000 | 03715nam a22005657a 4500 | ||
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008 | 240723s20242024 xxu||||| |||| 00| 0 eng d | ||
022 | _a1472-6963 | ||
024 | _a10.1186/s12913-024-10948-7 [pii] | ||
024 | _aPMC11005183 [pmc] | ||
040 | _aOvid MEDLINE(R) | ||
099 | _a38600578 | ||
245 | _aUnderstanding social needs screening and demographic data collection in primary care practices serving Maryland Medicare patients. | ||
251 | _aBMC Health Services Research. 24(1):448, 2024 Apr 10. | ||
252 | _aBMC Health Serv Res. 24(1):448, 2024 Apr 10. | ||
253 | _aBMC health services research | ||
260 | _c2024 | ||
260 | _p2024 Apr 10 | ||
260 | _fFY2024 | ||
265 | _sepublish | ||
265 | _tMEDLINE | ||
501 | _aAvailable online from MWHC library: 2001 - present | ||
520 | _aBACKGROUND: Health outcomes are strongly impacted by social determinants of health, including social risk factors and patient demographics, due to structural inequities and discrimination. Primary care is viewed as a potential medical setting to assess and address individual health-related social needs and to collect detailed patient demographics to assess and advance health equity, but limited literature evaluates such processes. | ||
520 | _aCONCLUSIONS: Within the MDPCP program there was widespread implementation of social needs screenings and demographic data collection. However, there was room for additional supports in addressing some challenging social needs and increasing detailed demographics. Further research is needed to understand any adjustments to clinical care in response to identified social needs or application of data for uses such as assessing progress towards health equity and the subsequent impact on clinical care and health outcomes. Copyright © 2024. The Author(s). | ||
520 | _aMETHODS: We conducted an analysis of cross-sectional survey data collected from n = 507 Maryland Primary Care Program (MDPCP) practices through Care Transformation Requirements (CTR) reporting in 2022. Descriptive statistics were used to summarize practice responses on social needs screening and demographic data collection. A stepwise regression analysis was conducted to determine factors predicting screening of all vs. a targeted subset of beneficiaries for unmet social needs. | ||
520 | _aRESULTS: Almost all practices (99%) reported conducting some form of social needs screening and demographic data collection. Practices reported variation in what screening tools or demographic questions were employed, frequency of screening, and how information was used. More than 75% of practices reported prioritizing transportation, food insecurity, housing instability, financial resource strain, and social isolation. | ||
546 | _aEnglish | ||
650 | _a*Housing | ||
650 | _a*Medicare | ||
650 | _aAged | ||
650 | _aCross-Sectional Studies | ||
650 | _aData Collection | ||
650 | _aHumans | ||
650 | _aMaryland | ||
650 | _aPrimary Health Care | ||
650 | _aUnited States | ||
650 | _zAutomated | ||
651 | _aMedStar Health Research Institute | ||
651 | _aMedStar Institute for Innovation | ||
656 | _aNational Center for Human Factors in Healthcare | ||
657 | _aJournal Article | ||
700 |
_aArem, Hannah _bMHRI |
||
700 |
_aBlumenthal, Joseph _bMHRI |
||
700 |
_aKazi, Sadaf _bNCHF |
||
700 |
_aMilicia, Arianna _bNCHF |
||
700 | _aSmith, MarjannabMHRI | ||
700 |
_aStarling, Claire M _bMHRI |
||
790 | _aStarling CM, Smith M, Kazi S, Milicia A, Grisham R, Gruber E, Blumenthal J, Arem H | ||
856 |
_uhttps://dx.doi.org/10.1186/s12913-024-10948-7 _zhttps://dx.doi.org/10.1186/s12913-024-10948-7 |
||
942 |
_cART _dArticle |
||
999 |
_c14291 _d14291 |