On feasibility and benefits of patient care summaries based on claims data

Stud Health Technol Inform. 2006:124:265-70.

Abstract

Background: Electronic availability of health care claims data maintained by health insurance companies today is higher than the availability of clinical patient record data.

Objective: To explore feasibility of automatically generated patient care summaries based on claims data and its benefit for health care professionals (HCP), when no shared electronic health record is available.

Methods: Based on an existing claims data model for German health insurance companies, a transformation and presentation algorithm was developed. To determine the utility of the resulting summaries, a focus group session comprising HCP and insurance representatives was arranged. Properties of an information system architecture capable of providing summaries to HCP were specified.

Results: A set of valuable healthcare information, in particular clinical pathways, medication, and anamnesis, can be derived from claims data that fits into the ASTM specification of a Continuity of Care Record. The focus group assessed the potential benefit of the summaries as high. Major issues are partial incompleteness and a lack of timeliness due to delayed reimbursement procedures as well as privacy-preserving and practicable access methods. The specified system architecture uses web services and a web interface to provide the summaries in HL7 CDA format. An important insight was that only a timely electronic reimbursement process will lead to precise, current, and reliable claims-based summaries.

Conclusion: Generating patient care summaries based on claims data is feasible and produces valuable information for HCP, provided that the reimbursement process is conducted timely. Integration into a national health telematics platform will facilitate access to the summaries. Evaluation of algorithm and prototype system is underway to prove the benefit in clinical practice.

MeSH terms

  • Algorithms
  • Feasibility Studies
  • Focus Groups
  • Germany
  • Humans
  • Insurance Claim Reporting*
  • Medical Records Systems, Computerized
  • Patient Care*