Article Figures & Data
Tables
SDH Data Tools Description SDH Data Collection Tools Included 14 SDH screening questions based on PRAPARE and National Academy of Medicine recommendations. Data collection modes included: data-entry flowsheets accessible by diverse clinic staff, a print version for patients to complete after which the data would be entered by CHC staff into a flowsheet, and an online portal form that patients could complete before the visit. SDH Summary Tools Patient’s most recent SDH data displayed (as entered in flowsheets or elsewhere in the EHR), and past SDH-related referrals. SDH Data Rosters Added SDH-related data columns to the EHR’s panel management tools to identify patients who (1) had a pending visit (enabling e-mailing those with online portal accounts about completing SDH screening pre-appointment); (2) had a positive SDH screen and needed follow-up; or (3) were due for SDH screening. Problem List Created a new SDH class of problem list diagnoses, so that users could manually categorize SDH diagnoses in the problem list. SDH Referral Tools Built as preference lists, to parallel the clinics’ processes for making clinical referrals. Worked with pilot clinics to create preference lists of local resources for addressing specific SDH needs. Used to add information about relevant resources to the patient’s after-visit summary and to identify resources that clinic staff could discuss with the patient. SDH Domainsa Alcohol useb Education Exposure to violence Race/ethnicityb Financial resource strain Physical inactivity Tobacco use and exposureb Housing insecurity Social isolation Depressionb Food insecurity Stress CHC = community health centers; EHR = electronic health record; PRAPARE = Protocol for Responding to and Assessing Patient Assets, Risks, and Experiences; SDH = social determinants of health.
↵a Wording defined in Supplemental Appendix 1, available at http://www.annfammed.org/content/16/5/399/suppl/DC1/.
↵b Information on these domains is routinely documented elsewhere in the EHR so they were not included in the SDH data collection tool flowsheet. Responses, however, were pulled into the SDH summary tool.
- Table 2
Patient and Visit Characteristics of Patients Seen During the Study Period, and of Those Screened for SDH, by Clinic
Patient Characteristics Clinic A Clinic B Clinic C Total Patients No. (%) Screened Patients No. (%) Total Patients No. (%) Screened Patients No. (%) Total Patients No. (%) Screened Patients No. (%) Number of patients 4,208 (100.0) 602 (14.3) 2,126 (100.0) 379 (17.8) 3,741 (100.0) 149 (4.0) Race American Indian/AK Native 122 (2.9) 14 (2.3) 56 (2.6) 9 (2.4) 39 (1.0) 0 (0.0) Asian 50 (1.2) 5 (0.8) 30 (1.4) 4 (1.1) 494 (13.2) 9 (6.0) Black/African American 62 (1.5) 8 (1.3) 31 (1.5) 5 (1.3) 303 (8.1) 9 (6.0) Native Hawaiian/PI 39 (0.9) 6 (1.0) 15 (0.7) 5 (1.3) 21 (0.6) 2 (1.3) White 3,798 (90.3) 541 (89.9) 1,726 (81.2) 322 (85.0) 2,569 (68.7) 105 (70.5) Multiple races 73 (1.7) 12 (2.0) 88 (4.1) 13 (3.4) 70 (1.9) 4 (2.7) Unknown 64 (1.5) 16 (2.7) 180 (8.5) 21 (5.5) 245 (6.5) 20 (13.4) Hispanic Yes 403 (9.6) 40 (6.6) 627 (29.5) 75 (19.8) 531 (14.2) 22 (14.8) No 3,710 (88.2) 545 (90.5) 1,457 (68.5) 292 (77.0) 3,110 (83.1) 121 (81.2) Unknown 95 (2.3) 17 (2.8) 42 (2.0) 12 (3.2) 100 (2.7) 6 (4.0) Sex Female 2,416 (57.4) 315 (52.3) 1,287 (60.5) 200 (52.8) 1,898 (50.7) 42 (28.2) Male 1,792 (42.6) 287 (47.7) 837 (39.4) 178 (47.0) 1,843 (49.3) 107 (71.8) Unknown 0 (0.0) 0 (0.0) 2 (0.1) 1 (0.3) 0 (0.0) 0 (0.0) Age: 1st study period visit, y 18–29 1,069 (25.4) 169 (28.1) 544 (25.6) 42 (11.1) 817 (21.8) 48 (32.2) 30–49 1,793 (42.6) 241 (40.0) 872 (41.0) 142 (37.5) 1,478 (39.5) 69 (46.3) 50–64 1,173 (27.9) 170 (28.2) 551 (25.9) 140 (36.9) 1,009 (27.0) 27 (18.1) ≥65 173 (4.1) 22 (3.7) 159 (7.5) 55 (14.5) 437 (11.7) 5 (3.4) Homeless status Yes 64 (1.5) 7 (1.2) 72 (3.4) 13 (3.4) 55 (1.5) 1 (0.7) No 1,858 (44.2) 198 (32.9) 713 (33.5) 114 (30.1) 1,299 (34.7) 44 (29.5) Unknown 2,286 (54.3) 397 (65.9) 1,341 (63.1) 252 (66.5) 2,387 (63.8) 104 (69.8) Migrant/seasonal worker Yes 13 (0.3) 3 (0.5) 47 (2.2) 0 (0) 7 (0.2) 0 (0) No 1,911 (45.4) 200 (33.2) 728 (34.2) 131 (34.6) 936 (25.0) 24 (16.1) Unknown 2,284 (54.3) 399 (66.3) 1,351 (63.5) 248 (65.4) 2,798 (74.8) 125 (83.9) Primary payer Medicaid 2,957 (70.3) 416 (69.1) 1,189 (55.9) 193 (50.9) 2,313 (61.8) 84 (56.4) Medicare 455 (10.8) 52 (8.6) 215 (10.1) 78 (20.6) 567 (15.2) 13 (8.7) Other public 11 (0.3) 2 (0.3) 9 (0.4) 0 (0.0) 5 (0.1) 0 (0.0) Private 264 (6.3) 39 (6.5) 299 (14.1) 40 (10.6) 94 (2.5) 4 (2.7) Uninsured 521 (12.4) 93 (15.4) 414 (19.5) 68 (17.9) 762 (20.4) 48 (32.2) Primary language English 3,915 (93.0) 582 (96.7) 1,703 (80.1) 330 (87.1) 2,761 (73.8) 126 (84.6) Spanish 189 (4.5) 6 (1.0) 418 (19.7) 48 (12.7) 336 (9.0) 12 (8.1) Other 56 (1.3) 6 (1.0) 4 (0.2) 1 (0.3) 639 (17.1) 11 (7.4) Unknown 48 (1.1) 8 (1.3) 1 (0.0) 0 (0.0) 5 (0.1) 0 (0.0) Veteran status Yes 118 (2.8) 26 (4.3) 87 (4.1) 17 (4.5) 78 (2.1) 10 (6.7) No 4,049 (96.2) 566 (94.0) 2,032 (95.6) 360 (95.0) 3,358 (89.8) 112 (75.2) Unknown 41 (1.0) 10 (1.7) 7 (0.3) 2 (0.5) 305 (8.2) 27 (18.1) Diabetes status Yes 557 (13.2) 68 (11.3) 279 (13.1) 110 (29.0) 531 (14.2) 7 (4.7) No 3,651 (86.8) 532 (88.4) 1,847 (86.9) 269 (71.0) 3,210 (85.8) 142 (95.3) Unknown 0 (0.0) 2 (0.3) 0 (0.0) 0 (0.0) 0 (0.0) 0 (0.0) New/established patients New patients 699 (16.6) 311 (51.7) 239 (11.2) 57 (15.0) 1,251 (33.4) 142 (95.3) Established patients 3,509 (83.4) 291 (48.3) 1,887 (88.8) 322 (85.0) 2,490 (66.6) 7 (4.7) Number of visits 13,990 (100.0) 611 (4.4) 8,162 (100.0) 385 (4.7) 16,281 (100.0) 149 (0.9) Type of practioner MD, DO, Locum Tenens 2,686 (19.2) 7 (1.1) 3,892 (47.7) 209 (54.3) 7,663 (47.1) 149 (100.0) NP, PA 8,827 (63.1) 24 (3.9) 2,577 (31.6) 76 (19.7) 4,399 (27.0) 0 (0.0) RN, LPN, CHN 1,359 (9.7) 187 (30.6) 1,427 (17.5) 79 (20.5) 2,428 (14.9) 0 (0.0) MA 1,049 (7.5) 1 (0.2) 59 (0.7) 0 (0.0) 109 (0.7) 0 (0.0) BHS, LCSW … 0 (0.0) 181 (2.2) 18 (4.7) 1,550 (9.5) 0 (0.0) Eligibility specialist … 392 (64.2) … 0 (0.0) … 0 (0.0) Other 69 (0.5) 0 (0.0) 26 (0.3) 3 (0.8) 132 (0.8) 0 (0.0) Clincian status Primary care clinician 7,119 (50.9) 22 (3.6) 4,439 (54.4) 204 (53.0) 9,151 (56.2) 145 (97.3) Other 6,871 (49.1) 589 (96.4) 3,723 (45.6) 181 (47.0) 7,130 (43.8) 4 (2.7) AK = Alaska; BHS = behavioral health specialist, CHN = community health nurse; DO = doctor of osteopathy; LCSW = licensed clinical social worker; LPN = licensed practical nurse; MA = medical assistant; MD = doctor of medicine; NP = nurse practitioner; PA = physician’s assistant; PI = Pacific Islander; RN = registered nurse.
Month Distinct Patients Screened, No. Clinic A (n = 602) Clinic B (n = 379) Clinic C (n = 149) Jul 2016 1 26 9 Aug 2016 32 13 31 Sep 2016 84 8 19 Oct 2016 78 7 19 Nov 2016 78 4 27 Dec 2016 70 22 12 Jan 2017 78 23 19 Feb 2017 52 21 13 Mar 2017 33 10 0 Apr 2017 21 51 0 May 2017 30 101 0 Jun 2017 28 31 0 Jul 2017 17 62 0 SDH = social determinants of health.
Note: Clinic C data based on encounters with 1 provider. SDH screening stopped in Clinic C in February 2017 for reassessment of workflows and EHR access policies.
Study Clinic Patients Screened, No. Screened Patients With SDH Domain Domains for Patients With Positive Screen, No. (%) Patients With Positive Screen and Matching Positive SDH Screen, No. (%) SDH Referral, No. (%) SDH Referrala, No. (%) Problem List dx, No. (%) A 602 583 (96.8) 141 (23.4) Financial resource strain 426 (70.8) 105 (24.6) 22 (5.2) Housing insecurity 206 (34.2) 60 (29.1) 19 (9.2) Food insecurity 331 (55.0) 91 (27.5) 22 (6.6) Intimate partner violence 175 (29.1) 1 (0.6) 0 (0.0) Inadequate physical activity 311 (51.7) 0 (0.0) 0 (0.0) Social isolation 433 (71.9) 12 (2.8) 4 (0.9) Stress 436 (72.4) 0 (0.0) 2 (0.5) B 379 367 (96.8) 26 (6.8) Financial resource strain 277 (73.1) 1 (0.4) 0 (0.0) Housing insecurity 103 (27.2) 3 (2.9) 0 (0.0) Food insecurity 216 (57.0) 0 (0.0) 0 (0.0) Intimate partner violence 94 (24.8) 0 (0.0) 0 (0.0) Inadequate physical activity 167 (44.1) 0 (0.0) 0 (0.0) Social isolation 235 (62.0) 0 (0.0) 0 (0.0) Stress 253 (66.8) 0 (0.0) 2 (0.8) C 149 148 (99.3) 44 (29.5) Financial resource strain 107 (71.8) 3 (2.8) 1 (0.9) Housing insecurity 56 (37.6) 3 (5.4) 1 (1.8) Food insecurity 86 (57.7) 2 (2.3) 0 (0.0) Intimate partner violence 36 (24.2) 0 (0.0) 0 (0.0) Inadequate physical activity 63 (42.3) 0 (0.0) 0 (0.0) Social isolation 111 (74.5) 1 (0.9) 0 (0.0) Stress 107 (71.8) 1 (0.9) 8 (7.5) dx = diagnosis; EHR = electronic health record; SDH = social determinants of health.
↵a Referrals were matched to screening domains based on evaluation of EHR documentation associated with the referral order, including type and/or specialty of the referral provider and diagnoses associated with the referral.
Additional Files
Supplemental Appendixes 1-3
Supplemental Appendixes 1-3
Files in this Data Supplement:
- Supplemental data: Appendixes - PDF file
The Article in Brief
Adoption of Social Determinants of Health EHR Tools by Community Health Centers
Rachel Gold , and colleagues
Background A growing awareness that social factors--the conditions in which people live, work and play--influence health suggests that it is crucial to document such information in patients' electronic health records. This pilot study assesses the feasibility of implementing electronic health record tools for collecting, reviewing, and acting on patient-reported social determinants of health data in community health centers.
What This Study Found The study found that adopting EHR tools to systematically document social determinants of health in primary care is feasible, but substantial barriers exist. Researchers implemented social determinants data tools in three Pacific Northwest community health centers. Among 1,130 patients for whom social determinants data were collected, 97 to 99 percent (n = 1,098) had one or more social need documented in the EHR, with 210 (19 percent) receiving an EHR-documented social determinants referral. Fifteen to 21 percent of patients with a documented social need wanted help from the clinic to address the need. Although the study identified many barriers to implementing and designing tools and workflows, participating community health centers successfully documented social determinants in the EHR and continued to do so post-study.
Implications
- The authors explain that, to meet the growing national emphasis on documentation of social determinants of health in EHRs, a wide range of factors and substantial gaps in knowledge must be addressed.
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