Interdisciplinary Development of Electronic Palliative Care Decision Support

Purpose: Palliative care (PC) is patient and family-centered medical care that prevents or treats symptoms and side effects of disease and treatment.(Wysham et al., 2016) PC is associated with more efficient resource use and decreased medical costs.(Bernacki et al., 2012) Ideally, PC is proactive and begun early in the illness in conjunction with other life prolonging therapies. Unfortunately, many PC consultations are reactive and occur in the acute care setting, once patient symptoms have become unbearable.(Aldridge et al., 2016; Grudzen, Hwang, Cohen, Fischman, & Morrison, 2012) Methods: Palliative care (PC) is patient and family-centered medical care that prevents or treats symptoms and side effects of disease and treatment.(Wysham et al., 2016) PC is associated with more efficient resource use and decreased medical costs.(Bernacki et al., 2012) Ideally, PC is proactive and begun early in the illness in conjunction with other life prolonging therapies. Unfortunately, many PC consultations are reactive and occur in the acute care setting, once patient symptoms have become unbearable.(Aldridge et al., 2016; Grudzen, Hwang, Cohen, Fischman, & Morrison, 2012)

Although there are few published examples in the literature of inter-disciplinary teams engaging and designing health information systems to support team processes, the nature of the EHR to capture the complexity of PC patients with multiple providers suggests it could provide the foundation for improving communication among patients, caregivers, providers, and could improve the timeliness of identifying programs and effectiveness of follow-up.(Dy et al., 2011; Tsavatewa, Musa, & Ramsingh, 2012) The targeted technology available in the EHR, including clinical decision support (CDS) could facilitate screening patients for earlier identification of patients in or about to be in distress; to provide more appropriate referrals to specialized care; and to facilitate more rapid communication among patients, caregivers, and clinicians.(Allsop et al., 2016; Chih et al., 2013; Hocker et al., 2015)A clinical-academic partnership was formed among a southern California health system and a school of nursing including palliative care nurses, EHR report writers, and research scientists to create a list of desired elements grounded in both clinical relevance and current scientific literature to be used to identify oncology patients who could benefit from a PC referral. The initial list of data points in the EHR was edited for redundancies and pathways were created to draw data from different EHR databases to create an efficient report of patient demographics, resource utilization, and clinical indicators.

Semi-structured interviews were carried out with a purposive sample of health professionals and EHR programmers who were part of the healthcare system’s palliative care steering group. Using a pragmatic qualitative approach, the study aimed to capture a representative view of key stakeholders/end users to inform implementation of the needed screening list. Six nurses, 4 physicians, 1 administrator, and 10 other clinicians and support staff were recruited. The participants offered their thoughts on the inclusion of needed information to build the correct patient profile. Negotiation of data points was based on role, system healthcare goals, and past experience with palliative care and oncology. They reviewed eight iterations of the trigger list until a final version of the preliminary report was designed. The report included a total of 49 items. Query results were validated by manual chart audits of 10%.

Results:

A randomized sample of 694 patients enrolled in palliative care services at three hospitals within the large multi-community hospital healthcare system from January 1, 2013 to December 31, 2015 were identified and the elements of the trigger list matched against their electronic chart retrospectively. Of these 51.7% were male, 65.4% were White, and 80.8% were English speaking. Almost half (49.7%) were Medicare recipients and 51.4% declared themselves as a ‘do-not-resuscitate’ (DNR). Nearly, all patients (97.6%) who would have been identified by the trigger list had been seen by a palliative care nurse. Successfully matched variables included the International Statistical Classification of Disease and Related Health Problems (ICD-9) code, admission date, gender, ethnicity, religion, language, age, insurance, code status, completion of an advance directive, emergency department visits, intensive care unit (ICU) admissions, less than 30 day readmission, and if the patient was on hospice within the last 24 months. Manual review was need to provide clinical details such as difficulty swallowing, unresponsiveness, oxygen dependency, inability to move self up in bed, inability to sit in bed, and presence of a palliative care or hospice note.

Conclusion:

Healthcare systems are exploring the use of CDS and related electronic algorithms as a way to alert clinicians and trigger a palliative care assessment based on patient symptomatology gathered in the EHR. This study demonstrated that a computer generated report is usefully for identifying individuals appropriate for palliative care. The next steps include further algorithm development; end-user testing; and data marker refinement to increase patient identification sensitivity. Although the project is still maturing, a key finding was that the interdisciplinary team worked well for the design of the approach, as well as its placement within the work flow.