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Acuity-based Performance Evaluation and Tactical Capacity Planning in Primary Care


Acuity-based Performance Evaluation and Tactical Capacity Planning in Primary Care

Aslani, Nazanin (2019) Acuity-based Performance Evaluation and Tactical Capacity Planning in Primary Care. PhD thesis, Concordia University.

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Effective primary care requires timely and equitable access to care for patients as well as efficient and balanced utilization of physician time.
Motivated by a family health clinic in Ontario, Canada, this research proposes ways to improve both of these aspects of primary care through tactical capacity planning based on acuity-based performance targets.

First, we propose a new metric based on acuity levels to evaluate timely access to primary care. In Canada, as well as other participant countries in the Organization for Economic Co-operation and Development (OECD), the main metric currently used to evaluate access is the proportion of patients who are able to obtain a same- or next-day appointment. However, not all patients in primary care are urgent and require a same- or next-day appointment. Therefore, accurate evaluation of timely access to primary care should consider the urgency of the patient request. To address this need, we define multiple acuity levels and relative access targets in primary care, akin to the CTAS system in emergency care. Furthermore, current access time evaluation in the province is mostly survey-based, while our evaluation is based on appointment data and hence more objective. Thus, we propose a novel, acuity-based, data-driven approach for evaluation of timely access to primary care.

Second, we develop a deterministic tactical capacity planning (TCP) model to balance workload between weeks for each family physician in the specific primary care clinic in this study. Unbalanced workload among weeks may lead to provider overtime for the weeks with high workload and provider idle time for weeks with low workload. In the proposed TCP model, we incorporate the results from access time evaluation in the first study as constraints for access time. The proposed TCP model considers 11 appointment types with multiple access targets for each appointment type. The TCP model takes as input a forecast of demand coming from an ARIMA model. We compare the results of the TCP model based on current access time targets as well as targets resulting from our acuity-based metrics. The use of our proposed acuity-based targets leads to allocation of time slots which is more equitable for patients and also improves physician workload balance.

Third, we also propose a robust TCP model based on the cardinality-constrained method to minimize the highest potential physician peak load between weeks. Therefore, the developed robust TCP model enables protection against uncertainty through providing a feasible allocation of capacity for all realizations of demand. The proposed robust TCP model considers two interdependent appointment types (e.g., new patients and follow ups), multiple access time targets for each appointment type and uncertainty in demand for appointments. We conduct a set of experiments to determine how to set the level of robustness based on extra cost and infeasibility probability of a robust solution.

In summary, this dissertation advocates for the definition and subsequent use of acuity-based access time targets for both performance evaluation and capacity allocation in primary care. The resulting performance metrics provide a more detailed view of primary care and lead to not only more equitable access policies but also have the potential to improve physician workload balance when used as input to capacity planning models.

Divisions:Concordia University > Gina Cody School of Engineering and Computer Science > Mechanical, Industrial and Aerospace Engineering
Item Type:Thesis (PhD)
Authors:Aslani, Nazanin
Institution:Concordia University
Degree Name:Ph. D.
Program:Industrial Engineering
Date:26 September 2019
Thesis Supervisor(s):Terekhov, Daria
ID Code:986325
Deposited On:25 Jun 2020 18:55
Last Modified:25 Jun 2020 18:55
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