Graduation Year


Document Type




Degree Granting Department

Business Administration

Major Professor

Alan Hevner, Ph.D.

Co-Major Professor

Richard Tarpey, DBA

Committee Member

Matthew Mullarkey, Ph.D.

Committee Member

Gert-Jan de Vreede, Ph.D.

Committee Member

Jean Kabongo, Ph.D.


star schema, elaborated action design research, reconciliation tool, design theory, test cases


The patient discharge summary is a document that conveys the patient's story to other healthcare practitioners, external users, and, most importantly from a financial perspective, health insurers. A defect or incompleteness in the patient's discharge summary will result in delays in the collection process through denial of the entire or partial reimbursement claim or, in the best-case scenario, delay until the discharge summary issue is resolved. The purpose of this project is to address the issue of the incompleteness of discharge summary from the perspective of healthcare providers, with the goal of understanding, diagnosing, and intervening in the research problem.

The research will follow an elaborated action design research (e-ADR) model to create an intelligent discharge summary that addresses and solves the incompleteness problem. A diagnosis cycle was applied through six structured interviews using stakeholders from two hospitals in Jerusalem who regularly access medical records. During this cycle, two artifacts were created, confirmed, and revised: the documentation flow process and the patient summary use case.

The design cycle resulted in two artifacts: the patient discharge summary star schema and a patient visit entity relationship diagram. To evaluate those artifacts, seven structured interviews were conducted with highly knowledgeable stakeholders.

During the implementation phase that took place at one of the hospitals, an intelligent discharge summary software was developed as a result of the single implementation cycle. The researcher re-ran the software four times to ensure all defects and bugs were removed. This resulted in a fully-functional intelligent discharge summary that uses the hospital database and transforms it into a comprehensible discharge summary using Python scripts.

The dissertation concludes with a discussion of the conclusion and limitations of the research and identifies several future research opportunities.