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SHARES: Substance use HeAlth REcord Sharing

SHARES: Substance use HeAlth REcord Sharing
分享:药物使用健康记录共享
批准号:
10582423
负责人:
MARIA ADELA GRANDO
金额:
$67.42万
依托单位国家:
美国
项目类别:
财政年份:
2023
资助国家:
美国
项目状态:
未结题
起止时间:
2023-08-01 至 2028-05-31

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PROJECT SUMMARY Integrated care is critical and becoming more common, but balancing the privacy needs of patients with substance use disorders (SUD) and increasing patient safety through data access is a challenge to realizing its full potential. Our previous award (R01MH108992) found: 1) a general dearth of research on SUD data privacy and confidentiality; 2) few publications on how SUD data sharing protections impact care; 3) inadequate interdisciplinary research on SUD data protections; 4) minimal inclusion of patients and advocates in SUD data privacy literature; 5) sparse quantitative and qualitative research on SUD data privacy (opinions and legal reviews are predominant); and 6) low accuracy for electronic health record sensitive data segmentation software sponsored by the Substance Abuse and Mental Health Services Administration (SAMHSA). The focus is to amplify patients’ and providers' voices on Substance use HeAlth REcord Sharing (SHARES). Research question: Elucidate SUD data sharing challenges and the feasibility of automated data segmentation to improve data interoperability and health care for those with SUD. Study sites: three integrated clinics, a health system, a SUD treatment clinic, a health plan and a state’s health information exchange. Specific aims: Aim 1: Explore patient and provider views on SUD data sharing and health care to inform policies on SUD data privacy and confidentiality; Aim 2: Demonstrate the feasibility and accuracy of automated SUD data segmentation by proposing novel informatics methods and tools that advance automated SUD data segmentation; Aim 3: Evaluate the clinical accuracy and impact of automated SUD data segmentation demonstrating that patient-controlled data sharing improves service delivery and SUD patient outcomes. Impact: SHARES introduces novel, standard-based, institution-independent, EHR-agnostic and scalable sensitive health data segmentation methods and technology to improve data sharing and interoperability between healthcare institutions and service delivery and patient outcomes for those with SUD.
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