{"id":29983,"date":"2026-04-02T08:00:00","date_gmt":"2026-04-02T12:00:00","guid":{"rendered":"https:\/\/michigan.it.umich.edu\/news\/?p=29983"},"modified":"2026-04-01T15:09:04","modified_gmt":"2026-04-01T19:09:04","slug":"when-the-data-already-exists-building-clinical-operations-tools-from-the-inside-out","status":"publish","type":"post","link":"https:\/\/michigan.it.umich.edu\/news\/2026\/04\/02\/when-the-data-already-exists-building-clinical-operations-tools-from-the-inside-out\/","title":{"rendered":"When the Data Already Exists: Building Clinical Operations Tools from the Inside Out"},"content":{"rendered":"
\n
\"Doctor
(Healthcare IT News)<\/figcaption><\/figure>\n<\/div>\n\n\n

Across healthcare administration, a quiet inefficiency persists. Critical decisions about provider schedules, workforce planning, and clinical coverage get made from spreadsheets, manual exports, and institutional memory \u2014 not because the data doesn’t exist, but because no one has built a bridge between raw data and the people who need to act on it.<\/p>\n\n\n\n

At the University of Michigan’s Division of Pulmonary and Critical Care Medicine (PCCM) and Allergy, that bridge is now being built from the inside out \u2014 by a program manager who wanted to operationalize institutional knowledge.<\/p>\n\n\n\n

The Problem With Being the Middleman<\/h2>\n\n\n\n

“As a program manager, I was spending significant time manually translating raw data into something leadership could use,” said Shelley Boa, Program Manager for PCCM and Allergy in the Department of Internal Medicine. “I knew the information existed \u2014 it was trapped in spreadsheets, vendor exports, and honestly, in people’s heads. I wanted to build something that could answer the questions without access being the bottleneck every time.”<\/p>\n\n\n\n

That recognition became the Clinical Operations Intelligence Suite: a set of SharePoint-native tools built without dedicated IT infrastructure, external licenses, or a development team \u2014 tools that turn flat, static data into something leadership can query, model, and act on.<\/p>\n\n\n\n

The Practitioner’s Advantage<\/h2>\n\n\n\n

There is something a program manager has that no enterprise software vendor does: an exact understanding of the operational problem. Which fields actually matter. What questions leadership asks at 8 a.m. on a Monday. Where the manual burden accumulates invisibly over weeks and months. What a useful answer looks like versus a technically correct one.<\/p>\n\n\n\n

That knowledge doesn’t come from a requirements document. It comes from doing the work.<\/p>\n\n\n\n

For years, the conventional path for turning that knowledge into tools was closed off \u2014 it required developers, licenses, infrastructure, and IT queues with no guaranteed timeline. What changed was access. Free and low-cost AI tools capable of writing functional code opened a door that previously required a team to walk through. The creativity was always there. The access wasn’t.<\/p>\n\n\n\n

Operational Questions, Finally Answered<\/h2>\n\n\n\n

The suite addresses three categories of clinical operations work where data existed but couldn’t speak.<\/p>\n\n\n\n

    \n
  1. In scheduling<\/strong>, clinic grids and provider coverage data sat in formats that required manual assembly to answer even basic leadership questions. That assembly work now happens automatically \u2014 and the tools are forward-looking, helping leadership model future gaps and anticipate coverage problems before they occur.
    <\/li>\n\n\n\n
  2. In workforce planning<\/strong>, the challenge was more fundamental: the data didn’t live anywhere structured. Faculty effort targets, clinical FTE needs, and multi-year planning assumptions existed in conversations, emails, and institutional memory. Giving that knowledge a structured home \u2014 one where leadership could build, compare, and revise planning scenarios \u2014 changed how the division thinks about future state modeling entirely.
    <\/li>\n\n\n\n
  3. In reporting<\/strong>, a vendor ceiling was creating a recurring manual burden. The scheduling platform’s native reporting capabilities stopped short of what the division actually needed, and the gap was being filled by hand every reporting cycle. Closing it reduced manual data work by 80 percent and improved both the speed and frequency of reporting to stakeholders.<\/li>\n<\/ol>\n\n\n\n

    The AI Fluency Advantage<\/h2>\n\n\n\n

    It would be easy to frame this as an AI story. Not quite.<\/p>\n\n\n\n

    Yes, AI, handled the extensive and advanced code. What it could not supply was operational context \u2014 the nuanced, accumulated domain knowledge of how a specific clinical division actually works, what its data means, and what its leadership needs to make decisions. That knowledge lives with practitioners, built over years of doing the work.<\/p>\n\n\n\n

    The more accurate frame is this: AI removed the technical barrier that previously kept practitioner knowledge from becoming practitioner-built tools. The creativity, the problem definition, the quality judgment \u2014 those remained human. What changed was that a program manager no longer needed a developer to build what she could already fully envision.<\/p>\n\n\n\n

    Constraints as Creative Forcing Function<\/h2>\n\n\n\n

    Each tool in the suite exists in part because a conventional solution wasn’t available \u2014 no Power BI license, no vendor reporting module, no IT development queue with capacity to spare. Rather than waiting, the gaps became opportunities to build exactly what was needed, nothing more and nothing less, deployed directly into SharePoint where staff already work.<\/p>\n\n\n\n

    The suite is now in beta testing, the important work of collecting end user feedback to improve the product continues.<\/p>\n\n\n\n

    For others sitting at similar intersections, deep operational knowledge, limited technical resources, and a growing pile of manual work, the lesson may be this: the data usually already exists. And for the first time, so do the tools to let it speak. Work like this doesn’t happen in isolation. The Automators Anonymous Community of Practice<\/a> at Michigan Medicine has been an ongoing source of inspiration, peer support, and creative encouragement, proof that the most powerful infrastructure is sometimes just people solving problems together.<\/p>\n","protected":false},"excerpt":{"rendered":"

    Across healthcare administration, a quiet inefficiency persists. Critical decisions about provider schedules, workforce planning, and clinical coverage get made from spreadsheets, manual exports, and institutional memory \u2014 not because the data doesn’t exist, but because no one has built a bridge between raw data and the people who need to act on it. At the University of Michigan’s Division of Pulmonary and Critical Care Medicine and Allergy, that bridge is now being built from the inside out.<\/p>\n","protected":false},"author":228,"featured_media":20966,"comment_status":"open","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"_uag_custom_page_level_css":"","_umich_oidc_access":"","_monsterinsights_skip_tracking":false,"_monsterinsights_sitenote_active":false,"_monsterinsights_sitenote_note":"","_monsterinsights_sitenote_category":0,"_ef_editorial_meta_date_first-draft-date":"","_ef_editorial_meta_paragraph_assignment":"","_ef_editorial_meta_checkbox_needs-photo":"","_ef_editorial_meta_number_word-count":"","footnotes":""},"categories":[5,4],"tags":[61,402,382],"class_list":["post-29983","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-campus-news","category-features","tag-ai","tag-michigan-medicine","tag-project-management"],"uagb_featured_image_src":{"full":["https:\/\/michigan.it.umich.edu\/news\/wp-content\/uploads\/2020\/11\/health-tech1_1200.jpg",724,380,false],"thumbnail":["https:\/\/michigan.it.umich.edu\/news\/wp-content\/uploads\/2020\/11\/health-tech1_1200-200x105.jpg",200,105,true],"medium":["https:\/\/michigan.it.umich.edu\/news\/wp-content\/uploads\/2020\/11\/health-tech1_1200-300x157.jpg",300,157,true],"medium_large":["https:\/\/michigan.it.umich.edu\/news\/wp-content\/uploads\/2020\/11\/health-tech1_1200.jpg",665,349,false],"large":["https:\/\/michigan.it.umich.edu\/news\/wp-content\/uploads\/2020\/11\/health-tech1_1200-700x367.jpg",600,315,true],"1536x1536":["https:\/\/michigan.it.umich.edu\/news\/wp-content\/uploads\/2020\/11\/health-tech1_1200.jpg",724,380,false],"2048x2048":["https:\/\/michigan.it.umich.edu\/news\/wp-content\/uploads\/2020\/11\/health-tech1_1200.jpg",724,380,false],"excerpt-thumbnail":["https:\/\/michigan.it.umich.edu\/news\/wp-content\/uploads\/2020\/11\/health-tech1_1200-200x140.jpg",200,140,true],"themonic-thumbnail":["https:\/\/michigan.it.umich.edu\/news\/wp-content\/uploads\/2020\/11\/health-tech1_1200-60x42.jpg",60,42,true],"ioslider-thumbnail":["https:\/\/michigan.it.umich.edu\/news\/wp-content\/uploads\/2020\/11\/health-tech1_1200-658x300.jpg",658,300,true],"post-thumbnail":["https:\/\/michigan.it.umich.edu\/news\/wp-content\/uploads\/2020\/11\/health-tech1_1200-665x349.jpg",665,349,true],"400x250-crop":["https:\/\/michigan.it.umich.edu\/news\/wp-content\/uploads\/2020\/11\/health-tech1_1200.jpg",400,210,false]},"uagb_author_info":{"display_name":"Shelley Boa, Program Manager, PCCM and Allergy, Dept. of Internal Medicine","author_link":"https:\/\/michigan.it.umich.edu\/news\/author\/sboa\/"},"uagb_comment_info":0,"uagb_excerpt":"Across healthcare administration, a quiet inefficiency persists. Critical decisions about provider schedules, workforce planning, and clinical coverage get made from spreadsheets, manual exports, and institutional memory \u2014 not because the data doesn't exist, but because no one has built a bridge between raw data and the people who need to act on it. At the…","_links":{"self":[{"href":"https:\/\/michigan.it.umich.edu\/news\/wp-json\/wp\/v2\/posts\/29983","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/michigan.it.umich.edu\/news\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/michigan.it.umich.edu\/news\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/michigan.it.umich.edu\/news\/wp-json\/wp\/v2\/users\/228"}],"replies":[{"embeddable":true,"href":"https:\/\/michigan.it.umich.edu\/news\/wp-json\/wp\/v2\/comments?post=29983"}],"version-history":[{"count":8,"href":"https:\/\/michigan.it.umich.edu\/news\/wp-json\/wp\/v2\/posts\/29983\/revisions"}],"predecessor-version":[{"id":29995,"href":"https:\/\/michigan.it.umich.edu\/news\/wp-json\/wp\/v2\/posts\/29983\/revisions\/29995"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/michigan.it.umich.edu\/news\/wp-json\/wp\/v2\/media\/20966"}],"wp:attachment":[{"href":"https:\/\/michigan.it.umich.edu\/news\/wp-json\/wp\/v2\/media?parent=29983"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/michigan.it.umich.edu\/news\/wp-json\/wp\/v2\/categories?post=29983"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/michigan.it.umich.edu\/news\/wp-json\/wp\/v2\/tags?post=29983"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}