Ann Brandau Explains Why Healthcare Analytics Only Matters If Someone Acts on It

Few hospitals are short on data. Claims, quality measures, staffing reports, patient-experience surveys, and payer statements come in every week, often faster than anyone can review them.

Where many organizations fall short is in moving reliably from information to decision. Ann Brandau, Principal Consultant at Prosperity Consulting, advises hospitals, physician practices, and nonprofit healthcare organizations on operational, financial, and regulatory performance. As she sees it, a report justifies itself only when it leads a specific person to take a specific action.

More Reports, Same Results

Healthcare organizations tend to pile on reports the way they pile on procedures. A board member asks a question, a payer changes a requirement, or a new system arrives with built-in dashboards, and each addition seems reasonable at the time.

Eventually leaders receive more information than they can use. Monthly packets get longer, meetings spend more time reviewing numbers than deciding what to do about them, and staff produce reports few people read closely.

The organization ends up measuring a great deal and changing very little. Data volume is easy to increase. Turning data into better care or steadier finances is harder and takes deliberate design.

Start With the Decision

Brandau’s perspective on healthcare analytics starts from a practical premise: every measure should connect to a decision someone is prepared to make.

Before a new report gets built, leaders can ask what question it answers, who will review it, and what result would prompt a change. If nobody can name the action a number might trigger, the report probably won’t improve performance.

The same approach helps with timing. Some measures, like patient flow or open appointment slots, need daily attention. Others, like payer mix or service-line margin, feed quarterly or annual planning. Setting review frequency by the decision keeps leaders focused on information they can act on.

Use the Data Already Available

Some of the most useful information is data hospitals already get from Medicare.

The Hospital Readmissions Reduction Program, established under Section 1886(q) of the Social Security Act, has reduced Medicare payments to hospitals with excess readmissions since October 1, 2012, with the reduction capped at 3 percent. The program measures 30-day unplanned readmissions for heart attack, heart failure, pneumonia, chronic obstructive pulmonary disease, coronary artery bypass graft surgery, and elective primary hip and knee replacement.

The Program for Evaluating Payment Patterns Electronic Report, known as PEPPER, is a second example. It summarizes provider-specific Medicare data for target areas CMS associates with improper payment risk and compares each hospital’s results with facilities nationally, within its Medicare Administrative Contractor jurisdiction, and within its state.

Both sources can flag problems early. What they’re worth depends on whether someone reviews them, looks into outliers, and adjusts discharge planning, documentation, or billing practices when the data calls for it.

Make Physician Data Credible

Physician performance data is a particular challenge. Productivity reports, panel sizes, and visit volumes can support better scheduling, staffing, and physician practice operations, but they can also erode trust when physicians see the numbers as incomplete or unfair.

Context and transparency build credibility. Physicians engage more readily with data when they understand how each measure is defined, when it accounts for factors they recognize, such as support staffing and schedule templates, and when they help decide how the results will be used.

Brandau’s background includes physician productivity analysis and physician alignment. In that work, productive conversations about performance usually begin with agreeing on what the data means, before anyone argues over what it shows.

Bring Payer Data to the Negotiating Table

Payer contracting is one place where analytics pays off directly. Denial patterns, payment timelines, and reimbursement measured against contract terms show where an agreement is underperforming and which issues need attention at renewal.

Brandau has negotiated commercial insurance agreements that organizations had been unable to secure for years, and negotiations like those depend on knowing the organization’s own numbers in detail. A hospital that can document how a payer’s policies affect patient access and operating costs negotiates from a much stronger position than one going on general impressions.

Agree on Definitions

Inconsistent definitions sink many analytics efforts. Finance, operations, and clinical departments may each count a visit, a new patient, or a denial in their own way, and leaders comparing those figures can draw conflicting conclusions from the same underlying activity.

A shared data dictionary covering the organization’s most important measures heads off much of that confusion. Each definition should name its source, its calculation, and the person responsible for maintaining it.

Data quality needs routine attention as well. Incomplete registration, inconsistent coding, and manual workarounds can skew results well before a report reaches leadership.

Scale the Effort to the Organization

Large health systems may have whole analytics departments. A rural hospital or small physician practice may depend on one or two people who have other jobs as well.

Smaller organizations do better concentrating on a short list of measures tied to their most significant operational, financial, and regulatory risks. A small set of trusted measures, reviewed consistently, will usually support better decisions than a large stack of reports nobody has time to study.

Ann Brandau on Closing the Loop

Analytics creates value when an organization follows through. Once a measure prompts action, leaders should record the response, set a date to review the result, and confirm whether the change worked.

That discipline comes from Brandau’s experience in governance. As a Commissioner on the Unified Government of Wyandotte County/Kansas City, Kansas, and over two terms on the Kansas Board of Regents, she reviewed information meant to guide public decisions and hold institutions accountable for results.

Hospitals answer to the same expectation from patients, payers, regulators, and their own boards. For Ann Brandau, an analytics program should be judged by the decisions it improves and the results those decisions produce.