Introduction and Background

In 2007 the Washington State Legislature passed a bill mandating that the Health Care Authority (a state agency) implement a shared decision making (SDM) demonstration project at one or more multi-specialty practice sites. Because the legislation did not include appropriated funds, the Health Care Authority sought collaborators for the demonstration. Researchers from the University of Washington obtained funding to facilitate an SDM and decision aid (DA) demonstration project. Three practice sites in western Washington are currently participating in the project. The demonstration project began in 2008. Early steps in the project included obtaining IRB approval, identifying executive champions and project managers at each site, choosing conditions of interest, and creating workflow process maps. Once this was accomplished, the sites began to distribute DAs. Multiple barriers, anticipated and unanticipated, were identified at this stage of the project. The following is a description of the identified barriers and methods used to overcome those barriers.

Site

The Everett Clinic

Demonstration sites and conditions of interest

Location

Everett, WA

Conditions of Interest

- Hip Osteoarthritis - Knee Osteoarthritis MultiCare Medical Group Tacoma, WA Virginia Mason Medical Center Seattle, WA - Low Back Pain - Chronic Pain - Depression - Diabetes - PSA Testing - Colon Cancer Screening - Ductal Carcinoma In Situ - Early Stage Breast Cancer

Supported in part by:

- Foundation for Informed Medical Decision Making - Health Dialog - National Center for Medical Rehabilitation Research, National Institutes of Health (T32HD007424)

Identifying and Overcoming Barriers to Implementation of Shared Decision Making and Decision Aids

Megan A. Morris, MS CCC-SLP

1

1,2

; Anne D. Renz, MPH

1

; Douglas A. Conrad, PhD, MBA, MHA

1

; Carolyn A. Watts, PhD

1

Dept. of Health Services, University of Washington, Seattle, Washington, USA

2

Dept. of Rehabilitation Medicine, University of Washington, Seattle, Washington, USA

Methods to Identify Barriers

1. Key informant interviews with clinical and operational staff 2. Monthly meetings with partners from the implementation sites 3. Monthly conference calls with 11 SDM demonstration sites across the U.S.

4. Synthesis of SDM-related journal articles, news articles, and state and federal legislation • • • • •

Identified Barriers

Barriers vary significantly by site, in part because of differences in how sites identify

•

patients and distribute DAs. Barriers include:

Capabilities of electronic medical records Patient volume Availability of support staff Wait times for appointments The nature of the targeted health conditions Competing priorities within the system • • • • • • •

Key Strategies to Overcome Barriers

Early identification of clinical and staff champions Alignment of SDM with other strategic initiatives and goals of the organization Creation of DA distribution workflow maps; review and revision of the process maps a few months post implementation Inclusion of steps to feed data back to providers and to solicit provider input Designation of a dedicated care coordinator to handle logistics and close the loop with patients (e.g., nurse navigator, health coach) Creation of a toolbox with sample templates to explain SDM to providers, staff, and patients Connection to a network of other sites that are implementing SDM

Examples of Different Methods of DA Distribution

Patient Identification Methods

Examples of methods of identifying patients eligible to receive decision aids: 1. During office visits, providers identify patients eligible to receive a DA. 2. Reception staff who are familiar with the patients can notify a provider about potential eligibility.

3. EPIC referrals from primary care to a specialty department are placed in a queue to receive a DA.

Corresponding DA Distribution

Examples of methods of distributing decision aids to patients: 1. After the visit, the provider refers the patient to the care coordinator down the hall. The care coordinator introduces the DA and hands it to the patient. 2. Exam rooms are kept stocked with DAs; provider hands DA to patient during the office visit.

3. Receptionists monitor the referral queue. When they call to schedule a specialty appointment, they introduce the DA and mail it to the patient.

Case Example

Summary:

The volume of patients identified by the electronic referral system for a common condition was significantly lower than expected; the majority of appropriate patients were not receiving DAs for which they were eligible.

• • •

Methods of Identifying the Barrier:

Met and discussed with other site groups (at monthly meeting) Changed diagnosis codes to be broader. This yielded a high number of patients. The front desk staff was in charge of screening patients to determine eligibility to receive DAs. The staff was overwhelmed with multiple tasks and distributing DAs fell to the bottom of the priority list.

Re-examined the referral queue code

Result:

The site had an electronic medical record system that used ICD-9 codes with an IMO letter (example: 784.15C). The original code for the referral queue was written to accept five digits (not the additional letter), so nearly all referrals for that particular condition were missed. Once the referral code was re-written, the number of patients identified for receiving increased dramatically from 3 DAs in 6 months to 26 DAs in 4 weeks.

Conclusions

Shared decision making can be implemented in a multispecialty fee-for-service system. Barriers to implementation can be overcome with engaged champions, operational planning, and communication with a network of other implementation sites.