Thomas M. Richards, MS; Sara N. Bleich, PhD; and Jodi B. Segal, MD, MPH
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Jennifer S. Myers, MD; and Richard P. Shannon, MD
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Tara F. Bishop, MD; Alex D. Federman, MD, MPH; and Joseph S. Ross, MD, MHS
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Chris Sistrom, MD, MPH, PhD; Niccie L. McKay, PhD; Jeffrey B. Weilburg, MD; Steven J. Atlas, MD, MPH; and Timothy G. Ferris, MD
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Tobias Freund, MD; Michel Wensing, PhD; Stefan Geissler, cand.med; Frank Peters-Klimm, MD; Cornelia Mahler, RN, MA, PhD; Cynthia M. Boyd, MD, MPH; and Joachim Szecsenyi, MD, MSc

Evaluation of Human Immunodeficiency Virus and Hepatitis C Telemedicine Clinics

Hemen N. Saifu, MPH; Steven M. Asch, MD, MPH; Matthew Bidwell Goetz, MD; Jason P. Smith, PharmD; Christopher J. Graber, MD, MPH; Dennis Schaberg, MD; and Benjamin C. Sun, MD, MPP
In an integrated health system, human immunodeficiency virus and hepatitis C telemedicine clinics are associated with improved access, high patient satisfaction, and reduction in health visit“related time.
Background: Geographical barriers to subspecialty care may prevent optimal care of patients living in rural areas. We assess the impact of human immunodeficiency virus (HIV) and hepatitis C telemedicine consultation on patient-oriented outcomes in a rural Veterans Affairs population.


Methods: This was a pre- and post-intervention study comparing telemedicine with in-person subspecialty clinic visits for HIV and hepatitis C. Eligible patients resided in 2 rural catchment areas. The primary binary outcome was clinic completion. We estimated a logistic regression model with patient-level fi xed effects. This approach controls for the clustering of visits by patient, uses each patient’s in-person clinic experience as an internal control group, and eliminates confounding by person-level factors. We also surveyed patients to assess satisfaction and patient-perceived reductions in health visit–related time.


Results: There were 43 patients who accounted for 94 telemedicine visits and 128 in-person visits. Clinic completion rates were higher for telemedicine (76%) than for in-person visits (61%). In regression analyses, telemedicine was strongly predictive of clinic completion (OR 2.2; 95% confi dence interval [CI]: 1.0-4.7). The adjusted effect of telemedicine on clinic completion rate was 13% (95% CI: 12-13). Of the 30 patients (70%) who completed the survey, more than 95% rated telemedicine at the highest level of satisfaction and preferred telemedicine to in-person clinic visits. Patients reported a signifi cant reduction in health visit–related time (median 340 minutes, interquartile range 250-440), mostly due to decreased travel time.


Conclusions: HIV and hepatitis C telemedicine clinics are associated with improved access, high patient satisfaction, and reduction in health visit–related time.


(Am J Manag Care. 2012;18(4):207-212)
We evaluated human immunodefi ciency virus (HIV) and hepatitis C telemedicine services at 2 rural clinics.
 
  •  HIV and hepatitis C are high-risk, prevalent, and chronic illnesses where subspecialty care can often improve quality of life and survival. Distance may be an important barrier to access.
 
  •  Visit completion rate, a proxy for access, was 13% greater for telemedicine compared with in-person clinics.
 
  •  >95% of respondents rated telemedicine at the highest level of satisfaction and preferred telemedicine to in-person visits.
 
  •  Telemedicine reduced health visit time by 340 minutes.
 
  •  This intervention was implemented within an existing telemedicine infrastructure without need for additional staff or equipment.
Electronic interactive healthcare consultations, also known as telemedicine, may reduce geographic barriers to timely subspecialty care. Human immunodefi ciency virus (HIV) and hepatitis C are ideal test conditions for telemedicine, because they are high-risk, prevalent, and chronic illnesses where subspecialty care can often improve quality of life and survival. The demand for such services will likely increase as more patients become eligible for treatment with new antiviral regimens.1 Unfortunately, limited access to subspecialty care is a major barrier to optimal care of patients infected with HIV and/or hepatitis C,2,3 particularly for those who live in rural settings.

The Veterans Affairs (VA) Healthcare System has taken a leadership role by investing heavily in telemedicine4-9 to better serve the 20% of veterans who reside in rural areas.9 Expanding telemedicine access to HIV/hepatitis C subspecialty care has been identified as a top priority by the VA national leadership and the VA HIV/Hepatitis Quality Enhancement Research Initiative.10 Although there have been reports of telemedicine care for HIV and hepatitis C in non-VA settings,11-14 we are unaware of published reports describing HIV/hepatitis C telemedicine efforts within the VA system. To address this clinical need, the VA Greater Los Angeles Health System (VAGLAHS) implemented HIV and hepatitis C telemedicine services at 2 rural clinics.

The goal of this study was to assess the impact of telemedicine services for the VAGLAHS HIV and hepatitis C clinics on patient-oriented outcomes. We used clinic completion rates as a proxy measure for access. Our primary hypothesis was that telemedicine would safely improve clinic completion rates. We also hypothesized that telemedicine would be associated with high patient satisfaction and reduced health visit–related time.

METHODS

Study Design and Setting

This is a pre-post intervention study of HIV/hepatitis C clinic visits clustered by patients. We used the pre-intervention, in-person clinic completion rate of each patient as an internal control group to assess the impact of the telemedicine clinics. The VAGLAHS HIV clinic initiated telemedicine consultations in February 2009 and the VAGLAHS hepatitis C clinic began telemedicine consultations in February 2010. Pre- and post-intervention data for this study were collected from June 2008 to June 2011. This study was approved by the VAGLAHS Institutional Review Board.

VAGLAHS has an existing telemedicine infrastructure that includes “hub” sites located in urban Los Angeles. The “spoke” sites in this study included the Santa Maria and Bakersfield clinics, which are respectively 160 and 110 miles driving distance from the urban clinics. Telemedicine consultations are performed utilizing video teleconferencing end units over a high-speed Internet connection (Polycom; Pleasanton, California). At the hub sites, mobile end units with 32" monitors can be moved between clinics. A clinical manager at each of the hub and spoke sites is responsible for providing support to the telemedicine program. The HIV/ hepatitis C telemedicine clinics utilized this existing infrastructure, and no additional funds, staff, or equipment were required for implementation. However, the “clinical champions”

and nursing staff for these clinics did provide in-kind time to develop policies and processes to implement telemedicine services.

Telemedicine consultations were performed by healthcare providers during the existing infectious disease and hepatitis C clinic times at the urban hub sites. For both the HIV and hepatitis C clinics, there was a single half-day clinic per week. Patients scheduled for a telemedicine consultation presented to a spoke site. An onsite nurse measured vital signs, and patients were placed in a private examination room set up with teleconferencing equipment. The healthcare providers at the hub sites could remotely conduct consultations; perform interviews and patient education; view chart notes, radiology tests, and electrocardiograms; enter orders for pharmacy,

laboratory, and radiology; and perform documentation using the VA computerized patient record system. During the study period, there was a single provider in each of the HIV and hepatitis C clinics who performed all telemedicine consultations (CJG, JPS).

Study Cohort

The study population is a convenience sample of patients residing in the Santa Maria and Bakersfi eld catchment areas who were referred by their HIV or hepatitis C provider to the telemedicine clinic. Providers selected patients who were deemed to have stable disease. There were no other eligibility criteria such as viral load or active antiviral therapy.

Outcomes and Measurements

The primary binary outcome was clinic completion, defi ned as the completion of a scheduled appointment. Reasons for non-completion of a scheduled appointment included no-shows and patient cancellations. Cancellations by the clinic were excluded from this analysis.

Determination of clinic completion was performed by review of electronic medical records and administrative data. All telemedicine clinic encounters were reviewed. To create patient-specifi c internal control groups, we also reviewed all condition-specifi c in-person visits that occurred during the study period. For example, if a patient was scheduled for an HIV telemedicine clinic visit, we collected data on all prior scheduled HIV in-person clinic visits for that patient.

Secondary outcomes included patient satisfaction and health visit–related time. At the end of each telemedicine consult, a research assistant administered a 10-minute survey from the hub site. Overall satisfaction and ratings of physician interaction, privacy, physical environment, and convenience were measured on a 5-level Likert scale (very dissatisfied, somewhat dissatisfied, neither satisfi ed nor dissatisfied, somewhat satisfied, very satisfied). Preference for in-person versus telemedicine consultation was measured on a binary scale. Patients were also asked to estimate travel and on-site time required for in-person and telemedicine visits. For estimates of on-site time, patients were asked to consider time for checking in, waiting, and completing the consultation. Total health visit–related time is defi ned as the sum of travel and on-site time related to a clinic visit.

We collected demographic data on age at time of the first telemedicine visit, gender, and race/ethnicity from review of electronic medical records and administrative data. Race/ethnicity data were self-reported to VAGLAHS. Finally, we assessed whether there were any hospitalizations at a VA facility or deaths that occurred within 30 days of a subspecialty clinic.

All electronic and administrative records were reviewed by a research assistant (HNS). To assess inter-rater reliability, a physician-investigator (BCS) blinded to the research assistant’s abstractions independently re-reviewed notes from 50 randomly selected visits. There was 100% concordance on all data elements, including visit completion, demographic data, and occurrence of 30-day hospitalization or death.

Analysis

We performed unadjusted and adjusted analyses of the primary outcome of clinic completion rates. Contingency table methods were used to estimate unadjusted clinic completion rates for scheduled in-person and telemedicine visits. To assess the adjusted effect of telemedicine on clinic completion, we estimated a logistic regression model with personfi xed effects. The binary outcome is clinic completion, and the predictor is clinic setting (in-person vs telemedicine). This approach controls for the clustering of visits by patient, uses each patient’s in-person clinic experience as an internal control group, and eliminates confounding by person-level factors. Odds ratio and 95% confi dence intervals were calculated directly from the regression results. We performed sensitivity analyses with person-level random effects, and with no person-level effects; there were no qualitative differences in the results.

Although odds ratios are commonly reported effect measures, they may be difficult to interpret clinically. We used a bootstrapping approach to estimate the adjusted impact of telemedicine on clinic completion rates. We generated 1000 re-samples of the patient population of equivalent size to the original patient population. For each sample, we fit the logistic regression model with patient-level fixed effects, and the absolute rate difference was estimated by hypothetically setting all visits to either in-person or to telemedicine. We used estimates across all 1000 re-samples to generate a mean point estimate and 95% confi dence intervals of the absolute rate difference between in-person and telemedicine visits.

To explore the possibility of condition-specific effects of telemedicine on visit completion, we re-fit the regression model with an interaction term between telemedicine and condition (HIV vs hepatitis C).

We describe all secondary outcomes in descriptive tables. All time-interval outcomes were highly right-skewed. Using patient estimates of health visit–related time, we calculated the median and interquartile range of the differences between in-person and telemedicine clinic visits. We used the Wilcoxon rank-sum test for non-parametric data to assess time-based measures.

Data entry was performed using Microsoft Access (Redmond, Washington). Data management and analyses were performed using SAS 9.1 (Cary, North Carolina).

RESULTS

There were 43 patients who accounted for 94 telemedicine visits and 128 in-person visits to HIV or hepatitis C subspecialty clinics. This cohort was predominantly male, as expected for a VA population, and the majority of patients were evaluated for hepatitis C (Table 1).

The in-person clinic completion rate of the study cohort was 61%, which is similar to the historic in-person clinic completion rate of 61% for HIV and hepatitis C visits by all patients from the study catchment areas from 2008 to 2010 (P = 0.9). The adjusted odds ratio of clinic completion associated with telemedicine was 2.3 (95% CI: 1.0-4.7; P = 0.04). In bootstrapped analysis, telemedicine was associated with an increased clinic completion rate of 13% (95% CI: 12-13) (Table 2). There was no evidence of a statistically important interaction effect (P = 0.2) between telemedicine and condition (HIV vs hepatitis C).

Of the 43 study cohort patients, 30 (70%) completed a telemedicine-facilitated survey. The remaining 13 patients did not complete the survey either because they did not show for their telemedicine visit or because of research assistant unavailability. There were no refusals to participate in the survey. Patients were highly enthusiastic about telemedicine, and >95% of respondents gave the highest possible rating for overall satisfaction and expressed a preference for telemedicine over in-person clinic visits (Table 3).

Respondents estimated that total health visit time was 340 minutes less for telemedicine compared with in-person visits (P <0.001); time reduction was attributable to both shorter travel and on-site times (Table 4). However, the majority of perceived time reduction was related to travel. Approximately 65% of respondents reported that they traveled to the urban hub site by car, and the remainder used a VA shuttle or public transportation.

There were no study patients who died or were hospitalized at a VA facility within 30 days of the scheduled clinic visits.

DISCUSSION

 
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