| Literature DB >> 26687507 |
Delphine S Tuot1,2, Kiren Leeds3, Elizabeth J Murphy4,5, Urmimala Sarkar6, Courtney R Lyles7, Tekeshe Mekonnen8, Alice H M Chen9,10.
Abstract
BACKGROUND: Access to specialty care remains a challenge for primary care providers and patients. Implementation of electronic referral and/or consultation (eCR) systems provides an opportunity for innovations in the delivery of specialty care. We conducted key informant interviews to identify drivers, facilitators, barriers and evaluation metrics of diverse eCR systems to inform widespread implementation of this model of specialty care delivery.Entities:
Mesh:
Year: 2015 PMID: 26687507 PMCID: PMC4684927 DOI: 10.1186/s12913-015-1233-1
Source DB: PubMed Journal: BMC Health Serv Res ISSN: 1472-6963 Impact factor: 2.655
Characteristics of participating health delivery organizations, ordered by type of eCR system. SFGH included as reference
| Geographic Area | Type of Organization | Safety net | Patients Served Annually | Type of electronic referral and consultation system (eCR) | Number of patients with electronic referrals or consultations submitted |
|---|---|---|---|---|---|
| Colorado | Public system – county | Yes | 133,000 | None | none; pre-pilot |
| Washington | Public system – county | Yes | 240,000 | None | none; pre-pilot |
| Hawaii, all islands | Health plan | No | 314,500 | Referral | 100 patients in referral pilot as of October 2013 |
| Central Massachusetts | Academic medical center | No | 1,000,000 | Referral | Appointment requests for 300 patients as of March 2014 |
| Southern California | Public system – county | Yes | 500,000 | Referral | 18,000 consults in 2013 |
| Southern California | Public system – county | Yes | 240,000 | Referral | 59,400 in 2013 |
| Northern California | Network of community health centers | Yes | 31,000 | Referral | 4000 patients with consults |
| Boston, Massachusetts | Academic medical center | No | data not available | Consultation | 47 consults in 3-month pilot as of October 2013 |
| Southern California | Academic medical center | No | 971,000 | Consultation | 330 consults |
| Northern California | Academic medical center | No | 232,774 | Consultation | 550 consults between April 2012 and May 2013 |
| Southern California | Advocacy organization | Yes | 400 | Consultation | 250 patients with consults in 2012 |
| Northern California | Public system – county | Yes | 100,000 | Consultation | data not available; significant volume |
| Northern California | Public system – county | Yes | 80,000 | Consultation | data not available |
| Connecticut | Network of community health centers | Yes | 130,000 | Integrated eCR | 125 consults for 120 patients |
| Southern California | Health plan | Yes | 1,300,000 | Integrated eCR | 100,000 consults |
| Southern California | Public system – county | Yes | 850,000 | Integrated eCR | 60,000 consults |
| San Francisco General Hospital | Public system – County | Yes | 123,500 | Integrated eCR | 58,000 yearly |
Main drivers, facilitators and barriers to implementation of referral, consultation and integrated eCRs and representative quotes
| Drivers | Representative quotes | |
| Referral systems | Enhance operational and clinical efficiency | “Specialists wanted to have all of the relevant clinical history for patients prior to a visit; productive visits are key and prior communication [wasn’t] sufficient.” |
| Consultation systems and Integrated eCRs | Poor access to specialty care | “The service was developed to improve access to high-need specialties with long wait times.” |
| Leakage of patients to other systems | “Drivers included coordinating and improving integration of care with the goal of retaining patients; payor data showed that approximately 30 % of patients were going outside of [organization’s name] for specialty care.” | |
| Enhance care coordination and communication | “We’re trying to build good relationships with our community clinics to create an integrated safety net care system.” “I think efficiency helps the supply–demand mismatch… we have driven down the mismatch with eConsult, not by inventing new specialists, but by using our existing specialists in a better way.” | |
| Facilitators | Representative quotes | |
| Referral systems | Engaged executive leadership | “For our program, it was important to make eConsults/eReferrals mandatory [by the leadership]. We found that [others] that did not do this had low uptake.” |
| Early clinician adopters | “Having a physician leader who was able to have dedicated time to have lots of the conversations with people, to message it, to overcome concerns and resistance, to really be the driving force behind it, I think was critical in our implementation.” | |
| Consultation systems and Integrated eCRs | Provider incentives | “[Our system] is now funding reimbursement of specialists’ time for using the service.” |
| User-friendly technology | “The template was easy to build and make friendly for staff and the doctors.” | |
| Platform integrated into electronic medical record | “We have a platform available within our electronic health record program that we were able to adapt to our need/s.” | |
| Barriers | Representative quotes | |
| Referral systems | Provider resistance to change workflows | “As you well know, unless you can mandate, it is very difficult to get PCPs to adapt if they view this as taking any more time.” |
| Lack of eCR integration into electronic medical record | “With no shared [technology], it has been difficult to get providers to [move past the workflow issues] and see the benefit of … improved integration of care.” | |
| Consultation systems or integrated eCRs | Primary care provider resistance to change in workflows | “Many physicians didn’t want to submit [the referral] themselves.” |
| Lack of reimbursement mechanisms | “The biggest barrier to adoption we faced was reimbursement. … It is this funding issue that is preventing expansion of the program to include additional specialties.” “In order to support adoption of the electronic consult system, we obtained grant funding. We are currently using the results … to build a case for the state reimbursing electronic referrals.” | |
| Specialist provider liability concerns | “When we implemented … we got quite a lot – not surprising, but consistent – feedback or questions or skepticism from specialists with the liability, specialist skepticism about whether the PCP [would] be able to provide reliable information.” | |
Unique existing evaluation metrics pertinent to referral, consultation and Integrated eCR systems, by domain
| Operational | Scheduling | Clinical | Communication | |
|---|---|---|---|---|
| Referral | • Percent of referrals completed electronically vs. fax/paper | • Percent of eReferral slots used | • Patient follow-up by electronic vs. paper/fax referral | |
| • Disposition (scheduled vs not scheduled) as determined by referral management department | • Slot availability for eReferred-patients | |||
| • Wait time for specialty service by insurance status | ||||
| Consultation and integrated eCR | • Time to first specialist response | • Self-reported PCP ability to manage a patient with specialist guidance | • Specialist satisfaction | |
| • Disposition (e.g., scheduled immediately, scheduled after review, consultation only) as determined by specialist reviewer | • Emergency department utilization | • PCP expectation for referral | ||
| • Time spent by specialist | • Cardiac outcomes: appropriate diagnoses, percent of patients with blood pressure control, PCP prescription of guideline-conoirdance cardiovascular medicationsa | • Quality of PCP referral | ||
| • Economic impact of provider reimbursement strategy | • Specialty clinic complexitya | • Quality of specialist response | ||
| • Patient leakage to other health systems for specialty care | • Number of exchanges per consult | |||
| • Primary care clinic adoption of systema | • Number of consults with document uploadsa |
aDenotes metrics that were only examined among integrated eCR systems
Fig. 1Elements of successful implementation of electronic consultation systems