Socio-behavioral determinants of health (SBDH) Data Catalog

Socio-behavioral determinants of health (SBDH) – a combination of behavioral, social, economic, environmental, and occupational factors – are powerful drivers of morbidity, mortality, and future well-being of individuals and communities, yet they mostly lie outside domain of the conventional medical care delivery system. Modifiable behaviors and exposures that occur in the community play a significant role in 60% of preventable deaths in the U.S.1

Social and Non Clinical Risk Factors

Social and Non Clinical Risk Factors2

Project Executive Summary

In 2017, the Institute for Clinical and Translational Research’s (ICTR) Behavioral, Social and Systems Science (BSSS) Translational Research Community (TRC) advisory board funded this project to examine the availability of social and behavioral data in JHMI’s EPIC EMR/PHR systems. Both researchers and administrators recognize that patients’ socio-behavioral determinants play a critical role their care experiences and outcomes. Being located in Maryland with its global budgets and population-based reimbursement scheme, it is advantageous for JHU/JHMI to find cost-effective, community-level solutions that improve the population’s health status. The vision of the BSSS TRC board is to enable JHU researchers to utilize social and behavioral data collected from JHMI patients and stored in various data sources such as EPIC.

EHR data (i.e., Epic) will play an instrumental role in population health management efforts of value-based providers such as JHMI[3-9]. EHR-extracted socio-behavioral determinants data can potentially help to coordinate care and risk stratification efforts [10]. However, certain challenges will remain while extracting socio-behavior factors from JHMI’s Epic such as: data quality issues and missing socio-behavioral data [11-12], ongoing immaturity of EHR’s advanced functionality across various providers [13], and the need for complex methods to extract socio-behavioral determinants from EHR’s unstructured text [14].

Given the increasing alignment of population and public health efforts [15-18], identifying socio-behavioral factors of high-risk JHMI patients will be key in addressing underlying disparities within JHMI’s population as Maryland’s all-payer waiver program is already piloting population-level outcome measures [19-20]. Using non-Epic data sources, such as CRISP information (i.e., Maryland’s health information exchange), can also be used to extract socio-behavioral determinant data [21].

For the purposes of this project, Epic is the sole data source. No legacy or ancillary systems were queried. As of 7/1/2018, there are approximately 5.4 million unique patients in Epic. The contents of this page will be reviewed and updated regularly.

Phase I Social Project Guide

Phase II Social Project Guide

Data Availability Timeline

The following diagram depicts the approximate timeline for when data was migrated into Epic or when Epic began capturing data, segmented by data type and facility.

Data Availability Timeline for Epic Go Live

Data Variables

Address/Zip Code

Most Common Collection Method

The most common method to collect patient permanent address is upon registration of each encounter. Address is defined as a street address/number, an optional line for apartment or other information, a city, a state or province, and a zip code.

General Completeness Rate

95% – out of approximately 5.4 million patients, 5.2 million patients have indicated a permanent address using this collection method.

Collection Date Range

Permanent address was migrated into Epic beginning in 2003 and is currently collected.

Facility Type (Inpatient or Outpatient)

Permanent address is collected at all facilities at the time of registration.

Address History

In 66% of the 5.4 million patients in Epic, there are address change records available. Effective start and end dates are included to track address changes over time. Address change records were first collected in 2003 and are currently tracked.

Other Collection Methods

In addition to the most commonly collected method, patient address is captured in the following cases:

Collection Method Completeness Rate Facility/Provider Dates of Collection
Hospital Account 73% of the 7.3 million hospital accounts Inpatient facilities, primarily in imaging and PT services at Howard County General and Sibley Memorial Hospital.  2013 – current
Temporary Address .3% out of 5.4 million patients  All facilities at the time of registration  2003 – current
Billing Address  99% of 2.1 million patient accounts where the guarantor is the patient  All facilities at the time of registration   2003 – current
Claims Processing Address  100% of 4.9 million claims where the patient was listed  2013 – current
Insurance Coverage Address  92% of 3.1 million coverage records where the subscriber is also the patient  All facilities at the time of registration  2006 – current
Home Health Encounters and Episodes 99% of the 41,604 home care encounters  At the time of the Home Health scheduling encounter  September 2015 – current
MyChart Patient Proxy Addresses 79% of the 30,410 MyChart proxy records  MyChart proxies are MyChart users who log in to MyChart on behalf of a patient. In this case, proxies are not patients. Note that address is not complete for all records.
Communications for Specific Encounters 100% of the 747,616 encounter-based communications  Clinicians have the ability in Epic to track communications associated with specific encounters. The most common provider types are physicians and medical assistants.  2013 – current
Social Work Assessment Questionnaire: Primary Caregiver Address Question 7% of the 14,129 times that the questionnaire was completed, address was provided. Sibley and Bayview inpatient emergency services, by social workers July 2014 – current
Social Work Assessment Questionnaire: Patient Address 7% of the 14,129 times the template was used and the question was answered This questionnaire focuses on the patient’s social, economic, safety, and psychological well-being. Captured at inpatient admissions by social workers. June 2014 – current
Maltreatment Assessment: Father’s address/Mother’s address 7% of the 14,129 times the template was used and the question was answered JHH Pediatric ED, other pediatric clinics, by social workers. April 2013 – current

Alcohol Use

Most Common Collection Method

Alcohol use is captured in the Social History portion of Epic during a patient encounter, whether in-person or non in-person encounters (telephone, MyChart, documentation). For the purposes of this data catalog, the variable of focus is “Alcohol Drinks Per Week”.

Collection Date Range

Social History has been collected since April 2013 and is currently collected.

General Completeness Rate

Of the approximately 5.4 million patients, 490,348 (.09%) patients reported having any value (including 0 alcoholic drinks per week) in social history. 178,789 (.03%) reported having one or more alcoholic drinks per week.

Facility Type (Inpatient or Outpatient)

Alcohol use is collected at all facilities at the time of an encounter.

Other Collection Methods

For future revisions of this data catalog, alcohol use data collected from flowsheets, questionnaires, and clinical notes will be included.

Ethnicity

Epic captures a patient’s ethnicity separate from a patient’s race, and ethnicity is defined as either Hispanic or Not Hispanic.

Most Common Collection Method

The most common method to collect patient ethnicity is upon registration of each encounter.

General Completeness Rate

50% – out of approximately 5.4 million patients, 2.7 million patients have indicated ethnicity using this collection method.

Collection Date Range

Ethnicity has been collected in Epic since 2003 and is currently collected.

Facility Type (Inpatient or Outpatient)

Ethnicity was migrated into Epic beginning in 2003 and is currently collected.

Other Collection Methods

In addition to the most commonly collected method, ethnicity is captured in the following cases:

Collection Method Completeness Rate Facility/Provider Dates of Collection
Transplant Organ Donors 50% of the 4,647 human transplant donors in Epic August 1996 – present
Ethnicity Questionnaire In 20% of the 2,471 times that the questionnaire was completed, the question “What is your race/ethnicity” was answered. The choices for selection are “Black”, “Hispanic”, and “Neither Black Nor Hispanic”. Inpatient encounters at Johns Hopkins Hospital by registered nurses and case workers. Between January 2016 and October 2016
Ethnicity Origin Questionnaire In 5% of the 3,558 times that the questionnaire was completed, the questions “Father’s Ethnic Origin” and “Mother’s Ethnic Origin” were answered. The choices for selection are:

  • Caucasian
  • Hispanic
  • Black
  • Asian
  • Middle Eastern
  • Other
Two ophthalmology clinics by technicians Between April 2013 and September 2017
Pregnancy/Delivery Episodes: Father’s Ethnicity .1% of the 109,574 combined pregnancy episodes

The choices for selection are:

  • Not Hispanic or Latino
  • Hispanic or Latino
  • Unknown
  • Patient Refused
Two JHCP OB/GYN outpatient clinics 2015 – current

Income/Financial Issues

Patients with income/financial issues are patients in deteriorated financial status, financial hardship, or in poverty. They are unable to afford the basics of life and/or medical interventions. They are in need and eligible for any benefit or enrolment in financial assistant programs.

Collection Methods

In order to determine the population and distribution of patients having income/financial issues, several collection methods were utilized.

Diagnosis Codes (ICD-10)*

Searching Epic for patients having ICD-10 coded diagnoses on the problem list, billing codes, or recorded at the time of an encounter yielded the following results:

ICD-10 Code Patient Count
Z59.7 Insufficient Social Insurance and Welfare Support 46
Z59.8 Other Problems Related to Housing and Economic Circumstances 3,357
Z59.5 Extreme Poverty 68
Z59.6 Low Income 72

* Patients with ICD-9 coded diagnoses are also included in this query. The timeframe is January 1, 2003 through June 26, 2018.

Clinical Notes

Using Natural Language Processing (NLP) techniques, keyword phrases indicating specific SDH were extracted from 23 million clinic notes authored by specific provider types between July 1, 2016 and May 31, 2018. The notes represent 1,188,202 unique patients and 9,066,508 unique encounters.3

We pre-processed the notes to mark the line boundaries and remove non-Unicode characters. To identify notes containing SDH, we used hand-crafted linguistic patterns developed by a team of experts based on SDH descriptions in LOINC, SNOMED, ICD10, Public Health Surveys and Instruments (ACS, American Housing Survey, NHANE, etc.), phrases from the literature review and other studies, and manual tagging.

To craft the linguistic patterns, the expert team focused on three domains: Housing, Finance, and Social Support.

Findings for Financial Issues:
  • Of the 1,188,202 unique patients, 1% have at least one note containing mentions of financial issues.
  • Of the 20,219 notes containing mentions of financial issues, about 52% were authored by physicians, 37% were authored by social workers, 8% were authored by nurses, 3% were authored by case managers and case coordinators.
  • The top note types for mentions of social support are progress notes (46%), H&P notes (8%), treatment plans (6%), consults (6%), with the remaining note types dispersed among committee review, patient instructions, discharge summaries, and plan of care notes.

Housing Issues

Housing issues are categorized to those related to housing instability or insecurity, homelessness, and characteristics of the house and a number of sub-categories as follows:

  • Housing Instability
    1. Having a House with Problems
    2. Prone to Homelessness
  • Homelessness
    1. Currently Homeless
    2. Homelessness Being Addressed
  • Housing Characteristics
    1. Quality of Building
    2. Characteristics of Building
    3. Building Environmental Health Hazards
      1. Air Quality (Including Mold)
      2. Infestation
      3. Old Paint
      4. Hazardous Material and Fire Protection
      1. Problems with House Amenities
        1. Water
        2. Sewage and Disposal
        3. Fuel and Heating/ Cooling System
        4. Electricity and Internet
        1. Age of Building
        2. Quality Problems Being Addressed

Collection Methods

In order to determine the population and distribution of patients having a housing insecurity situation, several collection methods were utilized.

Diagnosis Codes (ICD-10)*

Searching Epic for patients having ICD-10 coded diagnoses on the problem list, billing codes, or recorded at the time of an encounter yielded the following results:

ICD-10 Code Patient Count
Z59.0 (Homelessness) 7,022
Z59.1 (Inadequate Housing) 120
Z59.8 (Other problems related to housing and economic circumstances) 3,291

* Patients with ICD-9 coded diagnoses are also included in this query. The timeframe is January 1, 2003 through May 31, 2018.

Clinical Notes

Using Natural Language Processing (NLP) techniques, keyword phrases indicating specific SDH were extracted from 23 million clinic notes authored by specific provider types between July 1, 2016 and May 31, 2018. The notes represent 1,188,202 unique patients and 9,066,508 unique encounters.3

We pre-processed the notes to mark the line boundaries and remove non-Unicode characters. To identify notes containing SDH, we used hand-crafted linguistic patterns developed by a team of experts based on SDH descriptions in LOINC, SNOMED, ICD10, Public Health Surveys and Instruments (ACS, American Housing Survey, NHANE, etc.), phrases from the literature review and other studies, and manual tagging.

To craft the linguistic patterns, the expert team focused on three domains: Housing, Finance, and Social Support. We delved into the housing domain by created patterns for its subdomains, including homelessness, prone to homelessness, homelessness being addressed, housing instability, housing characteristics – characteristics of the building, housing characteristics – the quality of the building.

Findings:

  • Of the 1,188,202 unique patients, 3% have at least one note containing mentions of housing issues.
  • Of the 108,439 notes containing mentions of housing issues, about 53% were authored by physicians, 32% were authored by social workers, 10% were authored by nurses, 5% were authored by case managers.
  • The top note types for mentions of housing issues are progress notes (46%), ED provider notes (13%), H&P notes (8%), with the remaining note types dispersed among discharge summaries, consults, and plan of care notes.
  • Manual annotation of 100 randomly selected notes containing the phrase “homeless” revealed:
    • Out of 100 notes, there are 130 mentions of the word “homeless”.
    • In 2 out of 100 notes, there were conflicting true positives and false positives within the same note.
    • In 20 out of 100 notes, there were true negatives (the note was derived from a SmartPhrase), and the answer to Homeless Y/N was No.
    • From the remaining notes, 64% were true positives, and 14% were false positives. The other notes were true negatives or unclear.
  • The following numbers show the count of notes containing specific variables from the housing subdomains:
    • Homelessness Being Addressed: 82
    • Housing Instability: 5,653
    • Housing Characteristics – Characteristics of the Building:148
    • Housing Characteristics – Quality of the Building: 2,011

Questionnaires

Several questionnaires exist in Epic that capture data related to housing issues. Each is described briefly below, including frequency, general completeness rate, and facility type where the questionnaire answers were completed. Please note that data provided on general completeness reflects questions that were available to an Epic user and were answered.

Questionnaire template Question Completeness Rate Facility/Provider Dates of Collection
Housing/Utility Voucher-Moore Clinic Housing Assistance Provided? Of the 217 times the times that the questionnaire was completed, 97 (44%) indicated that housing financial assistance was awarded. Bartlett HIV Clinics by social workers and case managers March 2017 – current
Abuse/Neglect Screen Homeless Of the 12,058 times that the questionnaire was completed, 96% answered the question of homelessness  (yes or no). The top four facilities that answer the question are the infusion center at Sibley Memorial Hospital, the Breast Clinic at Howard County General Hospital, Physical Therapy at Howard County General Hospital, and the Howard County General Wound Center. The top providers completing the form at these facilities are registered nurses, physical therapists, and wound ostomy and continence nurses. June 2013 – current
Screening, Brief Intervention, and Referral to Treatment (SBIRT) Social History Questionnaire Need Help Finding Housing? Of the 1,900 times that the questionnaire was completed, 96% answered the question (yes or no). The top two facilities that answer the question are Bayview Emergency Services and the BMC Chemical Dependency Unit. Peer recovery coaches complete this question.  July 2017 – current
ED Triage Abuse Indicators and Resource Planning Patient indicators, resource planning, and outcomes for shelter, transportation, and clothing Of the 713,702 times that the questionnaire was completed, 5.5% answered the questions. Inpatient, mostly in emergency units, by registered nurses. May 2013 – current
Sibley Chemical Dependence Unit Admission Screen Homeless Of the 15,056 times that the questionnaire was completed, 15% answered the question. The top facility that answers the question is the Sibley Memorial Hospital Clinical Decision Unit, by registered nurses.  July 2014 – present
Ambulatory Priority Access Primary Care (PAPC) Screen What is Your Housing Situation? Of the 1,116 times that the questionnaire was completed, 7% answered the question. JHCP Internal Medicine EBMC is the only facility that captured this information, by physicians and medical assistants  April 2015 – May 2017
Adult Admission General Intake Form  Homeless Of the 77,230 times that the questionnaire was completed, 35% answered the question (yes/no). Top facilities where the template was used are inpatient units at Sibley Memorial Hospital and Howard County General Hospital, by registered nurses.  May 2013 – April 2016
Pediatric/Newborn General Intake Form  Homeless Of the 1,067 times that the questionnaire was completed, 55% answered the question (yes/no). Top facilities are inpatient units at Johns Hopkins Hospital and Bayview Medical Center, by social workers. The form was not widely used until 2016. It is currently used.
JHM Psychiatry Social Work Assessment Living Arrangement Of the 4,913 times that the questionnaire was completed, 90% answered the question. The top facility is BMC inpatient Psychiatry, by social workers. September 2015 – current

Language

Most Common Collection Method

Patient preferred language is captured in Epic at the time of admission.

Collection Date Range

Preferred language was migrated into Epic beginning in 2003 and is currently collected.

General Completeness Rate

Of the approximately 5.4 million patients, 2,718,416 patients (49%) have indicated a preferred language in Epic. Of those indicating a preferred language, 2,624,122 indicated English as their preferred language.

The top 7 preferred languages, by unique patient count are as follows:

  1. No language reported (null) – 2,804,973 (51%)
  2. English – 2,626,379 (48.5%)
  3. Spanish – 53,446 (1%)
  4. Arabic – 7,317 (.1%)
  5. Unknown (a valid value in Epic, different from an empty record) – 5,936  (.1%)
  6. Chinese (Mandarin) – 4,036  (.1%)
  7. Korean – 3,168  (.1%)

Facility Type (Inpatient or Outpatient)

Preferred language is collected at all facilities at the time of an encounter.

Other Collection Methods

For future revisions of this data catalog, preferred language collected from flowsheets, questionnaires, and clinical notes will be included.

Race

Most Common Collection Method

The most common method to collect patient race is upon registration of each encounter. Patients can select multiple races to self-identify:

        • American Indian or Alaska Native
        • Asian
        • Black or African American
        • Declined to Answer
        • Native Hawaiian or Other Pacific Islander
        • Other
        • Unknown
        • White or Caucasian

General Completeness Rate

90% – out of approximately 5.4 million patients, 4.9 million patients have indicated at least one race using this collection method.

Collection Date Range

Race was migrated into Epic beginning in 2003 and is currently collected.

Facility Type (Inpatient or Outpatient)

Race is collected at all facilities at the time of registration.

Other Collection Methods

In addition to the most commonly collected method, race is captured in the following cases:

Collection Method Completeness Rate Facility/Provider Dates of Collection
Home Health 84% of the 40,301 Home Health episodes in Epic. For Home Health encounters only, patients can select multiple races to self-identify. The selections differ from the most common collection method:

  • American Indian or Alaska Native
  • Asian
  • Black or African-American
  • Hispanic or Latino
  • Native Hawaiian or Pacific Islander
  • White
 2004 – current
BCRA Race .05% of the 113 million BCRA encounters Race is also collected at outpatient and inpatient encounters at breast imaging, ultrasound, and MRI clinics throughout the institution.

One race per patient is selected, and race selection is restricted to the following:

  • White
  • African American
  • Hispanic
  • Chinese American
  • Japanese American
  • Filipino American
  • Hawaiian
  • Pacific Islander
  • Other Asian American
May 2013 – current
Transplant Organ Donors 44% of the 4,602 organ donors Multiple races are captured for each donor from the same selections as available during the patient registration process. 1996 – current
Race Questionnaire 7.4% of the 1,748 times the questionnaire was used at an HIV clinic encounter Race is documented for patients seen in the JHH HIV Clinics, specifically collected by social workers and case managers. Only one race can be selected. Selections are restricted to the following:

  • White
  • Black or African American
  • Asian
  • Native Hawaiian or Other Pacific Islander
  • American Indian or Alaska Native
  • Other (Comment)
 April 2013 – current

Smoking Status

Most Common Collection Method

Smoking status is captured in the Social History portion of Epic during a patient encounter, whether in-person or non in-person encounters (telephone, MyChart, documentation). For the purposes of this data catalog, the variable of focus is “Smoking Status”.

Collection Date Range

Smoking status has been collected since April 2013 and is currently collected.

General Completeness Rate

Of the approximately 5.4 million patients, 1,728,749 patients (32%) reported having any value smoking status in social history. Smoking Quit Date is also populated, but only in 137,958 (3%) of the time. The status breakdown, with collection rate, is as follows:

Smoking Status selection options include:

  • Current Every Day Smoker (114,566 – 2.1%)
  • Current Some Day Smoker (28,547 – .5%)
  • Former Smoker – (297,099 – 5.5%)
  • Heavy Tobacco Smoker (3,111 – .1%)
  • Light Tobacco Smoker (12,857 – .2%)
  • Never Assessed (302,631 – 5.6%)
  • Never Smoker – (952,636 – 17.7)
  • Passive Smoke Exposure – Never Smoker – (4,274 – .1%)
  • Smoker, Current Status Unknown – (1,133 – < .01%)
  • Unknown if Ever Smoked – (11,915 – < .2%)

Facility Type (Inpatient or Outpatient)

Smoking status is collected at all facilities at the time of an encounter.

Other Collection Methods

For future revisions of this data catalog, alcohol use data collected from flowsheets, questionnaires, and clinical notes will be included.

Social Support

Lack of Social Support (Social Isolation) or At Risk for Social Isolation

Referred to patients in deteriorated aloneness state with lack of interaction with others, feel lonely, detached, and isolated with no help and support system. They have restricted social participation and can’t maintain social relationships. They are unable to communicate with others and have difficulty visiting friends, attending clubs, meetings, and going to parties. They might be the target of perceived adverse discrimination or persecution.

Collection Methods

In order to determine the population and distribution of patients lacking social support, several collection methods were utilized.

Diagnosis Codes (ICD-10) *

Searching Epic for patients having ICD-10 coded diagnoses on the problem list, billing codes, or recorded at the time of an encounter yielded the following results:

ICD-10 Code Patient Count
R45.8 Other symptoms and signs involving emotional state 3,340
Z60.4 Social Exclusion and Rejection  223
Z60.2 Problems related to living alone 1,222
Z63.0 Problems in relationship with spouse or partner 852
Z63.5 Disruption of family by separation and divorce 548
Z63.8 Other specified problems related to primary support group 2,230
Z63.9 Problem related to primary support group, unspecified 3,247
Z65.9 Problems related to unspecified psychosocial circumstances 938
Z73.4 Inadequate social skills, not elsewhere classified 81
Z91.89 Other specified personal risk factors, not elsewhere classified 18,947

* Patients with ICD-9 coded diagnoses are also included in this query. The timeframe is January 1, 2003 through May 31, 2018.

Clinical Notes

Using Natural Language Processing (NLP) techniques, keyword phrases indicating specific SDH were extracted from 23 million clinic notes authored by specific provider types between July 1, 2016 and May 31, 2018. The notes represent 1,188,202 unique patients and 9,066,508 unique encounters.3

We pre-processed the notes to mark the line boundaries and remove non-Unicode characters. To identify notes containing SDH, we used hand-crafted linguistic patterns developed by a team of experts based on SDH descriptions in LOINC, SNOMED, ICD10, Public Health Surveys and Instruments (ACS, American Housing Survey, NHANE, etc.), phrases from the literature review and other studies, and manual tagging.

To craft the linguistic patterns, the expert team focused on three domains: Housing, Finance, and Social Support.

Findings for Social Support:

  • Of the 1,188,202 unique patients 2.6% have at least one note containing mentions of social support.
  • Of the 63,185 notes containing mentions of social support, about 70% were authored by physicians, 15% were authored by nurses, 13% were authored by social workers, 2% were authored by case managers and case coordinators.
  • The top note types for mentions of social support are progress notes (46%), H&P notes (8%), treatment plans (6%), consults (6%), with the remaining note types dispersed among committee review, patient instructions, discharge summaries, and plan of care notes.

Questionnaires

Several questionnaires exist in Epic that capture data related to social support. Each is described briefly below, including frequency, general completeness rate, and facility type where the questionnaire answers were completed. Please note that data provided on general completeness reflects questions that were available to an Epic user and were answered.

Questionnaire template Question Completeness Rate Facility/Provider Dates of Collection
Nursing Assessment – Psychosocial Psychosocial (WDL) Of the 1,026,988 times that the questionnaire was completed, 92% answered the question. Top units are inpatient units at Howard County General and Suburban Hospital by registered nurses, licensed practical nurses, and case managers May 2013 – current
ED Assess Head to Toe Psychosocial (WDL) Of the 237,143 times that the questionnaire was completed, 39% answered the question. The top site is the inpatient SH Clinical Decision Unit, Suburban Hospital by registered nurses October 2013 – current
T AD ED Nursing Assessment Psychosocial (WDL) Of the 217,954 times that the questionnaire was completed, 94% answered the question. The top units are emergency medicine inpatient units at Johns Hopkins Hospital and Bayview Medical Center by registered nurses December 2015 – current
T CD ED NURSING ASSESSMENT Psychosocial (WDL) Of the 278,084 times that the questionnaire was completed, 61% answered the question. The top units are emergency units at Howard County General Hospital, Sibley Memorial Hospital, and Suburban Hospital by registered nurses December 2015 – current
T AD/CD ED PEDS ASSESSMENT Psychosocial (WDL) Of the 131,134 times the questionnaire was completed, 71% answered the question. The top units are pediatric emergency departments at Johns Hopkins Hospital, Bayview Medical Center, Sibley Memorial Hospital, and Howard County General Hospital by registered nurses December 2015 – current
T JHM OR AD PACU FLOWSHEET Psychosocial (WDL) Of the 147,694 times the questionnaire was completed, 56% answered the question. Inpatient post-anesthesia units at Johns Hopkins Hospital by registered nurses September 2015 – current
JHM IP OT NEW HOME SETUP Social support available at discharge Of the 131,948 times the questionnaire was completed, 36% answered the question. Inpatient orthopedic and surgical floors at Bayview Medical Center and Suburban Hospital by occupational therapists June 2015 – current
IP OB POSTPARTUM Recent loss, or change in status? (Includes loss of social status, job, divorce, death, demotion, etc.) / Has multiple friends/family members with several close confidants? Of the 135,587 times the questionnaire was completed, 89% answered the question. The top units were Howard County General and Sibley Memorial inpatient units by registered nurses May 2013 – current
IP SPIRITUAL CARE INTERVENTIONS Spiritual/Social Network Of the 116,719 times the questionnaire was completed, 59% answered the question. The top units are Howard County General and Sibley Memorial inpatient units by chaplains. May 2013
PED SCREENING Personal-Social / 22. Relationship with peers / Is there a recent stress on the family or child such as birth of a child, moving, divorce or separation, death of a close relative / 23. Relationship with parents / 24. Relationship with siblings / 25. Relationship with peers / Socially withdrawn-decreased interaction with others / Socially withdrawn-decreased interaction with others Of the 144,659 times that the questionnaire was completed, 59% answered the question. The top clinics are outpatient JHCP pediatric clinics by medical assistants, physicians, and nurse practitioners April 2013 – current
JHM SBIRT SOCIAL HISTORY Marital Status / Need to improve relationships with family? / Social Network / Social Network Comments / Participation in other social activities? / Social Activities Comments Of the 2,015 times that the questionnaire was completed, 99% answered the question. Inpatient units at Bayview Medical Center by peer recovery coaches July 2017 – current
JHM ED SW SUICIDE/HOMICIDE ASSESSMENT Suicide Risk: Single, Widowed, or Divorced / Suicide Risk: No Social Support Of the 15,101 times that the questionnaire was completed, 97% answered the question. The top units are inpatient units at Sibley Memorial Hospital and Suburban Hospital by social workers and therapists June 2013 – current
JHM ED SOCIAL WORK PATIENT INFO Support System’s Name(s) / Support System Contact / Other Support System Information / Support System Of the 14,481 times that the questionnaire was completed, 88% answered the question. The top units are emergency departments at Suburban Hospital and Bayview Medical Center by social workers and therapists July 2014 – current

References

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Notes


3Disclaimer about NLP findings: The reported NLP findings are based on the occurrences/mentions of specific linguistic patterns (aka, keywords or key phrases) within a given clinical note. At this stage of the project, we did not perform a manual quality check but we think occurrences of variable-specific patterns could give us a good proxy of the variable in question.